Ligand-channel-induced ion liberation in crowded zwitterionic hydrogel electrolyte for efficient zinc metal batteries

Domain: physics
Published: 2025-12-11
Editorial outcome: minor_revision

Abstract
Developing efficient electrolytes is vital for realizing the vision of aqueous rechargeable zinc-metal batteries as a safe and sustainable energy storage technology. Emerging electrolyte engineering approaches including concentrated and molecular crowding electrolytes restrict water reactivity but usually incur limited bulk ionic conductivity and sluggish interfacial kinetics as well. Here we show that this dilemma can be addressed by deploying hydrogel electrolytes that incorporate typical molecular crowding electrolytes with a zwitterionic polymer matrix. This crowded zwitterionic hydrogel electrolyte counterintuitively entails Zn2+ liberation for higher ionic conductivity and prompt interfacial desolvation kinetics while maintaining essential advantages of molecular crowding electrolytes, thereby fundamentally overcoming the critical issues associated with such electrolytes. Such electrolytes enable the assembled zinc-metal batteries and zinc-ion hybrid capacitors to work effectively and stably at high rates (up to 5 Ag−1) and frozen temperatures (down to −60°C). The applicability of this crowding-induced ion liberation strategy was also extended to other aqueous metal-ion (Mg2+ and Na+) batteries. This work has the potential to provide a general solution to efficient electrolytes for safer, energy-dense, and cost-effective aqueous energy storage technologies.

Introduction
The rapid technological progress of renewable electricity necessitates commensurate energy storage systems (ESSs). Citing concerns over safety and cost, traditional lithium-ion batteries fall short in meeting the requirements of the grid-scale ESSs. Rechargeable zinc-metal batteries (RZMBs) emerged as such a promising and sustainable alternative, merited by their intrinsic safety, low-cost, and easy manufacturing1–4. Though the batteries’ aqueous nature is central to these advantages, it concomitantly restricts the electrochemical voltage window and interfacial stability of the electrodes in RZMBs. These problems mainly stem from the high reactivity of essential water species within the electrolyte, posing major hurdles for the eventual applications of RZMBs2,5–9. For example, excess free water molecules easily decompose and dissolve electrode materials, whilst solvated water species can corrode Zn negative electrode, aggravated dendrite formation, and incur high desolvation barriers10,11. In this context, electrolyte engineering strategies including concentrated “water-in-salt” (WIS), hybrid-solvent, and “molecular crowding” electrolytes have been vibrantly scrutinized, with great strides realized in the last few years3,10,12–15. Nevertheless, WIS electrolytes deploy excess salts that inevitably cause safety (particularly for fluorine-containing electrolytes) and cost concerns, contradicting the innate advantages of RZMBs. Worse still, while effective in widening voltage window and stabilizing electrodes, these electrolytes always engender low bulk ionic conductivity and sluggish interfacial desolvation kinetics that hurdle RZMBs’ realistic rate performance and low-temperature adaptability16.

Another strategy with growing interest is deploying polymer matrices to fabricate hydrogel electrolytes (HEs), which feature liquid-like ion transport diffusivity and solid-like cohesive integrity. These HEs entrap water with tunable hydrogen-bonding and/or ion-dipole interactions, thereby circumventing the leakage issues and offering an alternative approach to alleviate the water-relevant side reactions17–19. Nonetheless, these advantages are still at the expense of conductivity and kinetics compared to those of their liquid counterparts, given that the water-binding hydrophilic nature of the gel backbone impedes the transport of cations as well20. This is particularly pronounced for viscous solutes that have fewer side reactions, such as concentrated or crowded electrolytes. To increase ionic conductivity and interfacial kinetics, a common strategy is to introduce a large amount of water into the gel, which in turn spawns side reactions and limits the electrochemical window. This dilemma underscores the critical importance of hydrogel matrix design for the delicate balance of the water-ion-polymer nexus. Recently, zwitterionic (Zw) small molecules or polymers with “inner salt” dissociation properties have been proven to improve the dissociation of target salt species and form somehow aligned ion channels, thereby enhancing the ionic conductivity of the corresponding electrolytes21–24. Despite these advances, the overall impact and general applicability of Zw matrices on cation liberation, including conductivity, transference number, interfacial kinetics, and Zn negative electrode interface regularity, remain obscure. Therefore, addressing this knowledge gap is essential to fully leverage suitable HEs for realizing the full potential of RZMBs.

In this work, we demonstrated that a Zw hydrogel matrix can counterintuitively enable Zn2+ liberation in a molecular-crowded electrolyte. The Zw gel was chosen over other conventional polymer matrices (e.g., polyvinyl alcohol, polyacrylamide) due to its inner-salt structure, which holds potential to facilitate ion transport. Among various molecular crowding agents, disaccharides (such as maltose, sucrose) were chosen due to their strong covalent-like hydrogen bonding capability, which bridges polymer networks and effectively immobilizes water molecules, enhancing electrolyte performance and stability25,26. With the dual-induction effect of concentrated maltose molecules in bridging both ions and polymer chains, the ion-water-polymer interactions in the Zw HE were finely tuned. Combined spectroscopic studies with molecular-scale modeling reveal that the Zn2+ carriers feature less solvation water and fewer contact ion pairs (CIPs), thus are liberated to migrate more efficiently along the Zw polymer ion channel and better desolvate for interfacial reactions. As such, the crowded Zw HE provides ionic conductivity comparable to or higher than that of the liquid equivalent, a wider electrochemical window (2.6 V), stable and reversible Zn negative electrode interfaces at high utilizations (up to 57%), and good temperature adaptability. This HE sustains the assembled RZMBs and hybrid capacitors working stably at high rates and low temperatures (down to −60°C). Further, the universality of this crowding-induced ion liberation strategy was validated in other aqueous metal-ion (Mg2+ and Na+) batteries, presenting new opportunities to innovate energy-dense, low-cost, and safe energy storage technologies.

Results
Promotion of Zn2+ migration by enhanced ion-polymer interactions in crowded Zw gel electrolyte
The water species within the hydrogel network can be classified into bound water, intermediate water, and free water27. Bound water refers to those firmly bound to the hydrophilic polymer network by hydrogen bonding or electrostatic forces. Intermediate water is immediately adjacent to bound water but interacts with adjacent water or polymer networks with less than four hydrogen bonds. Free water interacts negligibly with the gel polymer chains17. Given the high polarity and dielectric constant of water, it can easily solvate most typical zinc salts. However, at low concentration, the zinc salts will dominantly dissociate in the free water moiety of HEs, with weak (or even negligible) interactions between solvated ions and the gel polymer chains (illustrated in Fig. 1a, c). In this scenario, the electrochemical behavior of ions in the HE more resembles their liquid equivalents, easily causing premature failure of the batteries.

To enhance the polymer-ion interactions, we deployed a dual-induction strategy at the molecular level by introducing maltose into the ZwHE, as illustrated in Fig. 1b. These disaccharide molecules can induce strong covalent-like hydrogen bonding between their -OH groups and the polar groups on the gel chains26, thereby holding together the cross-linked polymer chains in the hydrogel network (illustrated in Fig. 1d). Meanwhile, the introduced maltose molecules essentially crowd the dilute salt species (exemplified by 3 m Zn(ClO4)2 here) by stabilizing excess free water25. More significantly, as unraveled below, these maltose molecules can substantiate gel backbone’s charged groups to interact with dissociated anions and cations, inducing ion migration through the otherwise inaccessible transport avenues in the Zw polymer chains (illustrated in Fig. 1e).

To validate polymer-ion interactions from the dual-induction strategy, we first compared Raman spectra of the serial crowded Zw hydrogel electrolytes (CZHEs) and the liquid electrolyte (LE) counterparts, both are comprised of 3 m Zn(ClO4)2 plus n wt% maltose (n = 0 to 40, wt% of maltose in solution). Figure 2a and Supplementary Fig. 1 present the Raman spectra of the serial LEs. The three peaks at 464, 631, and 934 cm−1 correspond to the v2, v4, and v1 vibrational modes of ClO4−, respectively28,29. As maltose concentration increased to 40 wt%, these peaks remained almost identical full widths at half maximum (FWHMs) and relative peak intensities. However, the reversed intensity of the increased v C-H stretch band and the decreased v O-H band (Supplementary Fig. 1c) suggests that the added maltose indeed breaks the tetrahedral structure and restricts the activity of water molecules25. These results suggest the ClO4− ions are barely affected in LEs, though the electrolytes have been effectively crowded. The deconvoluted spectra of the water species further reveal the obviously reduced oscillation of fully four-hydrogen bonded water (viz., free water, at ca. 3250 cm−1) molecules (Supplementary Fig. 1d, e), resulting from the perturbation of the water hydrogen bonding network through the water-maltose interactions. These results are in line with the general expectations of “molecular crowding” electrolyte13, indicating that maltose can increase electrochemical stability of the electrolyte.

When incorporated with the Zw hydrogel matrix, however, the ClO4− ions show distinct peak features within the crowded electrolyte environment (Fig. 2b, c). Specifically, in contrast to the constant band signals from the Zw backbone (~810 and ~1020 cm−1), FWHMs and relative peak intensities of ClO4− ions’ bands (v1, v2, v4) decreased significantly with increasing maltose concentration (Fig. 2b, Supplementary Fig. 2). Such an evolution trend is more clearly seen by benchmarking the areas of the ClO4− ion’s three bands with those of the Zw backbone as a reference, which displayed gradually declining ion-to-backbone ratios with higher maltose concentrations (Supplementary Figs. 3, 4). The decline in relative peak intensities indicates that the relative components surrounding ClO4− changed as the maltose concentration increased30. Considering the liquid crowding electrolyte does not show such changes (Fig. 2a), and the ClO4− is a well-known “salt-in” anion that has certain interactions with polymer matrix31, this phenomenon is reasonably caused by the induction effect of maltose that prompts ClO4− ions to interact intensely with the Zw backbone. Meanwhile, the reduction of FWHMs (Fig. 2d, e) substantiates that the disordering of ClO4− collectively escalates, denoting that the bulk CIPs from the zinc salt are diminished as the anions are crowded toward the positively charged group on the Zw backbone32.

Such coordination interactions are also directly corroborated by the 67Zn nuclear magnetic resonance (NMR) spectroscopy. As shown in Fig. 2f, the maltose crowded Zn(ClO4)2 electrolyte shows a chemical shift of 0.58 ppm from the pristine bare Zn(ClO4)2 equivalent (–0.52 ppm). This shift is possibly from the reduced shielding effect by more anions and/or less water molecules within the Zn2+ primary solvation shell, as a result of the crowding effect33–36. With the Zw matrix, the 67Zn resonance peak further displays a chemical shift to downfield of 2.65 ppm, strongly insinuating the much more intense interaction between Zn2+ and the sulfonate group (-SO3−, which has better coordination capability and de-shielding effect than ClO4−) on the polymer backbone. Meanwhile, the gradually broadened resonance peak also highlights a substantially reduced Zn2+ exchange rate during the acquisition time that is caused by enhanced Zn2+-sulfonate interaction33,37. Hence, as summarized in Fig. 2g, h, the maltose molecules of the original crowding electrolyte exert dual roles within the Zw hydrogel matrix, impacting both the gel framework and the ions. In detail, the polymer chains are drawn together through the covalent-like hydrogen bonds facilitated by maltose, creating a confined space38. This rearrangement bridges the otherwise separate charged polymeric chains (caused by the anti-polyelectrolyte effect of Zw hydrogels), which avails the polymer-ion interactions. Within this confined space, the crowded maltose molecules also push anions and cations to the intrinsically dissociated counterionic sites of “inner salt” chains, thereby effectively dissociating the possible CIPs induced by the crowding effect. However, it is worth mentioning that the 40 wt% maltose crowded Zw hydrogel electrolyte has a much lower free water content than that of the liquid equivalent (5.4% vs. 25.2%, Supplementary Figs. 1e, 2e). Given the advantages of reduced free water, hereinafter, CZHE and LE refer exclusively to the 40 wt% maltose-based gel electrolyte and liquid electrolyte, respectively.

To further uncover Zw matrix’s impacts on ion speciation and coordination configurations in the crowded electrolyte, we performed molecular dynamics (MD) simulations on CZHE, LE, with bare 3 m Zn(ClO4)2 electrolyte as a reference (Fig. 2i–k, Supplementary Figs. 5–8, Supplementary Data 1). The snapshots in Supplementary Fig. 5 show that the ions and maltose are generally homogeneously distributed in the polymer and/or water matrix. The radial distribution functions (RDFs) and specific coordination numbers (CNs) show that, within LE, one Zn2+ ion is solvated with 4.34 H2O, 1.27 ClO4−, and 0.39 maltose in its first solvation sheath (Fig. 2i). In contrast to the case in bare 3 m Zn(ClO4)2 electrolyte with or without Zw polymer (Supplementary Fig. 6 and 7), the maltose crowding agent cannot ably decrease the number of the cation’s solvation H2O (from 4.91 to 4.56 on average), though it has weak solvation capability. The reduced solvation water can potentially ameliorate side reactions and facilitate the desolvation process. Nonetheless, the crowding environment incurs an increased CN of ClO4− from 1.09 to 1.27 (Fig. 2i, Supplementary Fig. 6b), along with a substantially elevated CIP portion (18.9% to 42.5%, Supplementary Fig. 8a). More CIPs will impair the ionic conductivity of the electrolyte and cause capacity loss, particularly at low temperatures39.

Upon introducing Zw polymer, the maltose coordination remains almost unchanged, but the negatively charged sulfonate group from the Zw backbone enters the primary solvation shell of Zn2+. Remarkably, this cation-polymer interaction favors a reduced CN of H2O and ClO4− to 3.94 and 1.1, respectively (Fig. 2j). The CIP also shows a dramatic decline from 42.5% to 24.4% (Supplementary Fig. 8). Note these values are very close to the experimental results from deconvoluted Raman spectra analysis (Supplementary Fig. 1b, 1f, 1g, 2b, 2f, 2g, Table 1). Such evolution trends can be rationalized by the crowding effect of maltose on ions within CZHE, consistent with the above spectroscopic results (Fig. 2d–f). In other words, the gel matrix of CZHE can strengthen the crowding effect of expelling solvated water, yet circumvent its drawback of the inevitably induced CIPs, thereby ensuring prompt ion migration kinetics. As such, the dynamic behavior of Zn2+ in different electrolytes were compared by computing the mean square displacement (MSD) at 298.15 K (Fig. 2k). It can be ascertained from the MSD profiles that under an external electric field the migration capability of Zn2+ in CZHE considerably surpassed that in LE, validating that the enhanced polymer-ion interactions can effectively leverage the ion hopping channels along the Zw backbone cohort. Taken together, the MD simulation results coincide well with the Raman and NMR measurements, both suggesting that the maltose-induced reciprocal effort of ions and polymer chains can essentially confine free water, reduce solvated water and CIPs, and harness the elaborated ion transport highways.

Electrochemical performance and enhanced interfacial kinetics of CZHE
For an intuitive comparison of the facilitated Zn2+ migration in CZHE, its ionic conductivity was compared with that of LE. The influence of the gel backbone was additionally benchmarked with two other types of crowded HE, i.e., the neutral polyacrylamide (PAM) and a polyanion (polyzinc 2-acrylamido-2-methylpropanesulfonate, marked as PAMPS) electrolytes. All three HEs share the same acrylamide basal moiety except for the different charged groups (Supplementary Fig. 9), hence PAM and PAMPS can be ideal references to verify the role of the ion hopping channels in the Zw HE. Figure 3a shows the Arrhenius plot of the ionic conductivity of different electrolytes (all HEs containing 40 wt% of maltose crowded 3 m Zn(ClO4)2) as a function of temperature. The CZHE affords a much higher ionic conductivity and a lower activation energy (Ea) than the two control HEs, attesting the critical role of the zwitterion effect21. Further, unlike commonly observed decreased ionic conductivity when transforming LE to quasi-solid-state gel electrolytes, here the CZHE demonstrated even slightly better conductivity than that of LE. At 25°C, the CZHE has a high ionic conductivity of 33.1 mS cm−1, meeting the requirements of high-rate RZMBs. Within the low-temperature region (–60–0°C), the CZHE also displays the lowest Ea of conductivity among all the electrolytes, indicating the Zn2+ migration barrier is reduced more prominently at low temperatures by the Zw gel matrix. As a result of the dramatically diminished free water over LE, the electrochemical stability window of CZHE is broadened from 2.1 to 2.6 V (Fig. 3b), enabling potential energy-dense Zn2+ storage. Moreover, the CZHE delivers a Zn2+ transference number (tZn2+) up to 0.67, much higher than the LE of 0.24 (Fig. 3c, Supplementary Fig. 10). Such a drastic improvement can be synergistically attributed to the dehydration-enhanced anion-polymer interactions (Fig. 2d) that hinder ClO4− transport40, and the elevated kinetics for more selective and prompt Zn2+ migration (Supplementary Fig. 11). Given the dual induction effect from maltose, the CZHE also features decent mechanical strength (Supplementary Fig. 12), enabling additional functions as a flexible electrolyte for emerging wearable electronics.

The influence of the electrolytes on the reversibility and stability of Zn negative electrode was then assessed. Figure 3d shows that the Zn||Zn symmetric cell assembled from the CZHE can strip and plate stably at 1 mA cm−2 and 1 mAh cm−2 for 1200 h, while the LE-based cell can only run for about 300 h before short-circuiting yet with a larger voltage loop gap. A parallel control cell assembled from the non-crowded Zw HE delivered an even shorter duration of less than 100 h (Supplementary Fig. 13). The significantly extended lifespan of the symmetric cells by CZHE is probably rendered by the effective confinement of free water, which prevents side reactions and dendrite formation during Zn plating/stripping. Such conclusions are also consolidated by the water-retention test, which shows the CZHE can tightly hold the water within 200 days (94% retention) in ambient environment (Supplementary Fig. 14). The CZHE can support the cell to work at other customized current densities and capacity densities (Fig. 3e), with a maximum Zn negative electrode depth of discharge (DOD) of 57%. For example, at a practical large rate of 3 mA cm−2 and 3 mAh cm−2, the symmetric cell still sustained for 1000 h (Supplementary Fig. 15). Of particular note, in investigating the Zn plating/stripping stability of Zn||Zn symmetric cells, the suspected “soft short” may lead to a deceptive stability when operating cells at large current densities (≥2 mA cm−2). Here, we deployed the in situ temperature response test to scrutinize this issue. After the Zn plating/stripping at different rates (Fig. 3e), the symmetric battery displays increased voltage gaps at lower temperatures, yielding a positive Ea in the dynamic stripping/plating process (Fig. 3f, Supplementary Fig. 16). This positive Ea aligns with the characteristics of ionic conduction (the electronic conduction mechanism in short-circuit would result in a negative Ea), thereby confirming the genuinely stable interfacial reactions enabled by CZHE. The enhanced reversibility of the Zn interface by CZHE was also assessed with Zn||Ti asymmetric cells, which sustained well for 600 cycles with a high average coulombic efficiency (CE) of 99.6% (Fig. 3g, h), both substantially surpassing that of LE (Supplementary Fig. 17).

It is known that interfacial charge transfer is critical for the electrolyte-electrode stability, which even becomes the rate-determining step in electrochemical reactions under high current densities and/or low temperatures41. Besides, the divalent Zn2+ ion has intense interactions with its aqua and anion ligands, such that its sluggish desolvation process impedes the kinetics at the electrode-electrolyte interface and leads to aggravated battery polarization and diminished rate performance42,43. Hence, the desolvation kinetics of the cation in different electrolytes was studied in Zn||Zn symmetric cells by electrochemical impedance spectroscopy (EIS). Note that the interfacial processes are usually coupled/convoluted (e.g., adsorption, interfacial Zn2+ desolvation, and possible diffusion in passivation/interphase layers). To avoid the erroneous pre-modeling of the equivalent circuit model method that leads to possible misunderstandings, the distribution of relaxation time (DRT) analysis that directly distinguishes the relaxation time (τ) constants of the principal electrochemical processes was used44. All the electrolytes show a temperature-dependent overall interfacial resistance (Supplementary Fig. 18). However, the deconvoluted charge transfer resistance (Rct) of the CZHE-based cell is only about half of that of LE and bare 3 m Zn(ClO4)2 electrolyte based ones at all temperatures (Fig. 4a, b, Supplementary Fig. 19), denoting a much faster interfacial kinetics in the former. The Ea of interfacial desolvation process on CZHE-Zn interface is 21.81 kJ mol−1, much smaller than the other two counterparts (Fig. 4c). This remarkably enhanced desolvation process is bestowed by the reduced solvated water and less ClO4− attraction in the Zn2+ solvation structure, as well as the selective hopping channel afforded by the Zw hydrogel matrix. Equally importantly, compared with LE, CZHE does not spawn the interfacial diffusion resistance (Rdif), which is most probably engendered by the passivation layer on the Zn negative electrode surface resulting from excess free water and more solvated water as discussed above. This trend was also validated by 3 m Zn(ClO4)2 electrolyte, where a much more significant Rdif is proliferated particularly at low temperatures (Supplementary Fig. 19). The boosted desolvation and the exemption of Rdif well account for the better rate performance and reversibility of CZHE over LE in different cells (Fig. 3d, g).

