Rapid growth in global photovoltaic (PV) deployment is creating an expanding stream of end-of-life crystalline-silicon modules, yet advanced recycling routes remain difficult to evaluate because high-resolution inventories that resolve internal unit operations are still limited. Here, we assess the Advanced PhotoLife (APL) solvent-based recycling process by integrating process simulation, material flow analysis (MFA), life cycle assessment (LCA), and life cycle costing (LCC) for the treatment of 1000 kg of retired modules in China. The treatment stage emits 829 kg CO2-eq and consumes 6168 MJ, with physical-chemical classification contributing 71.0% of global warming potential and 64.6% of cumulative energy demand, mainly due to cyclohexane-related upstream burdens, direct emissions from the thermal oxidation of ethylene vinyl acetate flakes and residual cyclohexane, and electricity use. After system expansion, the process achieves net reductions of -2362 kg CO2-eq and -30,983 MJ, and all midpoint impact categories remain net negative under the adopted substitution assumptions. The baseline net economic profit reaches 1734 CNY/t, while the net environmental profit reaches 7529 CNY/t. Sensitivity analysis identifies energy recovery, solvent-loop closure, silver recovery efficiency, transport distance, and electricity-mix evolution as the principal performance levers. These results indicate that robust assessment of advanced PV recycling should integrate mass recovery, product quality, credible substitution, solvent containment, energy integration, and regionally coordinated recycling networks.

Ammonia is indispensable for food production and an emerging carbon-free energy vector, yet its synthesis via the fossil-fuelled Haber-Bosch process makes it a major source of carbon dioxide. We introduce the Ammonia Rainbow, a classification framework combining physics-based modelling, learning-curve analysis, and life-cycle sustainability assessment to evaluate net-zero transitions across eight ammonia production technologies. Here we show that, assuming global ammonia demand doubles to meet projected food and energy needs, net-zero ammonia is not achievable by 2050 under any current policy or technological scenario. Even optimistic deployment of green routes demands extensive infrastructure, consuming over 40 percent of available green hydrogen alongside large fractions of carbon capture and renewable energy capacity. Electrochemical routes offer long-term promise but are unlikely to reach commercial viability before 2070 without disruptive innovation. By exposing these hidden systems-level burdens, we challenge the prevailing assumption of unchecked demand growth and argue for demand-side measures, efficiency improvements, and alternative decarbonisation strategies.

Electrochemical carbon capture offers a sustainable route to mitigate CO2 emissions, but practical deployment is often limited by modest capture rates and system complexity. Here we report a saline-water electrolysis strategy that simultaneously captures CO2 and converts it to sodium bicarbonate (NaHCO3 ) without external chemical additives. Hydroxide ions (OH-) generated in situ at the cathode via the hydrogen-evolution reaction (HER) enable rapid CO2 absorption and selective conversion to NaHCO3 by maintaining the catholyte at pH 8-9, consistent with thermodynamic speciation. In simulated flue gas, the system delivers a CO2 capture rate of 5.27 CO2 cm(-2) h(-1) (55.6 kg(CO2) m(-2) day(-1)) at 300 mA cm(-2), >99.5% capture efficiency, >90% faradaic efficiency, and energy consumption as low as 87 kJ mol CO2 (-1) (1.98 GJ CO2 (-1)). The process is tolerant to sulfur dioxide (SO2), maintaining similar to 85% NaHCO3 conversion for >240 h with 1.0% SO(2)in the feed. Using pure water as the catholyte enables direct production of high-purity NaHCO3 , enhancing operational flexibility. Techno-economic analysis indicates capture costs with US$90.3 per t(CO2) when co-located with a desalination facility and low-cost electricity, while considering the revenues from products NaHCO3 , H-2 and Cl-2 can further improve the economics. This multifunctional, impurity-resistant, and renewable-compatible approach offers a practical, scalable pathway for industrial CO2 capture and mineralization.

