Enabling low-temperature aqueous zinc/copper-sulfur hybrid batteries through electrolyte design

Domain: physics
Published: 2026-02-25
Editorial outcome: major_revision

Abstract
Rechargeable aqueous batteries show promise for large-scale energy storage, yet suffer from low specific energy and poor low-temperature performance. Existing low-temperature aqueous batteries typically use ion-insertion positive electrodes with limited capacity. While aqueous sulfur-based batteries offer high theoretical capacity, their low-temperature operation remains challenging. Current improvement strategies often compromise room-temperature performance due to the inclusion of non-active additives. Here, we present a low-temperature sulfur-based battery using a Cu(BF4)2-based electrolyte, which boasts a low glass transition temperature of −115.1 °C, and an ionic conductivity of 5.16 mS cm−1 at −60 °C. This electrolyte enables faster reaction kinetics and higher overall specific energy than traditional CuSO4-based systems. The resulting zinc-sulfur battery delivers a discharge capacity of 348 mAh g−1 and an specific energy of 339 Wh kg−1 at −50 °C, based on the total mass of both the positive and negative electrodes, competitive with existing aqueous batteries.

Introduction
Large-scale energy storage systems are essential for integrating renewable energy sources like wind and solar power into the grid1,2. Among various storage technologies, rechargeable aqueous batteries standout due to their safety, cost-effectiveness, and environmental advantages3–5. However, the practical application of aqueous batteries is currently limited by two major challenges: (i) low specific energy and (ii) poor electrochemical performance at low temperatures6,7. Despite significant efforts, the development of low-temperature aqueous batteries with high specific energy remains largely unrealized.

In current low-temperature aqueous batteries, positive electrodes typically rely on ion insertion and extraction mechanisms8–13. However, these systems are often limited by relatively low capacities, frequently falling below 200 mAh g−1 at low temperatures. This limitation underscores the need for the development of low-temperature aqueous batteries capable of achieving higher discharge capacities. Positive electrode materials based on conversion reactions generally offer higher specific capacities compared to ion-insertion-based counterparts. Among these, sulfur, a well-established conversion-reaction positive electrode, has been investigated for use in aqueous batteries, demonstrating a high theoretical capacity of 3350 mAh g−1 based on a four-electron conversion mechanism14. This represents the highest specific capacity achieved for any positive electrode materials. Despite these promising advancements, existing aqueous sulfur-based batteries typically employ 0.5 m copper sulfate as the electrolyte15–18, which exhibits limited anti-freezing ability, thus restricting their applicability in extreme environments such as high-altitude, deep-space, and deep-sea conditions. Thus, the development of low-temperature sulfur-based batteries is highly desirable.

The development of anti-freezing aqueous electrolytes compatible with four-electron sulfur positive electrodes is crucial. So far, various strategies have been adopted in the design of low-temperature-tolerant electrolytes, such as the utilization of high-concentration electrolytes19,20, organic additives21,22, and anti-freeze hydrogel electrolytes23,24. However, these approaches often lead to trade-offs, such as reduced ionic conductivity, compromised safety, or diminished specific energy due to the incorporation of non-electrochemically active additives. Consequently, there is a pressing need to improve the anti-freezing performance of aqueous electrolytes without sacrificing their ionic conductivity or adversely affecting the overall specific energy and safety of the battery system.

Here, we identify redox-active 3.5 m Cu(BF4)2, which exhibits a low glass transition temperature of −115.1 °C and a high ionic conductivity of 5.16 mS cm−1 at −60 °C. Comprehensive spectral analysis and molecular dynamics simulations show that BF4− anions can significantly disrupt the existing hydrogen bond (HB) network among water molecules, resulting in robust low-temperature resistance. Compared with traditional 0.5 m CuSO4 electrolyte, the 3.5 m Cu(BF4)2 electrolyte endows the sulfur positive electrode with faster reaction kinetics, better rate performance (1575 mAh g−1 at 20 A g−1), and higher specific energy. In addition, the prepared zinc-sulfur (Zn–S) full cells provided a high discharge specific capacity of 1767 mAh g−1 and an specific energy of up to 1724 Wh kg−1 at −50 °C, competitive with the performance of current low-temperature aqueous batteries. This work introduces the four-electron sulfur positive electrode into low-temperature aqueous battery systems, thereby providing a promising pathway for large-scale low-temperature energy storage applications. Crucially, this study overcomes the limitations of traditional anti-freezing additives, which, while improve the anti-freezing ability, often compromise the electrochemical performance and energy efficiency of aqueous systems.

Results
S@CNT positive electrode preparation and anti-freezing electrolytes design
To improve the electronic conductivity of sulfur and alleviate its volume expansion during the discharge process, carbon nanotubes (CNTs) were used as the host for sulfur. The scanning electron microscope (SEM) image of CNTs is shown in Supplementary Fig. 1. A melt diffusion method was used to synthesize S@CNT composite. X-ray diffraction (XRD) pattern of the composite exhibits peaks consistent with crystalline sulfur (Supplementary Fig. 2a), and the thermogravimetric analysis (TGA) shows the sulfur content in the composite is 63% by mass (Supplementary Fig. 2b). Elemental mappings confirm the sulfur is evenly distributed throughout the CNT host (Supplementary Fig. 3).

A critical challenge in developing low-temperature sulfur-based batteries is the creation of a low-temperature-tolerant copper ion electrolyte that remains compatible with sulfur positive electrodes. In previously reported aqueous four-electron sulfur-based batteries, copper sulfate (CuSO4, 0.5 m) was commonly used as the electrolyte14–18. To evaluate the low-temperature performance, we investigated the anti-freezing properties of copper sulfate solutions at various concentrations. As shown in Supplementary Figs. 4 and 5, differential scanning calorimeter (DSC) measurements indicate that the freezing points of various concentrations of CuSO4 are above −10 °C, which severely impedes the Cu2+ transfer process and limits the battery performance at low temperatures. Therefore, copper sulfate solutions are unsuitable as electrolytes for low-temperature applications.

Introducing HB acceptors into the water to break its original HB network is an effective strategy for improving the anti-freezing ability of the solution21. Fluorine (F), with high electronegativity, acts as a suitable HB acceptor, facilitating the O−H∙∙∙F interaction with water molecules25. The tetrafluoroborate anion (BF4−), with four B−F bonds, is capable of forming multiple HBs with water, greatly disrupting the original HB network between water molecules. Furthermore, compared to other chaotropic anions such as ClO4− and TFSI−, Cu(BF4)2 exhibits a significant cost advantage (Supplementary Fig. 6). This makes Cu(BF4)2 a promising copper ion electrolyte for low-temperature aqueous sulfur-based batteries.

As shown in Fig. 1a, keep at −60 °C, Cu(BF4)2 solutions with low concentrations (1–2 m) freeze, while those with high concentrations (3-5 m) remain liquid, indicating that the anti-freezing ability of Cu(BF4)2 solution is influenced by its concentration. The phase transition behaviors of Cu(BF4)2 at different concentrations was further studied using differential scanning calorimetry (DSC) (Supplementary Fig. 7). As the concentration of Cu(BF4)2 increases, the phase transition temperature initially decreases and then increases, and 3.5 m Cu(BF4)2 delivers the lowest glass transition temperature of −115 °C (Fig. 1b).

In addition, ion conductivity at low temperatures is crucial for constructing high-performance low-temperature aqueous batteries. Electrochemical impedance spectroscopy (EIS) was used to study the ionic conductivity of different concentrations of Cu(BF4)2 solutions at different temperatures (Fig. 1c and Supplementary Fig. 8). At 25 °C, there is little difference in ionic conductivity across different concentrations. But as the temperature drops to −40 °C, 3.5 m Cu(BF4)2 shows higher ion conductivity and maintains an ion conductivity of 5.16 mS cm−1 at −60 °C, competitive with previously reported low-temperature electrolytes (Fig. 1d)8,19,22,26–28. While the concentration is greater than 3.5 m, the ionic conductivity decreases, which could be due to the increase in electrolyte viscosity (Supplementary Fig. 9). To further investigate the temperature dependence of ion conductivity, the activation energy of conductivity in Cu(BF4)2 solutions at various concentrations was calculated using the Arrhenius equation29 (Supplementary Fig. 10). The activation energy, which governs the ion conductivity-temperature relationship19, was found to be lowest in the 3.5 m Cu(BF4)2 solution at 0.24 eV (Fig. 1e), indicating good low-temperature ionic conductivity and temperature stability.

Anti-freezing mechanism of electrolyte
To comprehensively understand the mechanism behind the anti-freezing ability of the Cu(BF4)2 electrolyte, Raman spectra of Cu(BF4)2 solutions at different concentrations were collected (Supplementary Fig. 11a). The peak at ~767 cm−1 is attributed to the stretching vibration of the B−F bond, which gradually becomes stronger with the increase of the Cu(BF4)2 concentration (Supplementary Fig. 11b)30,31. The O–H stretching vibration of water typically occurs in the range of 2900–3800 cm−1 (see refs. 32,33), which can be deconvoluted into three components corresponding to three types of HBs: strong HBs (~3200 cm−1), weak HBs (~3400 cm−1), and non-HBs (~3600 cm−1). With increasing Cu(BF4)2 concentration, the peak intensity attributed to non-HBs rises (Fig. 2a), indicating a strengthened interaction between BF4− anions and water molecules25,34. This is further supported by the observation that the proportion of non-HBs increases while that of strong HBs decreases (Fig. 2b and Supplementary Fig. 12). In contrast, CuSO4 solutions show only minor variations in peak intensity with changing concentration (Supplementary Fig. 13), suggesting a negligible enhancement of non-HB interactions. These results collectively demonstrate that Cu(BF4)2 progressively disrupts the HB network among water molecules.

Fourier transform infrared (FTIR) spectra provide additional confirmation of the evolution of the HB structure in the Cu(BF4)2 electrolyte (Supplementary Fig. 14). The stretching vibration of the B−F bonds shifts to lower wavenumbers (redshift) with increasing Cu(BF4)2 concentration (Supplementary Fig. 15), which is attributed to the enhanced interaction between the H atoms of water molecules and the F atoms of the BF4− anions35. Similarly, fitting the O−H stretching region and deconvoluting it into three components (Supplementary Fig. 16 and 17) shows that the proportion of non-HBs increases with Cu(BF4)2 concentration, consistent with the Raman spectroscopy results. Therefore, the introduction of BF4− significantly disrupts the original HB network in water, suppressing ice crystal nucleation and improving the anti-freezing ability.

To investigate the anti-freezing mechanism of the electrolyte, theoretical simulations were also performed. The results reveal that although SO42− exhibits stronger interaction with water molecules than BF4− (Fig. 2c and Supplementary Fig. 18), it is the BF4−-based electrolyte that demonstrates good anti-freezing performance. This can be attributed to their distinct influences on the HB network of water. SO42−, with its high charge density, strongly binds to H2O via ion-dipole interactions, leading to the formation of a highly ordered and stable hydration shell (Fig. 2d). This ordered structure consequently strengthens the long-range HB network of water, facilitating ice formation. In contrast, BF4− shows weaker binding energy with water molecules, which prevents the formation of an ordered hydration shell, leading instead to a loose and flexible hydration structure (Fig. 2d). This disruption of the extended HB connectivity effectively inhibits the water molecular arrangement necessary for freezing. Therefore, the anti-freezing performance of the aqueous electrolyte is determined by the ability to disrupt the global HB network, rather than the strength of the local bonding energy between the two species.

Molecular dynamics (MD) simulations were used to investigate the structure of Cu(BF4)2 electrolyte at different concentrations (Supplementary Fig. 19). As the concentration increases, the number of HBs among water molecules decreases monotonically (Supplementary Fig. 20). This trend appears to contradict the V-shaped phase transition temperature, which reaches a minimum at 3.5 m. This can be understood from an entropic perspective. As demonstrated by Mai et al.11,12, increasing salt concentration introduces two competing effects: the disruption of the water HB network increases entropy, while the enhanced ion-water and ion-ion interactions decrease it. The balance of these opposing effects results in an optimal concentration—in this case, 3.5 m—where the phase transition temperature is minimized. Structural analysis at this optimal concentration provides further insight: in 3.5 m Cu(BF4)2, the proportion of HBs between water molecules drops to 33.5%, compared to 70.6% in the 1 m system, whereas the ratios of H2O−BF4− and H2O−Cu2+ increased substantially (Fig. 2e). Besides, each F atom in BF4− can form H-bonds with multiple neighboring H2O molecules (Supplementary Fig. 21), resulting in a higher ratio of H2O−BF4− interactions compared to H2O−Cu2+, suggesting BF4− plays a predominant role in improving the anti-freezing ability of the electrolyte. Additionally, further kinetic analysis through mean squared displacement (MSD) calculations shows that water molecules in the 3.5 m Cu(BF4)2 electrolyte exhibits a lower diffusion coefficient (1.51 × 10−5 m2 s−1) compared to 1 m system (4.26 × 10−5 m2 s−1) (Fig. 2f). This slowdown can be attributed to the enhanced H2O−BF4− (or Cu2+) interactions in the electrolyte.

The enhanced reaction kinetic of positive electrode
In addition to exhibiting anti-freezing performance, 3.5 m Cu(BF4)2 electrolyte also enhances the reaction kinetics of the sulfur positive electrode. Compared to traditional CuSO4 electrolytes, 3.5 m Cu(BF4)2 electrolyte shows enhancement in both rate performance and specific energy. To evaluate this, we compared the electrochemical performance of the sulfur positive electrode in different electrolytes, including 3.5 m Cu(BF4)2 and 0.5 m CuSO4 electrolytes. The Cu|3.5 m Cu(BF4)2|S@CNT coin cell demonstrated good rate performance, delivering high specific capacities of 1697, 1679, and 1575 mAh g−1 even at high specific current of 5, 10, and 20 A g−1, respectively (Fig. 3a, b). In contrast, the Cu|0.5 m CuSO4|S@CNT cell only achieved specific capacities of 1327, 1011, and 492 mAh g−1 at the same specific current, showing a distinct advantage for the 3.5 m Cu(BF4)2 electrolyte. Furthermore, we also compared the polarization of the cells based on 3.5 m Cu(BF4)2 and 0.5 m CuSO4 electrolytes at different specific current. The cells with 3.5 m Cu(BF4)2 electrolyte exhibited lower polarization, with values of 0.102, 0.127, 0.176, and 0.263 V at specific current of 2, 5, 10, and 20 A g−1 (Supplementary Figs. 22–24), respectively. Notably, compared to the traditional 0.5 m CuSO4 electrolyte, the 3.5 m Cu(BF4)2 electrolyte enhances the specific energy of the Cu–S@CNT cell. The specific energy improvement becomes more pronounced with increasing specific current, reaching 203% at 20 A g−1 (Fig. 3c). Moreover, the Cu|3.5 m Cu(BF4)2|S@CNT cell also exhibits stable cycling performance, maintaining 91% capacity retention after 400 cycles at 5 A g−1 (Supplementary Fig. 25). Furthermore, comparative rate performance analysis shows that Cu(BF4)2 electrolytes across different concentrations exhibit enhanced kinetics compared to the 0.5 m CuSO4 (Supplementary Fig. 26).

To investigate the mechanism behind the improved rate performance, we systematically characterized the electrochemical properties of the electrolyte systems. The ionic conductivity of the 3.5 m Cu(BF4)2 electrolyte at 25 °C was measured to be 100.3 mS cm−1, significantly higher than the 21.8 mS cm−1 observed for the 0.5 m CuSO4 electrolyte (Supplementary Figs. 27–29). Charge transfer impedance (Rct) was used to evaluate the diffusion resistance of ions at the electrolyte-electrode interface, a crucial factor influencing the rate performance of the cell. We measured the Rct of Cu–S@CNT cell with two different electrolytes at different voltages and found that the Rct for the cell with 3.5 m Cu(BF4)2 was significantly lower than that with 0.5 m CuSO4 (Supplementary Figs. 30 and 31 and Supplementary Table 1). Galvanostatic intermittent titration technique (GITT) is also used to study the diffusion kinetics of Cu2+ in the electrode material, revealing higher diffusion coefficients with 3.5 m Cu(BF4)2 electrolyte compared to 0.5 m CuSO4 electrolyte (Supplementary Fig. 32). The enhanced performance of the 3.5 m Cu(BF4)2 electrolyte is further evidenced by its higher Cu2+ transference number (0.698) compared to the 0.5 m CuSO4 electrolyte (Supplementary Figs. 33 and 34). MD simulations were conducted to investigate the origin of this enhanced Cu2+ transport (Supplementary Fig. 35).

The solvation structure of the electrolyte plays a critical role in desolvation kinetics36–38, which in turn determines reaction kinetics. Thus, we systematically compared the solvation structures of the two electrolytes. The high binding energy between Cu2+–BF4−, Cu2+–SO42− suggested that BF4− and SO42− ions can preferentially participate in the solvation sheath of Cu2+ in electrolytes (Fig. 3d). The radial distribution function (RDF) analysis of 0.5 m CuSO4 reveals negligible participation of SO42− in the primary solvation shell of Cu2+ at this low concentration (Fig. 3e). For Cu(BF4)2 electrolyte, the coexistence of Cu2+–O(H2O) and Cu2+–F(BF4−) interactions in the electrolyte (Fig. 3e), with coordination numbers of 4.87 and 1.12, respectively. Notably, the percentage of BF4− surrounded Cu2+ solvation structure reaches 79.69% (Fig. 3f), indicating the significant involvement of BF4− ions in the Cu2+ solvation structure. The solvation structure plays a crucial role in determining the desolvation energy. During the discharge process, the BF4− anions in the solvation shell of Cu2+ are repelled by the electric field at the positive electrode surface37,39. This repulsion decreases the desolvation energy, thereby enhancing the reaction kinetics. Consequently, we evaluated the desolvation energy (Ea) of two electrolytes. As shown in Supplementary Fig. 36 and Fig. 3g, the Ea of 3.5 m Cu(BF4)2 (0.204 eV) is less than that of 0.5 m CuSO4 (0.247 eV), indicating that 3.5 m Cu(BF4)2 has faster desolvation kinetics (Supplementary Table 1).