To assess the generality of this sugar crowding agent-induced interfacial regulation strategy, other hydroxyl-rich saccharides such as sucrose and fructose were also evaluated in the same CZHE framework. Despite structural differences from maltose, both sugar-based CZHEs exhibited comparable (or even better) ionic conductivity, remarkably suppressed passivation features, and reduced charge transfer resistances with regard to their respective liquid counterparts (Supplementary Figs. 20–22). Their interfacial desolvation activation energies were also significantly lower than those of LEs (Supplementary Fig. 23), indicating that the sugar-induced water immobilization and solvation modulation effects are broadly applicable, though the extent of enhancement varies depending on the specific sugar-gel backbone interactions.

The tuned interfacial reaction by CZHE is crucial for the regularity of Zn negative electrode surface. The 3D morphology scanning image shows that the post-cycled Zn surface is compact and dendrite-free, and combined XRD patterns verify that no byproducts (e.g., Znx(ClO4)y(OH)z) formed during the cycles (Fig. 4d, e). Also, after 20 cycles with CZHE, the electro-crystallization orientation (ECO) analysis of the Zn negative electrode based on the relative texture coefficient (RTC(hkl)) shows an increased RTC(002) with declined RTC(100) and RTC(101) (Fig. 4f, Supplementary Fig. 24), highlighting the regulated Zn [002]-preferred deposition texture that contributes to the even surface45,46. In comparison, the cycled Zn negative electrode in LE exhibits comparatively random ECOs with significant irregular morphologies (Fig. 4d, Supplementary Fig. 25), which are probably caused by the passivation layer (Fig. 4b) and the low tZn2+-resulted polarization (Supplementary Fig. 11). The effectiveness of the Zw gel matrix was further validated by the referenced non-crowded HE (Supplementary Fig. 26).

The underlying impact of the Zw gel matrix on the ECO was then evaluated by density functional theory (DFT) calculations (Fig. 4g, Supplementary Fig. 27, Supplementary Data 1). On the bare Zn surface, the interfacial Zn2+ will be preferably plated on (100) and (101) facets of the hexagonal close-packed Zn substrate, given their much higher binding energy (BE) with Zn2+ than that of the (002) facet (i-iii in Fig. 4g). Therefore, if not regulated, Zn2+ will continuously be plated along (100) and (101) and gradually induce the “tip-effect” sites, which are the main culprits of dendrite formation and/or side reactions45. However, with Zw matrix the high energy (100) and (101) planes can be efficiently blocked, as a result of the preferential adsorption of the polymer backbone on them (iv-vi in Fig. 4g). In this scenario, the natural deposition propensity of Zn atoms is guided along the (002), thereby rendering a more compact and stable Zn deposition texture. Further, the intense Zn-polymer interaction hinders the in-plane diffusion, and the hydration effect of the Zw backbone also restricts the accessible free water on the otherwise bare water-Zn interface (vii-ix in Fig. 4g and Supplementary Fig. 28), both enabling a uniform Zn morphology with eliminated side reactions. In a nutshell, the incorporated Zw matrix fully leverages the advantages of molecular-crowding electrolytes while offering higher ion migration rates, larger tZn2+, and improved interfacial kinetics (illustrated in Fig. 4h), fundamentally overcoming the critical issues associated with such electrolytes.

Electrochemical performance of full RZMBs and their low-temperature adaptability
The practical utilization of CZHE was evaluated in a full battery by pairing the polyaniline (PANI) positive electrode and Zn negative electrode alongside the electrolyte. Benefiting from the higher ionic conductivity and better interfacial kinetics, the CZHE based battery delivered obviously better rate capability than the LE-based equivalent (Fig. 5a, b, Supplementary Fig. 29). The reversibility of the Zn|CZHE|PANI battery was also high, as indicated by its higher CEs at different rates, particularly under low specific currents (Fig. 5b). After 1000 cycles at 3 Ag−1, the quasi-solid-state battery could deliver a reversible capacity of 92.6 mAh g−1 with a capacity retention of 85%, also surpassing that of the LE-based battery (Fig. 5c). Even after 4000 cycles at a high current density of 5 mA cm-2, the quasi-solid-state battery retained 83.4% of its initial capacity (Supplementary Fig. 30), and the Zn surface in the CZHE remained relatively smooth and uniform (Supplementary Fig. 31). Meanwhile, compared with LE, the CZHE-based battery exhibits strong self-discharge resistance, retaining the highest voltage and 91.2% of its capacity after 24 h (Supplementary Fig. 32).

To meet realistic requirements of high areal capacity and large electrode areas, a pouch cell was assembled. The pouch cell utilizes a PANI loading mass of 15 mg cm−2 and a polished Zn foil of 15 µm thickness (with a negative electrode-to-positive electrode (N/P) mass ratio of 0.71:1) over an area of 12 cm2 (3 × 4 cm). The thus assembled pouch cell featured a maximum areal capacity of 1.3 mAh cm−2 at a practical low rate of 1.15 C (Fig. 5d). It also delivered an average areal capacity of about 1 mAh cm−2 and higher CE for 200 charge-discharge cycles at 0.3 Ag−1 (Fig. 5e). To further validate the practical relevance of CZHE for high Zn utilization, we assembled Zn||NaV3O8·1.5H2O (NaVO) full batteries using a thin 10 µm Zn negative electrode (Supplementary Fig. 33). The CZHE-based pouch cell delivered a peak areal capacity of 3.2 mAh cm−2, corresponding to a Zn depth of discharge (DOD) of 55%. CZHE enabled such pouch cells to retain 82.6% capacity after 350 cycles, which is higher than that of the LE-based counterpart (Supplementary Fig. 33d). Post-Zn plating/stripping scanning electron microscopy (SEM, Supplementary Fig. 34) checking the negative electrode further confirms the smoother Zn surface, indicating effective dendrite suppression and stable Zn plating/stripping enabled by CZHE.

Inherited from the flexible nature of CZHE, a flexible RZMB (with a device thickness of 0.67 mm, Supplementary Fig. 35) can be fabricated, which sustained stable performance despite different bending angles across 250 times of deformation (Fig. 5f). The flexible batteries could be connected in tandem for customized applications, as exemplified by powering a typical light-emitting diode belt upon bending (Supplementary Fig. 35d).

The more favorable ion conduction and desolvation process of CZHE over LE was more clearly demonstrated in Zn-ion hybrid capacitors (ZIHCs)47,48. CZHE enabled ZIHCs to deliver a high specific energy of 186.7 Wh kg−1 at a specific power of 11 kW kg−1 (based on the active positive electrode material) and a maximum areal capacity of 1.41 mAh cm−2 at 1 Ag−1 (Supplementary Figs. 36–39), representing decent performance among ZIHCs based on different gel electrolytes14. The CZHE additionally endowed strong anti-self-discharge capability (83.7% capacity retention after 120 h, Supplementary Fig. 40), enabled by the crowded and coordinated configurations that inhibit the self-diffusion of the adsorbed ions.

A vital challenge for concentrated and crowded electrolytes is their severely deteriorated performance at subzero temperatures, given the high viscosity and sluggish kinetics of these electrolytes become key barriers for battery operations9,49. Differential scanning calorimeter (DSC) tests revealed the CZHE possesses a solid-liquid transition temperature (Tt) down to −90°C, much lower than that of the LE and bare 3 m Zn(ClO4)2 electrolyte (Fig. 6a). Such a lowered Tt is reasonably warranted by the combined hydration effect and ion-dipole interactions in CZHE that deconstruct the tetrahedral hydrogen bonding network of water and deter ice crystallization and salt precipitation. MD simulations were also performed to check the temperature-dependent solvation configuration of the electrolytes. When the temperature varied from 25 to −60°C, noticeable changes include the increased CN of maltose (0.39 to 0.41) in the first solvation sheath of Zn2+ accompanied by the reduced number of solvated water (3.94 to 3.91) in CZHE (Figs. 2j, 6b, Supplementary Data 1). Moreover, the cation-anion interaction was strengthened at low temperature, as evidenced by more CIPs (27.8%) over the 25°C equivalent (24.4%, Supplementary Fig. 8). Despite so, compared with the coordination configurations in LE, CZHE features obviously less solvated water (4.28 vs. 3.91) and CIPs (46.7% vs. 27.8%), as a result of the intense cation-polymer (i.e., Zn2+-sulfonate on Zw backbone) interactions at −60°C (Fig. 6c, Supplementary Fig. 8, 41b). The optimal ion speciation and their migration kinetics therefore elucidate the higher ionic conductivity as well as the better interfacial kinetics in CZHE at lower temperatures measured above (Figs. 3a, 4c). As a result, the CZHE-based Zn||PANI battery delivered a specific capacity of 44 mAh g−1 at 0.1 Ag−1 under −60°C, higher than that of the LE-based batteries (Fig. 6d). The zwitterionic effect was essential for the low-temperature performance of CZHE, as compared with the other two crowded HEs (Fig. 6e). The Zn|CZHE|PANI could run stably for 300 cycles with a CE of 100% (Fig. 6f), suggesting its good low-temperature adaptability.

General applicability
To further verify the practical relevance of the sugar-induced crowding strategy, full-cell evaluations were carried out using sucrose-based and fructose-based CZHEs in Zn||PANI configurations. Both systems delivered higher capacities and improved CEs across a range of specific currents compared to their respective LE counterparts (Supplementary Fig. 42), affirming that the conductivity and interfacial kinetic advantages imparted by sugar-induced water-ion regulation can be translated into enhanced device-level performances. These results reinforce the general applicability of the strategy, although the degree of improvement depends on the specific molecular characteristics of the sugar used.

More critically, in light of the successful demonstration of the crowding induced ion-liberation effect in Zw gel matrix, we envisage it is universal to various aqueous mono- or multi-valent ion chemistries (as illustrated in Fig. 7a). Therefore, the general applicability of the CZHE in mono- or multi-valent batteries was further demonstrated by rechargeable Na+ ion batteries (NIBs) and Mg2+ ion batteries (MIBs) with different anion-based salts. The CZHE and LE were prepared by adjusting 40 wt% maltose in 3 m NaCl or 3 m Mg(NO3)2 aqueous electrolyte for the two batteries accordingly. PANI and commercial activated carbon (AC) were used as the positive electrode and negative electrode material in both batteries to exclude the possible disturbance from different electrode materials. As expected, the different CZHEs again exhibited an ionic conductivity almost identical to their LE equivalents (Supplementary Fig. 43). When used in the two batteries, the CZHE-based batteries delivered obviously better rate capability compared with those assembled with LE (Fig. 7b, d), presumably because of the facilitated interfacial desolvation kinetics by CZHE. The trend is more prominent in MIBs, since Mg2+ has a higher charge density and stronger solvation interactions with water, which entails more desolvation penalty than that of Na+50,51. This in turn corroborates the fact that CZHE indeed enables fast desolvation kinetics and is particularly beneficial for high-rate multivalent ion batteries. Moreover, both the MIB and NIB based on the CZHE afforded satisfactory stability during cycling, also with better reversibility than their LE counterparts (Fig. 7c, e). These results prove the ion-liberation effect of CZHE can be harnessed in various aqueous batteries.

Methods
Synthesis of the Zw Hydrogels
Zwitterionic (Zw) hydrogels were prepared by dissolving 20 g [3-(Methacryloylamino)propyl]dimethyl(3-sulfopropyl)ammonium hydroxide inner salt (≥97%, Sigma-Aldrich) monomer in 20 mL of deionized (DI) water under magnetic stirring for 10 min. Then, 7 mg N, N′-methylenebisacrylamide (BIS, ≥99.5%, Sigma-Aldrich) was introduced as a crosslinking agent, and the solution was stirred for an additional 30 min. 110 mg Ammonium persulfate, (APS, ≥98%, Sigma-Aldrich) was then added as an initiator. The mixture was then stirred continuously and bubbled with N2 gas to remove O2 at 0°C for 0.5 h. Afterward, the above mixture was injected into a plastic mold and kept at 75°C for 2 h to form Zw hydrogel.

Synthesis of the PAMPS Hydrogels
Poly sodium 2-acrylamido-2-methylpropanesulfonic acid (PAMPS) hydrogels were prepared by dissolving 20.7 g 2-acrylamido-2-methylpropanesulfonic acid (≥98.5%, Sigma-Aldrich) monomer in DI water (15 mL). A 5 mL aliquot of 20 M NaOH (prepared by NaOH pellets, ≥98%) was slowly added to adjust the solution to pH 7, followed by continuous stirring for 10 min to ensure uniform neutralization. Subsequently, 7 mg BIS was introduced as a crosslinking agent, and the mixture was stirred for another 30 min. 110 mg APS was then added as the initiator. The resulting precursor solution was then stirred continuously and bubbled with N2 gas to remove O2 at 0°C for 0.5 h. Afterward, the above mixture was injected into a plastic mold and kept at 65°C for 2 h to form PAMPS hydrogel.

Synthesis of the PAM Hydrogels
Polyacrylamide (PAM) hydrogels were prepared by dissolving 7 g acrylamide (≥99%, Sigma-Aldrich) monomer in DI water (22 mL) under stirring for 10 min. Then, 7 mg BIS was added into the solution as a crosslinker. After stirring for 30 min, 110 mg APS was added to the mixture as an initiator. The mixture was then stirred continuously and bubbled with N2 gas to remove O2 at 0°C for 0.5 h. Afterward, the above mixture was injected into a plastic mold and kept at 65°C for 2 h to form PAM hydrogel.

Preparation of PANI Electrodes
The polyaniline (PANI) was synthesized by APS oxidizing aniline monomer in HCl solution. Typically, 0.365 mL aniline (≥99.5%, Sigma-Aldrich) was added into 15 mL 1 M HCl (Sigma-Aldrich) in an ice bath under stirring for 1 h. 0.228 g APS was added into 5 mL 1 M HCl and was dropped into the above solution. After string for 1 h, the dark green sample was obtained. Then, sample was washed with DI water and ethanol and dried at 60°C for 12 h. PANI positive electrodes were prepared by mixing PANI, carbon black (Super P, ≥99%, Alfa Aesar), and polyvinylidenefluoride (PVDF) binder (average Mw ~534,000 by GPC, Sigma-Aldrich) at a mass ratio of 7:2:1 in 1-Methyl-2-pyrrolidone (NMP, ≥99%, Sigma-Aldrich) solvent. The prepared slurry was uniformly coated onto carbon cloth (CeTech) using a doctor-blade technique and subsequently dried in a vacuum oven at 60°C overnight. The average electrode material loading on the carbon cloth was controlled at 1±0.05 mg cm−2 for unit cells. For pouch cells, the loading mass of PANI was 15±0.2 mg cm−2.

Preparation of activated carbon electrodes
Activated carbon (AC) positive electrodes were prepared by mixing commercially available AC (YP-80F, Kuraray), carbon black, and PVDF binder at a mass ratio of 8:1:1 in NMP solvent. The mixture was then coated on to a carbon cloth (CeTech) by a doctor-blade and dried overnight in a vacuum oven at 60°C. The average mass loading electrode materials on carbon cloth were 1, 2, 3, 5, 10±0.1 mg cm−2.

Preparation of NaV3O8·1.5H2O Electrodes
The preparation method for NaV3O8·1.5H2O (NaVO) involves adding 3 g of V2O5 powder (≥99%, Sigma-Aldrich) to 100 mL of a 2 M NaCl (prepared by NaCl powder, ≥99%, Sigma-Aldrich) solution, followed by magnetic stirring at 400 rpm for 72 h. The resulting orange-colored powders were then centrifuged and washed five times with deionized water and ethanol, and subsequently dried at 80°C for 10 h. NaVO positive electrodes were prepared by mixing NaVO, carbon black, and PVDF binder at a mass ratio of 7:2:1 in NMP solvent. The mixture was then coated onto a carbon cloth by a doctor-blade and dried overnight in a vacuum oven at 60°C. The average mass loading electrode materials on carbon cloth were 16±0.2 mg cm−2 for pouch cells.

Assembly of flexible RZMBs and ZIHCs
The prepared Zw, PAMPS, and PAM hydrogels were soaked in 3 m Zn(ClO4)2 (prepared by Zn(ClO4)2.6H2O, Sigma-Aldrich, where m denotes the molality, 1 m means 1 mol solute dissolved in per kilogram of DI water) and 3 m Zn(ClO4)2 with 40 wt% Maltose (≥95%, Sigma-Aldrich) solution for 72 h until they reached an equilibrated state. The hydrogels were then wiped-dried with lab tissues until there was no noticeable surficial liquid and carefully sliced to serve as gel electrolytes. Zn-metal battery unit cells (1×1 cm) were assembled by sandwiching hydrogel electrolytes (with a thickness of ca. 300 µm) between a Zn foil (contact area with HE of 1 cm2) and a PANI-loaded carbon cloth (contact area 1 cm2). ZIHC unit cells (1×1 cm) were assembled in the same way. In the case of liquid electrolytes, glass fiber filters were used as separators. The electrodes were manually cut to size using a high-precision stainless-steel guillotine cutter. The Zn foil in all the unit cells has a thickness of 50 µm (≥99.9%, Sigma-Aldrich). CR2032-type coin cells were assembled using stainless-steel cases and springs. Each cell contained a single-side coated positive electrode and a Zn electrode with 100 µL liquid electrolyte. For pouch cells, a sandwich structure was formed by stacking one positive electrode, the gel electrolyte, and one thin Zn (15 or 10 µm, ≥99.9%, Sigma-Aldrich) negative electrode. The assembled stack (3×4 cm effective area) was then enclosed in an aluminum-laminated pouch for sealing. Then, the pouch cells were degassed, heat-sealed, and cycled without additional external pressure. Zn foil was polished with sandpaper, rinsed with deionized water and ethanol, and dried in air before use.

Electrochemical measurements
Cyclic voltammogram (CV), galvanostatic charging/discharging (GCD), and electrochemical impedance spectroscopy (EIS) tests were performed by an electrochemical workstation (CHI760E). EIS measurements were performed using a potentiostatic mode with an AC amplitude of 10 mV over the frequency range of 100 kHz to 0.01 Hz, with 12 points per decade. The cells were stabilized for 30 min at open-circuit voltage before each measurement. The electrochemical windows of the electrolytes were measured using an inert current collector (Ti foil, ≥99.99%, Sigma-Aldrich). Linear sweep voltammetry (LSV) measurements were carried out in a three-electrode configuration, where a titanium foil served as the working electrode, and two zinc foils were used as the reference and counter electrodes, respectively. The potential was scanned at a rate of 2 mV s−1 to evaluate the electrochemical stability of the electrolytes. Zn||PANI cells were tested at voltage range of 0.5–1.6 V at 0.1, 0.3, 0.5, 1, 2, 3, 5 Ag−1 Zn||NaVO cells were tested at voltage range of 0.2–1.6 V at 0.1, 0.5, 0.6, 1, 2, 5 Ag−1. Zn||AC cells were tested at voltage range of 0–2.2 V at 2, 5, 10, 20, 50, 100, 200 mV s−1 and 0.5, 1, 2, 5, 10 Ag−1. Zn||Ti cells were pre-cycled at 1 mA cm−2 with a cutoff capacity of 1 mAh cm−2. All the general electrochemical tests (CV, GCD, EIS, LSV) were performed in an open environment within a temperature range of 25±2°C. Long-term stability tests were conducted by a battery testing system (LANHE). For Zn||Zn and Zn||Ti cell tests, Zn foils of 15 µm or 50 µm were used. All the electrochemical energy storage tests and cycling experiments were conducted in an environmental chamber at a constant temperature of 25±0.5°C unless otherwise specified. The low-temperature performance was tested in a temperature chamber (–60-25±0.5°C).