This work presents an integrated data-driven modeling and control framework for alkaline water electrolysis (AWE). In the developed two-scale control framework, a high-fidelity multiphysics model was first developed to describe the coupled electrochemical, thermal, and two-phase flow behavior across five interacting domains and experimentally validated. The validated model was then used to generate training data for a data-driven surrogate model. Building on this, a PID-control-oriented surrogate model was developed using a Long Short-Term Memory (LSTM) network to accurately capture the system’s nonlinear transient dynamics. An adaptive PID controller enhanced by ANN was then designed, where the LSTM provides predictive state information and the ANN adjusts the PID gains online. The proposed LSTM-ANN-PID controller was validated in two cases: (1) Disturbance in operating voltage and inlet temperature to assess lag-compensation capability, and (2) real solar-power data to emulate renewable-driven fluctuations. Results show that, under realistic operating conditions, the controller reduces overshoot by approximately 60%, shortens settling time by 10%, and achieves around 10% lower total energy consumption for hydrogen production. Overall, this framework effectively integrates physics-based modelling with intelligent control, enabling accurate, stable, and energy-efficient AWE operation under variable power inputs.

This study presents an open-cathode proton exchange membrane fuel cell stack with a passive thermal management system based on micro heat pipe arrays. The system enables self-driven heat recovery and internal heat circulation under low-temperature conditions without relying on external power input or external heat sources. Experiments and modeling were conducted to evaluate its thermal-electrical behavior, dynamic power output, and startup performance. The results show that, at 35 A, the stack with heat replenishment achieved a 6.8% improvement in output performance and a 12.4 °C higher operating temperature compared with the stack without heat replenishment. When the current increased from 30 A to 40 A, the voltage undershoot and recovery amplitude were reduced by 23.4% and 65.6% respectively. The stack temperature increased with the load ramp rate, accompanied by improved transient output performance. The stack with heat replenishment also showed a lower 33.0% temperature difference at 35 A. At an ambient temperature of 0 °C, the output performance at each current level showed an average improvement of 2.4% compared with that of the stack without heat replenishment. These results demonstrate the effectiveness of the proposed system in improving fuel cell performance and stability under cold conditions while reducing auxiliary energy consumption.

Perfluorosulfonic acid (PFSA) membranes suffer from severe conductivity decay caused by dehydration at elevated temperatures, hindering their application in medium- to high-temperature proton exchange membrane fuel cells (MHT-PEMFCs). To address this, Nafion/SiO2 composite membranes with systematically varied filler contents were fabricated via a sol-gel-assisted casting strategy to enhance hydration stability and proton transport. Spectroscopic and microscopic analyses reveal a homogeneous nanoscale dispersion of SiO2 within the Nafion matrix, along with strong interfacial hydrogen bonding between SiO2 and sulfonic acid groups. These interactions effectively suppress polymer crystallinity and stabilize hydrated ionic domains. Thermogravimetric analysis confirms markedly improved water retention in the composite membranes at intermediate temperatures. Proton conductivity measurements at 50% relative humidity (RH) identify the Nafion/SiO2-3 membrane as exhibiting optimal transport behavior, delivering the highest conductivity of 61.9 mS·cm-1 at 120 °C and significantly improved conductivity retention compared to Nafion 117. Furthermore, single-cell tests under MHT-PEMFC conditions (120 °C, 50% RH) demonstrate the practical efficacy of these membrane-level enhancements, with the Nafion/SiO2-3 membrane exhibiting an open-circuit voltage and peak power density 11.2% and 8.9% higher, respectively, than those of pristine Nafion under identical MEA fabrication and operating conditions. This study elucidates a clear structure-property-transport relationship in SiO2-reinforced PFSA membranes, demonstrating that controlled inorganic incorporation is a robust strategy for extending the operational temperature window of PFSA-based proton exchange membranes toward device-level applications.

Electrochemically switched ion membrane extraction (ESIME) technology enables continuous Nd(III) extraction, using an electrochemical–chemical dual-functional di(2-ethylhexyl) phosphoric acid-incorporated multi-walled carbon nanotubes (P204-MWCNTs) membrane. To elucidate the electrochemical–chemical transmembrane transport in ESIME, a dynamic model for Nd(III) extraction was developed and validated. This model quantitatively reveals the coupled extraction–diffusion–stripping transmembrane process. In the model, the electroactive carrier concentration and the ion-exchange carrier concentration bridge the external driving forces (electric field and H+ concentration gradient) and the spatiotemporal evolution of Nd-complexes. Simulation results indicate that the rate-limiting step of the transmembrane process alternates between extraction and diffusion, while stripping remains rapid. To quantify the extraction-diffusion competition, a dynamic Damköhler number (DaII) is introduced, revealing that the rate-limiting step shifts from diffusion control (DaII>1) to extraction control (DaII<1) at an extraction efficiency () of ∼67% (membrane thickness: 95 μm). Parameter analysis further indicates that a voltage of 0.9 V maximizes the synergistic electrochemical and chemical contribution (53% and 47%, respectively), achieving an of 93%. Multi-parameter optimization identifies an optimal operational window achieving >95% stripping efficiency. Finally, the model was successfully extended to multi-ion systems and validated in simulated NdFeB recovery solution. This DaII-based framework serves as an efficient in-silico tool for evaluating and optimizing rare-earth separation process in ESIME systems.

