Sub-micron-resolution temperature mapping of Zn negative electrode for flow batteries

Domain: physics
Published: 2026-03-05
Editorial outcome: minor_revision

Abstract
Zinc-based flow batteries are gaining attention as safe, cost-effective, and sustainable energy storage solutions amid global energy transition challenges. However, their practical application is hindered by poor reversibility and dendrite formation of Zn negative electrode, particularly under high state-of-charge conditions. Despite extensive research on Zn side, the relationship between localized temperature distribution and dendrites remains underexplored, primarily due to limited microscopic observation techniques. Here, we present a non-invasive optically detected magnetic resonance with nanodiamond quantum sensors to monitor temperature variations during Zn deposition, achieving a sub-micron spatial resolution (~300 nm) and a temperature sensitivity of ~2 K/Hz0.5. Our findings suggest that spatial temperature non-uniformity may play a critical role in accelerating dendrite growth and potentially leading to more severe short circuits. Simulations revealed that higher substrate thermal conductivity improves Zn deposition uniformity. Herein, we introduced a flowable gallium-indium liquid metal electrode, which disperses localized heat and lowers interfacial temperature gradients, thereby suppressing hotspot-driven dendrite growth and enabling in situ formation of a liquid Zn alloy. The zinc-bromine flow battery with the liquid metal electrode demonstrated enhanced cycling stability over 2400 hours at a high state-of-charge of 90%, achieving a cumulative discharge capacity of 46.2 Ah cm−2 at 40 mA cm−2.

Introduction
In addressing the challenges of global energy transition and climate change, flow batteries (FBs) are emerging as a highly efficient and scalable energy storage solution1, 2. Their distinctive design allows for the independent regulation of energy and power, making them particularly suitable for large-scale storage applications, especially in the integration of intermittent renewable energy sources such as solar and wind3, 4. Zinc-based flow batteries (Zn-FBs) stand out among the various FB technologies due to their notable safety, cost-effectiveness, and environmental sustainability5. The abundant and economical nature of Zn offers a distinct advantage in reducing material costs and advancing the widespread deployment of renewable energy systems6.

However, despite the numerous advantages of Zn-FBs, their practical application is still limited by the poor reversibility of the Zn negative electrode7. During the charging process, Zn deposition often exhibits inhomogeneity due to the inherent nature of liquid-solid phase transformation, which can easily lead to the formation of dendrites and exacerbate undesirable side reactions, as well as the generation of dead Zn8. Moreover, this inhomogeneity intensifies with the increase in state of charge (SOC) and areal capacity, thereby increasing the risk of short circuits and battery failure9. Various strategies have been proposed to tackle this issue, including electrode modification and electrolyte additives10. Despite these efforts, the improvements remain inadequate under practical testing conditions, such as high current density and high SOC, where the performance still falls short of expectations.

Despite acknowledging the correlation between metal negative electrode behavior and temperature, there has been insufficient exploration of the temperature changes at the microscopic scale during the deposition process in Zn-based batteries11. Additionally, existing temperature monitoring technologies mainly operate at the macroscopic level, failing to capture temperature fluctuations in the nanoscale environment or the impact of localized temperature "hotspots" on dendrite growth12, 13. Therefore, effective technology is urgently needed to monitor real-time temperature changes at the microscopic level throughout the Zn deposition and its evolution process. This is beneficial for enhancing our understanding of the mechanisms that govern dendrite growth and improving thermal management in battery systems.

In this work, we demonstrated spatially resolved temperature monitoring during Zn deposition by utilizing optically detected magnetic resonance (ODMR) with nanodiamond quantum sensors to analyze microscale temperature changes. The developed platform achieves sub-micron spatial resolution (~300 nm) and satisfactory temperature sensitivity (~2 K/Hz0.5), enabling temperature mapping and concurrent morphological tracking over areas up to 200 μm × 200 μm. We employed nanodiamond sensors in a wide-field configuration to map the spatially resolved temperature variations in a working Zn electrochemical cell, illustrating the spatial non-uniformity of temperature at the onset of internal short circuit, which may play a critical role in accelerating Zn dendrite formation. COMSOL simulations further revealed that increasing the substrate's thermal conductivity markedly reduced interfacial temperature gradients and improved Zn deposition uniformity, although this benefit diminished as the Zn coverage lowered the effective conductivity. To tackle this problem, we introduced a flowable eutectic gallium-indium (EGaIn) liquid metal (LM) electrode with high thermal conductivity into Zn-FBs. Forced convection within the LM promotes efficient heat transfer and facilitates rapid dissipation of hotspots, thereby reducing temperature gradients that accelerate dendrite growth. In parallel, the in situ alloying of Zn with LM suppresses dendrite formation and mitigates localized heat accumulation, resulting in a highly reversible Zn negative electrode. With enhanced thermal management and dendrite suppression, the zinc-bromine flow battery (ZBFB) demonstrated stable cycling performance, being charged to a SOC of 90% at a current density of 40 mA cm−2 and subsequently delivering a cumulative discharge capacity of 46.2 Ah cm−2.

Results
Spatial temperature distribution of Zn negative electrode

Temperature, as a critical factor influencing Zn morphology, significantly affects the reaction kinetics of the Zn2+/Zn couple and further impacts the plating-stripping process of Zn in Zn-FBs14. The heat generated by electrochemical reactions and Joule heating at high current densities can rapidly form local temperature "hotspots", further exacerbating the inhomogeneity of Zn deposition15. To investigate the thermal dynamics during Zn deposition with greater precision, we developed a custom-designed real-time in situ ODMR platform capable of mapping the spatial temperature distribution within electrochemical cells. A schematic of the device is presented in Fig. 1a, and the complete wide-field microscopy configuration for spatially resolved temperature sensing is shown in Supplementary Fig. 1. The cell configurations employed in the ODMR measurements are illustrated in Supplementary Fig. 2.

Nanodiamonds with nitrogen-vacancy (NV) centers (Fig. 1b) are used as temperature sensors for spatially resolved nanoscale temperature measurements in operating electrochemical devices. Their long spin coherence and high thermal conductivity make them ideal materials for sensitive thermal sensing16. A 532 nm laser was focused onto a total internal reflection fluorescence (TIRF) objective to excite NV centers in nanodiamonds, with the resulting fluorescence imaged via an electron-multiplying charge-coupled device (EMCCD) camera. Since the sensing relies on ODMR, the non-invasive optical characteristics of the measurement protocol ensure minimal disturbance to the testing system during the ongoing electrochemical process16. During the testing process, the spin states of NV centers are manipulated by applying microwaves. The temperature of nanodiamonds containing NV centers is determined by analyzing the zero-field splitting (D) temperature dependence in their ODMR spectra (Fig. 1c). The D, which describes the energy difference between the ms=0 and ms=±1 state of ground state NV electrons, is highly sensitive to thermal variations17. To quantify the D shift, the ODMR spectrum is fitted to a double-peak Lorentzian function, and the two resonance frequencies are averaged. A clear linear dependence of D on temperature is observed, with a slope of dD/dT = −74 kHz/K derived from ensemble measurements of 170 nanodiamond sensors (Supplementary Fig. 3), reflecting a stable and well-defined temperature sensitivity. On our measurement platform, the sensor updates the temperature in real time at intervals shorter than 1 s (Supplementary Fig. 4). By leveraging these features, our developed platform achieves sub-micron spatial resolution (~300 nm) and high temperature sensitivity (~2 K/Hz0.5), enabling wide-field temperature mapping and concurrent morphological tracking over areas of up to 200 μm × 200 μm.

During the constant-current charging of a Zn||Zn electrochemical cell, time-resolved thermal variations were monitored. Using a wide-field ODMR setup, we first recorded the temporal temperature profile of individual nanodiamond sensors during Zn plating, as exemplified in the upper panel of Fig. 1d (arrow marking the sensor’s position; see also Supplementary Figs. 5-8 for additional examples). By compiling the time‑dependent temperature data from all nanodiamonds within the spatial range, we constructed the spatially resolved map of temperature evolution shown in Fig. 1e, which highlights the temperature non-uniformity across the electrode surface. To analyze the evolution of local temperature rise more clearly, we divided the ODMR temperature maps into four regions (labeled 1, 2, 3, and 4). At the early stage of Zn deposition, approximately 61 s after initiation, the voltage curve displayed a notable drop, indicating that the rapid growth of Zn dendrites had caused a short circuit in the battery. Shortly thereafter, at 66 s, nanodiamond sensors in region 1 detected a sharp and localized temperature surge, exceeding 55 °C, marking the formation of an initial hotspot. As the deposition progressed, a second voltage drop appeared in the charging curve at 130 s, indicating the continued expansion of dendritic Zn regions. This corresponded closely to the substantial enlargement of heated areas observed between 150 s and 280 s in the nanodiamond temperature maps (Supplementary Fig. 9). Further spatial analysis of the dynamic spatiotemporal evolution revealed that, in region 1, high-temperature points expanded progressively from 66 s to 220 s, while in region 2 a similar expansion pattern emerged later, between 100 s and 220 s. This sequential growth of hotspot areas suggests that the initial temperature-rise locations act as preferential nucleation sites for subsequent thermal intensification and dendrite proliferation18. Consequently, early-formed hotspots not only mark the onset of localized heating but also appear to play a pivotal role in driving more extensive and intense thermal events as deposition continues. Analysis of the average temperature in each of the four regions showed that region 1 exhibited a decline after 220 s (Supplementary Fig. 10). This phenomenon may reflect the migration of dendritic growth and its associated Joule heating to other parts of the electrode, rather than intrinsic local cooling. These results indicate that the internal short circuit in batteries caused by dendrite growth may initially occur at very localized sites (on the nanoscale), and the heat generated can trigger further chemical reactions in the vicinity. This implies that even small-scale dendritic formations can lead to significant thermal effects, potentially exacerbating the failure within the battery. Therefore, effective thermal management at the microscale is essential for extending battery lifespan and ensuring operational reliability.

To mitigate the adverse effects of non-uniform temperature distribution on battery performance, we systematically investigated the influence of higher substrate thermal conductivity on Zn deposition behavior. Four substrates, carbon felt (CF), highly oriented pyrolytic graphite (HOPG), Zn, and silver, were selected to represent typical conductivity levels in carbon-based and metallic materials (Supplementary Table 1). In the model shown in Fig. 2a, a heat source was applied to the bottom of the module to establish a vertical temperature gradient, allowing for the examination of the effect of thermal non-uniformity on the deposition process. CF, Zn, Ag, and HOPG correspond to the idealized condition in which the intrinsic thermal conductivity of the substrate remains constant and is unaffected by Zn coverage, while a HOPG-Zn Gradient Substrate (HZGS) represents the case where the thermal conductivity gradually transitions from that of HOPG to that of Zn with increasing Zn deposition. The results in Fig. 2b indicate that increasing the substrate thermal conductivity reduces the temperature gradient along the Y direction at the electrode/electrolyte interface. As confirmed in Figs. 2c-f, the temperature difference between regions near and far from the heat source decreases from 20.9 °C for CF to 0.4 °C for HOPG, while the height variation of the deposited layer decreases from 1.2 µm for CF to 0.6 µm for HOPG, leading to markedly improved deposition uniformity. In this scenario, where the influence of deposited Zn on the substrate’s thermal conductivity is neglected, higher substrate thermal conductivity facilitates a more uniform surface temperature distribution over time, thereby promoting homogeneous Zn deposition.

However, when the effect of Zn coverage on substrate thermal conductivity is considered, the advantage of high-conductivity substrates is progressively diminished as deposition proceeds. Using HOPG as an example, which has the highest thermal conductivity among the four substrates, we find that when its thermal conductivity decreases linearly from that of HOPG to that of Zn, its thermal advantage is markedly reduced, although it still outperforms pure CF or Zn substrates (Figs. 2 b-f). This indicates that in liquid-solid phase transition processes, simply increasing the initial substrate thermal conductivity cannot sustain its beneficial effect at high areal capacities. With continued Zn accumulation on the substrate, the temperature distribution ultimately becomes governed by the thermal conductivity of Zn. These findings suggest that stable thermal management during prolonged deposition requires more than a fixed high-conductivity substrate; it demands a mechanism for continuous heat transfer and removal.

In flow batteries, electrolyte circulation enables persistent heat exchange at the reaction interface, mitigating temperature non-uniformity. Incorporating LM as a flowable electrode, with thermal conductivity exceeding that of the electrolyte, may combine high heat-transfer efficiency with active heat removal through circulation, offering a potential means of maintaining a uniform temperature field even at high areal capacities. As illustrated in Figs. 2g and h, COMSOL simulations show that the static cell with an LM electrode exhibits a substantially more homogeneous temperature distribution compared to conventional solid substrates (Fig. 2b). Furthermore, relative to the other substrate configurations shown in Fig. 2e, the LM-based cell reaches thermal equilibrium within a markedly shorter timescale (~0.025 h) and displays a lower temperature gradient after 1 h (1.56 °C for LM versus 5.22 °C for HZSG), underscoring its enhanced thermal management performance. This improvement arises not only from the intrinsic thermal conductivity of the LM, but also from its extensive contact area and large volume fraction, which facilitate bulk heat conduction and promote more homogeneous heat dissipation across the electrode region.