To further elucidate the influence of solvation structure on Cu2+ redox kinetics, we investigated the electron transfer process between the electrode and solvated Cu2+ ions through reorganization energy (λ) analysis. The reorganization energy represents the energy required to rearrange the solvation sheath during electron transfer, which follows Marcus’ non-adiabatic electron transfer theory40,41. The λ values were obtained by fitting the Tafel plots (Fig. 3h) with the Marcus-Hush-Chidsey kinetic model (Eq. (1), “Methods”)38,42,43. Remarkably, the 3.5 m Cu(BF4)2 electrolyte exhibits a substantially lower reorganization energy (0.118 eV) compared to 0.5 m CuSO4 (0.180 eV) (Fig. 3i). This significant difference may be attributed to the participation of BF4− anions, which creates a more loosely coordinated environment (Supplementary Table 2). This looser solvation shell facilitates easier reorganization during the electron transfer process, thereby accelerating the kinetics.

Electrochemical performance at −60 °C
The low-temperature electrochemical performance of Cu|3.5 m Cu(BF4)2|S@CNT cell is further explored. At −60 °C, it showed a high capacity of 3158 mAh g−1 in the first cycle at 0.1 A g−1, as well as a reversible capacity of 1810 mAh g−1 (Fig. 4a and Supplementary Fig. 37). Additionally, the long-term cycling stability of the cell at low temperature is also evaluated. Under a specific current of 2 A g−1, it retained 76% of its initial capacity after over 400 cycles, with a Coulombic efficiency close to 100% (Fig. 4b). Furthermore, the cell demonstrated good rate performance at −60 °C (Fig. 4c, d), delivering 1730, 1645, 1249, and 763 mAh g−1 at specific current of 0.2, 0.5, 1, and 2 A g−1, respectively. A comprehensive comparison with existing low-temperature aqueous batteries reveals that conventional aqueous battery positive electrodes typically deliver discharge capacities below 250 mAh g−1 at low temperatures, with specific current rarely exceeding 1 A g−1. These data indicate that our system maintains high capacity even at temperatures as low as −60 °C and specific current up to 2 A g−1, as illustrated in Fig. 4e and Supplementary Table 310,19,21,25,44–50. These results highlight the potential of this approach for low-temperature applications.

Charge storage mechanism
To investigate the reaction mechanism of the sulfur positive electrode in Cu(BF4)2 electrolyte, various electrochemical measurements and characterizations were carried out. Supplementary Figs. 38 and 39 show the first three cyclic voltammetry (CV) curves recorded at 0.1 mV s−1. A single reduction peak was observed during the first cathodic scan, while a new reduction peak emerged in the second and third scans (Fig. 5a, b). The curves for the second and third cycles almost overlapped, indicating the high reversibility of the conversion reactions in subsequent cycles. The products at the end of different CV peaks are studied using XRD techniques.

In the first cycle, the reduction product is identified as Cu2S (Fig. 5c). In the second cycle, the initial reduction peak led to the formation of Cu9S8, which is further reduced to CuS in the second reduction peak (Fig. 5d). The oxidation profiles during the charging process are consistent across all cycles, with four distinct oxidation peaks observed (Supplementary Fig. 40). Upon analyzing the products corresponding to each oxidation peak, several intermediate products are detected, including Cu31S16, Cu7S4, Cu9S8, and the product at the end of charging is a mixture of CuS and S (Supplementary Figs. 40 and 41). This account for why the subsequent discharge capacity is lower than that of the first cycle, reaching about only 53% of the initial discharge capacity (Supplementary Fig. 42). The charge ratios of the two reduction peaks are further calculated (Fig. 5e). The second reduction peak has a charge ratio of 80.6%, corresponding to a specific capacity of 1390 mAh g−1. This aligns with the capacity released by 1.75 electrons during the reduction of Cu9S8 to Cu2S (1421 mAh g−1) (Fig. 5f).

The difference between the CV curve of the first cycle and those of subsequent discharge processes can be attributed to the nature of the product formed during the charging process. Transmission electron microscopy (TEM) measurements also confirmed that the product contains sulfur as well as a significant amount of CuS (Fig. 5g and Supplementary Figs. 43 and 44), which has high electrical conductivity. This conductive CuS enhances the reduction kinetics of sulfur (Fig. 5h), leading to the splitting of the reduction peak into two distinct peaks in the following cycles, alongside a discharge voltage plateau higher than that of the first cycle. The lack of sulfur lattice stripes may be due to the low crystallinity formed in its charging state.

Comprehensive analysis reveal that sulfur undergoes a multi-step phase transition during discharge (S ↔ Cu9S8 ↔ CuS ↔ Cu31S16 ↔ Cu2S), corresponding to a progressive increase in copper content within CuxS compounds, ultimately yielding CuS as the final discharge product. Conversely, the charging process involves the extraction of Cu from CuxS, with the thermodynamically favored endpoint being elemental sulfur (Fig. 5i). However, the high energy barrier associated with the conversion of sulfur results in incomplete phase transformation, leaving a mixture of S + CuS as the charging product. This explains the observed discrepancy between the first charge (lower) and discharge (higher) specific capacities. Interestingly, the residual CuS in the charge product enhances the overall conductivity, thereby accelerating the reaction kinetics of sulfur in subsequent cycles. This effect is clearly reflected in the second-cycle CV curve, which exhibit two distinct reduction peaks due to the improved electrochemical activity.

Zn–S full cell
The high redox potential of Cu2+/Cu (0.34 V vs. SHE) resulted in a low discharge voltage. Therefore, we designed a Zn–S full cell (Zn|3.5 m Zn(BF4)2||3.5 m Cu(BF4)2|S@CNT) with Zn as the negative electrode (Fig. 6a, Supplementary Fig. 45). To prevent direct contact reaction between Cu2+ and Zn negative electrode, we employed an anion exchange membrane (AEM) to divide the cell into two compartments, allowing only BF4− anions to exchange shuttle to maintain charge balance. During the discharge process, the sulfur positive electrode undergoes a four-electron transfer reaction with Cu2+ ions to transform into Cu2S. At the same time, the Zn negative electrode loses electrons and is oxidized to Zn2+. As shown in Supplementary Fig. 46, the 3.5 m Zn(BF4)2 electrolyte remains liquid at −60 °C, and the DSC curve shows its glass transition temperature at –122.7 °C. The stability of the Zn negative electrode is critical for the performance of Zn–S full cells. Here, the stability of ZnSO4 and Zn(BF4)2 on Zn negative electrodes was evaluated across varying temperatures (Supplementary Figs. 47 and 48). The findings indicate that a 3.5 m Zn(BF4)2 electrolyte maintains stability during long-term operation at low temperatures.

Benefiting from the enhanced anti-freezing properties of the electrolyte, the assembled Zn–S full cell exhibited reliable low-temperature electrochemical performance. At −50 °C, the Zn–S full cell provided a first cycle discharge specific capacity of 605 mAh g−1(S+Zn) and a high reversible capacity of 352 mAh g−1(S+Zn) at 0.5 A g−1 (Fig. 6b). It also delivered good cycling stability at −50 °C, the specific capacity remained about 239 mAh g−1(S+Zn) after 200 cycles at a high specific current of 1 A g−1 and the Coulombic efficiency almost maintains at 100% (Fig. 6c and Supplementary Fig. 49). The specific energy reaches 339 Wh kg−1(S+Zn), exceeding the values reported for other low-temperature aqueous batteries (Fig. 6d and Supplementary Table 4)19,21–24,46,51–54. In addition, the cost of sulfur positive electrode (55.6 Ah $−1 and 53.6 Wh $−1) is much lower than common aqueous and non-aqueous positive electrode materials (Supplementary Fig. 50 and Supplementary Table 5)7,55, highlighting the substantial application potential of sulfur-based batteries. Considering the high cost of the AEM, we propose an asymmetric electrode-membrane configuration (Supplementary Fig. 51), to reduce the overall cost of the Zn–S full cell. To validate this concept, we constructed an asymmetric electrode-membrane Zn–S cell (Supplementary Fig. 52a, b), which enhances the AEM utilization efficiency and reduces overall cost to 3.6 Wh $−1 (0.28 $ Wh−1) (Supplementary Fig. 52c). Given these results, future optimizations are expected to enable additional cost reductions (Fig. 6e).

During discharge, Zn2⁺ accumulation at the anolyte and Cu2⁺ consumption at the catholyte create a concentration gradient, and water could transport across the AEM to balances the ionic concentrations, preventing significant concentration polarization (Supplementary Fig. 53). Consequently, the electrolyte maintains relatively stable composition in both compartments, which is crucial for preserving its low-temperature performance.

Given the inherent advantages of flow batteries for large-scale energy storage and the high volumetric specific energy of this system (41 Wh L−1, competitive with that of all-vanadium flow batteries (<30 Wh L−1)56), we designed a Zn–S flow battery. It delivers a high initial areal capacity of 40 mAh cm−2 at −30 °C, with subsequent cycles stabilizing at 20 mAh cm−2, demonstrating its feasibility (Supplementary Fig. 54).

Methods
Materials
All materials, including sulfur (Aladdin, AR), CuSO4·5H2O (Aladdin, 99.9%), Cu(BF4)2·6H2O (Aladdin, 98%), and Zn(BF4)2·6H2O (Meryer, Reagent Grade), copper foil with 50 μm thickness (Suzhou Sinero technology Co., Ltd.), zinc foil with 50 μm thickness (Suzhou Sinero technology Co., Ltd.), stainless steel mesh (400 mesh, Guangdong Canrd New Energy Technology Co., Ltd.), carbon nanotubes (Aladdin, carboxylated multi-walled carbon nanotubes), carbon black (Alfa Aesar, 99%), polyvinylidene fluoride (PVDF, Mw~1,100,000, Alfa Aesar, 99.9%) N-methyl-2-pyrrolidone (NMP, Aladdin, 99.5%), and anion exchange membrane (150 μm thickness, AGC-APS, Apsilon technology Co., Ltd.) are used without further purification.

Synthesis of S@CNT composite and electrode preparation
S@CNT composites were prepared by a melt diffusion strategy. Carbon nanotubes and sulfur powder were mixed in a mass ratio of 30:70, and then heated for 12 h in an argon atmosphere at 155 °C. The preparation of the S@CNT electrode was as follows: S@CNT, carbon black, and PVDF binder with a mass ratio of 8:1:1 were milled into a slurry in an appropriate amount of NMP, and then the slurry was uniformly coated on a stainless steel mesh using a doctor blade. After drying under vacuum at 60 °C for 12 h, the positive electrode was obtained.

Material characterizations
The morphological characteristics of the material were analyzed using scanning electron microscopy (SEM, JSM-7900F) and energy dispersive spectroscopy (EDS, Ultima MAX 65, the voltage is set to 15 kV). The characterization of crystal materials was carried out using powder X-ray diffraction (XRD, DX-200, Cu-Kα, λ=0.15406 nm, 40 kV). The pattern data was 6° min−1 with a range from 10 to 80°. The sulfur content in composite materials was estimated using thermogravimetric analysis (TGA, TGA/DSC3+/1600). Measurements were conducted under a nitrogen atmosphere (flow rate: 50 mL min−1) from 30 to 600 °C at a heating rate of 10 °C min−1. Differential Scanning Calorimetry (DSC, Netzsch DSC 200 F3) was used to obtain the phase transition behaviors of electrolytes from 0 to −170 °C under a nitrogen atmosphere (flow rate: 50 mL min−1) at a heating/cooling rate of 10 °C min−1. FTIR spectra were collected using NEXUS 670 from 400 to 4000 cm−1. Raman spectroscopy studies of electrolyte structure were performed on LabRAM HR with a wavelength of 532 nm. Transmission electron microscopy (TEM) measurements were performed on JEOL JEM F200. Viscosity measurements were performed on Brookfield DV-Ⅱ+ Pro using 20 mL of electrolyte at 25 °C. For ex situ characterizations (including XRD, SEM, TEM), electrodes were carefully harvested from disassembled cells in an environmental chamber at 25 °C. The harvested electrodes were rinsed thoroughly with deionized water to remove residual electrolyte salts, followed by drying under vacuum at 60 °C for 2 h. For electrolyte sampling, aliquots were drawn from the prepared solution in an environmental chamber at 25 °C and transferred into sealed glass vials. All electrolyte samples for spectral analysis (Raman, FTIR, DSC) were measured immediately after preparation.

Electrochemical measurements
CR-2032 coin cells were assembled with an S@CNT positive electrode, a glass fiber separator (GF/A, Whatman, 16 mm diameter, 260 μm thickness), and 80 μL of 3.5 m Cu(BF4)2 electrolyte. For the Zn–Zn symmetric cells, two 12-mm-diameter zinc foil were employed. For Zn–S static full cell test, the S@CNT composite was coated onto a stainless steel mesh strip to serve as the positive electrode, while a Zn foil was cut into a strip shape as the negative electrode. The cell was assembled using a homemade configuration with 1 mL of Cu(BF4)2 catholyte and 1 mL of Zn(BF4)2 anolyte, separated by the anion exchange membrane. For the Zn–S flow battery (Changsha Spring New Energy Technology Co., Ltd.), an anion exchange membrane with lateral dimensions of 2.5 × 2.5 cm was used as the separator. The Zn–S flow cell was tested in a dynamic mode with a constant flow rate of 3 mL min−1 for both electrolyte. The specific capacities of Cu–S cell are calculated based on the mass of sulfur, and the specific capacities and specific energy of Zn–S full cell are determined using the mass of sulfur and zinc, and the zinc mass corresponds to the consumed Zn and not its total mass. The areal loading of sulfur is about 2 mg cm−2 throughout this work, unless otherwise specified in the figure captions. The galvanostatic charge/discharge (GCD) tests, rate, and cycling performance of all the cells were tested on the Neware battery test system, and potential cut-offs: 0.1–0.6 V (vs. AgCl/Ag) for Cu–S coin cell, 0.9–1.70 V (vs. Zn2+/Zn) for Zn–S full cell. The specific capacity of Cu–S cell is calculated to the discharge capacity of the second cycle. The cyclic voltammetry (CV) and chronoamperometry (CA) were recorded using an electrochemical workstation (SP-150e, BioLogic). CV tests were performed within a voltage range of 0.10–0.60 V (vs. AgCl/Ag) at scan rates of 0.05–0.1 mV s−1. Electrochemical impedance spectroscopy (EIS) measurements were carried out on a CHI760E electrochemical workstation. A sinusoidal potential amplitude of 5 mV was applied across the frequency range of 0.1 Hz to 100 kHz, with 12 data points collected per frequency decade. Before each measurement, the system was allowed to stabilize at open-circuit potential for 5 min. All electrochemical tests were performed in temperature-controlled chambers: at 25 °C (±1 °C) using an environmental chamber (MJS-DZ250, Nanjing MoJesi Energy Technology Co., Ltd.) for room temperature, and at specified low temperatures in low-temperature chamber (JL-E702-100B70, Hunan Julang Instrument Co.). To ensure the reliability of the reported data, key electrochemical experiments (including cycling test, rate performance, EIS, and XRD characterization) were conducted using at least three independent cells under identical conditions.

The reorganization energy (λ) was obtained by Marcus–Hush–Chidsey kinetics (Eq. (1)):

i=A \int_{-\infty}^{\infty} \exp \left( -\frac{(\chi+\lambda+\eta_e)^2}{4\lambda} \right) \frac{1}{1+\exp(\chi)} d\chi \quad (1)

where i is the current density; A is the pre-exponential factor; ηe = η e / κB T is the dimensionless overpotential; η is the overpotential; e is the elementary charge; κB is the Boltzmann’s constant; T is the absolute temperature; The dimensionless variable χ, which is integrated over, accounts for the Fermi statistics of electron energies distributed around the electrode potential; λ is the dimensionless reorganization energy, which, when multiplied by κB T, yields the reorganization energy with units of energy (eV) reported in the main text41.

The calculation of electrolyte ion conductivity is as follows Eq. (2):

σ = L / (R × A) \quad (2)

where L, R, and A are the distance between two electrodes, the electrolyte resistance, and the contact area with electrode, respectively.

The activation energy of electrolyte is calculated by the following Eqs. (3) and (4):

σ = A / T \exp(-E_a / kT) \quad (3)

ln σ(T) = ln(A) - E_a / kT \quad (4)

where T is the temperature (K), R is the Boltzmann constant (1.380649 × 10−23 J K−1), and A is a constant.

Measure the Cu2+ transfer number of Cu||Cu symmetric batteries in different electrolytes by using Eq. (5):

T_Cu2+ = I_s (ΔV - I_0 R_0) / (I_0 (ΔV - I_s R_s)) \quad (5)

In the equation, ΔV is the applied voltage polarization of 25 mV. Is and Rs are the steady-state current and resistance, and I0 and R0 are the initial current and resistance, respectively.

The diffusion coefficient of Cu2+ is calculated by the following Eq. (6):

D = \pi / 4 \tau (M_B V_m / S M_B)^2 (ΔE_s / ΔE_\tau)^2 \quad (6)

In this equation, MB, mB, and Vm correspond to the molecular weight, mass, and molar volume of the active material, respectively; S denotes the contact area between the electrode and electrolyte; τ represents the duration of each current pulse (600 s); ΔEs signifies the steady-state voltage change per titration step; and ΔEτ is the total voltage change during the pulse. Data were acquired at one-second intervals throughout the measurement.

Computational methods
Molecular dynamics (MD) simulations were performed to calculate the electrolyte structures using the Forcite module with the COMPASSIII force field57,58 in Materials Studio (MS) 2020. The numbers of water molecules and ions are provided in Supplementary Table 6. Geometry optimizations were conducted to relax the initial system with ultrafine quality settings (energy convergence tolerance: 2.0 × 10−5 kcal mol−1, force tolerance: 1 × 10−3 kcal mol−1 Å−1). Following energy minimization, the system was equilibrated under periodic boundary conditions for 5 ns in the NPT ensemble at 298 K, employing the Nose thermostat and Berendsen barostat, ensuring stabilization of the temperature, potential, and total energy. Once equilibrium was reached, an additional 5 ns simulation at 298 K under the NVT ensemble was carried out. The integration time step was 1 fs. Convergence tests based on electrolyte density, RDFs, and H-bond length distribution (between H2O) were used to determine the number of water molecules and ions in the systems (Supplementary Table 7 and Supplementary Figs. 55 and 56). The diffusion coefficients of H atoms were derived from the slope of the mean square displacement (MSD) curves using the Einstein relationship59, with analysis focused on the final 2 ns of the simulation. The initial and final electrolyte configurations from the MD trajectories in Supplementary Data 1–22.