Abstract Solar redox flow batteries (SRFBs) provide a promising platform for directly coupling solar energy conversion with electrochemical energy storage, but their performance is still limited by insufficient solar-spectrum utilization and sluggish interfacial charge transfer at photoelectrodes. Herein, an Er-modified TiO2−g-C3N4 heterojunction photoanode was constructed by growing Er-doped TiO2 nanorod arrays on fluorine-doped tin oxide followed by g-C3N4 deposition, and was evaluated in a TEMPO/VCl3-based SRFB. Structural and spectroscopic characterizations show that Er modification preserves the main TiO2 framework, promotes a nanorod-based heterostructure with intimate interfacial contact, and redistributes the optical response toward the visible−near-infrared region. Among the investigated electrodes, the 3 wt % Er:TiO2−g-C3N4 photoanode exhibits the most favorable photoelectrochemical behavior, with the charge-transfer resistance decreasing from 28.55 to 23.82 Ω compared with the undoped TiO2−g-C3N4 electrode. PL/TRPL and TPV measurements further indicate suppressed carrier recombination, with the TPV average lifetime increasing from 27.080 to 107.253 μs after Er modification. Wavelength-dependent IPCE and infrared-filtered photocurrent measurements reveal an enhanced but relatively weak long-wavelength photoresponse, suggesting that Er-related long-wavelength utilization acts as an auxiliary contribution rather than the sole origin of the improved performance. When assembled into a full SRFB, the optimized photoanode delivers stable unbiased photocharging currents of approximately 1.0−1.15 mA cm−2 over repeated cycles, together with a solar-to-chemical conversion efficiency of about 1.15% and an estimated solar-to-output energy efficiency of 0.46−0.50%. Post-cycling SEM and XRD results further support the short-term structural stability of the photoanode. These results demonstrate that optimized Er modification primarily enhances interfacial charge separation and transfer in TiO2−g-C3N4 photoanodes while providing an additional route for long-wavelength photon utilization in integrated solar conversion−storage systems.

Hydrogen production from renewable energy is a promising solution for clean and efficient hydrogen generation. The hybrid electrolyzers system (HES) consists of alkaline (ALK) and proton exchange membrane (PEM) electrolyzers. It balances PEM’s economic benefits and ALK’s hydrogen production capabilities. To enhance hydrogen production efficiency and ensure the operational stability of HES, this study proposes a novel multi-timescale rolling optimization strategy considering flexible hydrogen demand. A joint wind–photovoltaic power prediction model is used to provide accurate forecast data for scheduling optimization. The operating characteristics of the electrolyzers, including various operating states, start–stop behaviors, load variations, and hydrogen production features of ALK and PEM, are modeled in detail. Multi-timescale modeling is employed for rolling optimization to obtain the optimal scheduling solution. Finally, the validity of the proposed method is verified under varying weather types in Macheng, Hubei, China. The results show that HES significantly improves hydrogen production capacity and economics compared to ALK-only production, with a 25% increase in net revenue under extreme weather. Flexible hydrogen load demand response synchronizes fluctuations on both the supply and demand sides, multiplying grid trading benefits. The multi-timescale scheduling strategy enabled each electrolyzer to achieve over 96% execution of the day-ahead schedule across various weather conditions. The system’s economy achieves 98% of the ideal maximum benefit and 80% under extreme weather. This demonstrates that the proposed scheme holds promise for providing effective solutions for the optimal design and scheduling of renewable energy hydrogen production systems.

LCA of Tween/Span surfactants based on industrial raw data to support sustainable battery applications.