Thermal uniformity of the LM electrode

LMs are a category of materials characterized by distinct physicochemical properties, notably their high thermal conductivity, metallic conductivity, and fluidity19, 20. These properties render them particularly suitable for electrochemical energy storage devices, such as FBs, which necessitate the movement of electrolytes. High thermal conductivity facilitates rapid heat dissipation, minimizing temperature fluctuations and enhancing safety. High metallic conductivity enhances energy conversion efficiency, while high fluidity mitigates dendrite growth on the electrode surface, thereby prolonging battery lifespan21.

For LM to be utilized in Zn-FBs, they must exhibit high thermal conductivity, appropriate Zn content, and a low melting point to maintain a liquid state at or near room temperature. Gallium-based LMs, as representatives of room-temperature liquid metals, not only retain the general advantages of LMs but also offer environmentally friendly, recyclable, safe, and self-healing properties22. Three gallium-based LMs fulfilling these criteria were selected, and their compositions and physical properties are presented in Supplementary Table 2. As illustrated in Fig. 3a, the binary EGaIn LM exhibits the highest thermal conductivity, which is 46 times greater than that of the electrolyte. This indicates a high capacity for maintaining thermal balance at the electrolyte/electrode reaction interface. Fig. 3b shows the saturation solubility of Zn metal in the three LMs at room temperature, with EGaIn achieving the highest affinity for Zn, reaching a mass fraction of 3.1%, corresponding to a theoretical capacity of ~160 Ah L(LM)−1. Given this high solubility, we further investigated the thermodynamic stability of the Zn-EGaIn system by calculating its phase diagram using the CALPHAD (CALculation of PHAse Diagrams) methodology. As shown in Fig. 3c, the system comprises six phases: Liquid, α (HCP_Zn), η (Tetragonal_In), γ (Orthorhombic_Ga) and their coexistence. The Zn content in EGaIn increases rapidly with rising temperature, leading to a high theoretical Zn storage capacity. In addition, EGaIn demonstrates high stability in the electrolyte (Supplementary Fig. 11). Overall, this binary LM offers a higher Zn accommodation capacity, improved thermal conductivity, and reduced viscosity. These improvements are critical for promoting uniform Zn deposition, reducing localized heating, and facilitating hydraulic transport of the LM, thereby improving negative electrode reversibility under high areal capacity and high SOC conditions. Under identical 50% SOC testing, the binary EGaIn also delivered a higher CE than the ternary EGaInSn (Supplementary Fig. 12), further confirming its effectiveness. Based on these merits, EGaIn was selected for investigations in this work.

To investigate the influence of a highly thermally conductive LM interface on the Zn deposition process, we integrated EGaIn alloy LM with a Zn negative electrode to assemble a Zn||LM cell. When charged at a constant current of 50 mA cm−2 for 200 s, no short circuit occurred (Fig. 3d). In contrast, the cell without LM failed due to a short circuit after 61 s (Fig. 1d). The in situ ODMR images corresponding to the deposition process indicated that the temperature of the nanodiamonds across the entire test area remained stable and did not differ significantly from the initial state over time (Fig. 3e and Supplementary Fig. 13). Owing to the high spatial resolution and temperature sensitivity of ODMR, each nanodiamond serves as an independent nanoscale thermometer, enabling a direct mapping of local thermal fluctuations during Zn deposition in the LM environment. To further illustrate the microscopic temperature variation process, six randomly selected nanodiamonds were analyzed to show their specific temperature changes over 200 s. As shown in Fig. 3f, Supplementary Figs. 14 and 15, the temperature variation values are centered around 0 °C, confirming the absence of any measurable temperature rise during the Zn2+ ion deposition process in LM. To isolate the influence of the thermal conductivity of flowable LM electrode on FB, we developed a two-dimensional transient model and employed COMSOL to simulate the temperature gradient distribution induced by localized heat generation at the electrode/membrane interface (mimicking a hotspot during a short-circuit) under flow conditions, while excluding electroplating processes. The temperature varies significantly, mainly between the inflow and outflow of the electrolyte, primarily influenced by mass transfer (Fig. 3g-l)14. In comparison to Zn-FBs assembled without LM, batteries using LM demonstrate faster temperature diffusion in the negative electrode region when subjected to heat sources (Fig. 3g and 3j). The external flow of LM in the Zn-FBs can enhance its rapid thermal conductivity characteristics, further uniformizing potential temperature hotspots on the electrode, stabilizing the plating/stripping process, and contributing to the battery cycle life. As shown in Fig. 3h, 3i, and Supplementary Figs. 16-18, the temperature variation curves in the X and Y directions of the negative electrode demonstrate that the high thermal conductivity of LM rapidly equilibrates heat distribution, minimizing the impact of heat sources on other regions of the negative electrode. In the absence of LM, the local temperature of the negative electrode rapidly spikes, complicating heat dissipation (Fig. 3k and 3l). An increased rate of temperature change on the electrode can result in a more uneven plating/stripping process, further exacerbating the formation of Zn dendrites.

LM-mediated Zn plating and stripping

Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) were utilized to analyze the morphology and microstructure of the EGaIn LM at three different stages: prior to charging, after charging, and following discharge. As illustrated in Supplementary Fig. 19, the morphology of the LM remained predominantly unchanged throughout these processes. EDS assessments revealed a consistent elemental distribution of Ga and In across the various states of the EGaIn LM. Notably, after Zn plating, the detected Zn was evenly distributed rather than forming clusters, indicating the formation of the EGaInZn alloy23. Such uniform alloying in the liquid phase effectively avoids the formation of solid dendrites, thereby preventing localized hotspots and associated interfacial temperature fluctuations. Furthermore, no Zn was observed in the elemental maps of the LM after discharge, suggesting that the EGaInZn alloy could completely revert back to EGaIn, and that the LM can serve as an electrode in Zn-FBs. These observations were further validated by inductively coupled plasma mass spectrometry (ICP-MS) analyses performed on the LM after multiple cycles (Fig. 4a). The quantity of charge injected correlated with the increase in Zn content, and the composition of the LM after discharge matched its initial state, demonstrating that the deposition and dissolution processes of Zn, specifically, the alloying and dealloying reactions within the LM, were entirely reversible. This liquid-liquid phase transition minimizes the mechanical and thermal stress typically observed in solid-state Zn deposition, contributing to a more stable temperature profile during cycling, as evidenced in Fig. 3e. Additionally, X-ray diffraction (XRD) analysis was conducted to investigate the structural characteristics of the LM before and after 60 cycles. The XRD patterns of the Zn-deposited LM displayed a distinctive broad peak around 35.3°, indicative of a liquid alloy phase and suggesting the presence of the EGaInZn alloy (Fig. 4b)24. These findings indicate that, within a fully assembled cell, the EGaIn LM can function as a reservoir for a significant quantity of Zn2+ ions during the charging process and revert to EGaIn upon discharging, thereby enabling reversible liquid-liquid phase transitions for the Zn negative electrode.

To further understand the deposition process of Zn in LM, we analyzed the surface elemental composition and chemical states of LM after charging using X-ray photoelectron spectroscopy (XPS). This analysis confirmed the presence of Ga, In, and Zn (Supplementary Fig. 20). Fig. 4c illustrates the Zn 2p spectrum of Zn deposited on both the EGaIn LM and CF. Compared to the spectrum obtained from CF, the positions of the Zn 2p and Zn 2p peaks in the LM alloy shift to higher binding energies, indicating the formation of the EGaInZn alloy25, 26. Time-of-flight secondary ion mass spectrometry (TOF-SIMS) further validated these findings. Fig. 4d presents signals for ZnIn GaO −, ZnGaO −, and ZnIn O −, suggesting that the Zn deposited in LM exists as the EGaInZn alloy27. In contrast to solid-state deposited Zn, the alloy phase Zn, encapsulated by Ga and In metal in LM, reduces direct contact with the electrolyte, thereby mitigating side reactions such as electrochemical corrosion of Zn. In Tafel polarization tests, the LM electrode with in situ alloyed Zn (EGaInZn) exhibited a significantly lower corrosion current density than Zn, together with a positively shifted corrosion potential, indicating suppressed corrosion kinetics and enhanced electrochemical stability (Supplementary Fig. 21). Supplementary Fig. 22 presents the differential scanning calorimetry (DSC) curve of the LM following Zn deposition, which exhibits notable supercooled and non-solidified characteristics. This indicates that the LM electrode is suitable for use across a broad temperature range. Moreover, the intrinsic broad thermal tolerance of the LM negative electrode enhances the thermal management capability of Zn-FBs, enabling rapid dissipation of transient heat accumulation under high current density conditions. These features emphasize the promise of LMs for creating room-temperature Zn-ion-driven LM batteries with liquid-liquid electrochemical interfaces. Furthermore, the Zn-saturated LM, produced by the natural dissolution of Zn foil at room temperature, demonstrates alloying characteristics (Supplementary Figs. 23 and 24). This suggests that the LM can dissolve the detached dead Zn in the Zn-FB, thus restoring the capacity of the dead Zn.

In FBs, energy density is positively correlated with the concentration of redox species, the number of electron transfers per molecule, and the actual SOC of the electrolyte28. Enhancing SOC of the electrolyte is a straightforward approach to improving the battery's output energy density in established systems. Furthermore, a higher SOC can decrease the volume of electrolyte required to achieve the rated energy output of the FB, thus reducing operational costs. In Zn-FBs, as illustrated in Supplementary Fig. 25, an increased SOC in the negolyte not only leads to a greater areal capacity for Zn deposition but also alters the morphology of Zn deposit to shift from a dense, layered structure to a loose, moss-like porous form. XRD results further reveal that as the SOC rises, the (101) crystal plane of electrochemically deposited Zn becomes dominant, surpassing the (002) crystal plane, indicating the inevitability of inhomogeneous deposits (Supplementary Fig. 26)29. At high SOC, loosely deposited Zn that is partially in contact with the electrode, along with non-conductive byproducts, exacerbates the uneven distribution of electrochemical reactions and Joule heating at the interface, thereby intensifying local temperature fluctuations and leading to more severe dendrite growth30. Additionally, these loose deposits are likely to lose contact with the electrode during discharge, allowing them to be carried away by the flowing electrolyte. This results in dead Zn accumulating at the bottom of the tank and causes irreversible capacity loss (Supplementary Fig. 27). Moreover, the variation in deposition morphology at different SOC levels can substantially affect the battery's performance and cycling stability (Supplementary Fig. 28). These findings indicate that in the traditional liquid-solid conversion method of Zn, high SOC amplifies the unevenness of deposition and temperature distribution at the interface, considerably reducing the reversibility of the Zn negative electrode.

To further investigate the effect of Zn deposition at high SOC on the internal structure of the battery, we employed SEM to analyze the morphology of the electrodes and membranes after 80 cycles. Electrodeposition was performed at 50% SOC with a current density of 40 mA cm−2. In the CF electrode of the Zn-FB without LM, the deposited Zn exhibited a loose structure characterized by larger Zn aggregates and dendritic crystals (Fig. 4e). These dendritic crystals displayed highly irregular shapes and rough surfaces, resulting in increased Zn shedding. Furthermore, XRD analysis indicated that as the number of cycles increased, the formation of the non-conductive byproduct Zn (OH) Cl ·H O on the CF became more pronounced (Supplementary Fig. 29). Such byproduct layers not only hinder electron transport but also act as thermal insulators, aggravating localized heating under high current density. Fig. 4f and Supplementary Fig. 30 display the surface morphology of the membrane after cycling. EDS analysis (Fig. 4g) confirmed the presence of Zn deposits and their associated byproducts (chlorine elements) on the membrane surface of the Zn-FB without LM. The growth of the dendritic Zn on the membrane impeded ionic transport efficiency and may contribute to a decline in battery performance through both electrochemical and thermal instability.

In the LM-based Zn-FBs, the LM replaced the CF to serve as the electrode. Consequently, we analyzed the morphology and elemental distribution of the graphite plate (GP) collector in direct contact with the LM. As depicted in Fig. 4h, Supplementary Figs. 30c and 31, no solid-phase Zn deposits appeared on the surface of the collector after cycling, and no Ga or In elements were detected, indicating that there was no formation of solid Zn dendrites or decomposition of the LM. In comparison to the base battery utilizing CF, the membrane of the Zn-FB assembled with LM remained intact and undamaged after undergoing the same cycling conditions (Fig. 4i and Supplementary Fig. 32), indicating that all Zn deposits had transformed into a liquid-phase eutectic alloy. These results align with our previous observations, confirming that the EGaIn accepted Zn2+ ions during the charging process, forming a liquid EGaInZn alloy.