The binding energy, Mulliken charges and electron density difference calculations were performed via the Gaussian 16W software60. The structures of the studied molecules and their complexes were fully optimized using the B3LYP function and the 6-311++G(d,p) basis set with DFT-D3 (BJ) correction. Vibrational frequency analyses were subsequently carried out at the same theoretical level. Each optimized structure was confirmed as a local energy minimum on the potential energy surface. The Mulliken charges of the atoms for the studied systems were also calculated. The electron density difference (EDD) maps were also generated from Multiwfn packages61. The Visual Molecular Dynamics (VMD) program62 was used to plot the color-filled iso-surface graphs to visualize the EDD iso-surfaces. The binding energies (Figs. 2b and 3d) were computed with the B3LYP function with DFT-D3 (BJ) correction. A mixed basis set was adopted, utilizing the LANL2DZ63 pseudopotential basis set for the Cu atom and the 6-311++G(d,p) all-electron basis set for the light atoms (O, B, F, H). The atomic coordinates obtained using Gaussian software for the binding energy and electron density difference calculations are provided in Supplementary Data 23–28 and 29, 30, respectively.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this Manuscript, the authors proposed a Cu(BF4)2-based electrolyte and apply it to sulfur-based batteries. This electrolyte enables excellent anti-freezing, faster reaction kinetics and higher overall energy density. The proposed strategy overcame the bottleneck of low capacity in low-temperature aqueous batteries. Overall, it can be considered to be published in Nature Communication after discussing following detailed issues:\n1.Why BF4- was chosen rather than other chaotropic anions (e.g., ClO4-, TFSI-)?\n2.The authors should provide experimental data on conductivity and freezing point for different concentrations of CuSO4 (Including larger than 1.5m).\n3.In Fig. 3a, compared to 0.5 m CuSO4 electrolyte, the 3.5 m Cu(BF4)2 electrolyte shows much better rate performance. The author should further explain this phenomenon. Besides, in order to better highlight advantages of the Cu(BF4)2 electrolyte compared to the CuSO4, cycling performances and rate performances of different concentrations should be provided (Cu-S@CNT cells).\n4.Can the four-electron transfer process of the sulfur cathode be realized in CuSO4 electrolyte systems? The authors should further explain the four-electron storage mechanism of the the sulfur cathode and its connection with the BF4- system.\n5.The stability of the Zn anode usually affects the performance of the full cell. Will the BF4- decrease the stability of the Zn anode compared to SO42-? The authors should provide relevant experimental results to prove this point.", "reviewer_2": "In this manuscript, the authors developed a Cu(BF₄)₂-based electrolyte, which possesses a low freezing point and high ionic conductivity at low temperatures, to operate Cu–S cells under sub-zero conditions. They also demonstrated its application in Zn–S batteries, achieving high capacity and energy density at low temperatures. However, there is an issue in battery evaluation and lacks significant differentiation from prior studies. Detailed comments are provided below.\n1. There is an issue in the design of the cut-off voltages for Cu–S full cells throughout the manuscript. In Figures 3 and 4, under both high-rate and low-temperature conditions, the discharge cut-off voltage is set below 0 V. While it is understandable that a lower cut-off may have been chosen to accommodate the increased overpotential under harsh conditions, such settings are unacceptable from an application standpoint. A battery must provide usable energy to power devices, and discharging below 0 V renders the cell incapable of fulfilling its intended function. This undermines the practical value and relevance of the results.\n2. This study appears to lack clear novelty compared to previous research. The approach of lowering the freezing point of aqueous electrolytes by disrupting hydrogen bonding through salt concentration or anion selection is already well-established, both in methodology and mechanism. Furthermore, the manuscript does not identify any unique phenomena or properties specific to the Cu(BF₄)₂-based electrolyte. The authors are encouraged to clarify what distinguishes this work in terms of novelty.\n3. Regarding Figure 5, is the proposed charge storage mechanism specific to the Cu(BF₄)₂-based electrolyte? If not, and if this mechanism has already been reported in conventional Cu–S systems, it may not warrant particular emphasis.\n4. As is well known, unlike conventional rocking-chair-type batteries, dual-ion-type batteries require the mass of not only the active materials but also the electrolyte and the dissolved salt to be considered when calculating energy density and specific capacity. In this manuscript, the energy-related calculations are based on the mass of Zn + S. Could the authors clarify whether the Zn mass refers to the Zn in the electrolyte or the Zn anode? Please provide detailed calculation information along with the Zn mass in the electrolyte and the thickness of the Zn foil used.\n5. The authors claim that the BF₄⁻ anion strongly interacts with water molecules, disrupting hydrogen bonding between them and thus lowering the freezing point of the electrolyte. This is a widely recognized behavior of kosmotropic anions. Typically, in such cases, Raman and FT-IR spectra show an increase in strong hydrogen-bond peaks and a decrease in weak hydrogen-bond peaks, due to strong H-bonding between the anion and water. However, the opposite trend is observed in this manuscript, which does not support the proposed explanation.\nFurthermore, in Figure 2b, the binding energy of H₂O–Cu²⁺ (−120 kcal/mol) is significantly stronger than that of H₂O–BF₄⁻ (−10 kcal/mol). These results suggest that the freezing point depression is likely dominated by the presence of Cu²⁺ rather than BF₄⁻.\nOn the other hand, Figure 2e shows a higher H₂O–BF₄⁻ ratio compared to H₂O–Cu²⁺, which appears inconsistent with the binding energy data in Figure 2b. The authors are encouraged to address this discrepancy and clarify the underlying mechanism.\n6. In Supplementary Figure 10, electrolytes with concentrations above 3.5 m show strong intensities near 3000 cm⁻¹. If these peaks are also attributed to hydrogen bonding, it appears that the spectral deconvolution may not have been performed appropriately.\n7. In Supplementary Figure 5f, the 5 m electrolyte shows a heat flow signal near −20°C following the glass transition, which may indicate melting. However, in Figure 1a, the same electrolyte appears to remain in a liquid state even at −60°C. The authors are requested to clarify this discrepancy. Additionally, a clearer distinction and appropriate terminology for glass transition and freezing points should be applied throughout the manuscript.\n8. The authors mention that minimized Cu²⁺–Cu²⁺ repulsion leads to a high Cu²⁺ transference number. Please clarify the correlation between reduced ionic repulsion and increased transference number, as it is not clearly explained.\n9. In Supplementary Figures 25 and 26, Rct is measured as a function of voltage rather than temperature, which is not a common approach. If there is a specific reason for this method, please explain the significance of Rct measured at different voltages. Furthermore, please ensure consistency in the units used for activation energy throughout the manuscript (eV or kJ/mol).", "reviewer_3": "This study addresses one of the core limitations of aqueous batteries—poor low-temperature performance—by proposing a novel Cu(BF₄)₂-based electrolyte with a low freezing point (−119.8 °C) and strong ion transport properties. The Zn–S cell developed here shows superior low-temperature energy density.The current article is not suitable for submission to nature communications.\n1.The main logic of the manuscript centers on improving low-temperature performance by replacing the anion in the electrolyte. The authors are encouraged to clarify the causal relationship throughout the manuscript.\n2.At −60 °C, the cell delivers a record-breaking initial capacity of 3158 mA h gS⁻¹ at 0.1239 A g⁻¹, but the capacity retention drops to 53% by the second cycle (1810 mA h gS⁻¹). Could this irreversible capacity loss be mitigated through further optimization? The origin of this loss (e.g., side reactions or interface instability) should be analyzed, as it is critical for practical applications.\n3.The sulfur positive electrode is reported to undergo a four-electron transfer reaction with Cu²⁺ ions to form Cu₂S. It should be clarified whether the reaction is a multistep, reversible conversion or if irreversible intermediates are involved. Is this sulfur||copper multistep conversion mechanism newly proposed in this work, or has it been previously reported?\n3. Does the additional CV peak relate to the presence of BF₄⁻ anions? Have similar peaks been observed in systems using CuSO₄-based electrolytes? The authors should provide evidence for whether the mechanisms in CuSO₄ and Cu(BF₄)₂ systems are consistent, and clarify whether BF₄⁻ directly contributes to capacity.\n4. The cost comparison in Fig. 6f may not be well-justified. A full-cell cost analysis is recommended, considering the decoupled architecture, the use of functional membranes (anion exchange), and the relatively higher price of Cu(BF₄)₂ versus CuSO₄. The economic competitiveness of the proposed system should be re-evaluated.\n5. The driving of a small electronic device (e.g., a digital watch) in Fig. 6e may not convincingly demonstrate the electrolyte's practical capability, especially considering the large electrolyte volume used. A more representative demonstration of practical application is suggested.\n6.The study would benefit from a comparison with recent state-of-the-art aqueous sulfur batteries under low-temperature conditions. Additionally, a cost-to-energy density analysis is suggested to evaluate whether the proposed system offers real-world advantages.", "reviewer_4": "Low-temperature, low-cost rechargeable batteries are a crucial topic, particularly in technological applications. From an academic perspective, the fundamental issues are the explanation and design principles. This paper attempts to approach these two essential topics.\nThis research introduces Cu(BF4)2-based electrolyte for aqueous zinc-sulfur batteries that remains functional at extreme temperatures as low as -50°C, offering unprecedented ionic conductivity without compromising performance. While the demonstration of such performance is indeed publication-worthy, and the authors have conducted extensive measurements to characterize both the electrolyte and its performance in Zn-S full cells, many critical explanations remain unclear. In its current form, the manuscript would benefit from further clarification and refinement before it can be considered for publication. The following are several phenomena and proposed mechanisms that, in my view, require more rigorous discussion.\nThis paper proposes that Cu(BF4)2 can disrupt the hydrogen bond network and therefore enhance low-temperature performance. Fig 2b and Figure 3d show the comparison of binding energy between H2O-BF4-, Cu2+-BF4- , Cu2+-H2O, etc. A comprehensive comparison should include Cu2+-SO4-, H2O-SO42-, and present them in the same plot for readers.\nIn addition to the binding energy of anion-cation and cation-solvent, the electron charge density difference analysis between H2O and anions, i.e., SO42-, BF4-, can provide direct evidence that BF4- acts as a better HB acceptor than SO4-. This analysis is necessary because in MD simulations, partial charges constitute a significant portion of the calculations, yet these partial charges are parameterized (fitted) parameters that may not fully reflect charge polarization effects.\nThe Raman spectra and FTIR are provided to correlate the freezing point and the ratio of HB types. In Fig 1b, there is a minimum for the temperature-concentration relationship. However, the ratio of the three H-bond types shows monotonic behavior from 1m to 5m, Fig 2a. This counterintuitive behavior may need further explanation.\nThe MD simulation size (~500 molecules) is relatively small by modern standards. For electrolyte systems, several thousand molecules are typically used to ensure adequate statistical sampling and minimize finite-size effects. I suggest the authors double the system size and perform convergence tests to validate their conclusions.\nThe paper states that \"excessively high concentrations can increase the electrostatic interaction energy (Supplementary Fig. 17f), thereby raising the freezing point of the electrolyte. ref[17]\" This statement requires clarification on several points:\n1. It is unclear whether the calculated electrostatic interaction energy is normalized by per unit volume or by per mol of molecules. According to the MD simulation description in this paper, the total volume should differ for each concentration.\n2. Even considering ref [17], there is still no established relationship between electrostatic interaction energy and freezing point. While increasing the ion concentration enhances the overall Coulombic interactions, this does not necessarily correlate with changes in the freezing point.\nRegarding the reaction kinetics of the positive electrode, the authors conflate different concepts:\n1. While reaction kinetics (desolvation process and charge transfer) are indeed related to solvation structure, a lower electrostatic potential (EPS) around a cation's solvation shell does not necessarily facilitate charge transfer barrier crossing. Charge transfer resistance is more directly related to solvent reorganization energy rather than just the EPS value. I recommend the authors consult Marcus theory literature to better understand the relationship between reorganization energy and charge transfer kinetics.\n2. The authors mention that 3.5m Cu(BF4)2 has a higher Cu2+ transference number. The transference number relates to the relative self-diffusivity of cations and anions. At high concentrations, this phenomenon is further complicated by ion-ion correlated transport. However, there is currently no established universal model demonstrating that lower EPS correlates with higher transference numbers or lower charge transfer resistance.\n3. From 0.5m to 3.5m, ionic conductivity increases approximately five-fold, while charge carrier density increases seven-fold, indicating that ion mobility actually decreases. Simultaneously, the self-diffusivity of ions in bulk electrolytes is expected to decrease even more rapidly with concentration. From this perspective, further analysis using MD simulations could help elucidate why Cu2+ exhibits a higher transference number at 3.5m concentration.\n4. The concept expressed in Fig 3h is confusing. It's unclear whether the authors intend to demonstrate that (i) anions are more easily repelled near charged surfaces, or (ii) the reorganization energy of charge transfer processes is reduced. If the former, this pertains to how the electric double layer influences reaction kinetics. If the latter, the authors should discuss changes in free energy during the desolvation process rather than just electrostatic potentials.\nI would like to clarify whether the diffusion coefficient mentioned between Line 226-228, determined through Galvanostatic Intermittent Titration Technique (GITT), refers to ion diffusion within the cathode materials rather than ion diffusion in the bulk electrolyte.\nSupplementary Fig. 26 shows that the charge transfer resistance of Cu-S@CNT coin cells with 3.5m Cu(BF4)2 versus 0.5m CuSO4 differs by approximately a factor of two. However, in Supplementary Fig. 29, which uses Cu||Cu symmetric cells, the Rct values differ by at least two orders of magnitude (as the figure uses a logarithmic scale). This significant discrepancy is noteworthy and merits further investigation.\nFinally, regarding the operation of the Zn-S full cell: When utilizing an anion exchange membrane to enable the use of Zn electrochemistry, a concentration gradient may develop across the membrane, with Zn ion concentration increasing on one side while Cu ions are consumed on the other. This raises questions about potential concentration polarization effects.\nDuring the discharge process, Cu²⁺ ions are continuously reduced, leading to a progressive decrease in Cu(BF4)2 concentration at the positive electrode. At what point would this concentration decrease significantly deviate from the initially proposed 3.5 m Cu(BF4)2, potentially compromising the beneficial properties of the high-concentration electrolyte? These concentration dynamics warrant further investigation to fully validate the long-term practicality of this electrolyte system under actual operating conditions.\nThis work is an important research direction with significant potential for low-temperature battery applications. I look forward to seeing more detailed exploration of the fundamental scientific mechanisms underlying these observations, which would substantially strengthen this promising work and advance our understanding of electrolyte design for extreme temperature applications."}, "author_response": "Responses to referees’ comment\nComments from reviewer 1:\nIn this Manuscript, the authors proposed a Cu(BF ) -based electrolyte and apply it to sulfur-\n4 2\nbased batteries. This electrolyte enables excellent anti-freezing, faster reaction kinetics and\nhigher overall energy density. The proposed strategy overcame the bottleneck of low capacity\nin low-temperature aqueous batteries. Overall, it can be considered to be published in Nature\nCommunication after discussing following detailed issues:\nResponse: We highly appreciate the reviewer’s encouraging feedback and suggestions. The\ncomments have been carefully addressed below.\n1.Why BF ⁻ was chosen rather than other chaotropic anions (e.g., ClO ⁻, TFSI⁻)?\n4 4\nResponse: We would like to thank the reviewer for the question. The rationale for selecting\nBF ⁻ is as follows: Cu(ClO ) and Cu(TFSI) suffer from prohibitively high costs. Furthermore,\n4 4 2 2\nCu(ClO ) exhibits inherent toxicity and raises significant environmental concerns.\n4 2\nWe revised the manuscript as follows:\n“Furthermore, compared to other chaotropic anions such as ClO ⁻ and TFSI⁻, Cu(BF ) also\n4 4 2\nexhibits a significant cost advantage (Supplementary Fig. 6).” (Page 4, Lines 96-98)\nSupplementary Fig. 6 | Comparative costs of copper and zinc salts containing various\nchaotropic anions.