The emission of CO2 is the primary cause of global warming, and the absorption of CO2 by ammonia solution based on a bubble column reactor is an effective method for carbon capture. This paper utilizes the UDF function in commercial CFD software for numerical simulation and validates the results through experiments. The study investigates the impact of multi-stage baffle parameters (i.e., size, quantity, and position) on the CO2 absorption and ammonia escape processes, while also analyzing the mass transfer characteristics of the bubble column reactor under different operating conditions (i.e., ammonia concentration, inlet CO2 volume fraction, temperature, and pressure). The results indicate that the introduction of baffles promotes CO2 absorption, and the influence of baffle number and position are more significant than size. Increasing the number of bubble generators also enhances absorption, and the ammonia escape process becomes more intense as the removal efficiency increases. Through a comprehensive analysis of the system energy consumption and CO2 absorption enhancement, the optimal baffle configuration for the bubble column reactor consists of four baffles positioned on the left side, each with a length of 6 mm and separated by a spacing of 2 mm. Furthermore, increasing the ammonia concentration and temperature can enhance the CO2 removal efficiency and the overall mass transfer coefficient of ammonia escape, while an increase in the inlet CO2 volume fraction has the opposite effect. Although an increase in pressure promotes removal efficiency, it reduces the overall mass transfer coefficients of both CO2 and ammonia escape.

Passive miniature liquid fuel cells, which eliminate the need for external auxiliary power components, exhibit high system energy density and are considered ideal candidate power sources for portable electronics. However, due to the inherent absence of active purging and auxiliary drainage mechanisms, severe cathodic water flooding frequently occurs during high-current-density operation, leading to a dramatic surge in mass transport resistance and rapid performance degradation. To address this gas-liquid two-phase transport bottleneck, this study proposes a fully autonomous physical flow-remodeling strategy by constructing an asymmetric wettability gradient within the channels of the current collector. By depositing a hierarchical micro-nano superhydrophobic network on the membrane electrode assembly (MEA) side while maintaining weak hydrophobicity on the air-breathing side, an outward Young-Laplace capillary pumping force is spontaneously induced to autonomously expel liquid water in response to localized current loads. Experimental results demonstrate that this self-adaptive, directional capillary driving mechanism effectively unblocks the cathodic oxygen transport network without any parasitic power consumption. Under optimal feed concentration, the peak power density of the gradient configuration is enhanced by over 41% compared to the pristine substrate and 19% over the best-performing uniform treatment (PTFE). Furthermore, during a constant-current discharge test, this configuration eliminates potential oscillations caused by the periodic accumulation of water plugs, significantly retarding the physical degradation of interfacial components. The self-adaptive gas-liquid separation mechanism established in this study breaks the inherent engineering trade-off between passive drainage and Ohmic loss, providing a theoretical paradigm for the flow field structural design of next-generation highly efficient, fully self-sustained self-driven miniature energy systems.

To overcome the dual challenges of short endurance and poor environmental adaptability faced by portable mobile devices, this study proposes a dead-ended anode and cathode (DEAC), air-cooled proton exchange membrane fuel cell (PEMFC) power system based on online hydrolysis hydrogen generation. By integrating solid sodium borohydride hydrolysis hydrogen generation technology with a DEAC mode PEMFC, the power system constructs an internal "water-hydrogen-electricity" cycle, enabling the closed-loop utilization of reaction products. The cycle significantly enhances the system's energy density and liberates the system from dependence on external air. An artificial neural network-driven surrogate model is developed based on system simulation data. This model is coupled with a multi‑objective genetic algorithm to synergistically optimize key operating parameters: current density, temperature, purge duration, and purge interval. This multi-objective optimization framework is designed to simultaneously optimize three conflicting targets: electrochemical performance, water recovery, and oxygen utilization. Under the resulting optimal conditions, the proposed system outperforms traditional open‑cathode PEMFCs in dynamic voltage output, and its electrical efficiency is approximately 24.7% higher than that of traditional systems. Furthermore, in fixed‑endurance scenarios, the proposed system achieves a 66.55% higher gravimetric energy density than conventional high‑pressure hydrogen storage. This work provides theoretical and methodological support for developing next‑generation portable hydrogen power systems with high energy density and broad environmental adaptability.