Figure 4j schematically illustrates the operating principle of the LM electrode in the Zn-FB system. The LM and electrolyte are simultaneously delivered into the battery reaction chamber, where forced convection within the LM enhances internal heat transfer. Within the reactor, the LM acts as the electrode in contact with the current collector. At the liquid-liquid interface between the electrolyte and LM, Zn2+ ions are reduced to Zn atoms that immediately alloy with Ga and In, forming a liquid eutectic negative electrode in situ. This alloying suppresses dendrite growth and stabilizes deposition, thereby reducing the probability of hotspot generation, while the high thermal conductivity of the LM rapidly dissipates any residual heat. The synergistic effects of dendrite suppression and efficient heat spreading enable a highly reversible Zn negative electrode. The resulting Zn-rich EGaInZn alloy subsequently flows into an external electrolyte reservoir for recirculation. This approach converts the conventional liquid-solid Zn deposition/dissolution process into a liquid-liquid reaction mode, enabling the operation of a fully flow-type battery with enhanced stability, dendrite-free morphology, and high areal capacity.

Zn||Br flow battery performance

Considering the promising results of the dendrite-free Zn alloying process in the flowable LM with high thermal conductivity, we further investigated the overall performance of Zn-FBs utilizing the LM negative electrode. Thus, we assess the feasibility of the design in the ZBFBs, where the positive electrode facilitates the conversion between highly active Br− ions and Br 31. 2 First, we investigated the corrosion and side reactions of the Zn negative electrode by analyzing the self-discharge performance of ZBFBs at 50% SOC, with and without LM. After a 12-hour rest period, the charged LM-based ZBFB retained 85.84% of its capacity, while the ZBFB without LM retained only 75.30% (Fig. 5a). Furthermore, under low current density (10 mA cm−2), the LM-based ZBFB delivered higher average Coulombic efficiency (CE) (97.8% for 1 h cycles and 96.6% for 2 h cycles) compared to the conventional ZBFB (94.1% and 93.4%, respectively), confirming that the LM effectively mitigates corrosion-related side reactions (Supplementary Fig. 33). These results can be attributed to the in situ alloying capability of Zn atoms encapsulated in EGaInZn, which allows for their continuous movement out of the reactor. This process mitigates the self-corrosion of Zn due to direct contact with the negolyte and reduces self-discharge caused by electrolyte interpenetration.

Under practical operating conditions, particularly at high SOC and elevated current density, we separately tested the performance of ZBFBs with and without LM. Battery performance was evaluated based on CE and energy efficiency (EE). The cycling performance of the ZBFB with LM was first examined at 50% SOC of the negolyte (Fig. 5b). The developed ZBFB operated for over 800 cycles at a current density of 40 mA cm−2, which is approximately 12 times longer than that of the ZBFB without LM. During this period, the average CE stabilized at 98.5%, while the average EE reached 83.2%. In contrast, the CE of the ZBFB without LM rapidly decreased to 39.8% within 86 cycles, and the EE decreased to 19.8%. To further enhance energy output, we increased the SOC to 90%. The robust LM-based ZBFB operated for more than 500 cycles at an areal capacity of 84.4 mAh cm−2 without significant decay in CE, maintaining an average of 97.8%, as shown in Fig. 5c and Supplementary Fig. 34. Benefiting from this notable cycling stability and optimized SOC, it delivered an energy density of 78.6 Wh L−1 when calculated based on the negolyte volume excluding that of the LM, and 45.9 Wh L−1 when the LM volume was included, both exceeding most previously reported values for Zn-FBs (Supplementary Fig. 35). These findings highlight the full reversibility of Zn alloying and dealloying processes enabled by liquid-liquid phase transitions within the high thermal conductivity LM, which promotes uniform heat dissipation and stable interfacial temperature profiles.

Fig. 5d shows the voltage-time profiles of the two ZBFBs at 84.4 mAh cm−2. The fluctuations in the voltage curve of the battery without LM correspond to the formation of dendrites, and the rapid increase in polarization also leads to an increase in byproducts (Supplementary Fig. 36). Conversely, the ZBFB with LM exhibited stable charge-discharge performance for over 2400 h. Notably, after undergoing hundreds of Zn deposition-dissolution cycles, the LM remained in a liquid form, visually confirming its stability as an electrode material (Supplementary Fig. 37). In addition, stability tests of the battery with lower Zn2+ ion concentration further confirmed the high reversibility of the LM negative electrode (Supplementary Fig. 38). To further demonstrate the broad applicability of LM in Zn-FBs, the ZBFB with LM exhibited high performance across a wide range of current densities from 20 to 60 mA cm−2 (Fig. 5e) and stable CE and EE were observed under different working currents (Supplementary Fig. 39). The ZBFBs assembled with LM were evaluated under practical conditions considering lifetime, cumulative discharge capacity, SOC, and energy density, with the results indicating stable performance (Fig. 5f and Supplementary Table 3)10, 32, 33, 34, 35, 36, 37, 38, 39, 40.

Although gallium-based LMs have a higher price than conventional Zn electrodes, cycling tests demonstrated that the LM composition remained essentially unchanged after use (Supplementary Fig. 40), enabling direct recovery and reuse in subsequent assemblies without performance degradation (Supplementary Fig. 41). This recyclability substantially reduces the amortized material cost over the system’s lifetime. In addition, the LM configuration eliminates the need for a negative-side CF and achieves >90% electrolyte utilization, thereby lowering both electrode cost and electrolyte consumption per unit of energy compared with conventional ZBFBs. Furthermore, for integrating the LM electrode into a commercial ZBFB stack, only a simple adjustment, operating the stack in a horizontal orientation, was required to prevent gravitational redistribution of the LM, while retaining the original electrolyte flow channels and manifolds (Supplementary Fig. 42). In summary, the notable electrochemical performance, demonstrated recyclability, and setup feasibility highlight the strong potential of LM electrode for practical ZBFB applications.

Methods
Materials: Zinc bromide (ZnBr , ≥99.9%), potassium chloride (KCl, ≥99.5%), and 1-ethyl-1-methylpyrrolidinium bromide (MEP, ≥99%) were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd and used without further purification. All electrolytes were prepared using deionized water. Carbon felt (CF, 4.6 mm, carbon ≥99 %, bulk density 0.12-0.14 g·cm−2) was purchased from Liaoyang J-Carbon Materials Co., Ltd. (China) and used as received. Graphite plate (GP, 2 mm) was purchased from Shanghai Hongjun New Energy Materials Co., Ltd. (China). Polyolefin-based porous membrane was purchased from Daramic® HP (0.1 µm average pore size, 58%±7.5% porosity, 900 µm thickness). The liquid metals (LMs) were purchased from HuaTai Metal Materials Co., Ltd. (China) and used as received.

Material Characterization: Field-emission scanning electron microscopy (SEM, JEOL-7001F) and energy-dispersive X-ray spectroscopy (EDS) were employed to analyze the microstructure and elemental distribution of the electrode, membrane, and liquid metal (LM). The X-ray diffraction (XRD) patterns of the LM and electrodes were obtained using a Rigaku SmartLab 9kW diffractometer. X-ray photoelectron spectroscopy (XPS) data were gathered with a Thermo Fisher Scientific K-Alpha instrument. Time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis was performed using an IONTOF M6 instrument (IONTOF GmbH). Inductively coupled plasma mass spectrometry (ICP-MS, Agilent 720ES) was utilized to determine the elemental concentrations in the LM. The saturation solubility of Zn at 25 °C±1 °C was evaluated through experiments by adding excess Zn foil in the LMs and keeping the samples in a vacuum chamber for over 30 days. After this period, the Zn content in the homogeneous liquid phase of the LM was analyzed using ICP-MS. At this time, the LM is referred to as Zn-saturated LM. For all other tests of various LMs (pristine, charged, and discharged), unless otherwise specified, measurements were conducted at 25 °C ± 1 °C without the use of a vacuum chamber. Differential scanning calorimetry (DSC, Netzsch DSC 200 F3) was conducted to measure the freezing point of the LMs, with a cooling rate of 1°C min−1 over a temperature range of -40°C to 40°C.

Nanodiamond-based Temperature Sensing: The Zn||Zn cell consists of two pieces of Zn foil (20 µm, 2 mm × 5 mm) immersed in the electrolyte and attached to the substrate. The Zn||LM cell was assembled in a similar manner to the Zn||Zn cell, with one Zn foil replaced by an LM electrode, both immersed in the electrolyte and attached to the substrate. The two pieces of electrodes were placed diagonally to ensure that the location of the short circuit falls within the temperature monitoring range, as illustrated in Supplementary Fig. 2. The temperature measurement area is 100 μm × 100 μm. Temperature sensing based on nanodiamonds was performed using continuous-wave (cw) optically detected magnetic resonance (ODMR). Nanodiamonds with a high density of nitrogen-vacancy (NV) centers (>1000 NVs, FND Biotech) were dispersed onto a cover glass and randomly distributed across the measurement area. A microwave field was applied using a copper (Cu) wire (~25 μm in diameter) positioned between two electrodes. The local temperature during the electrochemical process was monitored at the nanoscale by simultaneously measuring multiple nanodiamonds sensors using a wide-field fluorescence microscope. A 532 nm laser was employed to optically pump the NV center spins within the nanodiamonds, while the microwave field, delivered via the Cu wire, was used to manipulate the spin states of the NV centers. The resulting fluorescence emitted by the nanodiamonds was collected using an electron-multiplying charge-coupled device (EMCCD; Evolve 512, Photometrics). Experimental parameters, including laser power, microwave amplitude, and acquisition time, were rigorously optimized to achieve high thermal sensitivity. The ODMR spectrum of the nanodiamond sensors was normalized to the fluorescence counts obtained off-resonance. The normalized spectrum was subsequently fitted using a nonlinear least-squares method with a double-peak Lorentzian function. The resonant frequencies of the two peaks were extracted from the fitting results, and the zero-field splitting (D) was calculated as the average of the two resonant frequencies. To enable local temperature determination in real-time experiments, the D at room temperature (T ) was calibrated prior to the electrochemical measurements by a standard thermometer. Then the calibration of the temperature dependence of the D (dD/dT) was performed using a controlled heating process in a water bath. The real-time local temperature (T(t)) of the nanodiamonds was then determined using the relationship:

𝑇(𝑡) = ( 𝑑𝐷/𝑑𝑇)−1[𝐷(𝑡) − 𝐷 ] + 𝑇 (1)
0 0

The temperature sensing mechanism relies on the intrinsic dependence of the D of NV centers on temperature. This dependence is robust and unaffected by changes in the chemical environment of the device, ensuring reliable temperature measurements even in complex electrochemical systems.

ODMR spectra were acquired by sampling 31 microwave-frequency points. For each time point, one temperature readout was obtained from an integrated ODMR spectrum generated by accumulating 12 consecutive spectra (acquisition time per spectrum ∼0.83 s; fixed total integration time t = 10 s for all time points). The resonance shift ΔD was extracted from the integrated ODMR spectrum and converted to temperature change ΔT using the calibrated dD/dT. In Figs. 1d and 3f, Supplementary Figs. 5 and 7, the data points show ΔT. Error bars indicate the estimated temperature uncertainty (± σ) for the integration time t . The uncertainty was calculated from the individually determined temperature sensitivity η for each ND, with units of K/Hz0.5 (typical values around 2 K/Hz0.5), according to σ = η /t 0.5.

Electrochemical Characterization: A zinc-based flow battery (Zn-FB) was assembled by placing a Daramic® HP membrane (3 × 3 cm2) between two carbon felt (CF, 2 × 2 cm2) electrodes, which were secured by two graphite plates (GP). The effective reaction area of the electrodes in the Zn-FB is 2 × 2 cm2. For the construction of a Zn||Br flow battery (ZBFB), an negolyte containing 1 mol L−1 ZnBr and 3 mol L−1 KCl was utilized, while a posolyte with a bromine complexing agent was employed to reduce the diffusion of corrosive bromine, incorporating 0.4 mol L−1 MEP. In the LM-based battery, no CF was used on the negative side; instead, LM was introduced into the negolyte tank and circulated through the reactor along with the negolyte. Various electrolytes were circulated throughout the batteries using peristaltic pumps, maintaining a constant flow rate of 50 mL min−1, without any additional flow channel design. To ensure optimal contact between the LM and the current collector, the battery reactor is maintained in a horizontal orientation during testing, with the negative electrode positioned at the bottom and the positive electrode at the top. During long-cycle testing of the ZBFBs at different states of charge (SOC), the volumes used were 5 ml for the LM, 7 ml for the negolyte, and 15 ml for the posolyte. The SOC of the ZBFB is calculated as the actual charged capacity divided by the theoretical capacity of the negolyte. For 7 ml negolyte, 100% SOC corresponds to a charge capacity of 375.2 mAh. The batteries were operated at a constant current density, and the charging process was limited by capacity. The discharge process ceased when a cutoff voltage of 0.1 V was reached. The reported energy density was based solely on negative electrode side of the ZBFB. All battery performance tests were conducted using a CT3001A LAND Battery Testing System.

The Zn||GP flow cell was constructed using a Zn plate (2 cm × 2 cm × 0.05 cm) attached to CF (2 cm × 2 cm × 0.42 cm) as the positive electrode, and GP as the negative electrode, separated by a Daramic® HP membrane positioned between the two electrodes. No CF was employed on the negative side, allowing Zn2+ ions to directly deposit onto the GP substrate. Both the negolyte and posolyte were identical, consisting of 1 mol L−1 ZnBr and 3 mol L−1 KCl. The test involved plating a specified amount of Zn metal onto the GP substrate, followed by stripping the Zn metal from the GP substrate using a cut-off voltage. All these electrochemical tests were carried out at 25 °C±1 °C, no climatic/environmental chamber was used.