For the calculation of specific capacity, specific current, and specific energy, the mass of the active material in the positive electrode was used as the reference. The specific capacity (C, mAh g−1) was determined from the GCD profiles according to the following equation:
C = (I × t) / 3.6m (1)
where I (Ag−1) denotes the current density, t (s) is the discharge time, and m (g) represents the mass of the active material in the positive electrode.

The areal capacity (Careal, mAh cm−2) was calculated as the product of the specific capacity (C, mAh g−1) and the active material loading (mloading, g cm−2) by the following equation:
Careal = C × mloading (2)

The capacity retention was calculated based on the discharge capacity of the first cycle as a reference.

The specific energy E and the specific power P of assembled ZIHCs were calculated from the following equations:
E = 1/2 C × V (3)
P = E / t (4)

Physicochemical characterizations
The morphology and microstructure of as-prepared materials (cycled Zn) were examined by a research grade laser confocal microscope (Optical Olympus LEXT OLS5000) and a scanning electron microscopy (SEM, ULTRA Plus, Zeiss) were performed at an accelerating voltage of 5 kV. A PANalytical X’Pert Powder X-ray diffractometer (XRD) analyzed the crystal structure of samples with Cu Kα radiation (λ = 0.15418 nm) operating at 45 kV and 40 mA over a 2θ range of 10–80°, with a step size of 0.02° and a scan rate of 5° min−1. After electrochemical cycling, the Zn electrodes were disassembled from the cells, rinsed with deionized water to remove residual electrolyte, and dried under vacuum at 25±1°C before ex situ characterization. Raman spectra were recorded using a Renishaw Raman inVia Reflex system under a 532 nm excitation laser at a power of 10 mW. The attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectra were recorded on a Perkin-Elmer spectrometer in the transmittance mode with 32 scans at a resolution of 4 cm−1 and a scan rate of 2 cm−1 s−1. 67Zn nuclear magnetic resonance (NMR) spectra were collected with a Bruker AVIII 500 MHz NMR spectrometer, and 3 m Zn(ClO4)2 liquid electrolyte was used as a reference for the 67Zn NMR characterizations. The hydrogel polyelectrolytes’ mechanical tests were conducted at 25±1°C using a universal mechanical tester (SUNS, Shenzhen, China). Rectangular hydrogel samples (30×10×0.3 mm) were clamped between grips and stretched at a constant strain rate of 10 mm min−1 until fracture. The stress–strain curves were automatically recorded to evaluate the tensile strength and elongation at break. The freezing and melting temperature of hydrogels was determined as the temperature where the melting ended using a differential scanning calorimeter (DSC) (Mettler Toledo 823e) at a scan rate of 5°C min−1, with the samples kept in a Pt pan.

Computational methods
All the spin theoretical DFT calculations were performed using the Vienna ab initio Simulation Package (VASP, version 5.4.4)52,53. The electronic exchange–correlation interactions were treated within the generalized gradient approximation (GGA) using the Perdew–Burke–Ernzerhof (PBE)54. The projector augmented-wave (PAW) methods55,56 was applied to describe the interactions between core and electron (valence electron). A plane-wave basis set with a kinetic energy cutoff of 600 eV was employed. The ground-state structures were relaxed until the atomic forces on all atoms were smaller than 0.01 eV Å−1, and the energy convergence criterion was defined as 1.0 × 10−6 eV per cell. The slab models of Zn(002), (100) and (101) surfaces were used with a 25 Å vacuum layer separation in z-direction. The (4×4) Zn (002) surface, (5×3) Zn (100) surface (3×3) Zn (101) surface were used to study the adsorption of Zn and Zwitterion on the surfaces using slab method. A surface-bulk like configuration was used by allowing the top three atomic layers to relax, while freezing the rest of atomic layers in their bulk coordinates. The Brillouin zone was sampled using a Monkhorst-Pack meshes with 5×5×1 (Supplementary Fig. 44 and Supplementary Table 2). The van der Waal (vdW) interactions are included by using DFT-D3 method of Grimme57,58. The adsorption energy was calculated using the following equation.
Eads = EZn+mol − EZn − Emol (5)
where EZn+mol, EZn and Emol are total electronic energies of Zn surface with adsorbed molecules, clean Zn surface and adsorbed molecule (including zwitterionic molecule, Zn atom and water molecule).

All molecular dynamics (MD) simulations were performed using an open-access GROMACS software package with the GAFF2 force field59. In this study, there are three models studied considering the presence of zwitterionic (Zw) hydrogel (poly[(3-(methacryloylamino)propyl)dimethyl(3-sulfopropyl)ammonium hydroxide] with 4 repeated units) and maltose as the additives. The simulation box size of 5×5×5 nm3 was used as the initial box in all simulation models. First, a model of 3 m Zn(ClO4)2 consists of 150 Zn(ClO4)2 and 2778 H2O molecules. Second, 3 m Zn(ClO4)2 40 wt% maltose with Zw hydrogel electrolyte consists of 90 Zn(ClO4)2, 1667 H2O, 59 maltose and 26 Zw polymer molecules. Third, 3 m Zn(ClO4)2 40% maltose consists of 90 Zn(ClO4)2, 1667 H2O and 59 maltose molecules. Fourth, 3 m Zn(ClO4)2 with Zw hydrogel electrolyte consists of 90 Zn(ClO4)2, 1667 H2O and 26 Zw polymer molecules.

At the beginning of the simulation, structure and energy minimization of the systems were conducted. The ACPYPE was employed to obtain the GAFF2 force field topology60. The system was initially relaxed in the NVT ensemble at 298.15 K for 10 ns after the steepest descent minimization. Then it was annealed between 298.15 and 500 K for 5 ns, between 500 and 400 K for 5 ns, and between 400 and 298.15 K for 5 ns using the NPT ensemble (illustrated in Supplementary Fig. 45), with temperature and pressure coupling achieved through the Nose–Hoover and Parrinello–Rahman methods61–64. Additional annealing using NPT ensemble was also conducted for 10 ns at 213.15 K. The pressure was maintained at 1 bar. The electrostatic interactions were computed using PME methods. The final production simulations were performed under the NVT ensemble at 298.15 or 213.15 K for 100 ns. Electrostatic interactions in reciprocal space were calculated using a fast Fourier transform (FFT) grid spacing of 0.1 nm with cubic interpolation for charge assignment. Both electrostatic and van der Waals interactions were truncated at a cut-off distance of 1.2 nm. The Velocity Verlet integrator was employed with a timestep of 1 fs. The cut-off distance of 1.2 nm was adopted for electrostatics and Van der Waals interactions. The Velocity Verlet integrator was adopted with a timestep of 1 fs. The solvation structures analysis, including the distribution of contact ion pairs (CIP) and solvent-separated ion pairs (SSIP), and the radial distribution function and coordination number analysis, were performed using the trajectory from the last 80 ns out of 100 ns simulation time. The definition of the Zn2+-anion coordination structures is illustrated in Supplementary Fig. 46. The salt–solvent clusters (SSIP, CIP, and AGG) are categorized based on the Zn2+-anion CN obtained from MD simulations. In our CN analysis, Zn2+ and ClO4− are considered coordinated when the Zn²⁺ ion lies within 2.3 Å of any oxygen atom of ClO4−. This cutoff distance was derived from the Zn–O(ClO4−) RDF, where 2.3 Å corresponds to the first minimum following the primary peak, representing the boundary of the first coordination shell (as shown in Figs. 2i, 2j, 6b, and Supplementary Figs. 6, 7, and 41). Trajectories were analyzed by MDAnalysis code whenever the respective tool was unavailable in GROMACS65,66.

To further investigate the influence of electric field on the drift of Zn2+ ions at 298.15 K, another multi-step run using NVT ensemble with static electric fields in z-direction of 0.1, 0.5, 1 and 2 V/nm for each 10 ns was conducted, which was then followed by final production run in NVT ensemble for 100 ns (Supplementary Figs. 47–49, Supplementary Table 3).

Transference number: The transference number (tZn2+) is defined as the ratio of the current carried by target ions to the total ionic current carried by all the charge species. To measure tZn2+, the Bruce-Vincent method was used. Typically, Zn|CZHE|Zn and Zn|LE|Zn symmetric cells were assembled. In order to improve the quality of experimental data and minimize the impact of interface instability on test results, the cell was first stabilized in the oven for at least 12 h, then cycled at a low current density of 0.1 mA cm−2 for several cycles, till a consistent overpotential value of each cycle is obtained. Next, a constant voltage of 5 mV was applied to the cell. Then, the resultant current decay profile as a function of time was recorded till a steady-state reached. Before and after the polarization, EIS was performed to determine the interfacial resistance, and tZn2+ was calculated via the following equation:67,68
tZn2+ = Iss (ΔV − I0 R0) / I0 (ΔV − Iss Rss) (6)
where I0 and Iss are the initial and steady-state currents, respectively, R0 and Rss are the interfacial resistances before and after direct current (DC) polarization (obtained from EIS), ΔV is the applied DC bias (typically 5 mV in our case).

Dielectric Loss: EIS measurements were performed using a symmetric two-electrode configuration. The electrolyte sample-either the CZHE or the LE- was sandwiched between two titanium (Ti) foils, which acted as blocking electrodes to prevent faradaic reactions and ensure that the impedance response is dominated by ionic processes. The measurements were conducted at 25°C over a frequency range from 1 Hz to 1×105 Hz, using an AC voltage amplitude of 5 mV.

The dielectric loss ε'', which reflects the energy dissipation associated with ion movement and interfacial polarization, was computed using the following equation:69
ε'' = Z' / (ω × C0 × |Z|2) (7)
Where Z' is the real impedance component, ω = 2πf is the angular frequency, C0 = ε0 × A/d is geometrical capacitance determined by the electrode area and electrolyte thickness. The vacuum permittivity ε0 is 8.854 × 10−12 F m−1.

From the EIS measurements, the real (Z') and imaginary (Z'') components of impedance were extracted at each frequency. The total impedance magnitude was calculated as:
|Z| = sqrt(Z'^2 + Z''^2) (8)

Mean square displacements (MSD): as a function of simulation time were calculated according to the equation (1).70,71
MSD(t) = <1/N ∑i=1N |ri(t) − ri(0)|^2> = 1/N ∑i=1N <|ri(t) − ri(0)|^2> (9)
In which N is the total atom number, <...> denotes the average value overall atoms, ri(0) and ri(t) are i-axis positions at simulation time 0 and t. The diffusion coefficient was calculated by least squares fitting a straight line (Dt+c) through the MSD(t) within the diffusive region time.