\n2.The authors should provide experimental data on conductivity and freezing point for different\nconcentrations of CuSO (Including larger than 1.5 m).\n4\ndifferent concentrations and determined the solubility limit to be ~2.0 m (saturated state),\npreventing further concentration increases. Despite this limitation, we systematically measured\nthe conductivity and freezing points for achievable concentrations (up to 2.0 m).\nWe revised the manuscript as follows:\n“As shown in Supplementary Fig. 4 and 5, DSC measurements indicate that the freezing points\nof various concentrations of CuSO are above −10 °C, which severely impedes the Cu2+ transfer\n4\nprocess and limits the battery performance at low temperatures.” (Page 3, Lines 87-90)\nWe revised the supporting information as follows:\n“Note: Cu(BF ) exhibits higher electrical conductivity over CuSO across all tested\n4 2 4\nconcentrations, further demonstrating its superior kinetics.” (Page 24, Lines 184-185)\nSupplementary Fig. 5 | (a) The optical photograph of ~2.0 m CuSO (saturated) at 25 °C; (b)\n4\nelectrolyte. d, Comparisons of ionic conductivity of different concentrations of Cu(BF ) and\n4 2\nCuSO electrolytes.\n4\n3. In Fig. 3a, compared to 0.5 m CuSO electrolyte, the 3.5 m Cu(BF ) electrolyte shows much\n4 4 2\nbetter rate performance. The author should further explain this phenomenon. Besides, in order\nto better highlight advantages of the Cu(BF ) electrolyte compared to the CuSO , cycling\n4 2 4\nperformances and rate performances of different concentrations should be provided (Cu-\nS@CNT cells).\nResponse: We sincerely appreciate the reviewer’s insightful comments. The enhanced rate\ncapability of 3.5 m Cu(BF ) versus 0.5 m CuSO is primarily attributed to as follows:\n4 2 4\nThe 3.5 m Cu(BF ) electrolyte exhibits higher ionic conductivity, superior Cu2+ transference\n4 2\nnumber, and reduced desolvation energy. These synergistic effects collectively enhanced the\nrate capability, as discussed in detail in the revised manuscript (Pages 8-10, Lines 210-260).\nAs suggested, we have now included: the rate performances (Supplementary Fig. 26) and\ncycling performances (Supplementary Fig. 27) of different concentrations of Cu(BF ) in the\n4 2\nrevised Supporting information (Page 21 and 22).\nSupplementary Fig. 26 | Rate performance of a 0.5 m Cu(BF ) and b 1 m Cu(BF ) ; c,\n4 2 4 2\nComparative rate performance of different electrolytes.\nSupplementary Fig. 27 | a, Cycling stability test of Cu|0.5 m Cu(BF ) |S@CNT cells and Cu|1\n4 2\nm Cu(BF ) |S@CNT cells. b, Cycling stability test, and c, GCD curves of the Cu|3.5 m\n4 2\nCu(BF ) |S@CNT cells at room temperature.\n4 2\n4. Can the four-electron transfer process of the sulfur cathode be realized in CuSO electrolyte\n4\nsystems? The authors should further explain the four-electron storage mechanism of the sulfur\ncathode and its connection with the BF − system.\nelectron transfer mechanism in different electrolytes. Our experimental results demonstrate that\nthe four-electron process is thermodynamically feasible in both CuSO and Cu(BF )\n4 4 2\nelectrolytes, but their kinetic behaviors differ significantly (Fig. 3b, Supplementary Fig. 41).\nWe revised the supporting information as follows:\n“The reaction mechanism is identical in both the CuSO and Cu(BF ) electrolytes; the\n4 4 2\ndistinction lies in their significantly different kinetic behaviors.” (Page 31)\nSupplementary Fig. 41 | a, CV curves for the first three cycles of the Cu|0.5 m CuSO |S@CNT\n4\ncell. b, GCD curves for the first three cycles of the Cu|0.5 m CuSO |S@CNT cell.\n4 2 4\n5. The stability of the Zn anode usually affects the performance of the full cell. Will the BF −\n4\ndecrease the stability of the Zn anode compared to SO 2−? The authors should provide relevant\n4\nexperimental results to prove this point.\nResponse: We would like to thank the reviewer for raising this critical point regarding the\ninfluence of anions on Zn anode stability. Our experimental results demonstrate that ZnSO\n4\ncannot enable low-temperature operation due to electrolyte freezing, whereas Zn(BF )\n4 2\nmaintains stable cycling performance at −50 °C (Supplementary Fig. 49-50). This superior low-\ntemperature capability makes Zn(BF ) a promising candidate for cryogenic applications.\n4 2\nHowever, we acknowledge that the BF − anion does impact Zn anode stability. To address this,\n4\nexploring artificial SEI construction and electrolyte engineering strategies may enhance\ninterfacial stability for practical applications.\nWe revised the manuscript as follows:\n“The stability of the Zn anode is critical for the performance of Zn-S full cells. Here, the\nstability of ZnSO and Zn(BF ) on Zn anodes was evaluated across varying temperatures\n4 4 2\n(Supplementary Fig. 49-50). The findings indicate that a 3.5 m Zn(BF ) electrolyte maintains\n4 2\nstability during long-term operation at low temperatures.” (Pages 14, Lines 337-341)\nWe revised the supporting information as follows:\n“Combining Supplementary Fig. 49 and Supplementary Fig. 50, both ZnSO and Zn(BF )\n4 4 2\nelectrolytes exhibit relatively poor Zn anode stability at room temperature. However, at sub-\nzero temperatures, Zn||Zn symmetric cells employing ZnSO fail to work, whereas the 3.5 m\n4 2\nSupplementary Fig. 49 a-c, Zn||Cu asymmetric and d-f Zn||Zn symmetric cell tests at room\ntemperature using electrolytes of 0.5 m ZnSO , 0.5 m Zn(BF ) , and 3.5 m Zn(BF ) .\n4 4 2 4 2\nSupplementary Fig. 50 | a-d, Zn-Cu asymmetric Zn||Zn symmetric cell tests at low\ntemperature using electrolytes of 0.5 m ZnSO , 0.5 m Zn(BF ) , and 3.5 m Zn(BF ) , and e\n4 4 2 4 2\nZn||Zn symmetric cell tests at low temperature using electrolytes of 3.5 m Zn(BF ) .\n4 2\nComments from reviewer 2:\nIn this manuscript, the authors developed a Cu(BF ) -based electrolyte, which possesses a low\n4 2\nfreezing point and high ionic conductivity at low temperatures, to operate Cu–S cells under\nsub-zero conditions. They also demonstrated its application in Zn–S batteries, achieving high\ncapacity and energy density at low temperatures. However, there is an issue in battery\nevaluation and lacks significant differentiation from prior studies. Detailed comments are\nprovided below.\nResponse: We sincerely appreciate the reviewer for providing these valuable suggestions. We\nwant to highlight that our work addresses three critical limitations that have hindered previous\naqueous sulfur-based battery systems:\ni) Low-temperature operation breakthrough:\nConventional systems relying on CuSO electrolytes inherently fail at sub-zero temperatures.\nperformance (ultra-high discharge capacity of 348 mA h g −1and an energy density of 339\n(S+Zn)\nW h kg −1 at −50 °C) that significantly surpasses all reported low-temperature aqueous\n(S+Zn)\nbattery systems.\nii) Reaction mechanism resolution:\nThe superior kinetics of the Cu(BF ) electrolyte, compared to conventional CuSO systems,\n4 2 4\nhave enabled us to resolve long-standing ambiguities in the sulfur conversion mechanism.\nConventional CuSO electrolytes exhibit poor reaction kinetics that obscure reaction\n4\nintermediates, the enhanced conductivity and charge transfer properties of Cu(BF ) allow clear\n4 2\ndifferentiation of all redox steps. This breakthrough has permitted precise identification of each\nphase transformation product through complementary techniques, including a novel charge\nanalysis method employed to further analyze the intermediate products, finally clarifying the\ncomplete 4-electron conversion pathway that was previously debated in literature.\niii) Resolving long-standing puzzles in aqueous sulfur battery electrochemistry:\nAqueous sulfur-based batteries have long faced two unresolved fundamental questions: (1) why\nthe initial CV cycle shows one reduction peak while subsequent cycles mysteriously develop a\nsecond peak, and (2) what causes the unexpected increase in discharge voltage after the first\ncycle. These puzzling phenomena have hindered the mechanistic understanding and\nperformance optimization of such batteries. Our work provides the first definitive answers to\nthese questions through comprehensive investigations, revealing the underlying mechanisms\nresponsible for both the evolving redox peaks and the anomalous voltage elevation in\nsubsequent cycles (Fig. 5).\n1. There is an issue in the design of the cut-off voltages for Cu–S full cells throughout the\nmanuscript. In Figures 3 and 4, under both high-rate and low-temperature conditions, the\ndischarge cut-off voltage is set below 0 V. While it is understandable that a lower cut-off may\nhave been chosen to accommodate the increased overpotential under harsh conditions, such\nsettings are unacceptable from an application standpoint. A battery must provide usable energy\nto power devices, and discharging below 0 V renders the cell incapable of fulfilling its intended\nfunction. This undermines the practical value and relevance of the results.\nResponse: We sincerely appreciate the reviewer’s insightful feedback regarding the cut-off\nvoltages in our Cu-S half-cell studies.\nIn Fig. 3 and 4, the primary objective is not to simulate practical operating conditions for a full\ncell, but rather to experimentally investigate the complete reaction mechanism of the sulfur\ncathode. In Fig. 6, the performance data for our assembled Zn-S full cell are presented with a\ndischarge cut-off voltage of ~1.0 V. This voltage is well within the practical range for powering\nelectronic devices and aligns with common application standards.\nIn response to your constructive suggestion, Cu-S all half-cell data (including those in Fig. 3\nand 4) have been updated; the potential values on the y-axis are now reported versus Ag/AgCl.\nFig. 3b GCD curves of Cu-S@CNT cells between 3.5 m Cu(BF ) and 0.5 m CuSO .\n4 2 4\nFig. 4a The first three GCD curves, c rate performance and corresponding GCD curves of\nCu|3.5 m Cu(BF ) |S@CNT cell at −60 °C.\n4 2\n2. This study appears to lack clear novelty compared to previous research. The approach of\nlowering the freezing point of aqueous electrolytes by disrupting hydrogen bonding through\nsalt concentration or anion selection is already well-established, both in methodology and\nmechanism. Furthermore, the manuscript does not identify any unique phenomena or properties\nspecific to the Cu(BF ) -based electrolyte. The authors are encouraged to clarify what\n4 2\ndistinguishes this work in terms of novelty.\nResponse: We appreciate the reviewer’s comment regarding the novelty of this work.\nOur work addresses three critical limitations that have hindered previous aqueous sulfur-based\nbattery systems:\ni) Low-temperature operation breakthrough:\nConventional systems relying on CuSO electrolytes inherently fail at sub-zero temperatures.\nperformance (ultra-high discharge capacity of 348 mA h g −1and an energy density of 339\n(S+Zn)\nW h kg −1 at −50 °C) that significantly surpasses all reported low-temperature aqueous\n(S+Zn)\nbattery systems.\nii) Reaction mechanism resolution:\nThe superior kinetics of the Cu(BF ) electrolyte, compared to conventional CuSO systems,\n4 2 4\nhave enabled us to resolve long-standing ambiguities in the sulfur conversion mechanism.\nConventional CuSO electrolytes exhibit poor reaction kinetics that obscure reaction\n4\nintermediates, the enhanced conductivity and charge transfer properties of Cu(BF ) allow clear\n4 2\ndifferentiation of all redox steps. This breakthrough has permitted precise identification of each\nphase transformation product through complementary techniques, including a novel charge\nanalysis method employed to further analyze the intermediate products, finally clarifying the\ncomplete 4-electron conversion pathway that was previously debated in literature.\niii) Resolving long-standing puzzles in aqueous sulfur battery electrochemistry:\nAqueous sulfur-based batteries have long faced two unresolved fundamental questions: (1) why\nthe initial CV cycle shows one reduction peak while subsequent cycles mysteriously develop a\nsecond peak, and (2) what causes the unexpected increase in discharge voltage after the first\ncycle. These puzzling phenomena have hindered the mechanistic understanding and\nperformance optimization of such batteries. Our work provides the first definitive answers to\nthese questions through comprehensive investigations, revealing the underlying mechanisms\nresponsible for both the evolving redox peaks and the anomalous voltage elevation in\nsubsequent cycles (Fig. 5).\n3. Regarding Figure 5, is the proposed charge storage mechanism specific to the Cu(BF ) -\n4 2\nbased electrolyte? If not, and if this mechanism has already been reported in conventional Cu–\nS systems, it may not warrant particular emphasis.\nResponse: Thank you for raising this important point about Fig. 5. The charge storage\nmechanism proposed in our study is not exclusively specific to the Cu(BF ) -based electrolyte.\n4 2\nPrevious studies on sulfur-based batteries predominantly employed copper sulfate\nelectrolytes14-16, which suffered from poor kinetics that obscured well-resolved redox peaks in\nCV measurements, leaving the reaction intermediates and transformation pathways persistently\ndebated. In this work, we address these limitations by introducing Cu(BF ) electrolyte, which\n4 2\nnot only exhibits a remarkably low freezing point but also enables superior sulfur redox kinetics,\nyielding clearly separated redox peaks that allow precise identification of reaction products at\neach stage.\nMore importantly, this work resolves two long-standing puzzles in aqueous sulfur\nelectrochemistry: (1) the origin of the one-to-two peak transition in reduction processes\nbetween initial and subsequent cycles, and (2) the mechanistic basis for the anomalous\ndischarge voltage increase after the first cycle. Through comprehensive investigations, we\nunambiguously reveal the underlying mechanisms governing both the evolving redox behavior\nand the voltage elevation phenomenon (Fig. 5), thereby overcoming fundamental barriers that\nhave hindered both mechanistic understanding and performance optimization in this field.\nReference:\n14. Wu X, et al. A Four‐Electron Sulfur Electrode Hosting a Cu2+/Cu+ Redox Charge Carrier.\nAngew. Chem. Int. Ed. 58, 12640-12645 (2019).\n15. Dai C, et al. Maximizing Energy Storage of Flexible Aqueous Batteries through\nDecoupling Charge Carriers. Adv. Energy Mater. 11, 14 (2021).\n16. Zhang X, et al. High‐Sulfur Loading and Single Ion‐Selective Membranes for High\nEnergy and Durable Decoupled Aqueous Batteries. Adv. Mater. 36, 3 (2023).\n4. As is well known, unlike conventional rocking-chair-type batteries, dual-ion-type batteries\nrequire the mass of not only the active materials but also the electrolyte and the dissolved salt\nto be considered when calculating energy density and specific capacity. In this manuscript, the\nenergy-related calculations are based on the mass of Zn + S. Could the authors clarify whether\nthe Zn mass refers to the Zn in the electrolyte or the Zn anode? Please provide detailed\ncalculation information along with the Zn mass in the electrolyte and the thickness of the Zn\nfoil used.\nResponse: We are deeply grateful for the reviewer’s exceptionally insightful comment, which\ndemonstrates their profound expertise in battery electrochemistry and comprehensive\nunderstanding of energy density calculations. The reviewer’s rigorous approach has prompted\nus to provide important clarifications regarding our calculation methodology. Following the\nconventional practice in sulfur-based battery research where specific capacities are typically\ncalculated based on active material mass. For fair comparison with existing literature, our\nreported values are based on active electrode masses (S + Zn), and the zinc mass corresponds\nto the consumed mass of the zinc anode.\nImportantly, inspired by the reviewer’s valuable suggestion regarding dual-ion system\ncharacteristics, we have further developed this concept into the first Zn-S flow battery system.\nThis innovative design fully leverages the advantages of our electrolyte system, achieving: (1)\na high electrolyte-based volumetric energy density of 41 Wh L−1, surpassing all-vanadium flow\nbatteries ( < 30 Wh L−1); and (2) unprecedented initial areal capacities of 40 mA h cm−2 (at\n−30 °C) stabilizing at 20 mA h cm−2, as demonstrated in Supplementary Fig. 56. These\nachievements not only validate the practical potential of our system but also highlight how the\nreviewer’s expert comments have significantly enhanced both the rigor and impact of our work.\nWe have implemented the above revisions in the manuscript. (Page 15, Lines 370-374)\nSupplementary Fig. 56 | a, Optical image of the Zn-S flow battery; b, GCD curves for the\nfirst three cycles of the Zn-S flow battery at −30 °C.\n5. 1) The authors claim that the BF ⁻ anion strongly interacts with water molecules, disrupting\n4\nhydrogen bonding between them and thus lowering the freezing point of the electrolyte. This\nis a widely recognized behavior of kosmotropic anions. Typically, in such cases, Raman and\nFT-IR spectra show an increase in strong hydrogen-bond peaks and a decrease in weak\nhydrogen-bond peaks, due to strong H-bonding between the anion and water. However, the\nopposite trend is observed in this manuscript, which does not support the proposed explanation.\nResponse: We sincerely appreciate the reviewer’s insightful observation regarding the\nhydrogen bonding interactions in our electrolyte. The apparent discrepancy arises from the\ndistinction between water-water and anion-water hydrogen bonding, which we clarify below:\ni) Interpretation of O-H stretching peaks:\nThe O-H stretching region primarily reflects water-water hydrogen bonding, categorized into\nstrong, weak, and non-hydrogen-bonded states. The “strong hydrogen bond” peaks in this\nregion originate from H O–H O interactions, which are the dominant driver of freezing. The\n2 2\nobserved decrease in strong water-water hydrogen bonds with increasing Cu(BF )\n4 2\nconcentration aligns with our claim: BF ⁻ disrupts the water network by preferentially forming\n4\nstrong anion-water interactions, thereby suppressing freezing. A similar trend has been reported\nin prior work (Adv. Funct. Mater. 2021, 31, 2010127).\nii) Anion-water interactions (~3600 cm−1):\nThe BF ⁻-water interaction is indeed reflected in the distinct peak at ~3600 cm−1 (Adv. Funct.\nbonded or anion-coordinated O-H groups. The increase in this peak’s intensity with Cu(BF )\n4 2\nconcentration directly supports our argument that BF ⁻ competes with and weakens the water-\n4\nwater hydrogen bonds, consistent with its kosmotropic behavior.