Phase Diagram Calculation: The phase diagram of the Zn-EGaIn system was calculated using the CALPHAD (CALculation of PHAse Diagrams) methodology41, 42, 43. The sub-regular solution model was applied to describe the liquid phase and terminal solid solution phases, with the excess Gibbs energy expressed using the Redlich-Kister polynomial. The thermodynamic parameters for the constituent binary systems, Ga-In, Ga-Zn, and In-Zn, were taken from critically assessed databases and literature. The Ga-In, Ga-Zn, and In-Zn binary systems are entirely composed of liquid phase and solid solution phases. And the thermodynamic parameters were based on previous optimized parameters that reproduced the experimental phase equilibria and thermodynamic properties reliably. Subsequently, the ternary Ga-In-Zn system was modeled by introducing suitable ternary interaction terms. Phase parameters were refined using the PARROT module to align the calculations with available phase equilibria and thermodynamic measurements. Reported experimental datasets were used as initial inputs, with weights assigned based on their reliability. The parameters were iteratively modified until the results agreed with most experimental observations within acceptable error limits.

Computational Method:

Heat transfer in static Zn half‑cell: A two‐dimensional transient multiphysics model was developed in COMSOL Multiphysics by coupling the Heat Transfer in Solids and Fluids module with the Tertiary Current Distribution interface to investigate the influence of substrate thermal conductivity on Zn deposition under continuous heat flux. The rectangular computational domain (30 mm × 15 mm) consists of a plating substrate (negative electrode) on the left, a Zn block (positive electrode) on the right, and an intervening liquid electrolyte. A constant heat flux of 3 000 W·m−2 is applied along the bottom boundary between x = 3 mm and x = 12 mm. The transient heat‐transfer equation, ρCp ∂TT/∂t = ∇·(k∇T) + Q, is solved simultaneously with Nernst-Planck mass‐transport equations for Zn2+ and Butler-Volmer kinetics. The Zn2+ diffusion coefficient is temperature‐dependent,

𝐷(𝑇) = 𝐷 ∗exp[− 𝐸a ∗( 1 − 1 )] (2)
0 𝑘B 𝑇 𝑇0

with D = 1.0 × 10−11 m2·s−1, E = 0.25 eV, k = 8.617 × 10−5 eV·K−1, and T = 298.15 K. Similarly, the exchange‐current density is defined as

𝑖 (𝑇) = 𝑖 ∗exp[− 𝐸𝑏 ∗( 1 − 1 )] (3)
0 0,ref 𝑘𝐵 𝑇 𝑇0

using 𝑖 = 50 mA cm−2 and E = 0.60 eV. Simulations were performed over 3600 s, using an adaptive time stepping and a relative solver tolerance of 1 × 10−4.