MSD Calculation under External Electric Field
Zn2+ drift distance along the z-direction electric field was calculated using the following equation:
Drift distance(t) = 1/N ∑i=1N (zi(t) − zi(0)) (10)
Where zi(t) is z-coordinate of ion i at time t, zi(0) is initial z-coordinate of ion i at t = 0.
N is number of Zn2+ considered.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Title : Crowding for Ion Liberation: Zwitterionic Gel-Ligand-Channel Enabled Fast Ion Migration and Interfacial Kinetics for\nEfficient Zinc Metal Batteries\nReview Comments\n1. The coloumbic efficiency (CE) mentioned in Fig 5(c) is incorrect while the CE line points to somewhere between 40-60%.\n2. In conjunction to the previous question, although CE of CZHE is greater than the liquid electrolyte (LE), why is CE of\nCZHE is only 60 % despite a better interfacial kinetics and high ionic conductivity (33 mS cm-1). Which of the two electrodes\n(anode and cathode) is limiting the high CE.\n3. For real time application of this system, it is also advisable to test the Zn|CZHE|PANI cell at high current densities w.r.t the\nZn anode in terms of mA cm-2 to get a deeper understanding on the effect of dendrite growth on long term cycling. A post\ncycling analysis, SEM can be recorded to get an information about plating of Zn with CZHEP.\n4. Try to replicate the same DOD of 57% in Zn|CZHE|PANI pouch cell as depicted in a symmetric cell to support the\npractical application of the device. Also provide information on the utilization of Zn from the electrolytes CZHEP and LE.\n5. Self- discharge studies to be carried out to show the minimized effect of HER due to the reduced free water molecules in\nCHEP in Zn|CZHE|PANI cell.\n6. What is the scientific reason for choosing Maltose to make the crowding electrolyte. Discuss it in the introduction.\n7. Mention the reference used for recording Zn NMR under physicochemical characterizations.\n8. Address to the typo error in pg12 under the results section. CWHE has to be corrected as CZHE\n9. Dielectric behavior of the CZHE hydrogel and LE can be studied and compared to support the conductivity behavior of the\nelectrolyte systems.\n10. Figures are crowded. Is it possible to segregate/ breakdown the figures in to different sections. Also, the figure numbers\ncan be in bold (a), (b) (c) etc, to follow the text and content easily. The writings on the figure are tiny to read.", "reviewer_2": "This manuscript titled \"Crowding for Ion Liberation: Zwitterionic Gel-Ligand-Channel Enabled Fast Ion Migration and\nInterfacial Kinetics for Efficient Zinc Metal Batteries\" presents an advancement in aqueous zinc batteries through the\nverification of an interesting ion conduction mechanism. The reported hydrogel electrolyte effectively addresses the typical\nlimitations of current molecular crowding electrolytes, including restricted ionic conductivity and sluggish interfacial kinetics,\nby leveraging the crowding-induced ion liberation mechanism. The electrochemical performances of the assembled\nbatteries are good, and impressive low-temperature adaptability was demonstrated. This proposed strategy can also be\nextended to other aqueous metal-ion batteries, highlighting its general applicability. Overall, this work is well-structured, with\ncomprehensive experimental and theoretical analyses supporting conclusions. The reviewer would suggest its publication,\nsubjecting to a few minor revisions noted:\n1. The Introduction section should clearly explain the rationale for selecting maltose and the Zw gel over other available\npolymers. Are the functional groups of these materials uniquely beneficial for ion conduction? How do they perform in terms\nof water solubility and mechanical properties compared to other options?\n2. Why do the Zw backbone peaks remain unchanged in the Raman spectra while ClO4- peaks show variations after\nmaltose is introduced?\n3. The Zn2+ transference number is a key parameter in this study, and the corresponding calculation equation with an\nappropriate reference should be provided to ensure clarity and reproducibility.\n4. Supplementary Fig. 11 shows a significant increase in tensile stress for CZHE compared to Zw hydrogel. Please provide\na detailed explanation of the changes occurring within the gel that contribute to this improvement.\n5. The manuscript presents MD simulation results for 3 m Zn(ClO4)2, LE, and CZHE. To help potential readers better\nunderstand the conclusion, it is suggested that the authors include MD simulations for 3 m Zn(ClO4)2 in the Zw gel.\n6. The authors highlight that CZHE demonstrates high water retention even after 200 days, which is an impressive feature.\nCould the authors elaborate on the unique advantages of this property? Additionally, what is the underlying scientific\nmechanism that enables such long-term water retention?\n7. It is suggested to include corresponding SEM results in Fig. 4d to provide a more intuitive visualization of the surface\nmorphology.\n8. The authors are encouraged to carefully review the units and values presented in the figures. For instance, the transport\nvelocities in Supplementary Fig. 6f appear excessively large. Please double-check the data to ensure accuracy.", "reviewer_3": "Using combined spectroscopic studies with molecular modeling, the authors reported zwitterionic polymer hydrogel\nelectrolytes for rechargeable zinc-metal batteries. The highlight of the work is that the cations are solvated in a crowding\nmolecular environment, which enables fast ion diffusion. While going through the manuscript, various concerns come to the\nobservation, so the manuscript can’t be recommended for publication.\nSerious concern: Computational methods\nFirst, the authors used a kinetic cut-off energy of 400 eV by relaxing the force below 0.02 eV/Å and the convergence criteria\nfor energy as 1.0 × 10-4 eV/cell.\nThese parameters are unacceptable with the journal standard the authors attempt to publish. The energy values are\nunreliable, except one uses a cut-off of more than 550 ev with convergence criteria for the energy of 1.0 × 10-6 eV/cell. The\nsystems are far from the minimized state, and binding energies are unreliable.\nSecond, The authors did not provide the exact equation that can be used to calculate transport properties from molecular\ndynamics trajectories. Even it is assumed that the authors used the correct equation to calculate the transport property from\nMSD, that equation is well appropriate when time is sufficiently large. What is the way to deal with this? The simulation time\nshould be large enough that the targeted particle should come out of the ballistic region and appear in the diffusive region.\nFinding diffusive regions is difficult for polymer/gel-based electrolytes, as particles follow a very different diffusion\nmechanism compared to low-density electrolytes. As a good practice, one should check how many times a particle leaves the\nreferred solvation shell; it should be enough so that the log-log plot of MSD will show linearly. The authors should realise\nthat diffusion from the MSD route depends on the slope of the log-log plot. Even one may follow a different method for\ndiffusion (If exists), one should not take it for granted without verifying the diffusion region. So, the results are unreliable\nunless the authors report the diffusion from a diffusive region.\nThe term CIP is discussed without quantifying (less solvated water and fewer CIPs); what is the percentage of CIP formation\nas compared to other microstructures? Do other microstructures exist in electrolytes other than CIP, like SSIP? This\ninformation can be obtained easily from molecular dynamics trajectories if the authors follow proper methods. Moreover,\nwithout finding the diffusive region, the quantification of CIP, SSIP, or any other microstructure is also unreliable.\nThe kinetic term in the title is not justified in the manuscript. The authors could have connected the dynamics of the system to\na rate equation or rate of formation of the microstructures generated in a crowded environment.", "reviewer_4": "This manuscript presents an interesting “crowding-induced ion liberation” strategy that realizes enhanced Zn2+ transport\nand faster reaction kinetics in crowded gel electrolytes, even at temperatures down to -60 °C. Authors performed a set of\nspectroscopic and computational analyses that corroborate their conclusions. More generally, this approach can be\nextended to other metal-ion systems (Mg2+, Na+), indicating broad potential for efficient aqueous energy storage. Overall,\nthe manuscript is well-structured and presents a novel insight into electrolyte design, meriting publication with minor\nrevisions noted as follows.\n1) Authors claimed the dual induction roles of a specific disaccharide molecule, maltose. How about the generality of such a\nstrategy? Will other sugars also work? Such justification will further underpin the proposed strategy.\n2) It is recommended that the authors perform additional DFT calculations to determine the binding energies between Zn2+\nand maltose molecules. Comparing these results with the coordination capability between Zn2+ and the Zw gel, as well\nother species, will better corroborate the current findings.\n3) After the introduction of maltose, the electrolyte appears to possess a markedly enhanced water-retention capacity. Is this\nretention effect primarily a synergistic contribution from both maltose and Zn(ClO4)2. In other words, does Zn(ClO4)2 also\ncontribute to the improved water retention in the hydrogel?\n4) For improved clarity and reader comprehension, it would be helpful to include an additional schematic illustrating how the\nflexible battery is constructed, as Figure S23 does not clearly show the specific device architecture.\n5) What is the thickness of the gel electrolyte used in the devices? Authors should clearly provide such information."}, "author_response": "Response Letter\nReviewer #1\nTitle : Crowding for Ion Liberation: Zwitterionic Gel-Ligand-Channel Enabled Fast Ion\nMigration and Interfacial Kinetics for Efficient Zinc Metal Batteries\nReview Comments\n1. The coloumbic efficiency (CE) mentioned in Fig 5(c) is incorrect while the CE line\npoints to somewhere between 40-60%.\nResponse: Thanks for the comment. We apologize for not presenting this information\nclearly. The Coulombic Efficiency (CE) of both CZHE and LE is close to 100 %\n(CZHE delivers a superior CE). The marked values indicate the capacity retention of\nthe batteries based on the two types of electrolytes (85% for CZHE and 71% for LE).\nTo enhance clarity and accuracy, we have now explicitly marked the CE and\ncorresponding capacity data points in Fig. 5(c) using arrows. We appreciate your\nattentive observation.\nFig. 5 (c) cycling performances at 3.0 A g-1 of batteries assembled with CZHE and LE.\n2. In conjunction to the previous question, although CE of CZHE is greater than the\nliquid electrolyte (LE), why is CE of CZHE is only 60 % despite a better interfacial\n1\nkinetics and high ionic conductivity (33 mS cm-1). Which of the two electrodes\n(anode and cathode) is limiting the high CE.\nResponse: We apologize again for the confusion caused by our previous unclear\npresentation. As replied above, in Fig. 5(c), the CE of CZHE is actually very close to\n100%. As you pointed out, this is indeed rendered by the superior interfacial kinetics\nand high ionic conductivity of CZHE. In contrast, the CE of the LE is a little bit lower.\nThe primary factor limiting the CE of LE is related to the anode side. As later described\nin our manuscript, the unique structure of CZHE facilitates uniform Zn²⁺ distribution at\nthe electrode-electrolyte interface, significantly suppressing dendritic growth and side\nreactions (Figures 3, 4). In comparison, the LE lacks such an interfacial regulatory\nmechanism, resulting in uneven Zn deposition, increased side reactions, and\nconsequently a lower CE.\n3. For real time application of this system, it is also advisable to test the Zn|CZHE|PANI\ncell at high current densities w.r.t the Zn anode in terms of mA cm-2 to get a deeper\nunderstanding on the effect of dendrite growth on long term cycling. A post cycling\nanalysis, SEM can be recorded to get an information about plating of Zn with CZHEP.\nResponse: Thank you for your valuable suggestion. To further evaluate the practical\napplicability of the Zn|CZHE|PANI cell, we supplemented long-term cycling tests at a\nhigh current density of 5 mA cm-2, as shown in Supplementary Fig. 30. The\nZn|CZHE|PANI cell demonstrates excellent cycling stability with a capacity retention\nof 83.4% after 4000 cycles, indicating effective suppression of possible dendrite growth\nunder aggressive operating conditions.\nIn addition, we conducted post-cycling SEM analysis of the Zn anode, presented\nin Supplementary Fig. 31. After prolonged cycling at 5 mA cm-2, the Zn surface from\nCZHE remains relatively smooth and uniform. These results further substantiate the\npractical merits of CZHE for high-rate and long-duration Zn-based energy storage\nsystems.\nassembled with CZHE.\nSupplementary Fig. 31 SEM images of Zn anodes after cycling at 5.0 mA cm-2 in\nZn||PANI batteries with CZHE.\n4. Try to replicate the same DOD of 57% in Zn|CZHE|PANI pouch cell as depicted in\na symmetric cell to support the practical application of the device. Also provide\ninformation on the utilization of Zn from the electrolytes CZHEP and LE.\nResponse: Thank you for this constructive suggestio. We fully agree that demonstrating\nsimilar Zn utilization at a high DOD in a full-cell configuration is critical to support the\npractical relevance of our electrolytes. We tried our best to realise such a high DOD\nvalue by increasing the PANI cathode loading to 35 mg cm-2, which was paired with an\nultrathin Zn anode of 10 μm (with a theoretical areal capacity of 5.85 mAh cm-2).\nHowever, due to the limited theoretical capacity as well as low conductivity of the PANI\ncathode, achieving a high DOD above 50% in the Zn|CZHE|PANI pouch cell was quite\n3\nchallenging.\nGiven this, we alternatively deployed a cathode with a higher theoretical capacity-\nNaV O ·1.5H O (NaVO)-to construct Zn|CZHE|NaVO and Zn|LE|NaVO batteries for\n3 8 2\nfurther validation, as shown in Supplementary Fig. 33. Of note, the NaVO-based\npouch cell with CZHE delivered a maximum areal capacity of 3.2 mAh cm-2,\ncorresponding to a peak DOD of ~55%. The cycling performance under this condition\nis presented in Supplementary Fig. 33d, where the Zn|CZHE|NaVO cell retained 82.6%\nof its initial capacity after 350 cycles, demonstrating decent reversibility and stability\nat a practically high Zn utilization. By contrast, the LE based pouch cell showed prompt\ncapacity decline after the initial few cycles.\nAdditionally, we have included post-cycling SEM images of Zn electrodes from\nthe pouch-cell in Supplementary Fig. 34. The Zn cycled with CZHE exhibits smoother\nand more uniform surface, further supporting the advantages of CZHE in suppressing\ndendrite formation and promoting stable Zn stripping/plating.\nWe have included these new results and discussion in the revised manuscript,\nhighlighted on Pg 19-20, and the Supplementary Information. Thank you again for your\nvaluable suggestion.\nLE at various current densities. (c) Rate performance of Zn||NaVO batteries with CZHE\nand LE. (d) Cycling performance of the pouch cells (55% DOD).\nSupplementary Fig. 34 SEM images of Zn anodes after cycling in Zn||NaVO pouch\ncells (55% DOD) with (a) CZHE and (b) LE.\n5\n5. Self- discharge studies to be carried out to show the minimized effect of HER due to\nthe reduced free water molecules in CHEP in Zn|CZHE|PANI cell.\nResponse: Thank you for your insightful suggestion. We have conducted self-discharge\nstudies on the batteries, as presented in Supplementary Fig. 32. The Zn|CZHE|PANI\ncell exhibits significantly improved voltage and capacity retention than that of LE (91.2%\nvs 62.8%) after 24 hours. These findings further highlight the reduced free water\nmolecules in CZHE can sustain long-term energy storage applications. We have\nincluded these results and discussions in the revised manuscript, highlighted on Pg 19,\nand the supplementary material.\nSupplementary Fig. 32 Self-discharge performance of Zn||PANI batteries with CZHE\nand LE.\n6. What is the scientific reason for choosing Maltose to make the crowding electrolyte.\nDiscuss it in the introduction.\nResponse: Thanks for your suggestions. We thank the reviewer for this insightful\ncomment.\nIn our work, maltose, as a typical disaccharide, was selected primarily because of\n6\nits ability to form covalent-like hydrogen bonds with both polymer chains and water\nmolecules. These strong interactions arise from the multiple hydroxyl (–OH) groups\npresent on the sugar rings, enabling multivalent hydrogen bonding that mimics the\nstability and strength of covalent linkages (Sci. Adv. 2022, 8, eabl5066). Through these\ninteractions, the disaccharide can dynamically bridge adjacent polymer chains, repair\nnetwork defects, and immobilize free water molecules. This not only enhances the\nstructural robustness of the electrolyte matrix (Supplementary Fig. 1), but also\nsuppresses water activity and ice crystallization—key to maintaining electrochemical\nand thermal stability under harsh conditions.\nTo evaluate the effectiveness of such strategy, we have supplemented parallel\nexperiments with another common disaccharide (sucrose) under identical conditions.\nAs shown in Supplementary Fig. 20, the sucrose-based CZHE shows a smaller\nactivation energy in terms of ionic conductivity than corresponding LE. Further, the\ncharge transfer resistance and desolvation energy required in CZHE is also much\nreduced with regard to those in LE, yet the former affords better interfacial reversibility\nand with no diffusion resistance (from passivation layers) noted (Supplementary\nFigure 21, 23a). Given these advantages, the rate capability and CE of the sucrose-\nbased CZHE in Zn||PANI batteries are also superior to those of the LE-based\ncounterparts (Supplementary Figure 42). These results support that disaccharide-\nbased crowding strategy is general.\nMore broadly, saccharides as a chemical class possess a unique combination of\nbiocompatibility, high water solubility, and dense hydrogen-bonding functionality,\nmaking them ideal for molecular crowding applications in gel-based or liquid\nelectrolytes. Their –OH groups serve as versatile binding sites that facilitate both water\nabsorption and retention through hydrogen bonding interactions, enabling the\nconstruction of structured aqueous environments that favor electrochemical stability\nacross a range of conditions (Nat. Water 2024, 2, 663–673).\nIn light of the above, maltose was not selected arbitrarily, but rather for its highly\neffective and reproducible hydrogen bonding behavior, and we also confirm that this\n7\nstrategy can be generalized to other disaccharides. We have supplemented the scientific\nreason for choosing Maltose in the introduction section. Please see the highlighted texts\non Pg 4, 6, 16, 17.\nSupplementary Fig. 2 Temperature-dependent conductivity of 3 m Zn(ClO ) with 40\n4 2\nwt% (a) sucrose in solution and Zw.\nSupplementary Fig. 3 Effect of replacing maltose with sucrose in CZHE and LE.\n(a, b) Temperature-dependent EIS and corresponding DRT plots of CZHE. (c) Contour\nDRT profiles of CZHE with sucrose. (d, e) Temperature-dependent EIS and DRT plot\n8\nof LE. (f) DRT analysis of LE with sucrose.\nSupplementary Fig. 4 Zn2+ desolvation activation energies of CZHE and LE with (a)\nsucrose, derived from Arrhenius fitting.\nSupplementary Fig. 42 Rate performances of Zn||PANI batteries with CZHE and LE\nusing (a) sucrose.\n9\n7. Mention the reference used for recording Zn NMR under physicochemical\ncharacterizations.\nResponse: Thanks for the comment. Apart from the crowding species and gel matrix\ndesign, the zinc salt used in this work is Zn(ClO ) . Thus, as a general practice deployed\n4 2\nin previous works (e.g., J. Am. Chem. Soc. 2020, 142, 21404; Energy Environ. Sci.\n2021,14, 4463; Angew. Chem. Int. Ed. 2023, 62, e202310290; J. Am. Chem. Soc. 2023,\n145, 36, 20109), we used 3 m Zn(ClO ) liquid electrolyte as a reference for the 67Zn\n4 2\nNMR characterizations. The relative chemical shift of the LE and CZHE can therefore\nbest reflect the chemical environment changes of Zn2+.\nWe have supplemented this information in the Methods section.\n8. Address to the typo error in pg12 under the results section. CWHE has to be corrected\nas CZHE.\nResponse: We apologize for this oversight. The typographical error has now been\ncorrected to \"CZHE\" in the revised manuscript. We have also carefully checked the\nwhole manuscript to minimize the errors/typos as we can find. Thank you very much\nfor pointing out this issue.\n9. Dielectric behavior of the CZHE hydrogel and LE can be studied and compared to\nsupport the conductivity behavior of the electrolyte systems.\nResponse: We appreciate your insightful suggestion. To further elucidate the ion\ntransport behavior in the electrolytes, we have calculated and compared the dielectric\nloss (ε՛՛) of both the CZHE and the LE based on the frequency-dependent\nelectrochemical impedance spectroscopy (EIS) data.\nThe dielectric loss ε՛՛, which reflects the energy dissipation associated with ion\nmovement and interfacial polarization, was computed using the following equation:\n10\n𝑍′\n𝜀′′ =\n𝜔∙𝐶 ∙|𝑍|2\n𝜔 = 2𝜋𝑓 is the angular frequency,\n𝐴\n𝐶 = 𝜀 ∙ is geometrical capacitance determined by the electrode area and electrolyte\n0 0\nd\nthickness. The vacuum permittivity 𝜀 is 8.854×10−12 F 𝑚−1.\nCZHE A=0.58 cm2, d=0.3 cm;\nLE A=2.0 cm2, d=0.765 cm.\nFrom the EIS measurements, the real (𝑍′ ) and imaginary (𝑍′′ ) components of\nimpedance were extracted at each frequency. The total impedance magnitude was\ncalculated as: |𝑍| = √𝑍′2 +𝑍′′2\nAs shown in the newly supplemented Supplementary Figure 11, CZHE exhibits\nsignificantly lower ε՛՛ than the LE across a broad frequency range, indicating reduced\ndielectric loss and more efficient ion transport pathways.\nThe detailed dielectric loss measurement method has been included in the\nSupplementary Information method.\nSupplementary Fig 11. Frequency-dependent dielectric loss (ε՛՛) of the CZHE and the\n10. Figures are crowded. Is it possible to segregate/ breakdown the figures in to different\nsections. Also, the figure numbers can be in bold (a), (b) (c) etc, to follow the text and\ncontent easily. The writings on the figure are tiny to read.\nResponse: Thank you for your thoughtful suggestion. We apologize for the initial\nformatting issues. In the revised manuscript, we have appropriately adjusted and\nreorganized some figures to reduce visual crowding and improve clarity. Additionally,\nwe have enlarged and bolded the panel labels to ensure better alignment with the main\ntext and enhance readability. We appreciate your feedback, which has helped us\nenhance the overall presentation quality of the manuscript.