\n2) Furthermore, in Figure 2b, the binding energy of H O–Cu2+ (−120 kcal/mol) is significantly\n2\nstronger than that of H O–BF ⁻ (−10 kcal/mol). These results suggest that the freezing point\n2 4\ndepression is likely dominated by the presence of Cu2+ rather than BF ⁻.\nreveal Cu2+ coordinates with up to 6 water molecules, while BF ⁻ to bound with more water\n4\nmolecules (about 8 water molecules) due to each F atom can form H-bonds with multiple H O\n2\nmolecules (Supplementary Fig. 22). Importantly, considering the 2:1 stoichiometric ratio of\nBF ⁻ to Cu2+ in the electrolyte system, the BF ⁻ anions collectively interact with a substantially\n4 4\nlarger number of water molecules than the Cu2+ cations. This quantitative analysis\ndemonstrates that BF ⁻ plays a more dominant role in disrupting the hydrogen-bond network\n4\nof water molecules (Fig. 2e), despite the stronger binding energy of H O–Cu2+.\n“Besides, each F atom in BF – can form H-bonds with multiple neighboring H O molecules\n4 2\n(Supplementary Fig. 22), resulting in a higher ratio of H O−BF − interactions compared to\n2 4\nH O−Cu2+, suggesting BF − plays a predominant role in improving the anti-freezing ability of\n2 4\nthe electrolyte.” (Page 7, Lines 181-184)\nSupplementary Fig. 22 | In 3.5 m Cu(BF ) electrolyte: a, number and percentage of H O\n4 2 2\nmolecules in Cu2+ solvation structure; b, H O molecules bonded to the BF – anion.\n2 4\nFig. 2 | e Free H O, Cu2+–H O, and BF ––H O ratio in 1 m and 3.5 m Cu(BF ) electrolytes.\n2 2 4 2 4 2\n3) On the other hand, Figure 2e shows a higher H O–BF ⁻ ratio compared to H O–Cu2+, which\n2 4 2\nappears inconsistent with the binding energy data in Figure 2b. The authors are encouraged to\naddress this discrepancy and clarify the underlying mechanism.\nResponse: We would like to thank the reviewer for the suggestion. Although the H O–Cu2+\n2\nbinding energy is higher than that of H O–BF – (Fig. 2e and 3d), the larger tetrahedral geometry\n2 4\nof BF – enables it to form H-bonds with more H O molecules. For more visualization, we\n4 2\nanalyzed the hydration structures of Cu2+ and BF – ions from the MD simulation\n4\n(Supplementary Fig. 22). The results indicate that Cu2+ coordinates with up to six water\nmolecules to form [Cu(H O) ]2+ hydrated structure, whereas each F atom in BF – can form H-\n2 6 4\nbonds with multiple H O molecules, enabling BF – to bound with a larger number of H O\n2 4 2\nmolecules.\nWe revised the manuscript as follows:\n“Detailed structural analysis reveals that the HBs between H O molecules in 3.5 m Cu(BF )\n2 4 2\nelectrolyte decreased from 70.6% (1 m Cu(BF ) ) to 33.5%, whereas the ratios of H O−BF −\n4 2 2 4\nand H O−Cu2+ increased substantially (Fig. 2e). Besides, each F atom in BF – can form H-\n2 4\nbonds with multiple neighboring H O molecules (Supplementary Fig. 22), resulting in a higher\n2\nratio of H O−BF − interactions compared to H O−Cu2+, suggesting BF − play a predominant\n2 4 2 4\nrole in improving the anti-freezing ability of the electrolyte.” (Page 7, Lines 179-184)\nSupplementary Fig. 22 | In 3.5 m Cu(BF ) electrolyte: a, number and percentage of H O\n4 2 2\nmolecules in Cu2+ solvation structure; b, H O molecules bonded to the BF – anion.\n2 4\n6. In Supplementary Figure 10, electrolytes with concentrations above 3.5 m show strong\nintensities near 3000 cm−1. If these peaks are also attributed to hydrogen bonding, it appears\nthat the spectral deconvolution may not have been performed appropriately.\nResponse: We thank the reviewer for raising this observation. The intensity rise near 3000\ncm−1 observed when the concentration exceeds 3.5 m does not reflect genuine hydrogen\nbonding features, and our deconvolution methodology remains valid for the following reasons:\nThe overall elevation in the 3000 cm−1 region in such plots is likely attributable to baseline\ndrift rather than a genuine spectral peak. Critically, there is no discernible peak shape at 3000\ncm−1. Furthermore, this region falls outside our defined hydrogen bonding vibrational ranges\n(strong H-bonding: ~3200 cm−1; weak H-bonding: ~3400 cm−1; non-H-bonding: ~3600 cm−1).\nIn the baseline-corrected spectra, the 3000 cm−1 region exhibits no characteristic peak. The\nelevation at this position does not affect the fitting of the hydrogen-bonding peaks at higher\nwavenumbers.\n7. In Supplementary Figure 5f, the 5 m electrolyte shows a heat flow signal near −20 °C\nfollowing the glass transition, which may indicate melting. However, in Figure 1a, the same\nelectrolyte appears to remain in a liquid state even at −60 °C. The authors are requested to\nclarify this discrepancy. Additionally, a clearer distinction and appropriate terminology for\nglass transition and freezing points should be applied throughout the manuscript.\nResponse: We thank the reviewer for the careful observation regarding the apparent\ndiscrepancy between the thermal behavior in Supplementary Fig. 5f and Fig. 1a.\nThe endothermic peak observed near −20 °C for 5 m Cu(BF ) during heating DSC\n4 2\nmeasurements is likely caused by a preceding cold-crystallization process. Similar phenomena\nhave also been reported in prior studies (J. Am. Chem. Soc. 2024, 146, 12743−12749). The\nelectrolyte maintains a liquid phase at −60 °C due to its exceptionally strong supercooling\ntendency, which kinetically suppresses freezing.\nTo clarify this behavior, we performed cooling DSC measurements on the 5 m Cu(BF )\n4 2\nelectrolyte. The resulting cooling curve showed no detectable freezing exotherm. Instead, the\nelectrolyte transitioned directly into a glassy state.\nConsequently, we have: (i) Replaced all heating DSC data with cooling curves in relevant\nfigures, and (ii) Strictly standardized terminology, distinguishing glass transition temperature\n(T ) from freezing point (T) to eliminate conceptual inconsistencies throughout the manuscript.\ng f\nFig. 1b The major phase transition temperature of Cu(BF ) at different concentrations (T:\n4 2 f\nfreezing points; T : glass transition temperature).\ng\nSupplementary Fig. 7 | DSC curves of 1.0 m, 2.0 m, 3.0 m, 3.5 m, 4 m, and 5 m Cu(BF )\n4 2\nelectrolytes.\n8. The authors mention that minimized Cu2+–Cu2+ repulsion leads to a high Cu2+ transference\nnumber. Please clarify the correlation between reduced ionic repulsion and increased\ntransference number, as it is not clearly explained.\nResponse: We thank the reviewer for the insightful suggestions. The electrostatic potential\n(ESP) is reduced, indicating that the electrostatic repulsion around Cu2+ can be alleviated,\nwhich can be helpful for the transportation of Cu2+ (Nat. Commun. 2022, 13, 5348; Angew.\nChem. Int. Ed. 2023, 62, e202315834).\nHowever, given the significant role of strong ion-ion correlations in concentrated solutions,\nthere is currently no established universal model demonstrating that a lower ESP correlates\nwith higher transference numbers. Consequently, we have removed the description in the\nmanuscript that Cu2+–Cu2+ repulsion leads to a high Cu2+ transference number.\n9. In Supplementary Figures 25 and 26, Rct is measured as a function of voltage rather than\ntemperature, which is not a common approach. If there is a specific reason for this method,\nplease explain the significance of Rct measured at different voltages. Furthermore, please\nensure consistency in the units used for activation energy throughout the manuscript (eV or\nkJ/mol).\nResponse: We sincerely appreciate the reviewer’s insightful suggestion regarding our EIS\nmethod and units. This work specifically investigates how electrolyte composition governs\ninterfacial reaction kinetics across different operating voltages. To directly capture these\nvoltage-dependent kinetic processes under practical battery operating conditions, we\ndeliberately measured Rct as a function of applied voltage rather than temperature\n(Supplementary Fig. 32).\nFurthermore, to maintain consistency, we have adopted eV as the standardized unit for\nreporting activation energy throughout the manuscript (Supplementary Fig. 38).\nSupplementary Fig. 32 | Comparisons of charge transfer impedance at different potentials of\nCu-S@CNT coin cell with 3.5 m Cu(BF ) and 0.5 m CuSO .\n4 2 4\nSupplementary Fig. 38 | Activation energies of Cu||Cu cells with 3.5 m Cu(BF ) and 0.5 m\n4 2\nCuSO .\nThis study addresses one of the core limitations of aqueous batteries—poor low-temperature\nperformance—by proposing a novel Cu(BF ) -based electrolyte with a low freezing point\n4 2\n(−119.8 °C) and strong ion transport properties. The Zn–S cell developed here shows superior\nlow-temperature energy density. The current article is not suitable for submission to nature\ncommunications.\nResponse: We sincerely appreciate the reviewer’s feedback and suggestions. We are grateful\nfor the opportunity to improve our manuscript to meet the high standards of Nature\nCommunications. Below is our detailed response to the points raised.\n1.The main logic of the manuscript centers on improving low-temperature performance by\nreplacing the anion in the electrolyte. The authors are encouraged to clarify the causal\nrelationship throughout the manuscript.\nResponse: We sincerely appreciate the reviewer’s valuable suggestion. In this work, we\ndeveloped a low-temperature electrolyte by strategically selecting and optimizing the anion\nspecies in copper-based electrolytes, where the copper ions serve dual functions as both charge\ncarriers and redox-active species. Based on the Hofmeister series and cost considerations, we\nidentified BF ⁻ as the optimal anion. The resulting 3.5m Cu(BF ) electrolyte not only exhibits\n4 4 2\nexcellent freeze tolerance but also maintains high ionic conductivity while enabling faster\nreaction kinetics and higher energy density compared to conventional CuSO systems–\n4\naddressing the common trade-off in conventional approaches that use non-electrochemically\nactive additives.\nThe fundamental principles of electrolyte design are elaborated in the Introduction (Page 2,\nLines 52-59), while the systematic anion selection and optimization process are detailed in\nPage 4 (Page 4, Lines 92-99).\nWe also revised the manuscript as follows:\n“Furthermore, compared to other chaotropic anions such as ClO ⁻ and TFSI⁻, Cu(BF ) also\n4 4 2\nexhibits a significant cost advantage (Supplementary Fig. 6).” (Page 4, Lines 96-98)\nSupplementary Fig. 6 | Comparative costs of copper and zinc salts containing various\nchaotropic anions.\n2.At −60 °C, the cell delivers a record-breaking initial capacity of 3158 mA h g −1 at 0.1 A\nS\ng−1, but the capacity retention drops to 53% by the second cycle (1810 mA h g −1). Could this\nS\nirreversible capacity loss be mitigated through further optimization? The origin of this loss (e.g.,\nside reactions or interface instability) should be analyzed, as it is critical for practical\napplications.\nResponse: We sincerely appreciate the reviewer’s insightful comment regarding the capacity\nfade. Our mechanistic investigations presented in the “Charge storage mechanism” section\nreveal that the observed irreversible capacity loss primarily originates from the incomplete\nelectrochemical conversion of CuS to S during the charging process. This is attributed to the\nsubstantial energy barrier for the CuS→S conversion reaction, resulting in a mixed-phase\nproduct (CuS + S) rather than complete sulfur regeneration.\nTo address this critical issue, we have expanded the discussion in our revised manuscript to\npropose two promising optimization strategies: (1) development of advanced catalytic host\nmaterials (such as single-atom catalysts) to lower the reaction energy barrier, and (2) further\nelectrolyte engineering to enhance the reaction kinetics at ultra-low temperatures. These\nmodifications are now incorporated in the revised Discussion section (Page 16, Lines 386-391).\n3.The sulfur positive electrode is reported to undergo a four-electron transfer reaction with\nCu2+ ions to form Cu S. It should be clarified whether the reaction is a multistep, reversible\n2\nconversion or if irreversible intermediates are involved. Is this sulfur||copper multistep\nconversion mechanism newly proposed in this work, or has it been previously reported?\nResponse: We thank the reviewer for raising these critical mechanistic questions.\nPrevious studies on sulfur-based batteries predominantly employed copper sulfate\nelectrolytes14-16, which suffered from poor kinetics that obscured well-resolved redox peaks in\nCV measurements, leaving the reaction intermediates and transformation pathways persistently\ndebated. In this work, we address these limitations by introducing copper fluoroborate\nelectrolyte, which not only exhibits a remarkably low glass transition temperature but also\nenables superior sulfur redox kinetics, yielding clearly separated redox peaks that allow precise\nidentification of reaction products at each stage.\nMore importantly, this work resolves the long-standing puzzle in aqueous sulfur\nelectrochemistry: the origin of the one-to-two peak transition in reduction processes between\ninitial and subsequent cycles.\nii) We revised the manuscript as follows:\n“Comprehensive analysis reveals that sulfur undergoes a multi-step phase transition during\ndischarge (S ↔ Cu S ↔ Cu S ↔ Cu S ↔ Cu S), corresponding to a progressive increase\n9 8 7 4 31 16 2\nin copper content within Cu S compounds, ultimately yielding Cu S as the final discharge\nx 2\nproduct. Conversely, the charging process involves the extraction of Cu from Cu S, with the\nx\nthermodynamically favored endpoint being elemental sulfur. However, the high energy barrier\nassociated with the conversion of sulfur results in incomplete phase transformation, leaving a\nmixture of S + CuS as the charging product. This explains the observed discrepancy between\nthe first charge (lower) and discharge (higher) specific capacities. Interestingly, the residual\nCuS in the charge product enhances the overall conductivity, thereby accelerating the reaction\nkinetics of sulfur in subsequent cycles. This effect is clearly reflected in the second-cycle CV\ncurve, which exhibits two distinct reduction peaks due to the improved electrochemical\nactivity.” (Page 13, Lines 317~327)\nReference:\n14. Wu X, et al. A Four‐Electron Sulfur Electrode Hosting a Cu2+/Cu+ Redox Charge Carrier.\nAngew. Chem. Int. Ed. 58, 12640-12645 (2019).\n15. Dai C, et al. Maximizing Energy Storage of Flexible Aqueous Batteries through\nDecoupling Charge Carriers. Adv. Energy Mater. 11, 14 (2021).\n16. Zhang X, et al. High‐Sulfur Loading and Single Ion‐Selective Membranes for High‐\nEnergy and Durable Decoupled Aqueous Batteries. Adv. Mater. 36, 3 (2023).\n4. Does the additional CV peak relate to the presence of BF ⁻ anions? Have similar peaks been\n4\nobserved in systems using CuSO -based electrolytes? The authors should provide evidence for\n4\nwhether the mechanisms in CuSO and Cu(BF ) systems are consistent, and clarify whether\n4 4 2\nBF ⁻ directly contributes to capacity.\nunrelated to BF ⁻ anions.\n4\nremarkable similarity to those of the Cu(BF ) electrolyte. This confirms identical reaction\n4 2\nmechanisms between both electrolytes, and the BF ⁻ anion does not contribute to the capacity.\n4 2\nrate capability compared to the CuSO electrolyte.\n4\ncell. b, GCD curves for the first three cycles of the Cu|0.5 m CuSO |S@CNT cell.\n4 2 4\n5. The cost comparison in Fig. 6f may not be well-justified. A full-cell cost analysis is\nrecommended, considering the decoupled architecture, the use of functional membranes (anion\nexchange), and the relatively higher price of Cu(BF ) versus CuSO . The economic\n4 2 4\ncompetitiveness of the proposed system should be re-evaluated.\nResponse: We sincerely appreciate the reviewer’s insightful comments regarding the cost\nanalysis. This valuable suggestion helps us significantly improve the quality of our manuscript.\ni) Focus on cathode material cost comparison:\nIn this study, we primarily compared cathode materials because they are critical components\ndominating the cost and performance of aqueous batteries. Moreover, for emerging battery\ntechnologies in early-stage research (like ours), a full-cell cost assessment may lack practical\nrelevance, as system-level costs are highly sensitive to industry maturity. For instance, lithium-\nion batteries achieved significant cost reduction only after decades of commercialization. Thus,\nwe focused on the cathode material.\nii) Mitigation of membrane costs:\nConsidering the high cost of the AEM, we propose an asymmetric electrode-membrane\nconfiguration (Supplementary Fig. 53), to reduce the overall cost of the Zn-S full cell.\nWe have implemented the above revisions in the manuscript. (Page 15, Lines 356-364)\niii) Competitiveness with commercial flow batteries:\nWe also developed a novel zinc-sulfur flow battery (Supplementary Fig. 56). It outperforms\nall-vanadium flow batteries in volumetric energy density, and delivers a record-breaking initial\nareal capacity of 40 mA h cm−2 at −30 °C, with subsequent cycles stabilizing at 20 mA h cm−2,\ndemonstrating its feasibility.\nWe have implemented the above revisions in the manuscript. (Page 15, Lines 370-374)\nRegarding Cu(BF ) vs. CuSO : We acknowledge that the cost of Cu(BF ) (35.5 $ kg−1)\n4 2 4 4 2\nsignificantly exceeds that of CuSO (< 5 $ kg−1). However, the BF ⁻ anion is critical for\n4 4\nenabling stable battery operation under low-temperature conditions. Future scale-up production\nmay potentially reduce this cost.\nSupplementary Fig. 53 | Schematic diagram of the asymmetric electrode-membrane battery.\nSupplementary Fig. 54 | a, Optical photograph of the asymmetric Zn-S battery design, with a\nsulfur mass loading of 5 mg (7.5 mg cm−2). b, Variation in sulfur loading relative to the AEM\narea. c, GCD curves of the asymmetric Zn-S battery at − 20 °C. The current density is 20 mA\ncm−2 based AEM areal.\nFig. 6e Cost advantage of the asymmetric electrode-membrane design.\nSupplementary Fig. 56 | a, Optical image of the Zn-S flow battery; b, Performance of the Zn-\nS flow battery at −30 °C.\n6. The driving of a small electronic device (e.g., a digital watch) in Fig. 6e may not\nconvincingly demonstrate the electrolyte’s practical capability, especially considering the large\nelectrolyte volume used. A more representative demonstration of practical application is\nsuggested.\nResponse: We sincerely appreciate the valuable comments provided by the reviewer.