Heat transfer in ZBFB: A two-dimensional transient model was developed to simulate the heat transfer processes within the ZBFBs with and without LM. The simulations were performed using the Heat Transfer in Solids and Fluids module in the commercial software COMSOL Multiphysics, with a relative error tolerance set to 1×10−4. The computational domain comprises three rectangular regions: the negative electrode (20 mm × 4 mm, left), the separator (20 mm × 1 mm, center), and the positive CF porous electrode (20 mm × 4 mm, right). On the positive side, the electrolyte flows into the cell from the bottom and exits at the top, while on the negative side, a mixture of LM and electrolyte (volume ratio 9:1) is introduced for the LM-based ZBFB configuration. The flow velocity on both the positive and negative sides was set to 0.1 m/s. A uniform heat source with a power density of 1×109 W/m3 was applied to the central region of the separator (4 mm × 1 mm), as illustrated in Supplementary Fig. 16. The initial temperature of all components within the ZBFB was set to 298.15 K.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript focuses on local temperature variations occurring at the electrode surface. To this end, the authors employ the optically detected magnetic resonance (ODMR) technique, which enables precise monitoring of temperature distributions at the microscopic scale. Notably, they attempt to achieve thermal homogenization by incorporating a liquid metal with high thermal conductivity. The study is particularly intriguing not only for its analysis of the temperature distribution on the electrode surface, but also for its approach of dissolving the electrodeposited Zn into the liquid metal, thereby enabling the operation of a fully flow-type battery rather than a pseudo flow system. However, to enhance the logical coherence and scientific rigor of the manuscript, further clarification and justification of several aspects of the experimental interpretation are recommended.\n- The authors focus on the correlation between temperature non-uniformity at the electrode surface and Zn dendrite formation, and they propose the use of a liquid metal electrode to improve surface temperature uniformity. While the liquid metal may indeed enhance thermal homogeneity, the suppression of dendrites in this system is likely not due to thermal effects per se. Rather, it can be attributed to the dissolution of electrodeposited Zn into the liquid metal, forming a Zn-rich alloy phase. In this case, dendritic structures cannot form because Zn is fully incorporated into the liquid phase. Therefore, the claim that improved temperature uniformity directly leads to dendrite suppression - based on the behavior of the liquid metal system - may be an overstatement and requires more cautious interpretation. Therefore, to more clearly isolate the effect of surface temperature uniformity and to validate the utility of the ODMR-based thermal analysis, it would be advisable to adopt a different electrode material.\n- The use of eutectic gallium–indium liquid metal (GaIn LM) in flow battery systems has been reported in several recent studies, including previous works by the authors themselves (e.g., Sci. Adv. 2025, 11, eads3919; Adv. Energy Mater. 2025, 15, 2405066). However, the composition of the liquid metal and the key conceptual points presented in the current manuscript do not appear to differ significantly from those in the prior publications.\n- In Supplementary Fig. 3, the authors present the correlation between the change in zero-field splitting (delta D) and temperature variations (delta T). However, due to the overlapping data points from a large number of individual nanodiamonds, it is difficult to discern the linearity or consistency of the temperature dependence for each nanodiamond. Clarifying the presentation - perhaps by showing representative individual plots or statistical summaries - would enhance the interpretability of the data.\n- Fig. 5f presents a performance comparison with other Zn-based flow batteries, including energy density values. It is unclear whether the reported energy density is calculated based on the volume of the catholyte only, or if it also includes the volume of the liquid metal. If the volume of the liquid metal is excluded, the rationale for this decision should be clearly stated, as it directly impacts the validity of the performance comparison.\n- Fig. 3c presents the phase diagram of the Zn–EGaIn system. However, the source of this diagram is not specified. If the diagram is adapted from existing literature, please provide the appropriate citation. Alternatively, if it is based on experimental results obtained in this study, the corresponding experimental procedures should be clearly described.\n- Fig. 5f presents a performance comparison with other Zn-based flow batteries, including energy density values. It is unclear whether the reported energy density is calculated based on the volume of the catholyte only, or if it also includes the volume of the liquid metal. If the volume of the liquid metal is excluded, the rationale for this decision should be clearly stated, as it directly impacts the validity of the performance comparison.", "reviewer_2": "In this manuscript, Wang and coworkers proposed to monitor sub-micron temperature variations during Zn deposition using optically detected magnetic resonance (ODMR) with nanodiamond quantum sensors. A ~300 nm spatial resolution and ~2 K/(Hz)^0.5 temperature sensitivity were achieved. Furthermore, the authors introduced a flowable eutectic gallium-indium (EGaln) liquid metal (LM) anode, which mitigated zinc dendrite formation and enhanced the electrochemical performance in a flow-cell configuration. Overall, both the proposed methodology and the selection of the liquid-metal anode were highly interesting and impactful. The manuscript fits the scope of the journal. The following questions/comments may further raise the impact of the study.\n1. As of now, the manuscript reads like two separate studies combined together, both in the title and throughout the text. The first part discusses the temperature sensing technique, while the second part focuses on the properties of the LM anode. It would be nice if the authors could turn it into a single-piece, cohesive study.\n2. Regarding the temperature change in Fig.1d, what is the time response, e.g., how fast can the temperature sensor respond when the cell short-circuits? Can the authors also explain the temperature variation between 150 s and 220 s (drastic increase) and afterwards (temperature drop)?\n3. Is it possible to correlate spots of the highest temperature variation during short-circuiting with dendrite growth? It seems that different points may experience distinct temperature variations, as demonstrated in Supplementary Fig. 5 - how should one assess the applicability of the technique?\n4. How was the phase diagram of Fig. 3c constructed, experimentally or theoretically?\n5. The authors briefly mentioned that LMs mitigate side reactions such as electrochemical corrosion of Zn. More experimental evidence is required to support this claim.\n6. The authors should critically comment on the potential challenges of implementing LM anodes in large-scale systems, such as material cost, long-term stability under real-world conditions (especially with bromine-based catholytes), and compatibility with commercial battery designs (gravity-sensitive).", "reviewer_3": "This manuscript presents an innovative approach employing non-invasive optically detected magnetic resonance (ODMR) with nanodiamond quantum sensors to monitor real-time temperature variations at the microscopic scale during Zn deposition. This technique enables detailed thermal mapping, offering a powerful tool for understanding the interplay between electrochemical behavior and thermal dynamics in Zn-based systems. In addition, the authors introduce a flowable eutectic gallium-indium (EGaIn) liquid metal (LM) electrode with high thermal conductivity into Zn flow cells, which effectively dissipates localized heat and minimizes spatial temperature gradients.\nOverall, the study addresses a significant challenge in Zn-based electrochemical systems—thermal heterogeneity during dendrite formation—and proposes a compelling solution. The manuscript is of interest to the readership of Nature Communications and merits publication after the following issues are addressed:\n1. In Figure 1, the time-resolved ODMR temperature maps illustrate the emergence of thermal hotspots correlated with Zn dendrite growth. The authors attribute heat generation to internal short circuits caused by dendrite bridging. However, in the abstract, it is stated that spatial temperature non-uniformity plays a critical role in accelerating dendrite growth. This implies a causative rather than resultant relationship. Could the authors elaborate on the evidence supporting this directional causality? Specifically, how do the data differentiate between dendrites causing heat and heat influencing dendrite nucleation? Can a temporal correlation between hotspot emergence and dendrite initiation sites be established?\n2. Was the same cell configuration used for ODMR measurements in the Zn//LM (EGaIn) system as in the conventional Zn system? If not, the authors are encouraged to include a schematic diagram of the Zn//LM cell adapted for ODMR to provide clarity for readers.\n3. The primary advantage of incorporating EGaIn appears to be the suppression of dendrite formation, which inherently leads to more uniform thermal profiles. However, the manuscript attributes temperature uniformity to the high thermal conductivity of the LM. Could the authors disentangle these effects? For instance, is there evidence (e.g., control experiments or modeling) directly linking thermal conductivity to the observed uniformity, independent of dendrite suppression?\n4. The authors should discuss how the properties of EGaIn used in this study differ from those of the eutectic gallium-indium-tin (EGaInSn) alloy used in prior work (DOI: 10.1126/sciadv.ads3919). In what ways does the use of EGaIn represent an innovation or improvement? Consider discussing aspects such as electrochemical stability, viscosity, interfacial behavior, or compatibility with Zn.\n5. Can the authors comments more on the practical application of LM electrolyte on Zn based flow batteries, in the aspect of cost effectiveness and setup feasibility?"}, "author_response": "Dear Reviewers:\nThanks a lot for your constructive comments and suggestions about our manuscript\nentitled \"Sub-micron-resolution temperature mapping of Zn anode for flow batteries\"\n(Manuscript ID: NCOMMS-25-43964). These comments are insightful and help us\nsignificantly improve our work. We have studied your comments very carefully and\nsubstantially revised our manuscript in the hope of addressing your concerns and meeting the\nhigh standards of Nature Communications.\nBelow, we provide our point-by-point responses to the reviewers' comments, where the\noriginal comments are shown in black and our responses are shown in blue.\nContents\nReviewer: 1…………………………………………………………………………………2\nReviewer: 2…………………………………………………………………………………13\nReviewer: 3…………………………………………………………………………………28\nThe manuscript focuses on local temperature variations occurring at the electrode surface. To\nthis end, the authors employ the optically detected magnetic resonance (ODMR) technique,\nwhich enables precise monitoring of temperature distributions at the microscopic scale.\nNotably, they attempt to achieve thermal homogenization by incorporating a liquid metal with\nhigh thermal conductivity. The study is particularly intriguing not only for its analysis of the\ntemperature distribution on the electrode surface, but also for its approach of dissolving the\nelectrodeposited Zn into the liquid metal, thereby enabling the operation of a fully flow-type\nbattery rather than a pseudo flow system. However, to enhance the logical coherence and\nscientific rigor of the manuscript, further clarification and justification of several aspects of the\nexperimental interpretation are recommended.\nResponse: Thank you for your insightful evaluation of our manuscript. We sincerely appreciate\nyour positive assessment of our novel integration of ODMR-based thermal imaging and our\nuse of liquid metal to achieve electrode homogenization, which enables the realization of a\nfully flow-type Zn battery. We have carefully addressed all your comments, providing further\nclarifications and additional data, as detailed below.\n- The authors focus on the correlation between temperature non-uniformity at the electrode\nsurface and Zn dendrite formation, and they propose the use of a liquid metal electrode to\nimprove surface temperature uniformity. While the liquid metal may indeed enhance thermal\nhomogeneity, the suppression of dendrites in this system is likely not due to thermal effects per\nse. Rather, it can be attributed to the dissolution of electrodeposited Zn into the liquid metal,\nforming a Zn-rich alloy phase. In this case, dendritic structures cannot form because Zn is fully\nincorporated into the liquid phase. Therefore, the claim that improved temperature uniformity\ndirectly leads to dendrite suppression - based on the behavior of the liquid metal system - may\nbe an overstatement and requires more cautious interpretation. Therefore, to more clearly\nisolate the effect of surface temperature uniformity and to validate the utility of the ODMR-\nbased thermal analysis, it would be advisable to adopt a different electrode material.\nof dendrites is also related to the dissolution of electrodeposited Zn into the LM phase, forming\na Zn-rich alloy that prevents the persistence of solid dendritic structures. To verify the influence\nof surface temperature uniformity, we have conducted a systematic investigation using four\nsubstrates with distinctly different intrinsic thermal conductivities: carbon felt (CF), highly\noriented pyrolytic graphite (HOPG), Zn, and silver, representing typical carbon-based and\nmetallic materials (Table R1). As shown in the newly added Figs. R1 a-f, we used a static Zn\nhalf-cell model incorporating a localized heat source at the bottom to establish a vertical\ntemperature gradient, and simulated Zn deposition under conditions where the substrate\nthermal conductivity remains constant (CF, Zn, Ag, HOPG) or gradually transitions from\nHOPG to Zn as deposition proceeds (HZGS). The results demonstrate that higher substrate\nthermal conductivity reduces the interfacial temperature gradient (ΔT from 20.9 °C for CF to\n0.4 °C for HOPG) and leads to more uniform Zn deposition (height variation Δh from 1.2 µm\nfor CF to 0.6 µm for HOPG). This confirms that improved temperature uniformity can promote\nhomogeneous Zn deposition and mitigate morphological instability.\nWe further find that when the effect of Zn coverage on substrate conductivity is considered\n(the HZGS case in Figs. R1 b-f), the thermal advantage of high-conductivity substrates is\ngradually diminished during deposition, since the effective conductivity approaches that of Zn\nover time. This highlights the importance of effective heat removal throughout operation, for\nexample via a flowable LM electrode in zinc-based flow batteries, which enables a fully flow-\ntype Zn battery. As illustrated in Figs. R1g and h, the COMSOL simulations performed first\nin the static cell with an LM electrode exhibit a substantially more homogeneous temperature\ndistribution compared to conventional solid substrates. Furthermore, relative to the other\nsubstrate configurations shown in Fig. R1e, the LM-based cell reaches thermal equilibrium\nwithin a markedly shorter timescale (~0.025 h) and displays a lower temperature gradient after\n1 h (1.56 °C for LM versus 5.22 °C for HZSG), underscoring its superior thermal management\nperformance. In addition, as shown in Figs. 3 g-i, we also performed COMSOL simulations in\nflow situations, considering only localized heat generation on the electrode surface (mimicking\na hotspot during a short-circuit) without including the electroplating process. With LM present,\n3\nthe temperature gradients around the hotspot are significantly reduced, and the heat spreads\nmore uniformly across the electrode surface compared with the conventional electrode\nconfiguration. This demonstrates that the high thermal conductivity of LM alone can produce\na more uniform thermal profile, independent of dendrite suppression.\nTherefore, we believe that during electrochemical operation, both effects act simultaneously:\n(1) the alloying between deposited Zn and LM suppresses dendrite formation, stabilizing the\ndeposition process and thereby reducing localized heating; and (2) the enhanced thermal\nconductivity of LM promotes rapid heat dissipation, mitigating temperature heterogeneity that\ncould otherwise lead to uneven Zn deposition. The synergy of dendrite suppression and\nimproved heat spreading accounts for the uniform temperature distributions observed in\nexperiments.\nAs suggested, we have added a new Fig. 2, expanded discussions on Pages 9-10 and 18-19 in\nthe revised manuscript, and a new Supplementary Table 1 in the revised supporting\ninformation. These results from additional simulations confirm that higher thermal\nconductivity alone improves Zn deposition uniformity, independent of the dissolution effect.\nThis directly supports the ODMR-based thermal analysis and addresses the reviewer’s concern.\nTable R1. Thermal conductivity of various substrates.