\nThis manuscript titled \"Crowding for Ion Liberation: Zwitterionic Gel-Ligand-Channel\nEnabled Fast Ion Migration and Interfacial Kinetics for Efficient Zinc Metal Batteries\"\npresents an advancement in aqueous zinc batteries through the verification of an\ninteresting ion conduction mechanism. The reported hydrogel electrolyte effectively\naddresses the typical limitations of current molecular crowding electrolytes, including\nrestricted ionic conductivity and sluggish interfacial kinetics, by leveraging the\ncrowding-induced ion liberation mechanism. The electrochemical performances of the\nassembled batteries are good, and impressive low-temperature adaptability was\ndemonstrated. This proposed strategy can also be extended to other aqueous metal-ion\nbatteries, highlighting its general applicability. Overall, this work is well-structured,\nwith comprehensive experimental and theoretical analyses supporting conclusions. The\nreviewer would suggest its publication, subjecting to a few minor revisions noted:\nResponse: We sincerely appreciate your efforts in reviewing our work. Thanks for\nhighlighting the significance and novelty of our work. We have provided point-to-point\nresponses to all your comments below.\n1. The Introduction section should clearly explain the rationale for selecting maltose\nand the Zw gel over other available polymers. Are the functional groups of these\nmaterials uniquely beneficial for ion conduction? How do they perform in terms\nof water solubility and mechanical properties compared to other options?\nResponse: Thank you very much for your insightful suggestions. Maltose was\nspecifically chosen due to its unique molecular structure featuring multiple hydroxyl\ngroups, which can strongly interact with the gel network via abundant covalent-like\nhydrogen bonds (Sci. Adv. 2022, 8, eabl5066). Such interactions effectively stabilize\nfree water molecules, leading to a molecular-crowding effect that liberates ions for\nenhanced conduction. Meanwhile, the Zw gel was selected because the zwitterionic\ngroups (“inner salt”) have been proven to improve the dissociation of target salt species\n13\nand form somehow aligned ion channels under external electric fields, thereby\nenhancing the ionic conductivity of the corresponding electrolytes (Nat. Mater. 2004,\n3, 29-32; Nat. Commun. 2016, 7, 1-8; Nat. Mater. 2022, 21, 228-236). Such advantages\nfrom the hydrogel matrix have also been demonstrated in our work (e.g., Figure 3a).\nIn terms of water solubility and mechanical properties, saccharides possess\nabundant hydroxyl (–OH) groups that form strong hydrogen bonds with water\nmolecules, effectively stabilizing them in a non-volatile, bound state within the\nhydrogel network. This interaction significantly reduces water loss by evaporation or\ndesiccation. Compared to unmodified systems, saccharide-containing hydrogels retain\nwater more efficiently over time, owing to the formation of a hydrogen-bonded matrix\nthat limits water mobility and promotes long-term stability (Nat. Water 2024, 2, 663–\n673). This conclusion was also corroborated by our water-retention tests in\nSupplementary Figure 14. Additionally, the incorporation of maltose significantly\nenhances the mechanical robustness and flexibility of the Zw gel due to its strong\nhydrogen-bonding interactions with the polymer backbone (Supplementary Figure\n12).\nWe have now explicitly discussed these points in the revised Introduction section\n(Pg 4) of our manuscript and the discussion notes following Supplementary Figure\n12, 14. We sincerely appreciate your constructive feedback, which has substantially\nimproved the clarity and scientific depth of our paper.\nand Zw with 3 m Zn(ClO ) .\n4 2\nSupplementary Fig. 6 (a) Water-retention test of Zw + 3 m Zn(ClO ) 40wt% maltose\n4 2\nand Zw + 3 m Zn(ClO ) . (b) Water-retention test of Zw, Zw + 3 m Zn(ClO ) and Zw\n4 2 4 2\n+ 40wt% maltose (Error bars represent standard deviation, SD). All tests were\nperformed in an environment with a relative humidity of 60% at 25 oC.\n2. Why do the Zw backbone peaks remain unchanged in the Raman spectra while ClO -\n4\npeaks show variations after maltose is introduced?\nResponse: Thank you for your thoughtful question. The reason why the Zw backbone\n15\npeaks remain largely unchanged in the Raman spectra, while the ClO - peaks show\n4\nnotable variations after the introduction of maltose, lies in the distinct roles these\ncomponents play in the electrolyte system.\nThe Zw polymer backbone provides a structurally stable matrix with characteristic\nvibrational modes (~810 and ~1020 cm⁻¹) that are minimally affected by maltose\nincorporation. This is because the Zw gel backbone peaks correspond to intrinsic\nvibrational modes of the comparatively rigid polymer framework, such as C–N+ or S=O\nstretching. These vibrational features are largely determined by the intrinsic chemical\nstructure and crosslinking of the gel, and are not significantly perturbed by the\nintroduction of maltose. Hence, the vibrational environment of the Zw backbone\nremains largely constant, resulting in stable Raman signals.\nIn contrast, the ClO - ions exhibit marked spectral changes upon maltose\n4\nintroduction, especially in the CZHE. Specifically, the full width at half maximum\n(FWHM) and relative peak intensities of the ClO - bands (ν₁, ν₂, and ν₄) progressively\n4\ndecrease with increasing maltose content (Figure 2b,d). Such an evolution trend is more\nclearly seen by benchmarking the areas of the ClO - ion’s three bands with those of the\nratios with higher maltose concentrations (Supplementary Fig. 3, 4). This trend was\nnot observed in the liquid counterpart (though the electrolytes have been effectively\ncrowded), indicating that the variations arise from synergistic effects between maltose\nand the Zw gel. These changes suggest that maltose crowding pushes ClO - anions to\n4\ninteract more closely with the positively charged groups on the Zw backbone, thereby\naltering their solvation structure. The narrowing of FWHM and decreased ion-to-\nbackbone signal ratios reflect a reduction in contact ion pairs (CIPs) and enhanced\npolymer-anion interactions. In essence, maltose not only crowds water molecules but\nalso facilitates closer association of ClO - with the polymer matrix—modifications that\n4\nare directly captured by their Raman spectral evolution.\nThese changes are further supported by complementary 67Zn NMR and MD\nsimulation results (Figure 2f, i-j), which confirm the formation of tighter ion-polymer\n16\ncoordination environments in CZHE.\nWe have properly reorganized the manuscript to better explain the above results.\nPlease see highlighted texts on Pg 8-9. Thank you again for your valuable comment,\nwhich helped us better articulate this important point.\n3. The Zn2+ transference number is a key parameter in this study, and the corresponding\ncalculation equation with an appropriate reference should be provided to ensure clarity\nand reproducibility.\nResponse: We apologize for our oversight in not including this important detail in the\noriginal manuscript. To ensure clarity and reproducibility, we have now added the\nspecific calculation method and appropriate reference in the revised manuscript.\nThe transference number was calculated using the widely accepted Bruce-Vincent-\nEvans equation:\n𝐼 (∆𝑉−𝐼 𝑅 )\n𝑠𝑠 0 0\n𝑡 =\n𝑍𝑛2+\n𝐼 (∆𝑉 −𝐼 𝑅 )\n0 𝑠𝑠 𝑠𝑠\nwhere:\nI and I are the initial and steady-state currents, respectively,\n0 ss\nR and R are the interfacial resistances before and after DC polarization (obtained\n0 ss\nfrom EIS),\nΔV is the applied DC bias (typically 5 mV in our case).\nWe have added this equation and citation to the SI Methods section.\n4. Supplementary Fig. 11 shows a significant increase in tensile stress for CZHE\ncompared to Zw hydrogel. Please provide a detailed explanation of the changes\noccurring within the gel that contribute to this improvement.\nResponse: Thank you for your insightful comment. The significant increase in tensile\nstress observed for CZHE compared to the pristine Zw hydrogel, as shown in\nstructural and interactional changes within the gel network induced by the incorporation\nof maltose.\nUpon introducing maltose into the Zw hydrogel, a dual-induction effect occurs:\nHydrogen bonding reinforcement: Maltose contains multiple hydroxyl groups that\nform covalent-like hydrogen bonds with the zwitterionic polymer chains. These\nadditional non-covalent interactions act as dynamic physical crosslinks, tightening the\nnetwork structure and enhancing the gel’s mechanical integrity.\nPolymer chain bridging and confinement: The maltose molecules also bridge\notherwise loosely associated or spatially separated polymer chains. This bridging effect\nnot only compacts the hydrogel matrix but also mitigates the anti-polyelectrolyte effect\ninherent in zwitterionic gels by drawing charged moieties into closer proximity, thereby\nforming a more cohesive and stress-bearing polymer framework.\nTogether, these effects increase the gel’s resistance to deformation under tensile\nstress, resulting in a notable enhancement in mechanical strength. We have also\nsupplemented the tensile strength of the 3 m Zn(ClO ) -impregnated, maltose-free Zw\n4 2\nhydrogel electrolyte (with the anti-polyelectrolyte effect as shown in Supplementary\nFig. 12), which corroborates this trend much more clearly.\nImportantly, such an improvement in the mechanical strength of CZHE does not\ncompromise its ionic conductivity or flexibility, thanks to the dynamic and reversible\nnature of the hydrogen bonding interactions.\nWe have now elaborated on this mechanism in the note following Supplementary\nFig. 12 in revised SI section. Thank you again for helping us better communicate this\nimportant aspect of our material design.\nand Zw with 3 m Zn(ClO ) .\n4 2\n5. The manuscript presents MD simulation results for 3 m Zn(ClO ) , LE, and CZHE.\n4 2\nTo help potential readers better understand the conclusion, it is suggested that the\nauthors include MD simulations for 3 m Zn(ClO ) in the Zw gel.\n4 2\nResponse: Thank you for your valuable suggestion. To provide a more comprehensive\ncomparison and enhance the mechanistic understanding, we have followed your advice\nand performed additional MD simulations for 3 m Zn(ClO ) in the Zw gel without\n4 2\nmaltose, which have now been included in the Supplementary Information\n(Supplementary Fig. 7).\nAs shown in Fig. Supplementary Fig. 7b, in the maltose-free system (3 m\nZn(ClO ) with Zw gel), the Zn-H O coordination number slightly decreases to 4.53\n4 2 2\ncompare with that in 3 m Zn(ClO ) couterpart, indicating a modest suppression of\n4 2\nhydration due to sulfonate-Zn2+coordination. Further, the CIPs portion reduced from\n20.3% to 17.6% when incorporating the 3 m Zn(ClO ) in Zw gel, highlighting that Zw\n4 2\ncan facilitate the dissociation of the salt.\nhighlighted texts on Pg 10.\nSupplementary Fig. 7 (a) Snapshots of the MD simulation of Zw + 3 m Zn(ClO ) .\n4 2\n(b) Corresponding RDF plots. (c) The proportion of CIP in 3 m Zn(ClO ) with Zw\n4 2\ngel.\n6. The authors highlight that CZHE demonstrates high water retention even after 200\ndays, which is an impressive feature. Could the authors elaborate on the unique\nadvantages of this property? Additionally, what is the underlying scientific\nmechanism that enables such long-term water retention?\nResponse: Thank you very much for highlighting this important aspect. The high-water\nretention capability of CZHE offers significant practical advantages, particularly for\nmaintaining stable electrolyte integrity, mechanical flexibility, and electrochemical\nstability over extended periods. This feature is crucial for the long-term operational\nreliability of energy storage devices, minimizing electrolyte drying-out and maintaining\nstable ion conduction pathways.\nThe scientific mechanism underlying this exceptional water retention primarily\noriginates from the strong covalent-like hydrogen bonding interactions among the\nabundant hydroxyl groups of maltose molecules, zwitterionic groups of the polymer\nbackbone, and water molecules. These robust interactions substantially reduce water\n20\nevaporation and effectively immobilize free water within the polymer matrix.\nAdditionally, the compact and dense network structure induced by the bridging effect\nof maltose further suppresses water diffusion and evaporation, ensuring prolonged\nmoisture retention within CZHE.\nWe have now included a clearer explanation of this mechanism and highlighted its\nunique advantages in the revised Supplementary Fig. 14. We appreciate your\ninsightful comments that have greatly improved the clarity of our work.\n7. It is suggested to include corresponding SEM results in Fig. 4d to provide a more\nintuitive visualization of the surface morphology.\nResponse: Thank you for the helpful suggestion. To provide a more intuitive\nvisualization of the surface morphology, we have now included the corresponding SEM\nimages in Supplementary Fig. 24, which complement the 3D confocal images shown\nin Fig. 4d. These images clearly reveal the differences in Zn surface morphology after\ncycling, further supporting the stabilizing effect of CZHE toward the Zn anode.\nSupplementary Fig. 8 SEM images for Zn in the Zn||Zn symmetric cells after cycling\nusing (a) CZHE and (b) LE.\n21\n8. The authors are encouraged to carefully review the units and values presented in the\nfigures. For instance, the transport velocities in Supplementary Fig. 6f appear\nexcessively large. Please double-check the data to ensure accuracy.\nResponse: Thank you very much for pointing this out. We have carefully reviewed all\nthe units and values presented in the figures to ensure their accuracy. The unit in\nSupplementary Fig. 6f was indeed incorrectly labeled in the original version, which\ncontributed to the impression of abnormally large transport velocities. We sincerely\napologize for this oversight. We have now conducted a more refined MD simulation\nwith improved accuracy and longer sampling time. Based on these new results, we have\nupdated the diffusion coefficient data, which are now presented in Fig. 2k of the revised\nmanuscript. We greatly appreciate your careful reading and constructive suggestion,\nwhich has allowed us to improve both the accuracy and clarity of our data presentation.\nUsing combined spectroscopic studies with molecular modeling, the authors reported\nzwitterionic polymer hydrogel electrolytes for rechargeable zinc-metal batteries.\nThe highlight of the work is that the cations are solvated in a crowding\nmolecular environment, which enables fast ion diffusion. While going through the manuscript,\nvarious concerns come to the observation, so the manuscript can’t be recommended for\npublication.\nSerious concern: Computational methods\n1. First, the authors used a kinetic cut-off energy of 400 eV by relaxing the force below\n0.02 eV/Å and the convergence criteria for energy as 1.0 × 10-4 eV/cell. These\nparameters are unacceptable with the journal standard the authors attempt to publish.\nThe energy values are unreliable, except one uses a cut-off of more than 550 ev with\nconvergence criteria for the energy of 1.0 × 10-6 eV/cell. The systems are far from the\nminimized state, and binding energies are unreliable.\nResponse: Thank you for your critical and constructive feedback. In response to your\nconcern, we have reperformed all DFT calculations. Specifically, we have increased the\nkinetic energy cut-off to 600 eV and tightened the energy convergence criterion to 1.0\n× 10-6 eV/cell. These updated parameters ensure that the systems are sufficiently\nrelaxed and that the calculated binding energies are reliable.\nThe recalculated results have been incorporated into the revised manuscript and\nSupplementary Information. Specifically, the updated data are presented in Fig. 4g and\nSupplementary Fig. 27. We have also updated the Methods section of the manuscript\nto reflect these revised computational settings and recalculated all relevant results\naccordingly.\nThe following method has been included in the Computational methods section:\nFor DFT calculations, all the spin theoretical simulations in our work were carried out\non the Vienna ab initio Simulation Package (VASP) with the version 5.4.4. The\nGeneralized gradient approximation (GGA) with the Perdew-Burke-Emzerhof (PBE)\nfunctional form was employed to evaluate the electron-electron exchange and\ncorrelation interactions while the projector augmented-wave (PAW) methods were\n23\nimplanted to represent the core-electron (valence electron) interactions. Plane-Wave\nbasis function was set with a kinetic cut-off energy of 600 eV. The ground-state atomic\ngeometries were optimized by relaxing the force below 0.01 eV/Å and the convergence\ncriteria for energy was set with the value of 1.0 × 10-6 eV. The slab models of Zn\n(002), (100) and (101) surfaces were used with a 25Å vacuum layer separation in z-\ndirection. The Brillouin zone was sampled using a Monkhorst-Pack meshes with 5×5×1.\nThe van der Waal (vdW) interactions are included by using DFT-D3 method of Grimme.\nThe adsorption energy was calculated using the following equation.\n𝐸 = 𝐸 −𝐸 −𝐸\n𝑎𝑑𝑠 𝑍𝑛+𝑚𝑜𝑙 𝑍𝑛 𝑚𝑜𝑙\nwhere 𝐸 , 𝐸 and 𝐸 are total electronic energies of Zn surface with\n𝑍𝑛+𝑚𝑜𝑙 𝑍𝑛 𝑚𝑜𝑙\nadsorbed molecule, clean Zn surface and adsorbed molecule (including zwitterionic\nmolecule, Zn atom and water molecule).\nSupplementary Fig. 27 Crystal structure of metal Zn for DFT calculations. Calculated\nmodels for Zn and Zw adsorption onto Zn (002), Zn (101), and Zn (100) planes, along\nwith corresponding adsorption energy values.\nus improve the accuracy and credibility of our theoretical analysis.\n2. Second, The authors did not provide the exact equation that can be used to calculate\ntransport properties from molecular dynamics trajectories. Even it is assumed that the\nauthors used the correct equation to calculate the transport property from MSD, that\nequation is well appropriate when time is sufficiently large. What is the way to deal\nwith this? The simulation time should be large enough that the targeted particle should\ncome out of the ballistic region and appear in the diffusive region. Finding diffusive\nregions is difficult for polymer/gel-based electrolytes, as particles follow a very\ndifferent diffusion mechanism compared to low-density electrolytes. As a good practice,\none should check how many times a particle leaves the referred solvation shell; it should\nbe enough so that the log-log plot of MSD will show linearly. The authors should realise\nthat diffusion from the MSD route depends on the slope of the log-log plot. Even one\nmay follow a different method for diffusion (If exists), one should not take it for granted\nwithout verifying the diffusion region. So, the results are unreliable unless the authors\nreport the diffusion from a diffusive region.\nResponse: Thank you very much for this insightful and important comment. We\napologize for the confusing calculation method in the previous manuscript version. In\nour initial molecular dynamics (MD) simulations, we introduced an external electric\nfield along the Z-axis. This approach was based on the consideration that real battery\nsystems operate under an applied voltage, and zwitterionic gel chains can align\ndirectionally under an electric field (as reported in Refs. Nat. Commun. 2016, 7, 11782;\nChem. Soc. Rev. 2019,48, 757-770; J. Polym. Sci. B Polym. Phys. 2004, 42, 3513-3538),\npotentially facilitating a field-driven hopping mechanism of ion transport. Therefore,\nwe referred to a few previous studies (e.g., Joule 2019, 3, 2761–2776; Nat. Commun.\n2023, 14, 3066; J. Am. Chem. Soc. 2025, 147, 10, 8488–8499) that employed electric-\n25\nfield-driven MD to explore directional ion migration and hopping behavior.\nUnder such conditions, the MSD curves become nonlinear due to field-induced\ndrift and are not suitable for extracting diffusion coefficients via the Einstein equation.\nInstead, in our previous manuscript, we estimated the ion transport velocity by directly\ncalculating the displacement per unit time under the applied field. However, we fully\nagree with you that this approach is not standard for evaluating diffusion coefficients,\nand it lacks a clear identification of the diffusive regime, particularly in polymer/gel-\nbased systems where hopping and sub-diffusive behavior can complicate analysis.\nAs highlighted by you, a reliable diffusion coefficient should be extracted from the\nlinear (diffusive) region of the MSD curve, which requires sufficient simulation time\nand confirmation that particles have exited the ballistic regime. To address this concern,\nwe have performed additional MD simulations without applying an external electric\nfield and extended the simulation time to ensure accurate sampling of the diffusive\nregion. All updated parts are now as shown in Fig. 2i, 2j, 2k, 6b, 6c and\nSupplementary Fig. 5, 7, 41.\nFurthermore, we have now included the explicit form of the Einstein equation\n(Nature 2024, 627, 101–107; Nature 2023, 621, 75–81; Nat Sustain 2024, 7, 661–671)\nused for diffusion coefficient calculation in the Methods section. The revised diffusion\ncoefficients for Zn2+ ions, obtained from the diffusive region of the MSD, show that\nZn2+ diffuses faster in CZHE than in LE across both room (25 oC) and low (-60 oC)\ntemperatures, consistent with our electrochemical measurements.\nWe have properly revised the manuscript to better discuss all these points. Please\nsee highlighted texts on Pg 10, 22. We sincerely hope these supplemented results can\naddress your concerns. Thank you again for highlighting this important aspect, which\nhas led us to improve the accuracy and clarity of our diffusion analysis.\nLE.\nFig. 2j Radial distribution functions and corresponding coordination plots of Zn2+ in\nCZHE.\nFig. 6b Radial distribution functions and corresponding coordination plots of Zn2+ in\nCZHE at -60 oC.\nFig. 6c Simulated mean square displacement of Zn2+ in LE and CZHE under -60 oC.\nComparison of the proportion of CIP in (c) LE and (d) CZHE under 25 oC.\nSupplementary Fig. 10 (a) Snapshots of the MD simulation of Zw + 3 m Zn(ClO ) .\n4 2\n(b) Corresponding RDF plots. (c) The proportion of CIP in 3 m Zn(ClO ) with Zw gel.\n4 2\n(c) Comparison of Zn2+ solvation structures in CZHE and LE at -60 oC.\n3. The term CIP is discussed without quantifying (less solvated water and fewer CIPs);\nwhat is the percentage of CIP formation as compared to other microstructures? Do other\nmicrostructures exist in electrolytes other than CIP, like SSIP? This information can be\nobtained easily from molecular dynamics trajectories if the authors follow proper\nmethods. Moreover, without finding the diffusive region, the quantification of CIP, SSIP,\nor any other microstructure is also unreliable.\nResponse: Thank you very much for this valuable and insightful comment. Quantifying\nthe CIP and SSIP is indeed helpful for elucidating the crowding-induced carrier\nsalvation and the ion transport properties. In the revised version, we have conducted a\nthorough analysis based on the correct MD simulations to quantify the CIP and SSIP\npopulations in different electrolytes . The results, now presented in Supplementary\nFigs. 