\nInspired by the reviewer’s valuable comments and to enhance the practical application of low-\ntemperature Zn-S systems, we have developed the first low-temperature Zn-S flow battery\nsystem. This system fully leverages the advantages of our electrolyte system, achieving: (1) a\nhigh electrolyte-based volumetric energy density of 41 Wh L−1, surpassing all-vanadium flow\nbatteries ( < 30 Wh L−1); and (2) unprecedented areal capacities of 40 mA h cm−2 (initial cycles\nat −30 °C) stabilizing at 20 mA h cm−2, as demonstrated in Supplementary Fig. 56. These\nachievements not only validate the practical potential of our system but also highlight how the\nreviewer’s expert comments have significantly enhanced both the rigor and impact of our work.\nWe have implemented the above revisions in the manuscript. (Page 15, Lines 370-374)\nSupplementary Fig. 56 | a, Optical image of the Zn-S flow battery; b, GCD curves for the\nfirst three cycles of the Zn-S flow battery at −30 °C.\n7. The study would benefit from a comparison with recent state-of-the-art aqueous sulfur\nbatteries under low-temperature conditions. Additionally, a cost-to-energy density analysis is\nsuggested to evaluate whether the proposed system offers real-world advantages.\nResponse: We thank the reviewer for their constructive suggestions. Our responses are\nsummarized as follows:\nAs noted, recent research on aqueous sulfur-based batteries has primarily focused on room-\ntemperature optimization, as exemplified by Zn-S (Adv. Energy Mater. 2023, 13, 2301279),\nAl-S (Chem. Commun. 2020, 56 (13), 2023−2026.), Cu-S (Energy Storage Materials. 2022,\n48, 74–81), and Fe-S (Adv. Energy Mater. 2019, 9 (40), 1902422.) systems. Systematic reports\non sub-zero performance remain scarce due to the intrinsically poor freeze resistance of\nconventional electrolytes.\nRegarding the cost-to-energy density evaluation, we have re-incorporated the anion exchange\nmembrane (AEM) cost into our assessment as suggested in Question 5. Through an asymmetric\nelectrode-membrane design strategy, the system attains an optimized cost efficiency of 3.6 Wh\n$−1 (0.28 $ Wh−1). Detailed analyses of cost savings are provided in the revised manuscript (Fig.\n6e, Page 15, Lines 356-364) and Supporting Information (Supplementary Fig. 53-54, Page 40-\n41).\nComments from reviewer 4:\nLow-temperature, low-cost rechargeable batteries are a crucial topic, particularly in\ntechnological applications. From an academic perspective, the fundamental issues are the\nexplanation and design principles. This paper attempts to approach these two essential topics.\nThis research introduces Cu(BF ) -based electrolyte for aqueous zinc-sulfur batteries that\n4 2\nremains functional at extreme temperatures as low as −50°C, offering unprecedented ionic\nconductivity without compromising performance. While the demonstration of such\nperformance is indeed publication-worthy, and the authors have conducted extensive\nmeasurements to characterize both the electrolyte and its performance in Zn-S full cells, many\ncritical explanations remain unclear. In its current form, the manuscript would benefit from\nfurther clarification and refinement before it can be considered for publication. The following\nare several phenomena and proposed mechanisms that, in my view, require more rigorous\ndiscussion.\nResponse: We sincerely appreciate the reviewer’s feedback and suggestions. The comments\nhave been carefully addressed below.\n1. This paper proposes that Cu(BF ) can disrupt the hydrogen bond network and therefore\n4 2\nenhance low-temperature performance. Fig 2b and Figure 3d show the comparison of binding\nenergy between H O-BF -, Cu2+-BF - , Cu2+-H O, etc. A comprehensive comparison should\n2 4 4 2\ninclude Cu2+-SO -, H O-SO 2-, and present them in the same plot for readers.\n4 2 4\nResponse: We would like to thank the reviewer for the suggestion. As suggested, we have\ncalculated the binding energy of H O–SO 2– (Fig. 2b) and Cu2+–SO 2– (Fig. 3d), and provide a\n2 4 4\ncomprehensive comparison with H O–H O, H O–BF –, Cu2+–H O, and Cu2+–BF –.\n2 2 2 4 2 4\nWe revised the manuscript as follows:\n“To investigate the anti-freezing mechanism of the electrolyte, theoretical simulations were\nalso performed. The strong binding energy between H O–BF – interaction effectively disrupts\n2 4\nHBs between H O molecules (Fig. 2b), thereby modifying the low-temperature performance\n2\nof electrolytes. While H O–SO 2– displays higher binding energy than H O–BF –, the electron\n2 4 2 4\ndensity analysis (Fig. 2c) reveals that BF – induces more significant electron loss from\n4\nhydrogen atoms in H O molecules, making BF – a superior HB acceptor compared to SO 2–.”\n2 4 4\n(Pages 7, Lines 163-168)\n“The high binding energy between Cu2+–BF –, Cu2+–SO 2– suggested that BF – and SO 2–ions\n4 4 4 4\ncan preferentially participate in the solvation sheath of Cu2+ in electrolytes (Fig. 3d). The radial\ndistribution function (RDF) analysis of 0.5 m CuSO reveals negligible participation of SO 2–\n4 4\nin the primary solvation shell of Cu2+ at this low concentration (Fig. 3e).” (Page 9 and 10, Lines\n235-238)\nFig. 2 | b The binding energies of H O with H O, BF –, and SO 2–.\n2 2 4 4\nFig. 3 | d The binding energies of Cu2+ with H O, BF –, and SO 2–.\n2 4 4\n2. In addition to the binding energy of anion-cation and cation-solvent, the electron charge\ndensity difference analysis between H O and anions, i.e., SO 2–, BF –, can provide direct\n2 4 4\nevidence that BF – acts as a better HB acceptor than SO 2–. This analysis is necessary because\n4 4\nin MD simulations, partial charges constitute a significant portion of the calculations, yet these\npartial charges are parameterized (fitted) parameters that may not fully reflect charge\npolarization effects.\nResponse: We appreciate the reviewer for this suggestion. We have conducted the electron\ncharge density analysis to compare the H-bond interactions between H O and anions, i.e., SO 2–,\n2 4\nBF – (Fig. 2c and Supplementary Fig. 19).\n2 4 2 4\natoms in H O bonded to BF – exhibit greater electron loss than in SO 2–. This enhanced electron\n2 4 4\nloss, attributed to the higher electronegativity of F, strengthens the covalent component of the\nH-bonds in H O–BF – complexes. Consequently, BF – acts as a better HB acceptor than SO 2–.\n2 4 4 4\nWe revised the manuscript as follows:\n“While H O–SO 2– displays higher binding energy than H O–BF –, the electron density\n2 4 2 4\nanalysis (Fig. 2c) reveals that BF – induces more significant electron loss from hydrogen atoms\n4\nin H O molecules, making BF – a superior HB acceptor compared to SO 2–.” (Page 7, Lines\n2 4 4\n166-168)\nSupplementary Fig. 19 | a, The detailed atomic charges of H O, SO 2–, and BF –. Calculated\n2 4 4\nelectron density of b, H O and SO 2–; c, H O and BF –. Key: electron accumulation (blue) and\n2 4 2 4\nelectron depletion (yellow).\n3. The Raman spectra and FTIR are provided to correlate the freezing point and the ratio of HB\ntypes. In Fig 1b, there is a minimum for the temperature-concentration relationship. However,\nthe ratio of the three H-bond types shows monotonic behavior from 1m to 5m, Fig 2a. This\ncounterintuitive behavior may need further explanation.\nResponse: We thank the reviewer for the insightful suggestion. Thermodynamically, an\nincrease in the system’s entropy (S) reduces the Gibbs free energy, thereby lowering the\nfreezing point.11-12 As the concentration of Cu(BF ) increases, interactions between water\n4 2\nmolecules weaken (associated with S increase), while ion-water and ion-ion interactions\nstrengthen (associated with S decrease). The competition between the two parts affects the S\nof the system, leading to the freezing point of the electrolyte exhibiting a non-monotonic, V-\nshaped trend.\nHowever, the O-H stretching vibrations in fitted Raman (Fig. 2a, Supplementary Fig. 14) and\nFT-IR (Supplementary Fig. 18) spectra only reflect the evolution of H-bonds between H O\n2\nmolecules, and do not reflect ion-pair or ion-water interactions (associated with S decrease).\nConsequently, the freezing point does not exhibit a monotonic behavior with concentration,\nnor the types of HBs formed between H O molecules.\n“The optimal anti-freezing performance at 3.5 m concentration can be explained by\nthermodynamic principles. Thermodynamically, the phase transition temperature of the\nelectrolyte is closely related to the entropy.11-12 Generally, higher system entropy corresponds\nto lower phase transition temperature. As Cu(BF ) concentration increases, two competing\n4 2\neffects emerge: (1) entropy decreases as enhances the interactions among electrolyte\ncomponents (Cu2+–H O, BF ––H O, Cu2+–BF –), while (2) entropy increases as ions disrupt\n2 4 2 4\nHB network of water (Fig. 2d). The 3.5 m Cu(BF ) electrolyte achieves an optimal balance\n4 2\nbetween H-bonds and ion-pair/ion-water interactions, yielding the lowest glass transition\ntemperature.” (Page 7, Lines 171-179)\nReference:\n11. Qiu M, et al. Tailoring water structure with high-tetrahedral-entropy for antifreezing\nelectrolytes and energy storage at −80 °C. Nat. Commun. 14, 601 (2023).\n12. Qiu, M. et al. Tailoring tetrahedral and pair-correlation entropies of glass-forming liquids\nfor energy storage applications at ultralow temperatures. Nat. Commun. 15, 10420 (2024).\nFig. 2d | The interaction energy (normalized according to volume) between H O and H O, Cu2+\n2 2\nand H O, BF – and H O, Cu2+ and BF – at different concentrations.\n2 4 2 4\n4. The MD simulation size (~500 molecules) is relatively small by modern standards. For\nelectrolyte systems, several thousand molecules are typically used to ensure adequate statistical\nsampling and minimize finite-size effects. I suggest the authors double the system size and\nperform convergence tests to validate their conclusions.\nResponse: We thank the reviewer for the insightful suggestion. We have conducted MD\nsimulation and performed convergence tests for the 3.5 m Cu(BF ) electrolyte by increasing\n4 2\nthe system size by factors of two (1000 H O molecules), four (2000 H O molecules), and eight\n2 2\n(4000 H O molecules) (Supplementary Fig. 57, Table 6).\n(between H O) indicates that the results obtained with the system size scaled by a factor of four\n2\n(2000 H O molecules) agree well with those from the system scaled by a factor of eight\n2\n(Supplementary Fig. 58). Consequently, simulations for all other Cu(BF ) concentrations and\n4 2\nthe 0.5 m CuSO electrolyte were conducted at the fourfold scaled system size (2000 H O\n4 2\nmolecules) (Supplementary Table 5) for consistent data analysis.\nWe revised the computational methods in manuscript as follows:\n“Convergence tests based on electrolyte density, RDFs, and H-bond length distribution\n(between H O) were used to determine the number of water molecules and ions in the systems\n2\n(Supplementary Table 6, Fig. 57 and 58)” (Page 18, Lines 474-478)\nBesides, we revised the supporting information as follows:\n“Note: convergence tests based on electrolyte density, RDFs, and H-bond length distribution\n(between H O) indicates that the results obtained with 2000 H O molecules agree well with\n2 2\nthose from the system with 4000 H O molecules. Consequently, simulations for all other\n4 2 4 2\nmolecules (Supplementary Table 5) for consistent data analysis.” (Page 44)\nSupplementary Fig. 58 | Convergence tests for the 3.5 m Cu(BF ) electrolyte with system\n4 2\nsizes according to Supplementary Table 6. Radial distribution function and coordination\nnumbers of a, Cu2+–O (H O), b, Cu2+–F (BF –). c, The density of simulated electrolytes. d,\n2 4\nDistribution of H-bond lengths between H O molecules in simulated electrolytes.\nfor 3.5 m Cu(BF ) used to perform convergence tests.\n4 2\nNamed H O Cu2+ BF −\n2 4\n500 500 32 64\n1000 1000 64 128\n2000 2000 128 256\n4000 4000 256 512\nSupplementary Table 5. The numbers of water molecules and ions in amorphous cell module.\nElectrolyte H O Cu2+ BF − SO 2− Volume (Å3)\n2 4 4\n0.5 m CuSO 2000 20 — 20 —\n4\n1 m Cu(BF ) 2000 36 72 — 65927.2\n4 2\n2 m Cu(BF ) 2000 72 144 — 69826.4\n4 2\n3 m Cu(BF ) 2000 108 216 — 73687.4\n4 2\n3.5 m Cu(BF ) 2000 128 256 — 76299.9\n4 2\n4 m Cu(BF ) 2000 144 288 — 78120.5\n4 2\n5 m Cu(BF ) 2000 180 360 — 82332.7\n4 2\n5.The paper states that “excessively high concentrations can increase the electrostatic\ninteraction energy (Supplementary Fig. 17f), thereby raising the freezing point of the\nelectrolyte. ref [17]” This statement requires clarification on several points:\nIt is unclear whether the calculated electrostatic interaction energy is normalized by per unit\nvolume or by per mol of molecules. According to the MD simulation description in this paper,\nthe total volume should differ for each concentration.\nResponse: We thank the reviewer for the insightful suggestion. We have calculated the\ninteraction energy of water-water, ion-ion, and ion-water pairs using the MD results obtained\nafter the convergence test and normalized it according to volume (Fig. 2d, Supplementary\nTable 5). The results indicate that increasing electrolyte concentration weakens the interactions\nbetween water molecules and enhances the ion-water and ion-ion interactions.\nFig. 2d | The interaction energy (normalized according to volume) between H O and H O, Cu2+\n2 2\nand H O, BF – and H O, Cu2+ and BF – at different concentrations.\n2 4 2 4\nEven considering ref[17], there is still no established relationship between electrostatic\ninteraction energy and freezing point. While increasing the ion concentration enhances the\noverall Coulombic interactions, this does not necessarily correlate with changes in the freezing\npoint.\nResponse: We thank the reviewer for this valuable question. We have calculated the interaction\nenergy of water-water, ion-ion, and ion-water pairs using the MD results to replace the previous\noverall electrostatic interaction energies (Fig. 2d).\nThermodynamically, the phase transition temperature is closely related to the entropy (S) of\nthe electrolyte (Nat. Commun. 2023, 14, 601; Nat. Commun. 2024, 15, 10420). Increasing\nsystem S constitutes an essential strategy for lowering the phase transition temperature of\nelectrolyte. With increasing Cu(BF ) concentration, more H-bond breakages to increase S and\n4 2\nthe enhance the interactions among electrolyte components (ion-pair or ion-water interactions)\nto lower S. The competition between the two parts affects the S of the system, leading to the\nfreezing point of the electrolyte exhibiting a non-monotonic, V-shaped trend.\nWe revised the manuscript as follows:\n“The optimal anti-freezing performance at 3.5 m concentration can be explained by\nthermodynamic principles. Thermodynamically, the phase transition temperature of the\nelectrolyte is closely related to the entropy.11-12 Generally, higher system entropy corresponds\nto lower phase transition temperature. As Cu(BF ) concentration increases, two competing\n4 2\neffects emerge: (1) entropy decreases as enhances the interactions among electrolyte\ncomponents (Cu2+–H O, BF ––H O, Cu2+–BF –), while (2) entropy increases as ions disrupt\n2 4 2 4\nHB network of water (Fig. 2d). The 3.5 m Cu(BF ) electrolyte achieves an optimal balance\n4 2\nbetween H-bonds and ion-pair/ion-water interactions, yielding the lowest glass transition\ntemperature.” (Page 7, Lines 171-179)\nFig. 2d | The interaction energy (normalized according to volume) between H O and H O, Cu2+\n2 2\nand H O, BF – and H O, Cu2+ and BF – at different concentrations.\n2 4 2 4\nRegarding the reaction kinetics of the positive electrode, the authors conflate different concepts:\n6. While reaction kinetics (desolvation process and charge transfer) are indeed related to\nsolvation structure, a lower electrostatic potential (EPS) around a cation’s solvation shell does\nnot necessarily facilitate charge transfer barrier crossing. Charge transfer resistance is more\ndirectly related to solvent reorganization energy rather than just the EPS value. I recommend\nthe authors consult Marcus theory literature to better understand the relationship between\nreorganization energy and charge transfer kinetics.\nResponse: We thank the reviewer for the insightful suggestion. Based on a careful recheck of\nthis part and a thorough review of the literature on Marcus’s theory, we have revised it\naccordingly. Specifically, the statement linking ESP to desolvation and charge transfer\nprocesses has been removed.\nWe revised the manuscript as follows:\n“To further elucidate the influence of solvation structure on Cu2+ redox kinetics, we\ninvestigated the electron transfer process between the electrode and solvated Cu2+ ions through\nreorganization energy (λ) analysis. The reorganization energy represents the energy required to\nrearrange the solvation sheath during electron transfer, which follows Marcus’ non-adiabatic\nelectron transfer theory.38-39 The λ values were obtained by fitting the Tafel plots (Fig. 3g) with\nthe Marcus-Hush-Chidsey kinetic model (Equation 1, Methods).40-41 Remarkably, the 3.5 m\nCu(BF ) electrolyte exhibits a substantially lower reorganization energy (0.118 eV) compared\n4 2\nto 0.5 m CuSO (0.180 eV) (Fig. 3h). This significant difference can be attributed to the unique\n4\nsolvation structure of Cu(BF ) , where the participation of BF – anions create a more loosely\n4 2 4\ncoordinated environment (Supplementary Table 1). The presence of BF – in the primary\n4\nsolvation shell increases the solvated radius (a ) of Cu2+, thereby reducing the energy barrier\n0\nfor solvent reorganization during electron transfer (Equation 2, Methods).42” (Page 10, Lines\n249-260)\nWe have also provided the corresponding experimental methods in the revised manuscript:\nThe reorganization energy (λ) was obtained by Marcus–Hush–Chidsey kinetics (equation\n1):\n∞\n(1)\n∞ 2\n+ (𝜒−𝜆±𝜂̃) 𝑑𝜒\nwhere is the current 𝑖de=nsAity ∫−; A i𝑒s𝑥 t𝑝he{ −pre-ex\n4\np\n𝜆\none}n\n1\nt\n+\nia\n𝑒\nl\n𝑥\nf\\𝑝\n{\n𝜒\n}\nt\nia\nl\nf\nc\nt\nor;λis reorganization energy;\nis the dimensionless overpotential, η is the overpotential, e is the elementary charge,\n𝑖 𝜂̃ = \ne\nηis 𝜅t𝐵h𝑇e Boltzmann’s constant, T is the absolute temperature. The fitted is divided by T𝜅 t𝐵o\ngive the non-scaled reorganization energy (eV).\n𝜆 𝜅𝐵\nThe reorganization energy (λ) can be expressed as a dielectric continuum formulation\n(equation 2):\n(2)\n2\n𝑒 1 1 1 1\nwhere is the vacuum per𝜆m=itt4𝜋i𝜀t0y(, 𝑎e0 i−s th𝑅e) (el𝜀e𝑜c𝑝t−ron𝜀𝑠 c)harge, is the solvated radius of the\ncations, R is the distance between the solvated ions and electrode surface, is the optical\n𝜀0 𝑎0\ndielectric constant, and is the static dielectric constant. (Page 17, Lines 433-444)\n𝜀𝑜𝑝\n𝜀𝑠\nFig. 3g Ohmic resistance-corrected Tafel plot for Cu stripping in 3.5 m Cu(BF ) and 0.5 m\n4 2\nCuSO electrolytes and fitting with Marcus-Hush-Chidsey kinetics. h The reorganization\n4\nenergy ( ) comparison in 3.5 m Cu(BF ) and 0.5 m CuSO electrolytes.\n4 2 4\n𝜆\nSupplementary Table 1. The solvated radius (a ) and reciprocal of solvated radius ( ) of Cu2+\n0\na0\n1\nsolvation structure for CuSO and Cu(BF ) electrolytes.