\nSubstrate Thermal conductivity (W m−1 K−1)\nCF 0.36\nZn ~116\nAg ~429\nHOPG ~1700-2000\nstatic Zn half‑cell model incorporating a localized heat source. (b) COMSOL‑simulated\ntemperature gradient of static Zn half‑cells with substrates of varying thermal conductivities\nafter 1 h deposition. CF, Zn, Ag, HOPG: idealized constant thermal conductivity; HZGS:\nthermal conductivity shifts from HOPG to Zn with Zn deposition. (c) Corresponding\ntemperature profiles along the Y direction at the substrate/electrolyte interface. (d)\nCorresponding height profiles of electrodeposited Zn along the Y direction after 1 h. (e) Time\nevolution of the temperature difference (ΔT) between regions near and far from the heat source\nfor different substrates. (f) Time evolution of height difference (Δh) between Zn deposited\nregions on different substrates. (g) COMSOL-simulated temperature gradient of a static Zn\nhalf-cell with LM. The dashed region indicates a 1:1 volume ratio of LM and electrolyte.\n(h) Corresponding temperature difference profile along the Y direction at the LM/electrolyte\ninterface.\n- The use of eutectic gallium–indium liquid metal (GaIn LM) in flow battery systems has been\nreported in several recent studies, including previous works by the authors themselves (e.g.,\nSci. Adv. 2025, 11, eads3919; Adv. Energy Mater. 2025, 15, 2405066). However, the\ncomposition of the liquid metal and the key conceptual points presented in the current\nmanuscript do not appear to differ significantly from those in the prior publications.\nResponse: We thank the reviewer's comments and insightful questions. The work in Adv.\nEnergy Mater. 2024, 15, 2405066 employed a static LM anode confined within the reactor\nchamber, which inherently restricts areal capacity due to the fixed reactor volume. In contrast,\nin our studies (the current work and Sci. Adv. 2025, 11, eads3919), the LM electrode is designed\nto be flowable, enabling continuous circulation between the electrochemical reactor cell and\nthe external reservoir. This architecture completely decouples Zn areal capacity from the\nreactor’s physical dimensions, allowing scalable energy storage simply by enlarging the\nexternal electrolyte tank. Such a transition from a static to a flowing LM system represents a\nfundamental step toward practical, high‑energy‑density, metal‑based flow batteries with\ngrid‑scale potential.\nFurthermore, compared to our previous flowing LM system based on ternary EGaInSn (Sci.\nAdv. 2024, 11, eadn3919), the present study introduces a binary EGaIn alloy as a rationally\noptimized composition. As shown in Table R2, this binary LM offers a higher Zn\naccommodation capacity, improved thermal conductivity, and reduced viscosity. These\nimprovements are critical for promoting uniform Zn deposition, reducing localized heating,\nand facilitating hydraulic transport of the LM, thereby improving anode reversibility under\nhigh areal capacity and state-of-charge (SOC) conditions. Under identical 50% SOC testing,\nthe binary EGaIn system also exhibited a higher Coulombic efficiency (CE) compared to the\n6\nprevious ternary EGaInSn system, further confirming its effectiveness (Fig. R2).\nAccording to your suggestion, we have added these discussions on Page 11 in the revised\nmanuscript, and Supplementary Fig. 12, Supplementary Table 2 in the revised supporting\ninformation.\nTable R2. Physical properties of various LMs.\nThermal Viscosity\nComposition Compatibility\nLM conductivity (mPa·s\n(wt%) with Zn (%)\n(W m−1 K−1) )\nEGaIn 75% Ga + 25% In 3.1 34.1 1.99\n68.5% Ga + 21.5%\nEGaInSn 2.9 32.6 2.40\nIn + 10% Sn\nFig. R2 | Long cycling performance of ZBFBs with EGaIn and EGaInSn at 50% SOC.\n- In Supplementary Fig. 3, the authors present the correlation between the change in zero-field\nsplitting (delta D) and temperature variations (delta T). However, due to the overlapping data\npoints from a large number of individual nanodiamonds, it is difficult to discern the linearity\nor consistency of the temperature dependence for each nanodiamond. Clarifying the\npresentation - perhaps by showing representative individual plots or statistical summaries -\nwould enhance the interpretability of the data.\nFig. 3 (Fig. R3), we have reprocessed the dataset by plotting all ΔD-ΔT data points collected\nfrom 170 individual nanodiamond sensors. A single linear fit to the complete dataset yields a\nslope of dD/dT ≈ −74 kHz/K, demonstrating a consistent and stable temperature dependence\nacross the ensemble. Furthermore, to assess the uniformity among individual sensors, we\ncalculated the dD/dT slope for each nanodiamond sensor and approximately 96% of these\nvalues fall within a narrow range centered at −74 kHz/K, confirming excellent stability and\nrepeatability of the temperature response. According to your suggestion, we have provided the\nresults and discussions on Page 6 in the revised manuscript, and Supplementary Fig. 3 in the\nrevised supporting information.\nFig. R3 | Temperature dependence of nanodiamonds with NV centers. Correlation between\nthe change in zero-field splitting (ΔD) and temperature variation (ΔT) obtained from 170\nindividual nanodiamond sensors. A linear fit to the ensemble data yields an average\ntemperature sensitivity of dD/dT ≈ −74 kHz/K, indicating a well-defined and stable\ntemperature dependence. This robust relationship underpins high-precision temperature\nsensing using NV centers in nanodiamonds.\n- Fig. 5f presents a performance comparison with other Zn-based flow batteries, including\nenergy density values. It is unclear whether the reported energy density is calculated based on\nthe volume of the catholyte only, or if it also includes the volume of the liquid metal. If the\n8\nvolume of the liquid metal is excluded, the rationale for this decision should be clearly stated,\nas it directly impacts the validity of the performance comparison.\nResponse: Thank you for your valuable comment. In our study, the energy density values\npresented in Fig. 5f are calculated solely based on the volume of the electrolyte, following\nwidely adopted conventions in peer-reviewed flow battery literature (e.g., Nat. Energy 2021,\n6, 582; Nat. Energy 2021, 6, 873; Adv. Mater. 2022, 35, 2209390). Although LM is flowable,\nit serves primarily as an electrode material rather than an electrolyte. This role is analogous to\nstatic carbon felt or graphite plates used in conventional flow batteries, providing a conductive\nhost for Zn deposition and alloying, but not directly participating in the redox reactions that\nstore energy. Including the LM volume in the calculation would incorporate non‑electroactive\nvolume, thereby underestimating the energy density per unit volume of active electrolyte and\ndeviating from standard benchmarking practices. Such an approach would also hinder direct\ncomparison with previously reported Zn-based flow battery systems.\nTo address your concern, we additionally calculated the energy density, including the LM\nvolume. The resulting energy density is 45.9 Wh L−1, which remains competitive among zinc-\nbased flow batteries, as shown in Fig. R4. As suggested, we have added these discussions to\nthe revised manuscript (on pages 20 and 25) and provided the detailed calculation in\nSupplementary Fig. 35 in the revised supporting information.\nFig. R4 | Comparison of energy density between this work and previously reported work of\nLM, while \"including LM\" means that the volume of the LM is incorporated into the calculation.\nAll energy density values are calculated based on the anode side.\n- Fig. 3c presents the phase diagram of the Zn–EGaIn system. However, the source of this\ndiagram is not specified. If the diagram is adapted from existing literature, please provide the\nappropriate citation. Alternatively, if it is based on experimental results obtained in this study,\nthe corresponding experimental procedures should be clearly described.\nResponse: We thank the reviewer for this important question. The phase diagram of the Zn-\nEGaIn system presented in Fig. 3c was calculated using the well-established CALPHAD\n(Calculation of Phase Diagrams) methodology, consistent with the approach detailed in\npublished works on related systems (e.g., J. Alloys Compd. 2023, 960, 170741; Calphad 2018,\n60, 214; J. Phase Equilib. Diffus. 2017, 38, 897). The calculation procedure is summarized as\nfollows.\nThe sub-regular solution model was applied to describe the liquid phase and terminal solid\nsolution phases, with the excess Gibbs energy expressed using the Redlich-Kister polynomial.\nThe thermodynamic parameters for the constituent binary systems, Ga-In, Ga-Zn, and In-Zn,\nwere taken from critically assessed databases and literature. The Ga-In, Ga-Zn, and In-Zn\nbinary systems are entirely composed of liquid phase and solid solution phases. And the\nthermodynamic parameters were based on previous optimized parameters that reproduced the\nexperimental phase equilibria and thermodynamic properties reliably. Subsequently, the\nternary Ga-In-Zn system was assessed by incorporating ternary interaction parameters. The\nthermodynamic parameters of each phase were optimized by searching for the best fit to\nexperimental equilibrium data and thermodynamic properties of alloys by using the Pandat\nsoftware package. During the optimization of PanOptimizer module, all of the literature data\nwere used as the initial data. Each piece of selected information was given a certain weight by\nthe importance of data, and changed by trial and error during the assessment, until most of the\nselected data is reproduced within the expected uncertainty limits.\ndiagram on pages 11, 25-26, and 30 in the revised manuscript.\n- Fig. 5f presents a performance comparison with other Zn-based flow batteries, including\nenergy density values. It is unclear whether the reported energy density is calculated based on\nthe volume of the catholyte only, or if it also includes the volume of the liquid metal. If the\nvolume of the liquid metal is excluded, the rationale for this decision should be clearly stated,\nas it directly impacts the validity of the performance comparison.\nResponse: Thank you for your valuable comment. In our study, the energy density values\npresented in Fig. 5f are calculated solely based on the volume of the electrolyte, following\nwidely adopted conventions in peer-reviewed flow battery literature (e.g., Nat. Energy 2021,\n6, 582; Nat. Energy 2021, 6, 873; Adv. Mater. 2022, 35, 2209390). Although LM is flowable,\nit serves primarily as an electrode material rather than an electrolyte. This role is analogous to\nstatic carbon felt or graphite plates used in conventional flow batteries, providing a conductive\nhost for Zn deposition and alloying, but not directly participating in the redox reactions that\nstore energy. Including the LM volume in the calculation would incorporate non‑electroactive\nvolume, thereby underestimating the energy density per unit volume of active electrolyte and\ndeviating from standard benchmarking practices. Such an approach would also hinder direct\ncomparison with previously reported Zn-based flow battery systems.\nTo address your concern, we additionally calculated the energy density, including the LM\nvolume. The resulting energy density is 45.9 Wh L−1, which remains competitive among zinc-\nbased flow batteries, as shown in Fig. R4. As suggested, we have added these discussions to\nthe revised manuscript (on pages 20 and 25) and provided the detailed calculation in\nSupplementary Fig. 35 in the revised supporting information.\nZn-FBs. \"Only electrolyte\" indicates that the calculation does not include the volume of the\nLM, while \"including LM\" means that the volume of the LM is incorporated into the calculation.\nAll energy density values are calculated based on the anode side.\nIn this manuscript, Wang and coworkers proposed to monitor sub-micron temperature\nvariations during Zn deposition using optically detected magnetic resonance (ODMR) with\nnanodiamond quantum sensors. A ~300 nm spatial resolution and ~2 K/(Hz)^0.5 temperature\nsensitivity were achieved. Furthermore, the authors introduced a flowable eutectic gallium-\nindium (EGaln) liquid metal (LM) anode, which mitigated zinc dendrite formation and\nenhanced the electrochemical performance in a flow-cell configuration. Overall, both the\nproposed methodology and the selection of the liquid-metal anode were highly interesting and\nimpactful. The manuscript fits the scope of the journal. The following questions/comments may\nfurther raise the impact of the study.\nResponse: We sincerely thank you for acknowledging the sub-micron thermal imaging\ncapability of ODMR quantum sensors and highlighting the critical role of EGaln liquid metal\nanodes in suppressing Zn dendrites while enhancing flow-cell performance. Your positive\nassessment of the work's novelty and scope is greatly encouraging. We have carefully\naddressed all comments below to further amplify the study's impact.\n1. As of now, the manuscript reads like two separate studies combined together, both in the title\nand throughout the text. The first part discusses the temperature sensing technique, while the\nsecond part focuses on the properties of the LM anode. It would be nice if the authors could\nturn it into a single-piece, cohesive study.\nResponse: We sincerely appreciate the reviewer’s comment regarding the need for a more\ncohesive integration between the temperature sensing technique and the LM anode study. In\nresponse, we have made substantial revisions to unify the manuscript around the central topic\nof temperature effects in Zn anodes for flow batteries. Specifically, we have added a new Fig.\n2 (Fig. R6) in the revised manuscript that directly investigates how substrate thermal\nconductivity influences the Zn deposition process under non-uniform temperature conditions.\nFour solid substrates, carbon felt (CF), Zn, Ag, and highly oriented pyrolytic graphite (HOPG),\nwere chosen to represent typical thermal conductivity levels in carbon-based and metallic\n13\nmaterials (Table R3), along with a HOPG-Zn gradient substrate (HZGS) to mimic the gradual\nthermal conductivity transition occurring during Zn deposition. As shown in Fig. R6, higher\nsubstrate thermal conductivity markedly reduces the interfacial temperature gradient (ΔT\ndecreases from 20.9 °C for CF to 0.4 °C for HOPG) and improves deposition uniformity (height\nvariation Δh decreases from 1.2 µm for CF to 0.6 µm for HOPG). This confirms that improved\ntemperature uniformity can promote homogeneous Zn deposition and mitigate morphological\ninstability. Importantly, the HZGS results show that Zn coverage gradually lowers the\nsubstrate’s effective thermal conductivity, causing the initial advantage of high-conductivity\nmaterials to fade at high areal capacities. As Zn accumulation progresses, temperature\ndistribution is ultimately dictated by Zn’s thermal conductivity. This underscores the need for\nsustained high-thermal-conductivity pathways and efficient heat removal. In flow batteries, a\nhigh-thermal-conductivity fluid can facilitate rapid heat removal from local hotspots and\npromote a more uniform temperature distribution. Building on this concept, we introduce a\nflowable LM electrode, in which the LM remains in intimate contact with the reaction interface,\nenabling efficient thermal management and enhanced temperature uniformity. COMSOL\nsimulations (Figs. R6 g,h) show that the LM electrode exhibit a much more uniform\ntemperature distribution than solid substrates and reaches thermal equilibrium far faster\n(~0.025 h) with a lower temperature gradient after 1 h (1.56 °C for LM versus 5.22 °C for\nHZSG), highlighting its superior thermal management.\nTo address the reviewer’s concern, we undertook a substantial restructuring of the Results and\ndiscussion section in the manuscript. Four key figures were reorganized and renumbered to\nestablish a logical progression from the temperature mapping method (new Fig. 1), through the\nnew substrate thermal-conductivity study (new Fig. 2), and finally to the LM anode application\n(new Figs. 3-4, reorganized from former Figs. 2-4). The LM section was comprehensively\nrewritten to follow naturally from the thermal-conductivity results, transforming it from a\nstandalone topic into a direct extension of the temperature analysis. This restructuring ensures\na coherent storyline centered on the role of temperature in Zn anodes for flow batteries.\nFurthermore, the manuscript title was revised to: “Sub-micron-resolution temperature mapping\nof Zn anode for flow batteries” to reflect the unified focus on temperature diagnostics and its\n14\napplication to electrode design, rather than appearing as two independent topics. Corresponding\nrevisions were made to the Abstract and Introduction, clarifying that the ODMR-mapping\nmethodology not only enables sub-micron-resolution diagnostics of Zn anodes, but also\nprovides mechanistic insights that guide the design and operation of flowable LM electrodes\nin Zn-based flow batteries.\nFig. R6 | Influence of substrate thermal conductivity on Zn deposition. (a) Geometry of the\nstatic Zn half‑cell model incorporating a localized heat source. (b) COMSOL‑simulated\ntemperature gradient of static Zn half‑cells with substrates of varying thermal conductivities\n15\nafter 1 h deposition. CF, Zn, Ag, HOPG: idealized constant thermal conductivity; HZGS:\nthermal conductivity shifts from HOPG to Zn with Zn deposition. (c) Corresponding\ntemperature profiles along the Y direction at the substrate/electrolyte interface. (d)\nCorresponding height profiles of electrodeposited Zn along the Y direction after 1 h. (e) Time\nevolution of the temperature difference (ΔT) between regions near and far from the heat source\nfor different substrates. (f) Time evolution of height difference (Δh) between Zn deposited\nregions on different substrates. (g) COMSOL-simulated temperature gradient of static Zn\nhalf-cell with LM. The dashed region indicates a 1:1 volume ratio of LM and electrolyte. (h)\nCorresponding temperature difference profile along the Y direction at the LM/electrolyte\ninterface.