5c, 5d, 6c, 7c, 41c, and 41d, show that the CIP content varies significantly\ndepending on the electrolyte environments. Specifically, in the 3 m Zn(ClO ) aqueous\n4 2\nsolution, the CIP proportion is approximately 20.3%, which then increases substantially\nto 43.1% in the LE (3 m Zn(ClO ) containing 40 wt% maltose). This increase is\n4 2\nattributed to the molecular crowding effect induced by the high concentration of\nmaltose, which reduces the availability of free water and compacts the local ion\nenvironment, thereby promoting closer Zn2+-ClO - interactions and enhancing CIP\n4\nformation. However, upon introducing the zwitterionic (Zw) gel matrix into this\n30\ncrowded electrolyte (forming the CZHE), the CIP proportion is markedly reduced to\n25.8%. This reduction arises from the competitive coordination interactions between\nZn2+ and the sulfonate groups (SO -) on the Zw polymer backbone, which effectively\n3\ndisplace some ClO - anions from the primary solvation shell and disrupt CIP formation.\nand pushes anions toward the polymer chains, promoting a more dissociated ionic state.\nThis CIP-reducing effect of the Zw gel matrix is also evident in the maltose-free\nhydrogel electrolyte (Zw+3 m Zn(ClO ) ), where the CIP proportion decreases from\n4 2\n20.3% to 17.6% upon addition of the Zw gel.\nWe also examined the structural configurations at -60 °C, as shown in\nSupplementary Figs. 41d and 41e. At this extremely low temperature, the CIP ratio in\nboth LE and CZHE increases, due to dramatically suppressed thermal motion and\nenhanced ion-ion interactions in the viscous medium. However, CZHE still maintains\na much low CIP level than LE (27.8% vs. 44.6%), demonstrating the effectiveness of\nthe zwitterionic coordination environment in mitigating ion pairing even under extreme\nsubzero conditions. To help potential readers better capture these changes, we have\nsummarized all these results in Supplementary Table 1 and Table 2.\nPlease note these structural features are consistent with our experimental evidence:\nRaman spectra (Fig. 2d-e) show decreased intensity and narrower FWHM of ClO -\n4\nbands upon gel incorporation, while 67Zn NMR (Fig. 2f) reveals downfield shifts and\npeak broadening, reflecting fewer anion and water ligands and stronger Zn-polymer\ninteractions. Taken together, these results confirm that the elevated CIP content in LE\nis a consequence of reduced solvation and enhanced local ion pairing due to maltose-\ninduced crowding, while the introduction of the zwitterionic gel effectively mitigates\nthis issue through polymer coordination and spatial reorganization. These\nmicrostructural transitions also underpin the improved ionic conductivity and Zn2+\ntransport behavior observed in CZHE, particularly at low temperatures (experimentally\nproved in Fig. 3a).\nWe have properly revised the manuscript to better discuss all these points. Please\n31\nsee highlighted texts on Pg 10, 22. We are grateful to you for highlighting this important\npoint, which has led us to provide a more complete and quantitative understanding of\nthe electrolyte microstructures.\nSupplementary Fig. 5 A snapshot of the MD simulation cell for (a) LE and (b) CZHE.\nComparison of the proportion of CIP in (c) LE and (d) CZHE under 25 oC.\nSupplementary Fig. 6 (c) The proportion of CIP in 3 m Zn(ClO ) .\n4 2\nSupplementary Fig. 7 (c) The proportion of CIP in 3 m Zn(ClO ) with Zw gel.\n4 2\nunder -60 oC.\nSupplementary Table 1. Quantitative comparison of CIP and SSIP in various\nelectrolytes at 25 °C.\nElectrolytes CIP SSIP\nCZHE 25.8% 74.2%\nLE 43.1% 56.9%\nZn(ClO ) 20.3% 79.7%\n4 2\nZn(ClO ) + Zw gel 17.6% 82.4%\n4 2\nSupplementary Table 2. Quantitative comparison of CIP and SSIP in various\nelectrolytes at -60 °C.\nElectrolytes CIP SSIP\nCZHE 27.8% 72.2%\nLE 44.6% 55.4%\n4. The kinetic term in the title is not justified in the manuscript. The authors could have\nconnected the dynamics of the system to a rate equation or rate of formation of the\nmicrostructures generated in a crowded environment.\nResponse: We appreciate your insightful comment regarding the use of the term\n33\n“kinetics” in our title. We fully agree that such terminology must be rigorously\nsupported by experimental and theoretical analysis. However, please note in our study\nthe phrase “interfacial kinetics” refers to the Zn2+ interfacial desolvation and charge\ntransfer processes, which are often the rate-determining steps in aqueous zinc-based\nelectrochemical systems. This issue is pronounced especially under high current\ndensities and/or low-temperature conditions.\nThe claim of enhanced interfacial kinetics has been comprehensively substantiated by\nthe following direct evidence:\n1. DRT (Distribution of Relaxation Times) analysis:\nAs shown in Fig. 4a, 4b, S19, the DRT contour plots clearly deconvoluted the\nrelaxation process associated with Zn2+ interfacial desolvation. The CZHE-based\nsystem exhibits a markedly lower charge transfer resistance (Rct) compared to the\nLE and bare Zn(ClO ) electrolytes. Furthermore, the activation energy (Ea) extracted\n4 2\nfrom Arrhenius fitting of this interfacial process is only 21.81 kJ mol-1, which is\nsignificantly lower than that of the LE and the diluted electrolyte (Fig. 4c). These results\nprovide direct and quantitative evidence of accelerated interfacial devolvation kinetics\nin the presence of the zwitterionic gel matrix.\n2. Electrochemical impedance spectroscopy (EIS) and Zn2+ transference number:\nThe EIS plots (Fig. 3c, inset) reveal that the CZHE exhibits a substantially reduced\nRct even before cycling, indicating facilitated interfacial charge transfer. Additionally,\nthe Zn²⁺ transference number increases from 0.24 in LE to 0.67 in CZHE, signifying\na shift in ionic transport dominance from ClO - to Zn2+. This shift minimizes ion\n4\nconcentration polarization at the interface and supports a more efficient Zn²⁺ delivery\nto the electrode, thereby promoting faster interfacial reactions.\n3. Zn||Ti asymmetric cells and long-term Coulombic efficiency:\nThe Zn||Ti cells assembled with CZHE exhibit stable cycling with an average\nplating/stripping process and minimal side reactions at the interface. Such high CE\nvalues are often indicative of favorable interfacial reaction kinetics.\n4. Zn||Zn symmetric cell stability and activation energy:\nIn long-term cycling tests, the Zn||Zn symmetric cells with CZHE demonstrate stable\noperation for over 1200 hours without short-circuiting (Fig. 3d). To rule out false\nindications due to soft shorting, we conducted temperature-dependent stripping/plating\nmeasurements (Fig. 3f), which yield a positive activation energy, confirming that the\nobserved stability originates from genuine ionic conduction rather than parasitic\nelectronic pathways. This further validates the kinetic robustness of the Zn||CZHE\ninterface.\n5. Supplementary evidence from Zn deposition structure:\nThe smoother Zn morphology and preferential (002) electrocrystallization orientation\n(Fig. 4d-f), together with DFT simulations of surface interactions (Fig. 4g), indicate\nthat the zwitterionic polymer matrix modulates not only ion transport but also Zn²⁺\ninterfacial deposition behavior, which again support controlled and faster interfacial\ndynamics.\nAs you can see that in all these electrochemical results, CZHE outperforms LE. We\ntherefore believe these well-adopted essential practices in evaluating the interfacial\nkinetics can adequately support our conclusion: zwitterionic gel prompts interfacial\ndesolvation kinetics while maintaining other advantages of molecular crowding\nelectrolytes, thereby fundamentally overcoming the critical issues associated with such\nelectrolytes. We have properly revised the manuscript to better elucidate this point.\nPlease see highlighted texts on Pg 13, 15, 22. Thanks again for raising this critical\nquestion, which has led us to better clarify the conclusion.\nThis manuscript presents an interesting “crowding-induced ion liberation” strategy that\nrealizes enhanced Zn2+ transport and faster reaction kinetics in crowded gel\nelectrolytes, even at temperatures down to -60 °C. Authors performed a set of\nspectroscopic and computational analyses that corroborate their conclusions. More\ngenerally, this approach can be extended to other metal-ion systems (Mg2+, Na+),\nindicating broad potential for efficient aqueous energy storage. Overall, the manuscript\nis well-structured and presents a novel insight into electrolyte design, meriting\npublication with minor revisions noted as follows.\nResponse: We sincerely appreciate your efforts in reviewing our work. Thanks for\nhighlighting the significance and novelty of our work. We have provided point-to-point\nresponses to all your comments below.\n1. Authors claimed the dual induction roles of a specific disaccharide molecule, maltose.\nHow about the generality of such a strategy? Will other sugars also work? Such\njustification will further underpin the proposed strategy.\nResponse: We sincerely thank you for this important and constructive question. Indeed,\nverifying the generality of our proposed sugar-mediated crowding strategy is critical\nfor establishing its broader applicability beyond the specific case of maltose. While\nmaltose was initially chosen due to its favorable physicochemical\ncharacteristics─including high water solubility, abundant hydroxyl groups, and a\nrelatively compact disaccharide structure that promotes both hydrogen bonding and\ncompatibility with the zwitterionic gel matrix─we recognize that it is important to\ndemonstrate whether other saccharides can elicit similar effects.\nTo this end, we systematically investigated two additional sugars: sucrose,\nanother disaccharide, and fructose, a monosaccharide with high hydration ability but\nsmaller molecular size. These were selected to represent different molecular geometries\nand solvation characteristics. Both sugars were incorporated into the same zwitterionic\nhydrogel electrolytes (CZHEs) formulation at equivalent concentrations, and their\neffects on electrolyte performance and interfacial behavior were carefully analyzed and\ncompared with those of their respective liquid electrolytes (LEs).\nexhibit very comparable (or even better) ionic conductivity compared to their\nrespective LE counterparts in a broad temperature range of 0-60 oC. Despite the slight\ndifference in the exact values, the two CZHEs possess even lower activation energies\nin terms of the conductivity over the corresponding LEs. This trend is consistent with\nthe results obtained using maltose, highlighting that the crowding effect from the sugars\nis generally similar, and the Zw gel matrix is indeed critical for ensuring the ionic\nconductivity in CZHEs.\nElectrochemical impedance spectroscopy (EIS) combined with distribution of\nrelaxation time (DRT) analysis (Supplementary Figs. 21 and 22) revealed that both\nthe sucrose- and fructose-based CZHEs exhibit significantly lower interfacial resistance\nand suppressed passivation-related relaxation processes compared with their LE\ncounterparts. This is also consistent with the behavior observed in the maltose-based\nCZHE (Fig. 4a and b), where the elimination of the R component is associated with\na reduction in excess free water and a more stabilized electrode–electrolyte interface.\nThe absence of R in all CZHEs indicates that the sugar-mediated hydrogen-bonding\ndiff\ninteractions contribute to mitigating parasitic interfacial reactions, regardless of the\nsugar identity.\nMoreover, we extracted the interfacial Zn2+ desolvation activation energies (E )\na\nvia Arrhenius analysis (Supplementary Fig. 23). For sucrose and fructose, the Ea\nvalues were reduced to 28.69 kJ mol⁻¹ and 27.85 kJ mol⁻¹, respectively, compared to\n39.91 kJ mol⁻¹ and 41.07 kJ mol⁻¹ in their corresponding LEs. Although slightly higher\nthan the 21.81 kJ mol⁻¹ measured for the maltose-based CZHE (Fig. 4c), these results\nconsistently demonstrate that sugar incorporation facilitates Zn2+ desolvation by\npartially restructuring the solvation environment and weakening Zn2+-H O interactions.\ndemonstrated above, we further compared the rate performance of Zn||PANI batteries\nconstructed with sucrose-based and fructose-based CZHEs. As shown in\nSupplementary Fig. 42, both systems (with sucrose or fructose) delivered superior\n37\ncapacity retention and higher Coulombic efficiency across various current densities\nwhen compared with their LE analogues, confirming that the benefits extend beyond\ninterfacial resistance reduction and translate into improved battery performance.\nTaken together, these results support the mechanistic generality of our strategy:\nhydroxyl-rich saccharide additives can indeed induce molecular crowding and water\nimmobilization effects within the gel matrix, contributing to more stable solvation\nstructures, enhanced Zn2+ desolvation kinetics, and improved electrochemical\ninterfaces. Nevertheless, the magnitude of these effects varies depending on the specific\nsugar’s structure, including molecular size, flexibility, hydroxyl group arrangement,\nand ability to engage in multivalent hydrogen bonding. Among the sugars studied,\nmaltose provides the most favorable balance between structural compatibility and\ncrowding strength, but the core concept of sugar-induced interfacial regulation\nwithin a zwitterionic gel framework proves to be broadly valid and tunable. We have\nincluded these results and discussions in the revised supplementary material. Please see\nhighlighted texts on Pg 16,17 and 20. Thank you again for your insightful suggestion.\nSupplementary Fig. 20 Temperature-dependent conductivity of 3 m Zn(ClO ) with\n4 2\n40 wt% (a) sucrose or (b) fructose in solution and Zw gel.\n(a, b) Temperature-dependent EIS and corresponding DRT plots of CZHE. (c) Contour\nDRT profiles of CZHE with sucrose. (d, e) Temperature-dependent EIS and DRT plot\nof LE. (f) DRT analysis of LE with sucrose.\nSupplementary Fig. 12 Effect of replacing maltose with fructose in CZHE and LE.\n(a, b) Temperature-dependent EIS and corresponding DRT plots of CZHE. (c) Contour\nDRT profiles of CZHE with fructose. (d, e) Temperature-dependent EIS and DRT plot\nof LE. (f) DRT analysis of LE with fructose.\nSucrose and (b) Fructose, derived from Arrhenius fitting.\nSupplementary Fig. 42 (a) Rate performances of Zn||PANI batteries with CZHE and\nLE using (a) Sucrose and (b) Fructose.\n2. It is recommended that the authors perform additional DFT calculations to determine\nthe binding energies between Zn2+ and maltose molecules. Comparing these results\nwith the coordination capability between Zn2+ and the Zw gel, as well other species,\nwill better corroborate the current findings.\nResponse: Thank you for your valuable suggestion. In response, we have performed\nadditional DFT calculations to compare the binding energies between Zn and maltose.\n(as shown in Supplementary Fig. 28), whereas the binding energy between Zn and Zw\nis -1.44 eV (Fig. 4g). This significant difference in binding energy clearly indicates that\nZn preferentially coordinates with the polymer matrix rather than with maltose.\nThese results further support our previous conclusion that strong Zn-polymer interactions\nhinder in-plane Zn mobility. The relatively weak Zn–maltose interaction allows maltose\nto subtly modulate the local solvation environment without significantly competing\nwith the polymer for Zn coordination, thus facilitating more efficient ion transport.\nWe have incorporated these new results and discussions into the revised manuscript.\nThank you again for your insightful recommendation.\nSupplementary Fig. 28 The binding energy of Zn with maltose.\n3. After the introduction of maltose, the electrolyte appears to possess a markedly\nenhanced water-retention capacity. Is this retention effect primarily a synergistic\ncontribution from both maltose and Zn(ClO ) . In other words, does Zn(ClO ) also\n4 2 4 2\ncontribute to the improved water retention in the hydrogel?\nResponse: Thank you for this valuable comment. To clearly identify the contribution\nof Zn(ClO ) and maltose to water retention, we have now conducted additional\n4 2\ncomparative experiments, including a pure Zw hydrogel (without additives) and a Zw\nhydrogel containing only 40 wt% maltose (without Zn(ClO ) ). These results, presented\n4 2\nin the revised supplementary information (Supplementary Fig. 14), demonstrate that\n41\nthe remarkable water-retention capability primarily originates from the interactions\nbetween maltose and the gel backbone. In contrast, the water-retention capability of the\nhydrogel containing only Zn(ClO ) is comparable to that of the pure Zw hydrogel,\n4 2\nindicating a negligible contribution from Zn(ClO ) .\n4 2\nThank you again for your insightful comment, which significantly improves the\nclarity of our conclusions.\nSupplementary Fig. 14 (b) Water-retention test of Zw, Zw + 3 m Zn(ClO ) and Zw +\n4 2\n40wt% maltose (Error bars represent standard deviation, SD).\n4. For improved clarity and reader comprehension, it would be helpful to include an\nadditional schematic illustrating how the flexible battery is constructed, as Figure S23\ndoes not clearly show the specific device architecture.\nResponse: Thank you for your valuable suggestion. We agree that a clearer schematic\nis essential for understanding the construction of the flexible battery. In response, we\nhave added a new illustration in Supplementary Fig. 35c, which clearly depicts the\nlayered architecture of the flexible Zn-based battery, including the zinc electrode,\nhydrogel electrolyte, and positive electrode. To further aid reader comprehension, we\nhave also provided a detailed description beneath the figure to explain the structural\ncomponents and assembly rationale. We believe this addition enhances the clarity of\n42\nour flexible device design and addresses your concern.\nSupplementary Fig. 35 (a) Schematic diagram of the structure of a flexible ZMB and\nits three key parameters (θ, R, L). (b) The thickness of a typical flexible battery device\n(hydrogel electrolytes with a thickness of ca. 300 µm). (c) Structure of flexible ZMBs.\n(d) A LED belt powered by three ZMBs connected in tandem.\n5. What is the thickness of the gel electrolyte used in the devices? Authors should\nclearly provide such information.\nResponse: Thank you for pointing this out. The thickness of the gel electrolyte used in\nall device configurations is approximately 300 μm. We have now clearly stated this\ninformation in the revised Methods section of the manuscript and Supplementary Fig.\n35.\nWe would like to thank all the Referees again for their constructive and valuable\ncomments and suggestions!\nReviewer #1 (Remarks to the Author):\nThe authors have addressed the comments satisfactorily. Therefore, the manuscript may\nbe accepted in the present form\nResponse: Thank you again for all your constructive suggestions and comments on\nreviewing our work.\nReviewer #2 (Remarks to the Author):\nThe authors have provided excellent responses. I agree to accept this paper.\nResponse: We appreciate all your constructive suggestions and comments for\nreviewing our work.\nReviewer #4 (Remarks to the Author):\nThe manuscript could be accepted for publication without change.\nResponse: Thank you again for your constructive suggestions and comments on our\nwork.\nReviewer #3 (Remarks to the Author):\nI went through the revised manuscript and the replies to the reviewers' comments. The\nauthors did not carefully modify the manuscript based on the comments concerning the\ncomputational calculations. The revised manuscript provides more issues than the\nearlier one. I already raised the issue of not performing simulations accurately. Further,\nthe added results raise more concerns. I also have serious concerns regarding the\nmethodology and reliability of the presented MD results.\nSo, the manuscript is not recommended for publication due to the following reasons.\nResponse: We sincerely thank you for the continued evaluation of our work. We are\nsorry that our previous revisions and responses did not adequately convey the\nmethodological details as well as the limitations of the MD component in our study. We\nalso appreciate this opportunity to carefully re-express the purpose of including MD in\nour work, clarify the specific methodology choices, and fully address your concerns\none by one. However, with respect, we wish to bring to your attention that about 80%\nof the content in this manuscript is about experimental evidence, and the conclusions\nof this work have been validated through combined spectroscopic analyses,\nelectrochemical measurements (including newly supplemented ones below), in\nconjunction with essential control experiments. In this specific work, while we fully\nrealize the value of theoretical calculations in supporting the experimental conclusions,\nwe did not aim to develop new methodologies or solve the disputes in the calculation\nsection. Following your suggestions, we have now, within the allowed timeframe of the\njournal, supplemented new DFT and MD results (following well-established, peer-\nacknowledged procedures/protocols, detailed below) with high rigor, full\nmethodological transparency, and robust reproducibility. All essential references\nstraddling experimental evidence and/or simulation protocols have been included in []\nin the following point-to-point responses for your direct check. We sincerely hope these\nnewly supplemented results and the following clarification can address your concerns,\nstrengthen and clarify the key conclusions of the work.\n1. The authors performed DFT calculations with a higher cutoff; however, the binding\nenergies reported in Figure 4 do not converge. Comparing the two cutoff values, four\nof the binding energy values increase with an increase in cutoff, and the other four\nvalues decrease. One value does not change. This means the cutoff values do not\nconverge for these systems, or these are improperly optimized to provide accurate\nbinding energies. One has to carefully choose the cutoff to get consistent values.\nResponse: Thank you for the follow-up comment. In our initial submission, we used a\ncutoff energy of 400 eV and an energy convergence criterion of 1.0 × 10-4 eV/cell.\nFollowing your prior recommendation, we revised all DFT calculations using a 600 eV\ncutoff and a tighter convergence threshold of 1.0 × 10-6 eV/cell.\nAs a result of these more stringent settings, we observed changes in some binding\nenergy values. While many adjustments were modest, a few values showed larger shifts,\nreflecting the re-optimization of surface–adsorbate configurations under more rigorous\nconvergence conditions. Nevertheless, the relative adsorption trends and surface\npreferences remained unchanged, which was the main purpose of our DFT analysis\n─ to qualitatively explain the facet-selective interaction behavior of Zn and the\nzwitterionic polymer groups, rather than to report absolute binding energy.