\n4 4 2\nReciprocal of\nMain solvation Solvated radius a 0 solvated radius\nElectrolyte Percentage (%)\nstructure of Cu2+ (nm)\n(nm–1)\na0\n4 2 6\n[Cu(H O) ]2+ 20.31 0.406 2.463\n2 6\n[Cu(H O) (BF )]+ 41.41 0.499 2.004\n2 5 4\nCu(BF )\n4 2\n[Cu(H O) (BF ) ] 25.78 0.550 1.818\n2 4 4 2\n[Cu(H O) (BF ) ]– 10.94 0.603 1.658\n2 3 4 3\nNote: the solvation structures are optimized using Gaussian 16W software. The a is defined\n0\nas the distance from the farthest atom to the geometric center of the optimized solvation\nstructures.\n7. The authors mention that 3.5 m Cu(BF ) has a higher Cu2+ transference number. The\n4 2\ntransference number relates to the relative self-diffusivity of cations and anions. At high\nconcentrations, this phenomenon is further complicated by ion-ion correlated transport.\nHowever, there is currently no established universal model demonstrating that lower EPS\ncorrelates with higher transference numbers or lower charge transfer resistance.\nResponse: We thank the reviewer for the insightful suggestion regarding the Cu2+ transference\nnumbers. We have now carefully rechecked and revised this part. Given the significant role of\nstrong ionic interaction in concentrated solutions, we have therefore removed the description\nin the manuscript that EPS correlates with higher transference numbers.\n8. From 0.5m to 3.5m, ionic conductivity increases approximately five-fold, while charge\ncarrier density increases seven-fold, indicating that ion mobility actually decreases.\nSimultaneously, the self-diffusivity of ions in bulk electrolytes is expected to decrease even\nmore rapidly with concentration. From this perspective, further analysis using MD simulations\ncould help elucidate why Cu2+ exhibits a higher transference number at 3.5 m concentration.\nResponse: We appreciate the reviewer for this suggestion. We simulated the diffusion\ncoefficients of Cu2+ and BF – in 0.5 m and 3.5 m Cu(BF ) based on the MD results\n4 4 2\n(Supplementary Fig. 36). As the concentration increases from 0.5 m to 3.5 m, the electrolyte\nviscosity rises (equation 1), reducing ion self-diffusion. Crucially, the diffusion coefficient of\nCu2+ decreases 3.28-fold, versus a 7.88-fold reduction for the larger BF – anions. This disparity\n4\nindicates a significantly greater suppression of BF – ion mobility compared to Cu2+ ions, as\n4\nestablished by the Nernst-Einstein (NE) relation (equation 2) (Plawsky, J.L. (2020). Transport\nPhenomena Fundamentals (4th ed.). CRC Press.). The Cu2+ transference number is governed\nby the relative ion mobility of the anion and cation (equation 3). Therefore, the more significant\nreduction in BF – ion mobility results in an elevated Cu2+ transference number in 3.5 m\n4 2\n(1)\n𝜅𝐵𝑇\n𝐷 = 6𝜋𝜂𝑟 (2)\n𝑧𝑒\nμ=D𝑇𝜅𝐵\n(3)\n𝜇+\nwhere D is diffusion coefficient; is𝑡 +io=n m𝜇+o+b𝜇i−lity; T is the absolute temperature; is the\nBoltzmann constant; is electrolyte viscosity; r is Stokes radius (solvation radius); z is the\nμ 𝜅𝐵\nionic charge number; e is the elementary charge; t is the transference number of cations.\n+\n𝜂\nWe added the above discussion in Supplementary Fig. 36 (Page 28) in the revised Supporting\nInformation and revised the manuscript as follows:\n“The superior performance of the 3.5 m Cu(BF ) electrolyte is further evidenced by its higher\n4 2\nCu2+ transference number (0.698) compared to the 0.5 m CuSO electrolyte (Supplementary\ntransport (Supplementary Fig. 36)”. (Page 8-9, Lines 220-223)\nSupplementary Fig. 36 | MSD of a, Cu2+ and b, BF –/SO 2– in 0.5 m Cu(BF ) , 3.5 m Cu(BF )\n4 4 4 2 4 2\nand 0.5 m CuSO electrolytes.\n4\n9. The concept expressed in Fig 3h is confusing. It’s unclear whether the authors intend to\ndemonstrate that (i) anions are more easily repelled near charged surfaces, or (ii) the\nreorganization energy of charge transfer processes is reduced. If the former, this pertains to\nhow the electric double layer influences reaction kinetics. If the latter, the authors should\ndiscuss changes in free energy during the desolvation process rather than just electrostatic\npotentials.\nResponse: We thank the reviewer for their expert and insightful feedback. To avoid ambiguity,\nwe have removed the original Fig 3h. As suggested in Question 6, we now analyze the solvent\nreorganization energy for the two electrolytes, presenting it as new Fig 3g and 3h.\n10. I would like to clarify whether the diffusion coefficient mentioned between Line 226-228,\ndetermined through Galvanostatic Intermittent Titration Technique (GITT), refers to ion\ndiffusion within the cathode materials rather than ion diffusion in the bulk electrolyte.\nResponse: We appreciate the reviewer’s thoughtful feedback regarding the diffusion\ncoefficient. We confirm that the GITT-derived diffusion coefficient (D ) specifically\nCu2+\nquantifies Cu2+ ion diffusion within the S@CNT composite cathode material, not bulk\nelectrolyte diffusion.\nTo avoid ambiguity, we revised the manuscript as follows:\n“Galvanostatic intermittent titration technique (GITT) is also used to study the diffusion\nkinetics of Cu2+ in the electrode material, revealing higher diffusion coefficients with 3.5 m\nCu(BF ) electrolyte compared to 0.5 m CuSO electrolyte (Supplementary Fig. 33).” (Page 8,\n4 2 4\nLines 218-220)\n11. Supplementary Fig. 26 shows that the charge transfer resistance of Cu-S@CNT coin cells\nwith 3.5 m Cu(BF ) versus 0.5 m CuSO differs by approximately a factor of two. However,\n4 2 4\nin Supplementary Fig. 29, which uses Cu||Cu symmetric cells, the Rct values differ by at least\ntwo orders of magnitude (as the figure uses a logarithmic scale). This significant discrepancy\nis noteworthy and merits further investigation.\nResponse: Thank you for your insightful suggestion regarding the differences in the impedance\ndata. We have conducted additional tests to verify the consistency of these measurements and\nconfirm that both datasets are valid.\nThe apparent difference in the charge transfer resistance (R ) arises from the following two\nct\nkey factors:\ni) Supplementary Fig. 29 (revised to Supplementary Fig. 38) employs a logarithmic scale,\nwhich visually amplifies the absolute difference in R values. Taking the 25 °C data as an\nct\nexample, the R for 3.5 m Cu(BF ) is 3.3 Ω, while that for 0.5 m CuSO is 54 Ω. The actual\nct 4 2 4\ndifference is only 50.7 Ω, which falls entirely within a reasonable range.\nii) Supplementary Fig. 26 (revised to Supplementary Fig. 32) is based on a Cu-S@CNT coin\ncell. In contrast, Supplementary Fig. 29 (revised to Supplementary Fig. 38) is based on a\nhomemade symmetric cell (Cu||Cu). It should be noted that the different cell configurations\nand interfacial reactions may result in R values that are not directly comparable in absolute\nct\nterms. However, both sets of data exhibit consistent trends: 3.5 m Cu(BF ) significantly\n4 2\nenhances the interfacial charge transfer kinetics.\n12. Finally, regarding the operation of the Zn-S full cell: When utilizing an anion exchange\nmembrane to enable the use of Zn electrochemistry, a concentration gradient may develop\nacross the membrane, with Zn ion concentration increasing on one side while Cu ions are\nconsumed on the other. This raises questions about potential concentration polarization effects.\nDuring the discharge process, Cu2+ ions are continuously reduced, leading to a progressive\ndecrease in Cu(BF ) concentration at the positive electrode. At what point would this\n4 2\nconcentration decrease significantly deviate from the initially proposed 3.5 m Cu(BF ) ,\n4 2\npotentially compromising the beneficial properties of the high-concentration electrolyte? These\nconcentration dynamics warrant further investigation to fully validate the long-term practicality\nof this electrolyte system under actual operating conditions.\nResponse: We sincerely appreciate your insightful comments. The potential formation of\nconcentration gradients across the AEM and consequent concentration polarization risks you\nhighlighted indeed represent critical challenges.\nOur investigations revealed that water molecules can migrate across the AEM from the high-\nconcentration side to the low-concentration side, partially mitigating the concentration gradient\n(Supplementary Fig. 55). Additionally, we designed a Zn-S flow battery configuration, which\nutilizes a large electrolyte reservoir to minimize the impact of localized concentration changes.\nThis approach ensures that the overall electrolyte composition remains stable, preserving the\nbeneficial properties of the 3.5 m Cu(BF ) electrolyte over extended cycling.\n4 2\nWe revised the manuscript as follows:\n“During discharge, Zn2⁺ accumulation at the anolyte and Cu2⁺ consumption at the catholyte\ncreate a concentration gradient, and water could transport across the AEM to balances the ionic\nconcentrations, preventing significant concentration polarization (Supplementary Fig. 55).\nConsequently, the electrolyte maintains relatively stable composition in both compartments,\nwhich is crucial for preserving its excellent low-temperature performance.\nGiven the inherent advantages of flow batteries for large-scale energy storage and the high\nvolumetric energy density of this system (41 Wh L−1, surpassing that of all-vanadium flow\nbatteries (< 30 Wh L−1))50, we designed a Zn-S flow battery. It delivers a high initial areal\ncapacity of 40 mA h cm−2 at −30 °C, with subsequent cycles stabilizing at 20 mA h cm−2,\ndemonstrating its feasibility (Supplementary Fig. 56).” (Page 15, Lines 365-374)\nReference:\n50. Trovò A, Rugna M, Poli N, Guarnieri M. Prospects for industrial vanadium flow\nbatteries. Ceram. Int. 49, 24487-24498 (2023).\nSupplementary Fig. 55 | Schematic diagram of water transport equilibrium concentration\nacross the AEM. After 48 hours of static conditions, water molecules were clearly observed\nmigrating toward the higher-concentration Cu(BF ) solution.\n4 2\nSupplementary Fig. 56 | a, Optical image of the Zn-S flow battery; b, GCD curves for the\nfirst three cycles of the Zn-S flow battery at −30 °C.\nThis work is an important research direction with significant potential for low-temperature\nbattery applications. I look forward to seeing more detailed exploration of the fundamental\nscientific mechanisms underlying these observations, which would substantially strengthen this\npromising work and advance our understanding of electrolyte design for extreme temperature\napplications.\nResponse: We sincerely appreciate your insightful and constructive comments, which have\ngreatly helped us improve the quality of our manuscript. We fully agree with your suggestions.\nWe have conducted additional experiments and analyses to further elucidate the key\ninteractions and principles governing electrolyte behavior at low temperatures. We believe\nthese revisions have significantly enhanced the manuscript, offering a more comprehensive\nunderstanding of electrolyte design for extreme-temperature applications. We hope the revised\nversion meets the high standards of Nature Communications.\nThank you again for your valuable input, which has been instrumental in advancing this\nresearch.\nResponses to referees’ comment\nComments from reviewer 1:\nThe authors have solved all my concerns. Now the manuscript is suitable to be\npublished.\nResponse: We sincerely thank the Reviewer for the positive feedback and confirmation\nthat all concerns have been adequately addressed. We are pleased that the manuscript\nnow meets the standard for publication.\nComments from reviewer 2:\nI appreciate the authors’ efforts; the revisions have satisfactorily addressed my previous\ncomments. No further revisions are necessary.\nResponse: We are sincerely grateful for your positive feedback and for acknowledging\nour revisions. We appreciate their time and insightful suggestions.\nComments from reviewer 4:\nI would like to thank the authors for carefully addressing the concerns raised in the\nprevious review. The revised manuscript shows substantial improvement and provides\nadditional analyses that strengthen the work. I have several questions and suggestions\nthat I believe could help strengthen the mechanistic understanding and theoretical\nframework presented in the manuscript.\nResponse: We sincerely thank the Reviewer for your thorough review and positive\nassessment of our revised manuscript. We also greatly appreciate the insightful\nquestions and suggestions provided, which have helped us further refine the\nmechanistic discussion and theoretical framework of our study. Our point-by-point\nresponses are detailed below.\n1. BF ⁻ versus SO 2⁻\n4 4\nThe manuscript's explanation for the differing effects of BF ⁻ and SO 2⁻ on the water\n4 4\nhydrogen-bond network remains unclear, particularly regarding the binding energy data.\nAccording to Figs. 2b and 3d, a more negative binding energy signifies a stronger\ninteraction. Fig. 2b suggests that the H O–SO 2⁻interaction is stronger than the H O–\n2 4 2\nBF ⁻ interaction. This leads to a key question: If SO 2⁻ binds more strongly to water,\n4 4\nwhy does BF ⁻, the more weakly interacting anion, cause a greater disruption to water's\n4\nhydrogen-bond network?\nResponse: We thank the reviewer for this insightful question. This apparent\ncontradiction—that SO 2⁻ exhibits a more negative binding energy with H O yet proves\n4 2\nless effective than BF – at disrupting the hydrogen bond (HB) network between water\n4\nmolecules—highlights a fundamental principle: strong ion-dipole interactions do not\nnecessarily translate into the ability to effectively disrupt the original HB network\nbetween water molecules.\nSO 2⁻, kosmotropic anion (Q. ReV. Biophys. 1997, 30, 241.) with high charge density,\n4\nforms a highly ordered and stable hydration shell through strong ion-dipole interactions\n(Fig. 2c). However, this locally enhanced structure tends to further strengthen the long-\nrange HB network in water, making it freeze more easily.\nIn contrast, BF ⁻, as a chaotropic anion, although shows more weakly binding energy\n4\nwith H O molecules (Fig. 2b). Its lower charge density prevents BF – from promoting\n2 4\nan ordered hydration shell, leading instead to a loose and flexible hydration structure\n(Fig. 2c). This disruption of the extended HB connectivity effectively inhibits the water\nmolecular arrangement necessary for freezing.\nTherefore, the anti-freezing performance of the aqueous electrolyte is determined by\nthe ability to disrupt the global HB network—rather than the strength of the local\nbonding energy between the two species—which explains the superior anti-freezing\nbehavior exhibited by the BF ⁻.\n“SO 2⁻ with high charge density exhibits a strong interaction with H O (Fig. 2b, and\n4 2\nSupplementary Fig. 19), which promotes the formation of a highly ordered and stable\nhydration shell through strong ion-dipole interactions (Fig. 2c). This ordered structure\nconsequently strengthens the long-range HB network of water, facilitating ice\nformation. In contrast, BF – exhibits weaker binding energy with H O molecules, which\n4 2\nprevents the formation of an ordered hydration shell, leading instead to a loose and\nflexible hydration structure (Fig. 2c). This disruption of the extended HB connectivity\neffectively inhibits the water molecular arrangement necessary for freezing. Therefore,\nthe anti-freezing performance of the aqueous electrolyte is determined by the ability to\ndisrupt the global HB network—rather than the strength of the local bonding energy\nbetween the two species.” (Page 7, Lines 163-171)\nFig. 2 | c, Radial distribution function of O (in SO 2⁻) – H atom and F (in BF ⁻) – H\n4 4\natom.\n2. The concept presented in Fig. h and Marcus-Hush-Chidsey analysis\nSeveral elements in Fig. h seem inaccurate:\n- Reorganization energy is not equivalent to the free energy barrier for charge transfer.\nResponse: We sincerely apologize for the error in the schematic diagram of Fig. 3h and\nfully concur with the reviewer’s comments. The reorganization energy (λ) represents\nthe energy required for the rearrangement of the solvent shell during electron transfer,\nwhereas the activation free energy barrier denotes the total energy obstacle that must\nbe overcome for the entire reaction. These two parameters are closely related yet\nconceptually distinct. We have removed the potentially misleading schematic diagram\nin Fig. 3h from the manuscript.\n- Overpotential (η) depends on current. There is no apparent reason why the\noverpotential of 3.5 m Cu(BF ) should be substantially lower than that of 0.5 m CuSO .\n4 2 4\nIf the authors intend to compare overpotentials between the two systems, the\ncomparison should be made at a specified current density.\nResponse: We hereby clarify that the overpotentials presented in Fig. 3h were all\nderived from measurements conducted at identical current densities in the two\nelectrolytes. The 3.5 m Cu(BF ) electrolyte demonstrates a lower overpotential, which\n4 2\nis directly correlated with its higher ionic conductivity (Supplementary Figs. 28-30)\nand faster desolvation kinetics (Fig. 3g).\nTo better highlight the comparison of the core parameters and prevent any potential\nmisinterpretation, we have removed the overpotential data from the original Fig. 3h and\nhave replotted it as a bar chart directly comparing the reorganization energy (λ) values\nof the 3.5 m Cu(BF ) and 0.5 m CuSO electrolytes. This modification makes the\n4 2 4\nsignificant difference between them clearer and more intuitive.\nFig. 3 | Comparison of Cu-S@CNT cells reaction kinetics between 3.5 m Cu(BF )\n4 2\nand 0.5 m CuSO . Comparisons of a rate performance, b GCD curves, c energy density\n4\nof Cu-S@CNT cells between 3.5 m Cu(BF ) and 0.5 m CuSO . d The binding energies\n4 2 4\nof Cu2+ with H O, SO 2–, and BF –. e Radial distribution function and coordination\n2 4 4\nnumbers of Cu2+−O (H O) in 0.5 m CuSO electrolyte, Cu2+−O (H O) and Cu2+−F\n2 4 2\n(BF −) in 3.5 m Cu(BF ) electrolyte. f The distribution of the solvation structures in\n4 4 2\n3.5 m Cu(BF ) electrolyte. g Activation energies of Cu||Cu cells with 3.5 m Cu(BF )\n4 2 4 2\nand 0.5 m CuSO . h Ohmic resistance-corrected Tafel plot for Cu stripping in 3.5 m\n4 2 4\ni The reorganization energy (𝜆) comparison in 3.5 m Cu(BF ) and 0.5 m CuSO\n4 2 4\nelectrolytes.\n- The manuscript describes two approaches for estimating reorganization energy: (i)\nfitting current–overpotential data with the Marcus–Hush–Chidsey (MHC) model, and\n(ii) estimation using a dielectric continuum formulation. However, the results from\nthese two approaches are not compared.