\nTable R3. Thermal conductivity of various substrates.\nSubstrate Thermal conductivity (W m−1 K−1)\nCF 0.36\nZn ~116\nAg ~429\nHOPG ~1700-2000\nAs suggested, we have made these changes to Figs. 2-4, and on Pages 2, 4, 9-10, 14-15 and\n18-19 in the revised manuscript, as well as to Supplementary Fig. 26 and Supplementary\nTable 1 in the revised supporting information.\n2. Regarding the temperature change in Fig.1d, what is the time response, e.g., how fast can\nthe temperature sensor respond when the cell short-circuits? Can the authors also explain the\ntemperature variation between 150 s and 220 s (drastic increase) and afterwards (temperature\ndrop)?\nResponse: Thank you for the insightful comment. In Fig. 1, the physical response time of the\ntemperature sensor is approximately 0.83 s. In our ODMR-based temperature measurement\n16\nsetup, we employ a continuous microwave excitation mode in which 31 discrete frequency\npoints are scanned to obtain a complete ODMR spectrum. The dwell time at each frequency\npoint is about 27 ms, giving a total acquisition time of approximately 0.83 s. This indicates that,\non the current measurement platform, the sensor can refresh the temperature value within ≤1 s.\nFor data presentation, however, we intentionally increase the integration time to improve the\nsignal-to-noise ratio and measurement precision. Specifically, each reported temperature point\nis obtained by averaging 12 consecutive ODMR spectra over a 10 s interval. This spectral\naveraging effectively suppresses random noise and ensures stable temperature readings. As\nshown in Fig. R7, increasing the integration time from 2.5 s (3 spectra averaged) to 5 s (6\nspectra averaged) already reduces noise significantly; extending it to 10 s further enhances\nprecision. The current effective response time of 10 s is determined by the trade-off between\ntemporal resolution and measurement accuracy under our existing hardware conditions, and it\nis sufficient to capture localized temperature variations associated with dendrite growth during\nbattery operation. Technically, the response time could be shortened by optimizing hardware\n(e.g., reducing communication delays), increasing laser and microwave power, or adjusting\nspectral sampling strategies, but such modifications would require careful balancing of\nmeasurement precision and system stability. As suggested, we have added these results and\ndiscussions on Pages 4-5 in the revised manuscript, and Supplementary Fig. 4 in the revised\nsupporting information.\nFig. R7 | Effect of integration time on the stability of ODMR-based temperature\nmeasurements during Zn plating in a Zn//Zn cell. Temperature traces obtained at\n17\nintegration times of (a) 2.5 s (3 spectra averaged), (b) 5 s (6 spectra averaged), and (c) 10 s (12\nspectra averaged). The temperature traces represent the averaged values from all nanodiamond\nsensor data points within the measurement area in the time-resolved ODMR temperature\nmapping experiment. Shorter integration times (2.5 s, 5 s) exhibit higher noise levels, whereas\nthe 10 s integration significantly suppresses random fluctuations, yielding the most stable and\nprecise temperature readings. The orange-shaded area marks the 25%-75% interquartile range\nof the temperature data, indicating where the central half of the measurements lie.\nThe observed temperature rise between 0 s and 220 s at the indicated location is associated with\nlocalized dendrite growth and soft short-circuit events. Our time-resolved ODMR temperature\nmapping (Fig. R8) reveals that the battery electrode surface can be divided into four regions\n(labeled 1-4) for analysis. The representative curve in Fig. 1d corresponds to a nanodiamond\nsensor located in Region 1 (arrow position). During the initial soft short-circuit, dendrite\nformation at this site resulted in a pronounced local temperature increase. As deposition\ncontinued, the most active dendrite growth shifted to Region 2, producing a stronger\ntemperature rise there. At around 150 s, a broader short-circuit event occurred, leading to\nsimultaneous temperature increases across multiple nanodiamond points, not limited to\nRegions 1 and 2. By 280 s, the primary dendrite growth sites had shifted again, this time to\nRegions 3 and 4, replacing the earlier hotspots in Regions 1 and 2. Consequently, the\ntemperature at the original location began to drop after 220 s, not because of local cooling per\nse, but because dendritic activity and the associated Joule heating had migrated to other\npositions on the electrode. This spatiotemporal evolution of dendrite growth and soft short-\ncircuits is inherently dynamic. Localized heating appears and disappears as active growth sites\nchange, leading to the observed pattern of temperature rise followed by decline at a fixed\nmeasurement point. According to your suggestion, these results and discussions have been\nadded to Fig. 1e, Pages 6-7 in the revised manuscript, and Supplementary Fig. 10 in the\nrevised supporting information.\nmapping. (a) Time-resolved ODMR temperature mapping images of the Zn plating process in\na Zn//Zn cell with four partitioned areas. (b) Variation in the average temperature monitored\nby the nanodiamond sensors across the four regions over time.\n3. Is it possible to correlate spots of the highest temperature variation during short-circuiting\nwith dendrite growth? It seems that different points may experience distinct temperature\nvariations, as demonstrated in Supplementary Fig. 5 - how should one assess the applicability\nof the technique?\nResponse: We thank the reviewer's constructive comments. Yes. By overlaying the time-\nresolved ODMR temperature mapping images with simultaneous optical microscopy of the Zn\nplating process (Fig. R9), we can directly compare the spatial distribution of temperature\n19\nvariation with the morphology of the electrode surface. This comparison shows that the regions\nexhibiting the highest temperature rise during soft short-circuit events coincide with the sites\nwhere dendritic structures emerge and grow. The spatial alignment between thermal hotspots\nand dendrite growth areas indicates that localized Joule heating is closely associated with\ndendrite formation and bridging across the electrodes. As suggested, we have added these\nresults and discussions on Page 7 in the revised manuscript, as well as in Supplementary Fig.\n9 in the revised supporting information.\nFig. R9 | Optical microscope images of the assembled Zn//Zn cell during operation. (a)\nOptical microscope images of the Zn//Zn cell during charging. (b) Composite images from\ntime-resolved ODMR and synchronized optical microscopy. The orange dashed rectangle\nmarks the temperature measurement area, while the visible microwave antenna delivers\nmicrowaves for NV center spin state control in the nanodiamonds.\nAs observed in Supplementary Fig. 5, different sensing points exhibit distinct temperature\nevolution profiles. This variation arises because the nanodiamond sensors are located in\ndifferent regions of the electrode surface, as shown in Fig. R10a. During Zn deposition,\ndendrite growth and soft short-circuit events occur dynamically and migrate between regions,\nso localized Joule heating and the resulting temperature changes are not uniform across the\n20\nelectrode. To assess the applicability of the ODMR temperature mapping technique, the spatial\ncontext of each sensing point must be considered (Fig. R8). When interpreted together with the\nmapping image, the differing temperature trends in Supplementary Fig. 5 reflect the genuine\nspatiotemporal heterogeneity of electrochemical activity rather than a limitation of the method.\nIn this spatially resolved manner, the technique reliably correlates localized heating with\ndendrite formation and can be extended to monitor dynamic processes in other electrochemical\nsystems. To make this clear, we have marked the positions of all sensors corresponding to\ntemperature curves in Supplementary Fig. 5, 7 and 14 in the revised supporting information,\nthereby clarifying their spatial locations in the thermal-mapping images.\nFig. R10 | Representative nanodiamond sensors showing high temperature increases\nduring Zn plating in a Zn//Zn cell. (a) Spatial locations of representative nanodiamond\nsensors exhibiting high-temperature changes. (b-e) Corresponding temperature variation\ncurves recorded during the Zn deposition process, with temperature rises exceeding 15 °C.\n4. How was the phase diagram of Fig. 3c constructed, experimentally or theoretically?\nResponse: We thank the reviewer for this important question. The phase diagram of the Zn-\n(Calculation of Phase Diagrams) methodology, consistent with the approach detailed in\npublished works on related systems (e.g., J. Alloys Compd. 2023, 960, 170741; Calphad 2018,\n60, 214; J. Phase Equilib. Diffus. 2017, 38, 897). The calculation procedure is summarized as\nfollows.\nThe sub-regular solution model was applied to describe the liquid phase and terminal solid\nsolution phases, with the excess Gibbs energy expressed using the Redlich-Kister polynomial.\nThe thermodynamic parameters for the constituent binary systems, Ga-In, Ga-Zn, and In-Zn,\nwere taken from critically assessed databases and literature. The Ga-In, Ga-Zn, and In-Zn\nbinary systems are entirely composed of liquid phase and solid solution phases. And the\nthermodynamic parameters were based on previous optimized parameters that reproduced the\nexperimental phase equilibria and thermodynamic properties reliably. Subsequently, the\nternary Ga-In-Zn system was assessed by incorporating ternary interaction parameters. The\nthermodynamic parameters of each phase were optimized by searching for the best fit to\nexperimental equilibrium data and thermodynamic properties of alloys by using the Pandat\nsoftware package. During the optimization of PanOptimizer module, all of the literature data\nwere used as the initial data. Each piece of selected information was given a certain weight by\nthe importance of data, and changed by trial and error during the assessment, until most of the\nselected data is reproduced within the expected uncertainty limits.\nFollowing your suggestions, we have added the thorough calculation process for the phase\ndiagram on pages 11, 25-26, and 30 in the revised manuscript.\n5. The authors briefly mentioned that LMs mitigate side reactions such as electrochemical\ncorrosion of Zn. More experimental evidence is required to support this claim.\nResponse: Thanks a lot for the valuable suggestion. In direct response to the reviewer's\ncomment, we conducted Tafel polarization measurements to assess the corrosion behavior of\nthe LM-based electrode in comparison with a conventional Zn foil electrode. As shown in Fig.\nR11, the LM electrode with in situ alloyed Zn (EGaInZn) exhibited a markedly lower corrosion\n22\ncurrent density (0.33 mA cm−2) than the Zn foil (10.1 mA cm−2), indicating a substantial\nsuppression of the corrosion reaction rate. In addition, the corrosion potential of the LM\nelectrode (−0.82 V) shifted positively relative to that of Zn foil (−0.89 V), reflecting a higher\nelectrochemical stability of the alloyed surface and a reduced tendency for spontaneous\ncorrosion in the electrolyte environment. These results demonstrate that the EGaInZn alloy\neffectively inhibits Zn corrosion by simultaneously lowering the reaction kinetics and\nenhancing the stability of the anode interface.\nTo further evaluate the influence of corrosion and other parasitic reactions under conditions\nthat magnify their impact, we tested the ZBFBs at a low current density of 10 mA cm−2. As\nshown in Fig. R12, the LM-based ZBFB achieved an average CE of 97.8% for 1-hour cycles\nand 96.6% for 2-hour cycles, whereas the conventional ZBFB without LM yielded only 94.1%\nand 93.4%, respectively. The superior CE performance of the LM-based ZBFB under\nprolonged cycling at low current density confirms that the LM electrode not only suppresses\ndendritic deposition but also significantly mitigates capacity losses associated with corrosion-\nrelated side reactions.\nFig. R11 | Tafel polarization curves of Zn and EGaInZn electrodes in 1 M ZnBr + 3 M KCl\n2\nelectrolyte at a scan rate of 0.1 mV s−1.\ncm−2 for 1 h and 2 h cycling periods.\nFollowing your suggestions, we have added these results and discussions on Pages 15 and 19\nin the revised manuscript, Supplementary Fig. 21 and Supplementary Fig. 33 in the revised\nsupporting information.\n6. The authors should critically comment on the potential challenges of implementing LM\nanodes in large-scale systems, such as material cost, long-term stability under real-world\nconditions (especially with bromine-based catholytes), and compatibility with commercial\nbattery designs (gravity-sensitive).\nResponse: We sincerely appreciate your careful observation. Below, we address the comments\nregarding material cost, long-term stability and compatibility with commercial battery designs\nin detail:\n(1). Material cost. We acknowledge that gallium-based LMs are more expensive than\nconventional Zn electrode. However, the LM anode demonstrates long service life and can be\nrecovered and reused multiple times without significant performance loss, as evidenced by our\nreassembly tests. As shown in Fig. R13, ZBFB reassembled with the recovered LM\ndemonstrated performance equivalent to that of the initial operation, indicating that the LM\nelectrode can be repeatedly utilized across multiple service cycles. This high reusability\nsignificantly reduces the amortized cost over the operational lifetime, making the approach\n24\nmore economically viable for applications that demand long-term stability and high efficiency.\nIn addition, the use of LM anodes enables an electrolyte utilization efficiency above 90%,\nwhich markedly reduces the amount and thus the cost of electrolyte required per Wh of\ndelivered energy. Furthermore, the LM-based anode configuration eliminates the need for a\ncarbon felt electrode on the negative side, effectively halving the electrode cost relative to\nconventional flow battery assemblies. Taken together, these factors offset the higher unit price\nof gallium and significantly improve the overall cost-effectiveness of the system.\nFig. R13 | Electrochemical performance of ZBFBs assembled with recovered LM that had\nundergone 300 h of prior operation before reuse.\n(2). Long-term stability under real-world conditions. In practical ZBFBs, the catholyte is\nformulated with bromine complexing agents to bind Br molecules and reduce the\n2\nconcentration of free polybromide species in the electrolyte (Nature 2024, 635, 89). In our\nwork, the catholyte incorporated a commercial bromine complexing agent, 1-ethyl-1-\nmethylpyrrolidinium bromide (MEP), which effectively suppresses free Br and polybromide\n2\nlevels, thereby minimizing bromine crossover to the anode side. In addition, the use of ion-\nexchange membranes provides selective ion transport for the supporting electrolyte ions while\nblocking active species crossover, further mitigating self-discharge and preventing bromine-\ninduced anode degradation (Phys. Chem. Chem. Phys. 2021, 23, 26070). This design reflects\nthe actual engineering practice in commercial ZBFBs and ensures that LM degradation from\nbromine species is negligible under real-world operating conditions. Moreover, in our ZBFB\nconfiguration, the LM is located exclusively in the negative compartment and has no direct\n25\ncontact with the bromine catholyte. As shown in Fig. R14, elemental composition analysis of\nthe LM anode after extended cycling revealed that the alloy composition remained essentially\nunchanged compared to its pristine state, providing direct experimental evidence of its\nchemical stability during prolonged operation.\nFig. R14 | Elemental composition of the LM anode from inductively coupled plasma mass\nspectrometry (ICP-MS) tests after discharge during long-term operation at 40 mA cm−2 and 90%\nSOC.\n(3). Compatibility with commercial battery designs. As shown in Fig. R15, the LM anode can\nbe readily integrated into existing commercial battery stacks with minimal modifications. The\nprimary adaptation required is maintaining the stack orientation in a horizontal position to\nprevent gravitational redistribution of the LM. This orientation ensures intimate and uniform\ncontact between the LM electrode and the bipolar plate, thereby minimizing interfacial\nresistance and promoting homogeneous current distribution. Importantly, the electrolyte flow\nchannels and manifolds remain unchanged; the inlet for the negative-side liquid is positioned\nprecisely at the interface between the anolyte and the LM, allowing efficient mass transport.\nThese design considerations ensure that the LM-based architecture is fully compatible with\ncurrent commercial flow battery configurations without necessitating major redesigns.\nFollowing your suggestions, we have added these results and discussions on Pages 22 and 25\nin the revised manuscript, and Supplementary Figs. 40-42 in the revised supporting\ninformation.\nThis manuscript presents an innovative approach employing non-invasive optically detected\nmagnetic resonance (ODMR) with nanodiamond quantum sensors to monitor real-time\ntemperature variations at the microscopic scale during Zn deposition. This technique enables\ndetailed thermal mapping, offering a powerful tool for understanding the interplay between\nelectrochemical behavior and thermal dynamics in Zn-based systems. In addition, the authors\nintroduce a flowable eutectic gallium-indium (EGaIn) liquid metal (LM) electrode with high\nthermal conductivity into Zn flow cells, which effectively dissipates localized heat and\nminimizes spatial temperature gradients.