\nFollowing your comments in the last round, we have also thoroughly re-examined\nour entire DFT workflow to understand the physical origins of the observed changes.\nSeveral plausible sources we identified are the slight displacement/rearrangement of\nthe Zn metal substrate that occurred during the calculation, and the possible\ninteraction between Zwitterion molecules due to periodic boundary conditions.\nTherefore, in this version, we introduce a surface-bulk like configuration in the slab\nmethods used, by allowing only the top 3 layers out of 5/6 layers to relax and\nmaintaining the rest of atoms to stay in their bulk coordinates. To avoid lateral\ninteraction due to periodic boundary condition, the (4×4) Zn (002) surface, (5×3) Zn\n(100) surface (3×3) Zn (101) surface were used to study the adsorption of Zn and\nZwitterion molecules.\nFurthermore, to ensure clarity and reproducibility, the details of new DFT results\nare based on the convergence criteria of electronic and geometric optimizations\nwith energy difference of 1 × 10-6 eV and force below -0.02 eV/Å. The Monkhorst-\nPack k-points of 5 × 5 × 1 were used to sample the Brillouin zone. All these settings\nwere justified based on the energy convergence criteria, as shown in Supplementary\nFig. 44 and Supplementary Table 2. We have taken the convergence requirement\nstrictly in this revision, and the selection of parameters of energy cut-off of 600 eV and\nthe Monkhorst-Pack k-points of 5 × 5 × 1 were sufficient to produce credible electronic\nenergy from DFT for the calculation of binding energies.\nIt is also important to note that the orientation of Zwitterion molecules can\nnoticeably change the binding energy profile, and in this version, we focused mostly on\nthe vertical adsorption of the molecule, which mainly involves the interaction between\nsurface Zn atoms and the oxygen atoms of Zwitterion moiety. The updated adsorption\nenergy results are now presented in Fig. 4g along with the specific adsorption structures.\nWe firmly believe that these new results can provide full transparency of the\ncomputational details and allow reproducibility. We also provide additional information\non how the values change from previous versions, by showing the main possible issues\nrelated to the changes of binding energy (See Table R1 below). We hope these revisions\ncan fully address your concerns regarding DFT calculations. Thanks in advance for\nyour consideration.\nTable R1. Comparison of binding energy and key considerations\nSystems Previous Previous concerns (Main) This version\nversions (eV) (eV)\nZn (002) – Zn -0.6 / -0.43 Surface reconstruction -0.61\nZn (002) – ZW -1.81 / -2.31 Lateral interaction between ZW -1.61\nZn (100) – Zn -1.7 / -1.91 ENCUT and K-points -1.94\nZn (100) – ZW -3.64 / -3.33 Lateral interaction between ZW -2.63\nZn (101) – Zn -1.58 / -1.09 Surface reconstruction -1.25\nZn (101) – ZW -1.99 / -2.54 Lateral interaction between ZW -1.68\nSupplementary Fig. 44 Convergence behavior of total energy with respect to\ncomputational parameters in DFT calculations. Energy difference is calculated from the\nelectronic energy at a particular plane-wave cutoff energy (ENCUT) and number of K-\npoints relevant to the electronic energy at each highest ENCUT and K-points value. (a)\nEnergy difference as a function of ENCUT. (b) Energy difference as a function of the\nnumber of K-points. The energy variation becomes negligible (within ±0.01 eV) when\nENCUT ≥ 600 eV and K-points ≥ 25.\nSupplementary Table 2. Summary of total energy and energy difference values under\nvarying ENCUT and K-point configurations used for convergence validation.\nEnergy\nEnergy\nENCUT K-POINT Difference\nDifference\n1×1×1 1 -123.18 -6.47\n400 -116.48 1.07E-01\n2×2×1 4 -115.93 0.78\n450 -116.54 4.49E-02\n3×3×1 9 -116.54 0.16\n500 -116.57 1.73E-02\n4×4×1 16 -116.63 0.07\n550 -116.58 5.56E-03\n5×5×1 25 -116.58 0.12\n600 -116.58 1.00E-05\n6×6×1 36 -116.67 0.03\n650 -116.59 -3.55E-03\n7×7×1 49 -116.70 0.00\n700 -116.58 0.00E+00\nFig. 4g Relaxed calculation models for Zn2+ and Zw monomer adsorption onto different\nplanes along with corresponding adsorption energy values; the binding energies of Zw\nwith Zn and water molecules, as well as the adsorption of H O onto the Zn (002) plane,\n2\nare presented.\n2. There are many issues with the MD methods and the obtained results. \"The system\nwas annealed from 200 to 500 K. While all electrolyte systems were investigated at\n298.15 K, only CZHE and LE were further examined at 213.15 K.\" Why was the target\ntemperature not maintained during annealing?\nResponse: Thanks for the comment. In the previous version of MD simulations, we\nfollowed the reported protocols recommended in some recent publications [e.g., Nat.\nCommun. 2024, 15, 302; Nat. Commun. 2024, 15, 8866; Nat. Sustain. 2025, 8, 530–\n541; Nat. Energy 2023, 8, 1365–1374] on analogous fields, namely, performing MD\nsimulations over a temperature range (e.g., 200–500 K) without maintaining the target\ntemperature during annealing. In these studies, the annealing process was used to\npromote structural relaxation and achieve uniform dispersion of the system constituents.\nFollowing the same considerations, we applied this method to obtain physically\nmeaningful and homogeneously mixed initial structures.\nHowever, we agree with your recommendation that maintaining the temperature\ncould have non-negligible effects. Hence, we have re-performed all MD simulations\nwith the updated protocol, adopting a multi-step annealing procedure using NPT\nensemble, with temperature and pressure coupling achieved through the Nose-Hoover\nand Parrinello-Rahman methods. The new annealing scheme was also combined with\na much longer 100 ns production run in NVT ensemble at 298.15 K and 213.15 K to\nensure adequate equilibration and accurate representation of the system. To help readers\nbetter understand and reproduce the results, the details of this updated annealing\nprocedure are now illustrated in Supplementary Fig. 45. Unless otherwise stated, all\nMD results presented in the revised manuscript are based on this updated simulation\nworkflow. The Computational methods section has been revised accordingly for\nclarity and completeness.\nSupplementary Fig. 1 Annealing protocol employed prior to production simulations\nat (a)298.15 K and (b) 213.15 K.\nThe system was initially pre-equilibrated at 298.15 K, followed by a stepwise\nannealing process consisting of heating to 500 K, cooling to 400 K, and then to\n298.15 K and 213.15 K. Each temperature step was held for 5–10 ns to promote\nstructural relaxation and homogeneous mixing. After annealing, independent 100 ns\nproduction runs were conducted at 298.15 K and 213.15 K, with the last 80 ns used for\nanalysis.\n3. The MD parameters are either missing or not presented accurately by the authors.\nFor example, \"The temperature was performed in Nose method.\" What are the\nparameters and relevant references?\nResponse: Thank you for raising this important comment. We are sorry that the\ndescription of our MD simulation in the previous manuscript was somehow\noversimplified. In the revised manuscript, we have now included complete details of\nsimulation parameters and algorithms that ensure reproducibility. We have revised the\nComputational Methods section, as shown below. Thank you again for the critical\nsuggestions to improve the quality of the manuscript.\nRevisions in the Methods section:\nAll molecular dynamics (MD) simulations were performed using an open-access\nGROMACS software package with the GAFF2 force field. [J. Comput. Chem. 25,\n1157-1174 (2004)] In this study, there are three models studied considering the presence\nof zwitterionic (Zw) hydrogel (poly[(3-(methacryloylamino)propyl)dimethyl(3-\nsulfopropyl)ammonium hydroxide] with 4 repeated units) and maltose as the additives.\nThe simulation box size of 5×5×5 nm3 was used as the initial box in all simulation\nmodels. First, a model of 3 m Zn(ClO ) consists of 150 Zn(ClO ) and 2778 H O\n4 2 4 2 2\nmolecules. Second, 3 m Zn(ClO ) 40wt% maltose with Zw hydrogel electrolyte\n4 2\nconsists of 90 Zn(ClO ) , 1667 H O, 59 maltose and 26 Zw polymer molecules. Third,\n4 2 2\n3 m Zn(ClO ) 40% maltose consists of 90 Zn(ClO ) , 1667 H O and 59 maltose\n4 2 4 2 2\nmolecules. Fourth, 3 m Zn(ClO ) with Zw hydrogel electrolyte consists of 90\n4 2\nZn(ClO ) , 1667 H O and 26 Zw polymer molecules.\n4 2 2\nAt the beginning of the simulation, structure and energy minimization of the\nsystems were conducted. The ACPYPE was employed to obtain the GAFF2 force field\ntopology.[ BMC research notes 5, 1-8 (2012)] The system was initially relaxed in the\nNVT ensemble at 298.15 K for 10 ns after the steepest descent minimization. Then it\nwas annealed between 298.15 and 500 K for 5 ns, between 500 and 400 K for 5 ns, and\nbetween 400 and 298.15 K for 5 ns using the NPT ensemble (illustrated in\nSupplementary Fig. 45), with temperature and pressure coupling achieved through the\nNose-Hoover and Parrinello-Rahman methods.[J. Appl. Phys. 52, 7182-7190 (1981); J.\nChem. Phys. 81, 511-519 (1984); Nature 416, 409-413 (2002); Nat. Commun. 14, 601\n(2023)] Additional annealing using NPT ensemble was also conducted for 10 ns at\n213.15 K. The pressure was maintained at 1 bar. The electrostatic interactions were\ncomputed using PME methods. The final production run was conducted in NVT\nensemble at 298.15 K for 100 ns. A FTT grid spacing of 0.1 nm and cubic interpolation\nfor charge distribution were used to compute electrostatic interaction in reciprocal space.\nThe cut-off distance of 1.2 nm was adopted for electrostatics and Van der Waals\ninteractions. The Velocity Verlet integrator was adopted with a time step of 1 fs. The\nsolvation structures analysis, including the distribution of contact ion pairs (CIP) and\nsolvent-separated ion pairs (SSIP), and the radial distribution function and coordination\nnumber analysis, were performed using the trajectory from the last 80 ns out of 100 ns\nsimulation time. The definition of the Zn2+-anion coordination structures is illustrated\nin Supplementary Fig. 2. Trajectories were analyzed by MDAnalysis code whenever\nthe respective tool was unavailable in GROMACS.[Report No. 2575-9752, (Los\nAlamos National Laboratory (LANL), Los Alamos, NM (United States), 2019); J.\nComput. Chem. 32, 2319-2327 (2011)]\nTo further investigate the influence of electric field on the drift of Zn2+ ions at\n298.15 K, another multi-step run using NVT ensemble with static electric fields in z-\ndirection of 0.1, 0.5, 1 and 2 V/nm for each 10 ns was conducted [Joule 2019, 3, 2761–\n2776; J. Am. Chem. Soc. 2025, 147, 25896-25909], which was then followed by final\nproduction run in NVT ensemble for 100 ns (Supplementary Fig. 47-49,\nSupplementary Table 3).\n4. \"Finally, a series of 8 ns production simulations were run for post-processing\nanalysis.\" 8 ns simulation time is not appropriate for dense systems.\nSpecifically, the MD simulations were limited to 8 ns, which is generally insufficient\nto reach the diffusive regime. Diffusivity estimation based on such relatively short\ntimescales(considering the density of the systems) is likely to be affected by the initial\nballistic motion and significant statistical noise. As a result, the interpretation built upon\nthese simulations is not well-supported. To support reliable transport analysis, One can\nexpect significantly longer simulation times (on the order of hundreds of nanoseconds\nor longer, ideally accompanied by multiple independent trajectories for uncertainties.\nConsidering the square root of MSD values, the entities do not show any multiple\nsolvation shell crossing. A log-log plot of MSD versus time or any other mathematical\nparameter should also confirm that the system has entered the diffusive regime.\nResponse: Thanks for the comments. We apologize for not clarifying this point in the\nprevious revision and would like to justify the new results in detail below.\nWe agree with you that diffusivity estimation based on relatively short timescales\n(a few ns or shorter) could be affected by the initial ballistic motion and statistical noise.\nTo address your concern, in this version, we have now extended all MD simulation\ndurations to 100 ns for each of the six electrolyte systems studied, within the allowed\nrevision time from the journal. Specifically, 3 m Zn(ClO ) , Zn(ClO ) + Zw gel,\n4 2 4 2\nand CZHE were simulated at room temperature (298.15 K), and LE and CZHE\nwere further compared at the low temperature (213.15 K), all using the workflow\nsummarized in Supplementary Fig. 45. The primary goal of these extended\nsimulations was to ensure more reliable evaluation of the structural characteristics in\nthe statistically reliable diffusive regime, including radial distribution functions (RDFs),\ncoordination numbers (CNs), and the distribution of solvated ion species (e.g., contact\nion pairs (CIP) and solvent-separated ion pairs (SSIP)), all are directly related to the\nsolvation environments and ion–gel interactions in the electrolytes.\nAs shown in Figure R1, within the extended simulation time, all MSD Log-Log\nplots generally show good linearity (all slopes within the range of [0.95, 1.05]).\nTherefore, it is safe to conclude that all the six simulation systems have entered the\ndiffusive regime. This ensures that the subsequent analysis of all the above parameters\nis reliable. As now shown in Fig. 2i, 2j, 6b, 6c and Supplementary Fig. 5, 6, 7, 41, the\nRDFs and CNs of the electrolytes have been updated (the distribution of solvated\nion species will be discussed in detail in response to your Comment 5 below). It is clear\nfrom these updated results that the tuned coordination environments by the Zw matrix\nenable Zn2+ with less solvated water and fewer interactions with anions within its\nprimary solvation shell, at both room temperature (298.15 K) and low temperature\n(213.15 K). These results are also highly consistent with experimental results from the\ncombined spectroscopic measurements, electrokinetic analyses, and rate-performance\nvalidation in batteries across different temperatures.\nFigure R1. Log-log plots of the mean square displacement of Zn2+ in different\nelectrolytes within the 100 ns simulation time; the dash lines indicate the diffusive\nregime.\nFig. 2 Radial distribution functions and corresponding coordination plots of Zn2+ in (i)\nLE and (j) CZHE.\nFig. 6 b Radial distribution functions and corresponding coordination plots of Zn2+ in\nCZHE at -60 oC. c Comparison of Zn2+ solvation structures in CZHE and LE at -60 oC.\nSupplementary Fig. 5 Snapshots of the MD simulation cell for (a) LE and (b) CZHE.\nSupplementary Fig. 6 (a) A snapshot of the MD simulation of 3 m Zn(ClO ) .\n4 2\n(b) Corresponding RDF plots.\nSupplementary Fig. 7 (a) A snapshot of the MD simulation of Zw + 3 m Zn(ClO ) .\n4 2\n(b) Corresponding RDF plots.\nSupplementary Fig. 41 Comparison of RDF plots of LE at (a) 25 oC and (b) -60 oC.\nAll the above MD simulations were performed without an applied electrical field.\nHowever, it must be emphasized that the Zw matrix will only align under an\napplied electric field (at least initially) to form ordered ion transport channels,\nwhich has been experimentally corroborated [e.g., Nat. Commun. 2016, 7, 11782; J. Am.\nChem. Soc. 2022, 144, 19344-19352; Chem. Soc. Rev. 2019,48, 757; Langmuir 2007,\n23, 6937; J. Polym. Sci. B Polym. Phys. 2004, 42, 3513]. Also, several key\nelectrochemical processes (e.g., Zn2+ deposition) involve certain applied electric fields.\nAs such, it is mandatory to investigate the system in response to external electric fields\nto genuinely reflect the effect of the Zw matrix on Zn2+ drift. Therefore, following\nprotocols reported in several previous works [e.g., Joule 2019, 3, 2761–2776; Nat.\nCommun. 2023, 14, 3066; J. Am. Chem. Soc. 2025, 147, 25896-25909; J. Am. Chem.\nSoc. 2025, 147, 8488–8499; J. Am. Chem. Soc. 2025, 147, 5943-5954], we further\ninvestigated the MSD of Zn2+ in LE and CZHE at 298.15 K, both upon a moderate\nconstant electric field of 2 V/nm in the z-direction in the NVT ensemble. The detailed\nsimulation procedures are summarized in Supplementary Table 3 to enable\nreproducibility.\nAs shown in the snapshots in Supplementary Fig. 47, 48, the Zw gel matrix under\nthe electric field indeed exhibits noticeable chain alignment and orientation along the\ndirection of the field (namely, z-direction), in contrast to the random, coiled matrix\nwithout the electric field. With this structural advantage, the MSD plots in the updated\nFig. 2k reveal that Zn2+ diffusion in CZHE is obviously expedited compared to the case\nin LE (without Zw matrix). Further, we extracted the Zn2+ migration trajectory along\nthe electric field (z-direction). The drift plots in Supplementary Fig. 49 unravel that\nZn2+ are indeed accelerated along the aligned channels in CZHE. These combined\nresults highlight the unique advantages of Zw gel matrix in affording better ion\nconduction as well as transference number [Phys. Rev. Lett. 128, 198002 (2022)].\nWe would like to thank you again for raising this critical point, which has prompted\nus to clarify the MD details with high calibre and reproducibility. We believe these\nresults can support the key conclusions of our work, and we hope all these supplements\nand justifications can address your concerns. We have properly discussed all these\nupdates in the revised manuscript, please see highlighted texts on Pgs 10, 11, 21, 28-\n30, and Methods section in the Supplementary Information. Thanks in advance for\nyour consideration.\nSupplementary Fig. 3 MD snapshots of the CZHE without an applied electric field.\nThe gel framework exhibits random, non-directional alignment. Red arrows illustrate\nthe disordered orientation and interchain interactions within the gel matrix.\nSupplementary Fig. 48 MD snapshots of the CZHE under an applied electric field\nalong the z-direction. The gel framework exhibits noticeable chain alignment and\norientation along the direction of the field (indicated by blue arrows), in contrast to the\ndisordered configuration observed without the electric field.\nFig. 2k MSD plots of Zn2+ in LE and CZHE under electric field at 25 oC.\nSupplementary Fig. 4 Zn2+ drift under z-direction electric field in (a) CZHE, and (b)\nLE.\nZn2+ drift distance along the z-direction electric field was calculated using the\nfollowing equation:\n𝑁𝑁\n1\n𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝑑𝑑𝐷𝐷𝑑𝑑𝐷𝐷𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑(𝐷𝐷) = [𝑧𝑧𝑖𝑖(𝐷𝐷)−𝑧𝑧𝑖𝑖(0)]\nWhere z\ni\n(t) is z-coordinate of ion i at time t, 𝑁𝑁z\ni\n(0𝑖𝑖=) 1is initial z-coordinate of ion i at t = 0.\nN is number of Zn2+ considered.\nStandard deviation of drift distance at time t was obtained from the\ndistribution of individua(l𝜎𝜎 i𝑑𝑑o𝑑𝑑n𝑖𝑖𝑑𝑑 d𝑑𝑑(is𝐷𝐷p)l)acements as:\n𝑁𝑁\n1 2\n𝜎𝜎𝑑𝑑𝑑𝑑𝑖𝑖𝑑𝑑𝑑𝑑(𝐷𝐷) =  (∆𝑧𝑧𝑖𝑖(𝐷𝐷)−∆𝑧𝑧(𝐷𝐷))\n𝑁𝑁𝑖𝑖=1\nWhere Δz(t) = z(t) - z(0) is net drift displacement of ion i along the z-axis,\ni i i\nis the average drift displacement at time t,\n1 𝑁𝑁\n∆ N 𝑧𝑧 == 90𝑁𝑁 f∑or 𝑖𝑖= t 1 he∆ 𝑧𝑧9 𝑖𝑖 0( 𝐷𝐷Z)n2+ considered.\nSupplementary Table 3. MD simulation procedures\nStep Stage Ensemble Time Temperature Thermostat Pressure Barostat Electric Field\nns (K) (bar) Strength\nAdditional\n4-b equilibration for NPT 10 298.15 – 213.15 NH 1 PR -\nLT\nAdditional equilibration under Electric Field\nEquilibration\nwith Electric\nField\nProduction with\nElectric Field\nAbbreviations: NH = Nose-Hoover, PR = Parrinello-Rahman.\n*Time step of 1.0 fs was used.\n5, The presented CIP and SSIP values mostly added up to exactly 100%. This means\nother types of structures are not obtained except CIP and SSIP. This is doubtful. Further,\nthe definitions of CIP and SSIP are not provided, which raises concerns about\nreproducibility. What are the reasons for not obtaining any other type of ion pairs and\nthe standard deviation in the obtained CIP and SSIP values?\nResponse: Thanks for your attention to the quantification of ion pairing structures in\nour MD analysis. We understand this concern and would like to provide a detailed\nexplanation and justification below.\nFirst, we sincerely apologize for not providing explicit definitions of CIP and SSIP\nin the previous version, which may have caused confusion. To address this, we have\nnow revised the manuscript with the widely accepted classification framework for\ncation and anion interactions in metal-ion battery electrolytes [Nat. Energy 6, 303–313\n(2021); Nat. Energy 7, 1217–1224 (2022); Nat. Commun. 13, 4538 (2022); Nat.\nMater. 22, 1531–1539 (2023); Nat. Chem. 16, 922–929 (2024); Nat. Energy 9, 1285–\n1296 (2024); Nat. Nanotechnol. 20, 798–806 (2025); Nat. Commun. 16, 2979 (2025)].\nThis is also the basis of our own analysis in this work. These include three distinct\naggregation states:\n• Solvent-separated ion pairs (SSIP): solvated metal ion without direct interaction\nwith anion\n• Contact ion pairs (CIP): metal ion coordinated with anion\n• Aggregates (AGG): an anion coordinated with two or more metal ions\nIn the context of aqueous Zn electrolytes, this framework is typically applied as\nfollows [Nat. Rev. Chem. 9, 102–117 (2025)]:\n• SSIP: [Zn(H O) ]2+-Anion\n2 6\n• CIP: Zn2+ -xAnions, x≤2\n• AGGs: Zn2+ -xAnions, x≥3\nAn illustration figure regarding these three species has been supplemented in\nSupplementary Fig. 46 for better understanding.\nSecond, Raman spectroscopy is powerful in detecting the coordination\nenvironments of anions, thus has been widely adopted to provide such information. In\nour study, the aqueous 3 m Zn(ClO ) electrolyte falls within the dilute concentration\n4 2\nregime. It has been well established by experimental and computational studies [e.g.,\nNat. Commun. 16, 71 (2025); Chem, 10, 3607 – 3621 (2024); ACS Nano 11, 10462–\n10471 (2017)] that in such dilute systems, most Zn2+ species exist as SSIPs, with a\nsmall fraction forming CIPs. The AGGs formed under these conditions are extremely\nlimited and often below the detection threshold of common experimental\ntechniques. On the other hand, blue shifts in Raman peaks [Nat. Rev. Chem. 9, 102–117\n(2025); Angew. Chem. Int. Ed. 64, e202418242 (2025)], typically corresponding to\nenhanced anion coordination, can serve as reliable indicators of AGGs formation.\nHowever, our Raman spectra analysis proves that despite the introduction of\nmaltose, zwitterionic gel, or a combination of both into the 3 m Zn(ClO ) electrolyte,\n4 2\nno blue shifts in the characteristic peaks associated with anion coordination were\ndetected (Supplementary Fig. 1b, 2b). We have also included a red bar in\nSupplementary Fig. 1b, 2b to highlight the absence of AGGs.\nFurthermore, we supplemented peak deconvolution of the anion-related Raman\nbands to quantify the relative portions of CIP and SSIP in Supplementary Fig.\n1f,1g,2f,2g, and the results are summarized in Supplementary Table 1. These\nexperimental results collectively validate that in all electrolytes involved in this work,\nthe dominant ion-pairing structures are SSIP and CIP, with negligible AGGs.