\nResponse: We thank the reviewer for raising this important point. It should be noted\nthat the calculation of reorganization energy using the dielectric continuum formulation\ninvolves several parameters that are difficult to measure directly through experiments,\nsuch as the precise distance between ions and the electrode surface (R), the optical\ndielectric constant (ε ), etc. The values of these parameters significantly influence the\nop\ncomputational results and are associated with considerable uncertainty. Therefore, after\ncareful consideration, we have decided to retain only the values obtained by directly\nfitting the electrochemical data with the Marcus-Hush-Chidsey (MHC) model, as this\nmethod provides a more direct and reliable measurement of the kinetics in our system.\nThe theoretical dielectric continuum model was removed to avoid any potential\nconfusion and to streamline our discussion.\nWe revised the manuscript as follows:\n“This significant difference may be attributed to the participation of BF ⁻ anions, which\n4\ncreates a more loosely coordinated environment (Supplementary Table 1). This looser\nsolvation shell facilitates easier reorganization during the electron transfer process,\nthereby accelerating the kinetics.” (Page 10, Lines 260-262)\n- On page 17, the MHC equation is not clearly presented. For example, the meaning of\nχ is not defined. The dimensional consistency also appears problematic: if λ has units\nof energy, how can it be summed with a dimensionless overpotential? If the authors\nintend to discuss this aspect, please cite the relevant literature carefully and verify the\ndimensional analysis and physical meaning of each parameter.\nResponse: We thank the reviewer for pointing out these critical omissions in the\npresentation of the MHC equations. We have now added the definition of χ and clarified\nthat the λ in the fitting formula represents the dimensionless reorganization energy.\nThe Methods section has been revised as follows:\n“The dimensionless variable χ, which is integrated over, accounts for the Fermi\nstatistics of electron energies distributed around the electrode potential; λ is the\ndimensionless reorganization energy, which, when multiplied by k T, yields the\nB\nreorganization energy with units of energy (eV) reported in the main text.41” (page 17,\nLines 439-442)\nReferences:\n41. Bai, P., Bazant, M. Z. Charge transfer kinetics at the solid-solid interface in porous\nelectrodes. Nat. Commun. 5, 3585 (2014).\nIt may, in fact, be beyond the scope of the manuscript to fully describe this system with\nthe MHC model. Removing the unclear part would not weaken the paper. Refining the\ndiscussion to emphasize the most robust findings would help ensure that readers clearly\nunderstand the significance of the results.\nResponse: We greatly appreciate the constructive suggestion raised by the reviewer. As\npreviously stated in our earlier responses, to ensure the clarity of the findings and the\nreliability of the conclusions in the manuscript, we have:\n(1) Removed the potentially misleading schematic in the original Figure 3h to avoid\nany confusion between the concepts of reorganization energy and activation energy\nbarrier.\n(2) Deleted the theoretical calculations based on the dielectric continuum model, in\norder to focus on the more direct and reliable kinetic parameters obtained through direct\nfitting of the MHC model using electrochemical data.\n(3) Added the definition of the integration variable χ and corrected the dimensionality\nissues related to the reorganization energy λ.\nThese revisions allow our discussion to concentrate more effectively on the central\nfinding of this work: the experimental confirmation that a 3.5 m Cu(BF₄)₂ electrolyte\nsignificantly reduces the reorganization energy during the charge-transfer process,\nthereby clarifying the microscopic mechanism behind the enhanced reaction kinetics of\nthe sulfur cathode.\n3. Fig. 2c and electronic structure analysis\nIt is unclear whether Fig. 2c shows an isosurface of constant electron density or electron\ndensity difference. The caption states electron density, but the plot itself suggests\nelectron density difference or possibly frontier orbitals.\nResponse: We sincerely apologize for the error in the caption of original Fig. 2c (now\nSupplementary Fig. 19), where “electron density difference” was mistakenly written as\n“electron density.” We have corrected it to “electron density difference” in the revised\nmanuscript. (Supplementary Fig. 19, page 15).\nFor Fig. S19, please specify which method was used to derive the atomic charges.\nSince partial charges in DFT are not uniquely defined (e.g., Bader, ESP, Mulliken),\nthe chosen scheme should be explicitly stated, as the numerical values depend strongly\non the method.\nResponse: We apologize for the oversight regarding the missing information in the\nmanuscript. In Fig. S19, we derive atomic charges using the Mulliken method. We have\nnow provided detailed information on the calculation of the Mulliken charges and\nelectron density difference in the revised manuscript.\nWe have included detailed information in the computational methods of revised\nmanuscript as follows:\n“The Mulliken charges and electron density difference were calculated using the DMol3\nmodule 59-60 within the Materials Studio package. The exchange-correlation energy was\ntreated with the generalized gradient approximation (GGA) functional combined with\nthe Perdew–Burke–Ernzerh (PBE) functional. Van der Waals interactions were\nincorporated using the Tkatchenko–Scheffler (TS) correction method61. The core\nelectrons and valence orbitals were described using an all-electron treatment and the\ndouble numerical plus polarization (DNP) basis set (version 4.4), respectively.\nGeometry optimization convergence criteria were set to 1.0×10–5 Ha for energy, 0.002\nHa/Å for force, and 0.005 Å for displacement. The self-consistent field (SCF)\nconvergence threshold was set to 1.0×10–6 Ha.” (Page 18, Lines 484-492)\nReferences:\n59. Delley, B. An all‐electron numerical method for solving the local density functional\nfor polyatomic molecules. J. Chem. Phys. 92, 508–517 (1990).\n60. Delley, B. From molecules to solids with the approach. J. Chem. Phys. 113, 7756-\n7764 (2000).\n61. Tkatchenko, A., Scheffler, M. Accurate Molecular Van Der Waals Interactions from\nGround-State Electron Density and Free-Atom Reference Data. Phys. Rev. Lett. 102,\n073005 (2009).\nAdditionally, I’m curious about the choice to use effective core pseudopotentials for the\nDFT calculations. For molecular systems of this size, computational cost is typically\nnot a limiting factor, and all-electron calculations are generally preferred for higher\naccuracy. It would be helpful if the authors could clarify the considerations that led to\nthis choice.\nResponse: We sincerely apologize for the omission of the calculation details in this\nsection. In the calculations of Mulliken charges and electron density differences using\nthe DMol3 module, the all-electron treatment was consistently applied. We have now\nprovided detailed information on the calculation of the Mulliken charges and electron\ndensity difference in the revised manuscript.\nWe have included detailed information in the computational methods of revised\nmanuscript as follows:\n“The Mulliken charges and electron density difference were calculated using the DMol3\nmodule 59-60 within the Materials Studio package. The exchange-correlation energy was\ntreated with the generalized gradient approximation (GGA) functional combined with\nthe Perdew–Burke–Ernzerh (PBE) functional. Van der Waals interactions were\nincorporated using the Tkatchenko–Scheffler (TS) correction method61. The core\nelectrons and valence orbitals were described using an all-electron treatment and the\ndouble numerical plus polarization (DNP) basis set (version 4.4), respectively.\nGeometry optimization convergence criteria were set to 1.0×10–5 Ha for energy, 0.002\nHa/Å for force, and 0.005 Å for displacement. The self-consistent field (SCF)\nconvergence threshold was set to 1.0×10–6 Ha.” (Page 18, Lines 484-492)\nReferences:\n59. Delley, B. An all‐electron numerical method for solving the local density functional\nfor polyatomic molecules. J. Chem. Phys. 92, 508–517 (1990).\n60. Delley, B. From molecules to solids with the approach. J. Chem. Phys. 113, 7756-\n7764 (2000).\n61. Tkatchenko, A., Scheffler, M. Accurate Molecular Van Der Waals Interactions from\nGround-State Electron Density and Free-Atom Reference Data. Phys. Rev. Lett. 102,\n073005 (2009).\n4. Interaction energy in Fig. 2d\nThe definition of “interaction energy” is unclear. For example, in the MD simulations,\nhow were Coulombic interactions decomposed to isolate contributions from different\nspecies? More methodological detail is required.\nResponse: We thank the reviewer for pointing out the issue. The interaction energy\n(normalized according to volume) between H O–H O, Cu2+–H O, BF ––H O, and\n2 2 2 4 2\nCu2+–BF – at different concentrations were calculated using molecular dynamics.\nmanuscript as follows:\n“The interaction energy of H O–H O, Cu2+–H O, BF ––H O, and Cu2+–BF – at\n2 2 2 4 2 4\ndifferent concentrations was calculated using molecular dynamics and normalized by\nvolume (Supplementary Table 5). The interaction energy between the two species was\ncalculated according to the formula:\nE = E – E – E\ninter combined A B\nwhere E represents the interaction energy between the two species, E is the\ninter combined\ntotal energy of the combined system (species A+B), E is the energy of isolated species\nA\nA, and E is the energy of isolated species B.” (Page 18, Lines 475-481)\n5. Consistency of Supporting Figures\nAre Supplementary Fig. 12 and Supplementary Fig. 14 derived from the same dataset?\nThe captions suggest they are, yet the spectral features for 3.5 m and 4 m differ\nsignificantly.\nResponse: We thank the reviewer for raising this important point. Both Supplementary\nFig. 12 and Supplementary Fig. 14 were derived from the same dataset. The apparent\ndiscrepancy in baseline intensity for the 3.5 m sample is indeed due to its spectrum\nbeing acquired at a different time, a common occurrence in Raman spectroscopy that\ncan lead to baseline drift. Crucially, this intensity variation occurs around ~3000cm⁻1,\nwhich is outside the defined fitting range for our hydrogen-bonding analysis (strong:\n~3200 cm⁻1; weak: ~3400 cm⁻1; non: ~3600 cm⁻1). The region lacks characteristic\npeaks and does not impact the peak deconvolution results or the reported trends.\nNevertheless, to ensure the highest data consistency and address the reviewer’s valid\nconcern, we have re-prepared all samples and reacquired all spectra under identical\ninstrumental conditions. The new data, now included, robustly confirm the original\nconclusion that higher salt concentrations more significantly disrupt the hydrogen-\nbonding network.\nSupplementary Fig. 11 | a, The all Raman spectra and b, Raman spectra for B–F bond\nof 1, 2, 3, 3.5, 4, and 5 m Cu(BF ) electrolytes.\n4 2\nSupplementary Fig. 12 | Raman spectra for O–H bond of 1, 2, 3, 3.5, 4, and 5 m\nCu(BF ) electrolytes.\n4 2\nSupplementary Fig. 14 | The fitted O−H stretching vibration of Raman spectra\nrepresenting water molecules with strong H−bond, weak H−bond, and Non H−bond in\nthe Cu(BF ) electrolytes with different concentrations. a, 1 m Cu(BF ) ; b, 2 m\n4 2 4 2\nCu(BF ) ; c, 3 m Cu(BF ) ; d, 3.5 m Cu(BF ) ; e, 4 m Cu(BF ) ; f, 5 m Cu(BF ) .\n4 2 4 2 4 2 4 2 4 2\nFig. 2a The proportion of strong HBs, weak HBs, and non HBs in Cu(BF ) electrolytes\n4 2\nwith different concentrations.\n6. I suggest the authors review whether the cited literature provides the most appropriate\nreferences for readers seeking to understand the discussed concepts. For example,\nReference 14 appears to report 3044 mAh g⁻1 rather than the cited 3350 mAh g⁻1. While\nReference 35 mentioned solvation-kinetics relationships, there might be more\nspecialized literature that could provide additional depth to this discussion.\nResponse: We thank the reviewer for raising this point. The cited Reference 14 is a\nlandmark study that first demonstrated copper ions can act as charge carriers and\nachieve an ultrahigh specific capacity. The value of 3044 mA h g⁻1 corresponds to the\nexperimentally measured capacity reported in that paper, while the theoretical specific\ncapacity, based on the proposed four-electron reaction mechanism, is 3350 mA h g⁻1.\nTherefore, we believe that citing this work is appropriate.\nAs for Reference 35, we cited it because it provides direct experimental and\ncomputational evidence demonstrating that modifying the solvation structure (through\nthe introduction of specific additives) can effectively reduce the desolvation energy\nbarrier and enhance reaction kinetics, which aligns with our discussion on the role of\nBF ⁻ in the solvation sheath of Cu2+.\ndeeper insights into the fundamental relationship between solvation structure and\ndesolvation kinetics. In response to this comment, we have now incorporated additional\nreferences that provide more profound mechanistic understanding: J. Am. Chem. Soc.,\n2022, 144, 18435, which investigates the influence of halide anions (such as Cl⁻) on the\nsolvation structure of Zn2+; and Science, 2021, 374, 172, which systematically\nelucidates how the reorganization of the solvation sheath of multivalent metal ions (e.g.,\nZn2+, Mg2+) affects interfacial kinetics. These findings are highly consistent with our\nobservation that BF ⁻ modulates the solvation structure of Cu2+ to improve desolvation\n4\nkinetics.\nOverall, the revised manuscript represents evident progress, and I appreciate the authors’\nefforts to address earlier concerns. Addressing the issues above will substantially\nstrengthen the paper and ensure that it makes a reliable and impactful contribution to\nthe field.\nResponse: We sincerely thank you for your positive feedback on the revisions made to\nthe manuscript and for acknowledging the progress achieved. We are also grateful for\nyour constructive suggestions, which have undoubtedly helped improve the quality of\nour work. We have carefully addressed each of the remaining points raised in the\ncomments and believe that these further revisions have significantly strengthened the\npaper’s clarity, validity, and overall impact. We appreciate the time and effort the\nreviewer has dedicated to providing insightful recommendations.\nResponses to referees’ comments\nComments from reviewer 4:\nReviewer #4 (Remarks to the Author):\nThe authors have addressed all concerns raised during the review process. The\nexplanations are clear, and the manuscript's presentation has been significantly\nimproved. I have no further comments and believe the work is now suitable for\npublication.\nResponse: We sincerely grateful for your positive feedback and for acknowledging our\nrevisions. We are pleased to hear that our responses and modifications have adequately\naddressed your previous comments.\nThank you once again for your time and constructive input."}, {"round": 2, "reviewer_comments": {"reviewer_4": "I want to thank the authors for carefully addressing the concerns raised in the previous review. The additional clarifications and refinements have made the manuscript more accessible and easier to understand. The expanded literature citations also help readers better appreciate the context and background of this research.\nHowever, several aspects require further clarification to meet the standards expected for Nature Communications.\n1. The authors have clarified that the interaction energy was calculated according to the formula E_inter = E_combined - E_A - E_B. However, the practical implementation remains unclear. For example, when calculating the interaction energy of Cu²⁺ with H₂O, if system A contains only the Cu²⁺ ion without any other species, the MD simulation should not converge due to the lack of charge neutrality and an appropriate forcefield. Similarly, if system A is an isolated system of BF₄⁻, I have concerns about the validity of MD simulations for such a pure negative ion system.\n2. In line 180, the manuscript states: \"(2) entropy increases as ions disrupt HB network of water (Fig. 2d).\" However, Fig. 2d shows interaction energy, not entropy. These are distinct thermodynamic quantities that should not be used interchangeably. If the authors intend to discuss entropy, they should remove the reference to Fig. 2d and provide explicit entropy calculations with appropriate methodology.\n3. Regarding the DFT calculations, the authors specifically clarified in their response that they used DMol3. However, the manuscript describes using DMol3 with PBE functional and all-electron treatment for Mulliken charges and electron density difference, while using Gaussian 16 with B3LYP functional and pseudopotentials for binding energies in Fig. 2b and 3d. This mixing of different packages and functionals raises consistency concerns. For molecular systems of this nature, PBE is generally less accurate than B3LYP. Given the size of these systems, performing all calculations using B3LYP with all-electron treatment should be entirely feasible.\n4. Since this manuscript explores the effects of temperature, it is essential to specify the temperature at which the MD simulations were performed. Temperature significantly impacts diffusion coefficients, yet Fig. 2f does not indicate the simulation temperature. The authors should clearly state the temperature for all MD calculations to ensure proper interpretation and reproducibility.\nOverall, the manuscript has improved substantially. Addressing these computational methodology issues would strengthen the paper and ensure it meets the rigorous standards expected by Nature Communications."}, "author_response": "Responses to referees’ comment\nComments from reviewer 4:\nReviewer #4 (Remarks to the Author):\nThe authors have addressed all concerns raised during the review process. The\nexplanations are clear, and the manuscript's presentation has been significantly\nimproved. I have no further comments and believe the work is now suitable for\npublication.\nResponse: We sincerely grateful for your positive feedback and for acknowledging our\nrevisions. We are pleased to hear that our responses and modifications have adequately\naddressed your previous comments.\nThank you once again for your time and constructive input."}, {"round": 3, "reviewer_comments": {"reviewer_4": "The authors have addressed all concerns raised during the review process. The explanations are clear, and the manuscript's presentation has been significantly improved. I have no further comments and believe the work is now suitable for publication."}, "author_response": ""}]

Decision letter