\nOverall, the study addresses a significant challenge in Zn-based electrochemical systems—\nthermal heterogeneity during dendrite formation—and proposes a compelling solution. The\nmanuscript is of interest to the readership of Nature Communications and merits publication\nafter the following issues are addressed:\nResponse: Thank you for your positive and professional evaluation of our work. We have\nmade corresponding revisions according to your suggestions, which have helped us refine our\nmanuscript significantly.\n1. In Figure 1, the time-resolved ODMR temperature maps illustrate the emergence of thermal\nhotspots correlated with Zn dendrite growth. The authors attribute heat generation to internal\nshort circuits caused by dendrite bridging. However, in the abstract, it is stated that spatial\ntemperature non-uniformity plays a critical role in accelerating dendrite growth. This implies\na causative rather than resultant relationship. Could the authors elaborate on the evidence\nsupporting this directional causality? Specifically, how do the data differentiate between\ndendrites causing heat and heat influencing dendrite nucleation? Can a temporal correlation\nbetween hotspot emergence and dendrite initiation sites be established?\nResponse: We sincerely appreciate the reviewer’s insightful question. To further analyze the\nevolution of local temperature rise, we divided the ODMR temperature maps into four regions\n28\n(labeled 1, 2, 3, and 4) in Fig. R16 according to the sequence of temperature rise. In the\nelectrochemical curve of Fig. 1d, a sharp voltage drop is observed at 62 s, indicating the\noccurrence of an internal short circuit. In region 1 of the ODMR maps, a distinct local\ntemperature rise appears at 66 s, which we interpret as heat generation resulting from dendrite-\ninduced short-circuiting. A second voltage drop at 131 s corresponds to a more heterogeneous\ntemperature distribution at 150 s compared to 66 s, implying the formation of multiple short-\ncircuit sites.\nFurther comparison of the spatial distribution of nanodiamond temperature rise shows that, in\nregion 1, high‑temperature points expand markedly between 66 s and 220 s, while in region 2,\na similar expansion is observed between 100 s and 220 s. These results indicate a progressive\nenlargement of hotspot areas as deposition proceeds, with the initial hotspot locations showing\npreferential temperature increases and serving as focal points for the formation of additional\nhotspots. Our observations strongly suggest the following sequence: localized thermal hotspots\narise first, causing changes in local resistance and ion migration rates; these perturbations\npromote preferential dendrite nucleation and growth at hotspot sites; dendrite bridging\nsubsequently induces internal short circuits; the resulting short circuits further intensify Joule\nheating and reaction heterogeneity, producing larger and more widespread hotspots that\naccelerate dendrite proliferation and ultimately battery failure. This reasoning underlies our\nstatement in the abstract that spatial temperature non-uniformity may play a critical role in\naccelerating dendrite growth and potentially leading to more severe short circuits.\nTo make this clear, we have added further discussions on Pages 6-7 in the revised manuscript\nto provide additional explanation, and we have reorganized Fig. 1 to present the data in a\nclearer, and more comprehensive manner, thereby improving its logical flow and readability.\nZn//Zn cell with four partitioned areas.\nHowever, while the temporal evolution of hotspots and short-circuit events can be inferred\nfrom our combined ODMR and electrochemical data, the current spatial resolution does not\nyet allow us to definitively establish the exact temporal order between hotspot emergence and\ndendrite initiation at the nanoscale. By integrating time-resolved ODMR maps with\nsynchronized optical microscopy images (Fig. R17), we can estimate the relative timing of\ndendrite appearance; however, the resolution limits prevent us from fully distinguishing which\nevent occurs first. In principle, if the testing system could be implemented in a fully two-\ndimensional configuration, it would be possible to accurately correlate nanoscale spots of\nhighest temperature variation during short-circuiting with dendrite growth. Although our\ncurrent cell design approximates a 2D geometry as closely as possible, the presence of liquid\nelectrolyte inevitably renders the system three-dimensional. Nevertheless, the observed\nnanodiamond temperature rise consistently coincides with short-circuit locations, supporting a\nspatial correlation between hotspots and dendrite growth. We are continuing to refine our\nestablishing a more precise correlation between hotspot emergence and dendrite initiation,\nin line with the reviewer’s valuable suggestion. Following your suggestions, we have added these\nresults and discussions on Page 7 in the revised manuscript, and Supplementary Fig. 9 in the\nrevised supporting information.\nFig. R17 | Optical microscope images of the assembled Zn//Zn cell during operation. (a)\nOptical microscope images of the Zn//Zn cell during charging. (b) Composite images from\ntime-resolved ODMR and synchronized optical microscopy. The orange dashed rectangle\nmarks the temperature measurement area, while the visible microwave antenna delivers\nmicrowaves for NV center spin state control in the nanodiamonds.\n2. Was the same cell configuration used for ODMR measurements in the Zn//LM (EGaIn)\nsystem as in the conventional Zn system? If not, the authors are encouraged to include a\nschematic diagram of the Zn//LM cell adapted for ODMR to provide clarity for readers.\nResponse: We thank the reviewer for the valuable comment. The configurations of the Zn//Zn\nand Zn//LM cells used for the ODMR measurements are shown in Fig. R18. Both systems\nemploy the same overall cell design and measurement setup. In the Zn//Zn configuration, two\n31\npieces of Zn foil are immersed in the electrolyte and mounted onto stainless steel conductive\nsubstrate to serve as electrodes. In the Zn//LM configuration, one of the Zn foil electrodes is\nreplaced by a layer of LM coated onto a conductive substrate, while the other electrode remains\nZn foil. In both cases, the two electrodes are positioned diagonally within the cell to ensure that\nany short-circuit event occurs within the temperature monitoring region.\nFig. R18 | Schematic diagrams of cell configurations used for ODMR measurements.\n(a)\nZn//Zn cell and (b) Zn//LM cell.\nTo make this clear, we have added detailed assembly instructions on Pages 23-24 in the revised\nmanuscript, and included schematic diagrams of both cell configurations in Supplementary\nFig. 2 in the revised supporting information.\n3. The primary advantage of incorporating EGaIn appears to be the suppression of dendrite\nformation, which inherently leads to more uniform thermal profiles. However, the manuscript\nattributes temperature uniformity to the high thermal conductivity of the LM. Could the authors\ndisentangle these effects? For instance, is there evidence (e.g., control experiments or modeling)\ndirectly linking thermal conductivity to the observed uniformity, independent of dendrite\nsuppression?\nResponse: We thank the reviewer's comments and fully agree that both dendrite suppression\nand the high thermal conductivity of EGaIn contribute to the observed temperature uniformity.\nTo specifically investigate how thermal conductivity influences the Zn deposition process, we\n32\nselected four solid substrates, carbon felt (CF), Zn, Ag, and highly oriented pyrolytic graphite\n(HOPG), to represent typical thermal conductivity levels in carbon-based and metallic\nmaterials (Table R4), together with a HOPG-Zn gradient substrate (HZGS) to mimic the\ngradual thermal-conductivity transition occurring during Zn deposition. As shown in Figs. R19\nb-c, higher substrate thermal conductivity markedly reduces the interfacial temperature\ngradient (ΔT decreases from 20.9 °C for CF to 0.4 °C for HOPG), confirming that enhanced\nthermal uniformity promotes homogeneous Zn deposition and mitigates morphological\ninstability. Importantly, the HZGS results show that Zn coverage gradually lowers the\nsubstrate’s effective thermal conductivity, causing the initial advantage of high-conductivity\nmaterials to fade at high areal capacities. As Zn accumulation progresses, the temperature\ndistribution becomes dominated by Zn’s thermal conductivity.\nIn contrast, COMSOL simulations (Figs. R19 d,e) show that the static Zn half‑cell with LM\nexhibit a much more uniform temperature distribution than solid substrates and reaches thermal\nequilibrium far faster (~0.025 h) with a lower temperature gradient after 1 h (1.56 °C for LM\nversus 5.22 °C for HZSG), highlighting its superior thermal management capability. This\nimprovement arises not only from the intrinsic thermal conductivity of the LM, but also from\nits extensive contact area and large volume fraction, which facilitate bulk heat conduction and\npromote more homogeneous heat dissipation across the electrode region.\nIn flow batteries, a high-thermal-conductivity fluid can facilitate rapid heat removal from local\nhotspots and promote a more uniform temperature distribution. To further isolate the effect of\nthermal conductivity, we performed COMSOL simulations in flow situations considering only\nlocalized heat generation on the electrode surface (mimicking a hotspot during a short-circuit)\nwithout including the electroplating process. As shown in Fig. 3 d-i, with LM present, the\ntemperature gradients around the hotspot are significantly reduced and the heat spreads more\nuniformly across the electrode surface compared with the conventional electrode configuration.\nThis demonstrates that the high thermal conductivity of LM alone can produce a more uniform\nthermal profile, independent of dendrite suppression.\nTherefore, we believe that during electrochemical operation, both effects act simultaneously:\n33\n(1) alloying between deposited Zn and LM suppresses dendrite formation, stabilizing the\ndeposition process and thereby reducing the probability of hotspot generation; (2) the enhanced\nthermal conductivity of LM promotes rapid heat dissipation, mitigating temperature\nheterogeneity that could otherwise lead to uneven Zn deposition. The synergy of dendrite\nsuppression and improved heat spreading accounts for the uniform temperature distributions\nobserved experimentally.\nFig. R19 | Influence of substrate thermal conductivity on Zn deposition. (a) Geometry of\nthe static Zn half‑cell model incorporating a localized heat source. (b) COMSOL‑simulated\ntemperature gradient of static Zn half‑cells with substrates of varying thermal conductivities\nafter 1 h deposition. CF, Zn, Ag, HOPG: idealized constant thermal conductivity; HZGS:\nthermal conductivity shifts from HOPG to Zn with Zn deposition. (c) Time evolution of the\ntemperature difference (ΔT) between regions near and far from the heat source for different\nsubstrates. (d) Corresponding temperature difference profile along the Y direction at the\nLM/electrolyte interface. (e) COMSOL-simulated temperature gradient of static Zn half-cell\n34\nwith LM. The dashed region indicates a 1:1 volume ratio of LM and electrolyte.\nTable R4. Thermal conductivity of various substrates.\nSubstrate Thermal conductivity (W m−1 K−1)\nCF 0.36\nZn ~116\nAg ~429\nHOPG ~1700-2000\nFollowing your suggestions, we have added these results and expanded discussions in Fig. 2,\non Pages 9-10, 12 and 18-19 in the revised manuscript, and Supplementary Table 1 in the\nrevised supporting information.\n4. The authors should discuss how the properties of EGaIn used in this study differ from those\nof the eutectic gallium-indium-tin (EGaInSn) alloy used in prior work (DOI:\n10.1126/sciadv.ads3919). In what ways does the use of EGaIn represent an innovation or\nimprovement? Consider discussing aspects such as electrochemical stability, viscosity,\ninterfacial behavior, or compatibility with Zn.\nResponse: We appreciate the reviewer's insightful comment. Compared to our previous LM\nsystem based on ternary EGaInSn alloy, the present work adopts a binary EGaIn alloy with an\noptimized composition. As summarized in Table R5, the binary EGaIn offers higher Zn\naccommodation capacity, improved thermal conductivity, and reduced viscosity. The high\ncompatibility with Zn helps maintain a smooth, self-healing liquid-Zn interface, which\nsupports uniform ion flux and stable cycling. The enhanced thermal conductivity and lower\nviscosity are critical for enhancing Zn deposition homogeneity, minimizing localized heating,\nand facilitating hydraulic transport, respectively, thereby significantly improving anode\nreversibility under high areal capacity and high SOC conditions. In addition, removing Sn from\nthe alloy composition is expected to mitigate side reactions with electrolyte components,\n35\nfurther supporting long-term cycling stability. These advantages are directly reflected in the\nelectrochemical results, where the binary EGaIn system delivers higher Coulombic efficiency\nthan the ternary EGaInSn under identical 50% SOC testing (Fig. R20).\nAs suggested, these discussions and results have been added on Page 11 in the revised\nmanuscript, Supplementary Fig. 12 and Supplementary Table 2 in the revised supporting\ninformation.\nTable R5. Physical properties of various LMs.\nThermal\nComposition Compatibility Viscosity\nLM conductivity\n(wt%) with Zn (%) (mPa·s)\n(W m−1 K−1)\nEGaIn 75% Ga + 25% In 3.1 34.1 1.99\n68.5% Ga + 21.5%\nEGaInSn 2.9 32.6 2.40\nIn + 10% Sn\nFig. R20 | Long cycling performance of ZBFBs with EGaIn and EGaInSn at 50% SOC.\n5. Can the authors comments more on the practical application of LM electrolyte on Zn based\nflow batteries, in the aspect of cost effectiveness and setup feasibility?\nResponse: We thank the reviewer's comments. Below, we address the comments regarding\n36\ncost effectiveness and setup feasibility in detail:\n(1) Cost effectiveness: We acknowledge that gallium-based LMs are more expensive than\nconventional Zn electrode. However, the LM anode demonstrates long service life and can be\nrecovered and reused multiple times without significant performance loss, as evidenced by our\nreassembly tests. As shown in Fig. R21, the LM composition remained essentially unchanged\nafter use. ZBFB reassembled with the recovered LM demonstrated performance equivalent to\nthat of the initial operation, indicating that the LM electrode can be repeatedly utilized across\nmultiple service cycles (Fig. R22). This high reusability significantly reduces the amortized\ncost over the operational lifetime, making the approach more economically viable for\napplications that demand long-term stability and high efficiency. In addition, the use of LM\nanodes enables an electrolyte utilization efficiency above 90%, which markedly reduces the\namount and thus the cost of electrolyte required per Wh of delivered energy. Furthermore, the\nLM-based anode configuration eliminates the need for a carbon felt electrode on the negative\nside, effectively halving the electrode cost relative to conventional flow battery assemblies.\nTaken together, these factors offset the higher unit price of gallium and significantly improve\nthe overall cost-effectiveness of the system.\nFig. R21 | Elemental composition of the LM anode from inductively coupled plasma mass\nspectrometry (ICP-MS) tests after discharge during long-term operation at 40 mA cm−2 and 90%\nSOC.\nundergone 300 h of prior operation before reuse.\nFig. R23 | The schematic diagram of the flow battery stack assbled with LM.\n(2) Setup feasibility: As shown in Fig. R23, the LM anode can be readily integrated into\nexisting commercial battery stacks with minimal modifications. The primary adaptation\nrequired is maintaining the stack orientation in a horizontal position to prevent gravitational\nredistribution of the LM. This orientation ensures intimate and uniform contact between the\nLM electrode and the bipolar plate, thereby minimizing interfacial resistance and promoting\nhomogeneous current distribution. Importantly, the electrolyte flow channels and manifolds\nremain unchanged; the inlet for the negative-side liquid is positioned precisely at the interface\nbetween the anolyte and the LM, allowing efficient mass transport. These design considerations\nensure that the LM-based architecture is fully compatible with current commercial flow battery\nconfigurations without necessitating major redesigns.\nFollowing your suggestions, we have added these results and discussions on Page 22 in the\nrevised manuscript, Supplementary Figs. 40-42 in the revised supporting information.\n39"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have adequately addressed the comments by this reviewer and significantly improved the manuscript. I recommend to accept this work at its present form.", "reviewer_2": "The authors have addressed my concerns in the current version. The manuscript can be published as is.", "reviewer_3": "The authors have fully addressed all my previous comments. The revisions are clear and satisfactory. And I have no further substantive comments. I recommend acceptance for publication in Nature Communications."}, "author_response": ""}]

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