\nTherefore, in the discussion regarding solvated cation species (Zn2+ structures), we\nquantified SSIP and CIP only (free anion has no coordination with cation), and\nnormalized their total portion to 100%. This approach allows us to clearly track\nvariations in CIP fraction, which is the key structural feature of interest in understanding\nion migration behavior and electrochemical performance [Nat. Rev. Chem. 9, 102–117\n(2025); Phys. Rev. Lett. 128, 198002 (2022)].\nIt is also worth mentioning that, as a classic inner salt compound, Zw matrix moiety\ncan intrinsically assist the dissociation of typical salts [Nat. Mater. 3, 29-32 (2004); Nat.\nMater. 21, 228-236 (2022)]. This is one of the key advantages of such compounds as\nelectrolyte matrices or additives, and a key design incentive for this work. Therefore,\nrather than agglomerating ions, the Zw matrix can actually suppress the formation of\nCIP or AGGs. It can also be concluded from all the Raman results that the CIP portion\nof the two liquid electrolytes has reduced as long as the Zw matrix was introduced:\n19.7% in 3 m Zn(ClO ) vs. 15.6% in 3 m Zn(ClO ) + Zw gel (both dilute electrolytes),\n4 2 4 2\nand 40.4% in LE vs. 23.1% in CZHE (both crowded electrolytes). These results further\nreinforced the key conclusions in this work.\nAs for MD simulations, we have also calculated the solvated cation species\nfollowing the same definition in Supplementary Fig. 46. Based on the re-performed\nMD simulations with extended production times and the confirmed diffusive regime,\nwe re-evaluated the CIP and SSIP fractions, and the updated results are summarized\nin Supplementary Fig. 8. While we cannot rule out the possibility of trace-level AGG-\nlike configurations due to thermal fluctuations, our results suggest that they are\nnegligible and structurally irrelevant in all the systems. If such transient configurations\ndo arise, they are inherently indistinguishable from loosely coordinated multi-anion\nCIPs in our system. Therefore, we categorized the solvated cation species into CIP and\nSSIP in the manuscript with a total portion of 100% to avoid unnecessary confusion.\nThe error bars of these statistically reliable results are also provided in Supplementary\nFig. 8 to ensure consistency and reproducibility. More importantly, the relative changes\nin CIP and SSIP populations derived from the extended MD simulations are also in\ngood agreement with the above Raman spectral results, thus validating the reliability\nof our computational interpretation.\nWe sincerely appreciate your comments and suggestions regarding this point, which\nhelped us strengthen the consistency between our experimental observations and\nsimulations. We believe the supplemented definition, illustration, table, and updated\nresults can convey clear conclusions with high reproducibility.\nSupplementary Fig. 46 Concentration-dependent Zn2+-anion coordination structures\nin zinc salt electrolytes: solvent-separated ion pairs (SSIP), contact ion pairs (CIP), and\naggregates (AGG).\nSupplementary Fig. 1 (b) Corresponding magnified section in the range of 860–1000\ncm-1 highlighting characteristic peaks corresponding to SSIP (936.8 cm-1), CIP (942.1\ncm-1), and absence of AGGs (950.7 cm-1, highlighted in red bar). (f) The fitted peaks of\nbare 3 m Zn(ClO ) electrolyte for ClO --related vibrations. (g) The fitted peaks of LE\n4 2 4\n(3 m Zn(ClO ) with 40 wt % maltose) for ClO --related vibrations. Note: Peaks at 922.0,\n4 2 4\n933.3, 936.8, 942.1, and 950.7 cm⁻¹ were assigned to the v - ClO - overtone, free ClO -,\n2 4 4\nSSIP, CIP and AGGs, respectively.\nSupplementary Fig. 2 (b) Corresponding magnified section in the range of 860–1000\ncm-1 highlighting characteristic peaks corresponding to SSIP (936.8 cm-1), CIP (942.1\ncm-1), and absence of AGGs (950.7 cm-1, highlighted in red bar). (f) The fitted peaks of\nZw hydrogelelectrolyte impregnated with 3 m Zn(ClO ) for ClO --related vibrations.\n4 2 4\n(g) The fitted peaks of CZHE (Zw with 3 m Zn(ClO ) 40 wt% maltose hydrogel\n4 2\nelectrolytes) for ClO --related vibrations.\ndifferent electrolytes at different temperatures from MD simulations.\nSupplementary Table 1. Comparison of CIP and SSIP based on Raman spectral\nanalysis in various electrolytes at room temperature (~20 °C).\nElectrolytes CIP SSIP\nCZHE 23.1% 76.9%\nLE 40.4% 59.6%\nZn(ClO ) 19.7% 80.3%\n4 2\nZn(ClO ) + Zw gel 15.6% 84.4%\n4 2\nWe would like to sincerely thank all Reviewers again for their constructive\nsuggestions and comments throughout the reviewing work!\nReviewer #3 (Remarks to the Author):\nI thank the authors for their efforts to rectify many issues earlier mentioned in the\nmanuscript. I am still not convinced that CIP and SSIP will add up to exactly (emphasize)\n100%, as statistical averaging of molecular dynamics does not work in this way. At least\nsome other structures should be there, which have not been analyzed properly. Further,\nthe authors did not understand the comment on the definition of CIP and SSIP. One has\nto define some conditions (distance, angle, wrt center of mass or atom based etc...) to\ndevelop an algorithm to find these structures. One has to defend the basis of these\nparameters, which are used to screen the CIP and SSIP. The manuscript fails to provide\nappropriate evidence of these structures, which can be reproducible. I am not sure why\nthe RAMAN expt also provides 100% adding CIP+SSIP. So, I am doubtful of these\nvalues.\nHaving said this, I also do not agree with the impression that computational calculations\nwere performed only to validate the experimental findings. The agreement will not\nalways happen. The theories are made to have some fluctuation from experiments.\nFurther, any results reported in a prestigious journal should be reproducible and error-\nfree. So, I request that the editor may take a decision on the manuscript considering all\naspects.\nResponse: We thank the reviewer for the careful reassessment and for acknowledging\nour efforts to address the earlier concerns. We highly appreciate the reviewer’s detailed\ncomments and would like to take this opportunity to further clarify our definitions and\nanalyses of CIP and SSIP.\n1. Regarding Reviewer #3’s comment “I am not sure why the Raman experiment also\nprovides 100% adding CIP + SSIP. So, I am doubtful of these values.”, we are sorry for\nnot providing a clearer explanation in the previous version, which may have caused\nconfusion. We are particularly grateful to Reviewer #4 for pointing out relevant\nexamples (Science 2021, 374, 172–178, and Nature Materials 2023, 22, 1531–1539) that\nhelp clarify this point. Following the same rationale, in electrolyte cluster analyses,\nthe focus is typically placed on ion-pairing (cation and anion) species that are directly\nrelevant to energy storage ─ namely, SSIP, CIP, and AGG. When all three species are\ndetectable, their relative populations are generally normalized to 100%. Conversely,\nwhen one species is nearly undetectable, such as showing no discernible Raman peak,\nthe remaining two are generally treated as comprising 100% of the composition.\nIn our case, the aqueous 3M Zn(ClO ) electrolyte falls within the dilute\n4 2\nconcentration regime. It has been well established by experimental and computational\nstudies (e.g., Nat. Commun. 2025, 16, 71; Chem, 2024, 10, 3607 – 3621; ACS Nano\n2017, 11, 10462–10471) that in such dilute systems, most Zn2+ species exist as SSIPs,\nwith a small fraction forming CIPs. The AGGs formed under these conditions are\nextremely limited and often below the detection threshold of common experimental\ntechniques like Raman. On the other hand, blue shifts in Raman peaks (Nat. Rev.\nChem. 2025, 9, 102–117; Angew. Chem. Int. Ed. 2025, 64, e202418242), typically\ncorresponding to enhanced anion coordination, can serve as reliable indicators of AGGs\nformation. However, our Raman spectra prove that no such blue shifts in the\ncharacteristic peaks associated with anion coordination were detected in all samples.\nWe have also included a red bar in Supplementary Fig. 1b, 2b to highlight the\nabsence of AGGs.\nBased on this rationale and previous works, in the discussion regarding solvated\ncation species (Zn2+ structures), we quantified SSIP and CIP only (free anion has no\ncoordination with cation), and normalized their total portion to 100%. This approach\nallows us to clearly track variations in CIP fraction, which is the key structural feature\nof interest in understanding ion migration behavior and electrochemical performance\n(Science 2021, 374, 172–178, Nature Materials 2023, 22, 1531–1539).\nTo avoid any possible confusion, we have now added this clarification in the Note\nof Supplementary Fig. 1, with the key references mentioned above cited to explain the\nnormalization basis. We believe this addition will eliminate potential ambiguity and\nimprove the transparency of our data interpretation.\n2. Regarding the comment from Reviewer#3 on “the definition of CIP and SSIP”, we\nagree that an explicit and physically grounded definition is critical for reproducibility\nand clarity. As explained in our previous response, our classification follows the widely\nadopted framework in this research field, where the clusters (SSIP, CIP, and AGG) are\ncategorized based on the cation–anion coordination number (CN) obtained from MD\nsimulations. As correctly pointed out by the Reviewer#3, the cation–anion distance\nplays a crucial role in determining the CN, and we truly appreciate his/her reminder to\nclarify this important criterion, which we have now explicitly added. In our CN analysis,\nZn2+ and ClO - are considered coordinated when the Zn²⁺ ion lies within 2.3 Å of\n4\nany oxygen atom of ClO -. This cutoff distance was derived from the Zn–O(ClO -)\n4 4\nradial distribution function (RDF), where 2.3 Å corresponds to the first minimum\nfollowing the primary peak, representing the boundary of the first coordination shell\n(see Fig. 2i, 2j, 6b, and Supplementary Figs. 6, 7, and 41). This distance is consistent\nwith the cation–anion coordination thresholds reported in other aqueous zinc battery\nstudies (Nat Commun 14, 3067 (2023); Nat Commun 14, 2720 (2023); Angew. Chem.\nInt. Ed. 63, e202410210 (2024)). Based on the coordination numbers determined by\nthis definition, the ion-pairing species are further classified as illustrated in\nSupplementary Fig. 46. This CN-based approach is consistent with the methodologies\nused in recent literature on aqueous and hybrid electrolytes (Nat. Rev. Chem. 9, 102–\n117 (2025)), and the complete description has now been included in the Methods\nsection for transparency and reproducibility.\n3. Regarding the existence of AGG species under this definition, we would like to\nreiterate the clarification provided previously. While we cannot completely rule out the\npossibility of trace-level AGG-like configurations that may transiently appear due to\nthermal fluctuations in molecular dynamics trajectories, our results consistently\nindicate that such configurations are negligible and structurally irrelevant in all\ninvestigated systems. If these transient configurations do arise, they are inherently\nindistinguishable from loosely coordinated multi-anion CIPs, both in terms of their\ngeometric characteristics and their short lifetimes. Therefore, introducing AGG as a\nseparate category would not provide additional physical insight but rather introduce\nunnecessary ambiguity.\n4. Regarding the reviewer’s comment that “Having said this, I also do not agree with\nthe impression that computational calculations were performed only to validate the\nexperimental findings.” we sincerely apologize for the misunderstanding, but we did\nnot intend to convey this impression. We fully acknowledge that computational\ncalculations are an advanced and powerful approach that provides valuable information\nin this work. Our intention was only to emphasize that in this work, we did not aim to\ndevelop new methodologies or solve the disputes in the calculation section. Instead, we\nhave now, within the allowed timeframe of the revision, supplemented new DFT and\nMD results following well-established, peer-acknowledged procedures/protocols, with\nhigh rigor, full methodological transparency, and robust reproducibility. We therefore\nbelieve that these computational results can fully and correctly support our conclusions.\nFinally, we would thank the reviewer again for the valuable and constructive comments.\nThese suggestions have helped us further clarify the definitions, analytical methods,\nand presentation of both experimental and computational results.\nReviewer #4 (Remarks to the Author):\nAt your request, I am pleased to reassess the latest revision, including the\npoint-by-point rebuttal (comment #5, pp. 20–25) and revised manuscript, with care\nand interest. Overall, I believe the record presents compelling responses from the\nauthors. I also provide the following observations on Reviewer #3’s remaining\nconcernsaboutthe CIPand SSIPissues.\n1.CIPandSSIP adduptoexactly 100%\nInstudies ofsalt-solvent clusters (SSIP,CIP andAGG) in electrolytes,itis possible in\nboth experiments (like Raman in this work) and simulations (like MD) to report\nfractions that sum to 100% over the states analyzed. It is particularly common when\none state (e.g., SSIP or AGG) is not detected or is operationally negligible (below\ndetection limit) under the measurement/simulation conditions, thus normalizing the\nremaining states to 100%. This practice is acceptable, and several high-calibre works\nhave reportedsuchresults.I havelisted two ofthem belowfor yourreference:\nScience 374, 172-178 (2021) Fig. 3c (Only SSIPs and CIPs, with a sum of 100%.)\nFigure Redacted\nFigure Redacted\n2. Why the RAMAN experiment also provides 100% adding CIP+SSIP\nIn light of Reviewer #3’s concern, I reviewed the Raman data and the cited references.\nThe peak assignments reported by the authors are correct and consistent with the cited\nreferences; no AGG feature (which would otherwise show obvious blue shifts) is\ndiscernible in the relevant Raman region under the stated conditions. On this basis,\nnormalizing CIP and SSIP to a combined 100% is appropriate. I think the authors had\nalready provided reasonable justification/explanation for this result in the latest\nresponse:\n“These experimental results collectively validate that in all electrolytes involved in\nthis work, the dominant ion-pairing structures are SSIP and CIP, with negligible\nAGGs. Therefore, in the discussion regarding solvated cation species (Zn2+\nstructures), we quantifiedSSIPandCIPonly (freeanionhasnocoordinationwith\ncation), and normalized their total portion to 100%. This approach allows us to\nclearly track variations in CIP fraction, which is the key structural feature of interest\ninunderstanding ion migrationbehavior andelectrochemical performance.”\n“While we cannot rule out the possibility of trace-level AGG-like configurations due\nto thermal fluctuations, our results suggest that they are negligible and structurally\nirrelevant in all the systems. If such transient configurations do arise, they are\ninherently indistinguishable from loosely coordinated multi-anion CIPs in our system.\nTherefore, we categorized the solvated cation species into CIP and SSIP in the\nmanuscript withatotalportion of100% to avoidunnecessaryconfusion”\n3.The sufficiency and reproducibility of the SSIP,CIP and AGG definitions,and\ntheassociatedcomputational classification\nI examined the definitions and citations the authors use for SSIP, CIP, and AGG. The\nmanuscript applies consensus definitions reflected in recent authoritative sources.\nUsing thisestablishedterminology supports clarity andcross-studycomparability.\nHaving said so, I also respect Reviewer #3’s request for explicit operational\ncriteria, for example distance, as a transparency measure. For completeness and ease\nof reproduction, it would be helpful if the authors state explicitly in the SI the\nnumerical criteria used to delineate salt-solvent clusters (i.e., the exact cutoff between\ncationandanion).\nFinally, based on my careful reading of the response letter, I think the authors did not\nintend to downplay the value of theoretical calculations. Rather, they clarified that\ntheir goal was not to develop new computational methodologies or resolve theoretical\ndebates, but to provide valuable interpretation to experimental findings using standard\nand transparent simulation protocols. Reviewer #3 may have misunderstood or\noverinterpretedthis justification.\nOverallRecommendation\nBased on all the above considerations, I think the authors’ response is sufficiently\nsatisfactory, and the paper is, in my judgment, suitable for publication in Nature\nCommunications.\nResponse: We sincerely thank Reviewer #4 for evaluation of our revision again. We\ndeeply appreciate the reviewer’s careful reassessment and recognition of our\nclarifications regarding the Raman normalization, CIP, SSIP and AGG definitions. The\nreviewer also kindly provided high-quality reference examples, which strongly\nsupported our interpretation and have been cited in the revised Supplementary\nInformation.\nFollowing the reviewer’s valuable suggestions, we have now explicitly stated in\nthe Methods section to enhance transparency and reproducibility. In our CN analysis,\nZn2+ and ClO - are considered coordinated when the Zn²⁺ ion lies within 2.3 Å of\n4\nany oxygen atom of ClO -. This cutoff distance was derived from the Zn–O(ClO -)\n4 4\nRDF, where 2.3 Å corresponds to the first minimum following the primary peak,\nrepresenting the boundary of the first coordination shell (see Figs. 2i, 2j, 6b, and\nSupplementary Figs. 6, 7, and 41).\nAt your request, I am pleased to reassess the latest revision, including the\npoint-by-point rebuttal (comment #5, pp. 20–25) and revised manuscript, with care\nand interest. Overall, I believe the record presents compelling responses from the\nauthors. I also provide the following observations on Reviewer #3’s remaining\nconcernsaboutthe CIPand SSIPissues.\n1.CIPandSSIP adduptoexactly 100%\nInstudies ofsalt-solvent clusters (SSIP,CIP andAGG) in electrolytes,itis possible in\nboth experiments (like Raman in this work) and simulations (like MD) to report\nfractions that sum to 100% over the states analyzed. It is particularly common when\none state (e.g., SSIP or AGG) is not detected or is operationally negligible (below\ndetection limit) under the measurement/simulation conditions, thus normalizing the\nremaining states to 100%. This practice is acceptable, and several high-calibre works\nhave reportedsuchresults.I havelisted two ofthem belowfor yourreference:\nScience 374, 172-178 (2021) Fig. 3c (Only SSIPs and CIPs, with a sum of 100%.)\nFigure Redacted\nFigure Redacted\n2. Why the RAMAN experiment also provides 100% adding CIP+SSIP\nIn light of Reviewer #3’s concern, I reviewed the Raman data and the cited references.\nThe peak assignments reported by the authors are correct and consistent with the cited\nreferences; no AGG feature (which would otherwise show obvious blue shifts) is\ndiscernible in the relevant Raman region under the stated conditions. On this basis,\nnormalizing CIP and SSIP to a combined 100% is appropriate. I think the authors had\nalready provided reasonable justification/explanation for this result in the latest\nresponse:\n“These experimental results collectively validate that in all electrolytes involved in\nthis work, the dominant ion-pairing structures are SSIP and CIP, with negligible\nAGGs. Therefore, in the discussion regarding solvated cation species (Zn2+\nstructures), we quantifiedSSIPandCIPonly (freeanionhasnocoordinationwith\ncation), and normalized their total portion to 100%. This approach allows us to\nclearly track variations in CIP fraction, which is the key structural feature of interest\ninunderstanding ion migrationbehavior andelectrochemical performance.”\n“While we cannot rule out the possibility of trace-level AGG-like configurations due\nto thermal fluctuations, our results suggest that they are negligible and structurally\nirrelevant in all the systems. If such transient configurations do arise, they are\ninherently indistinguishable from loosely coordinated multi-anion CIPs in our system.\nTherefore, we categorized the solvated cation species into CIP and SSIP in the\nmanuscript withatotalportion of100% to avoidunnecessaryconfusion”\n3.The sufficiency and reproducibility of the SSIP,CIP and AGG definitions,and\ntheassociatedcomputational classification\nI examined the definitions and citations the authors use for SSIP, CIP, and AGG. The\nmanuscript applies consensus definitions reflected in recent authoritative sources.\nUsing thisestablishedterminology supports clarity andcross-studycomparability.\nHaving said so, I also respect Reviewer #3’s request for explicit operational\ncriteria, for example distance, as a transparency measure. For completeness and ease\nof reproduction, it would be helpful if the authors state explicitly in the SI the\nnumerical criteria used to delineate salt-solvent clusters (i.e., the exact cutoff between\ncationandanion).\nFinally, based on my careful reading of the response letter, I think the authors did not\nintend to downplay the value of theoretical calculations. Rather, they clarified that\ntheir goal was not to develop new computational methodologies or resolve theoretical\ndebates, but to provide valuable interpretation to experimental findings using standard\nand transparent simulation protocols. Reviewer #3 may have misunderstood or\noverinterpretedthis justification.\nOverallRecommendation\nBased on all the above considerations, I think the authors’ response is sufficiently\nsatisfactory, and the paper is, in my judgment, suitable for publication in Nature\nCommunications."}, {"round": 2, "reviewer_comments": {"reviewer_3": "I thank the authors for their efforts to rectify many issues earlier mentioned in the manuscript. I am still not convinced that CIP and SSIP will add up to exactly (emphasize) 100%, as statistical averaging of molecular dynamics does not work in this way. At least some other structures should be there, which have not been analyzed properly. Further, the authors did not understand the comment on the definition of CIP and SSIP. One has to define some conditions (distance, angle, wrt center of mass or atom based etc...) to develop an algorithm to find these structures. One has to defend the basis of these parameters, which are used to screen the CIP and SSIP. The manuscript fails to provide appropriate evidence of these structures, which can be reproducible. I am not sure why the RAMAN expt also provides 100% adding CIP+SSIP. So, I am doubtful of these values.\nHaving said this, I also do not agree with the impression that computational calculations were performed only to validate the experimental findings. The agreement will not always happen. The theories are made to have some fluctuation from experiments. Further, any results reported in a prestigious journal should be reproducible and error-free.\nSo, I request that the editor may take a decision on the manuscript considering all aspects."}, "author_response": ""}]

Decision letter