The performance of CO2 electrolyzers is significantly affected by water transport through the anion exchange membrane (AEM). However, the role of membrane pretreatment in governing water transport behavior has seldom been investigated, and a standard pretreatment protocol remains absent. Therefore, we investigate the impact of the pretreatment protocol on CO2 electrolyzer performance in this work. We found that for two widely used commercial AEMs, the choice of pretreatment protocol exerts a profound influence on both performance and durability. In I-V polarization tests, the KOH-pretreated quaternary ammonium poly(N-methyl-piperidine-co-p-terphenyl) (QAPPT) membrane exhibited a Faradaic efficiency for CO product (FECO) of 81% at 500 mA cm−2, representing relative enhancements of 27% and 53% compared to K2CO3- and KHCO3-pretreated membranes, respectively. However, during durability tests for 50 h, the K2CO3-pretreated membrane achieved a stable FECO of 79%, a 16% relative improvement over the KOH-pretreated membrane. Furthermore, even though both were theoretically in the HCO3− form, the as-received poly(aryl piperidinium) (PiperION) membrane and the KHCO3-pretreated membrane displayed a distinct discrepancy in electrolyzer performance. This stability discrepancy is attributed to the water transport behavior across the AEM, which is determined by the pretreatment-induced membrane microphase separation morphology rather than the anion form, as evidenced by anode product analysis, attenuated total reflection infrared (ATR-IR), and atomic force microscopy (AFM) characterizations. Based on these findings, we propose a baseline pretreatment protocol to alleviate performance artifacts and improve cross-study comparability for similar AEM systems.

metal-organic frameworks (mofs) have emerged as promising platforms for photocatalytic co2 reduction owing to their modular architectures, well-defined active sites, and tunable photoelectronic properties. their structural versatility enables precise regulation of catalytic processes across multiple length scales, providing opportunities for the rational design of efficient photocatalysts. in this review, we summarize recent advances in mof-based systems for photocatalytic CO2 reduction to CO through a multiscale design framework spanning molecular, atomic, and interfacial levels. at the molecular level, ligand engineering modulates light harvesting, electronic structures, and catalytic microenvironments through strategies including (i) electronic modulation via electron-rich ligands, (ii) engineering of secondary coordination environments, (iii) ligand functionalization for adsorption and electronic regulation, and (iv) integration of photoactive or molecular catalytic units. at the atomic level, regulation of metal nodes governs the electronic structure and coordination environment of catalytic sites, with key approaches including (i) electronic structure and coordination engineering, (ii) construction of single-atom active sites, (iii) bimetallic cooperative systems, and (iv) multinuclear metal cluster nodes. at the interfacial level, heterostructure engineering-such as mof/cof and mof/semiconductor heterojunctions, facilitating efficient charge separation and carrier migration. these multiscale strategies highlight the importance of synergistically regulating light absorption, charge transfer, and catalytic reaction pathways. finally, we address the major challenges facing mof-based photocatalytic systems, particularly the dynamic evolution of active sites, catalyst stability, and the complexity of practical reaction environments, and we outline potential directions for future research. this review provides a unified framework and guiding principles for the development of efficient and sustainable mof photocatalysts for co2 reduction.

The traditional optimization of solid oxide fuel cell (SOFC) gas channel is largely heuristic, making it difficult to achieve optimal, inverse, and multi-objective optimization. Because traditional optimization approaches based on experience forward iterations are both time-consuming and economically inefficient. To address this limitation, this work proposed the multi-objective topology optimization method for SOFC flow channel design. This multi-objective topology optimization considered both minimum fluid dissipation and maximum current density, aiming to find a balance between these two objective functions. Besides, this work developed the progressive inheritance solution strategy to successfully solve the topology optimization model for the reaction flow in porous media. By comparing the topology optimization channel with the traditional straight channel, it can be found that, the pressure drops of the topologically optimized structure decreased by 39.8%. The topologically optimized channel can achieve a 10.3% increase in current density under similar channel widths and equal pressure drops. Previous studies have shown that the current densities of cells with profiled channels is merely 3.3% higher than that of conventional straight-flow channels. The comparison results show that the topology optimization method can obtain novel SOFC flow channel structure with superior performance. This work provides a new perspective and method for realizing optimal, reversible and multi-objective optimization design for SOFC flow channel.

Conventional cooling-type photovoltaic/thermal-humidification-dehumidification (PV/T-HDH) desalination systems are limited by PV overheating owing to full-spectrum solar absorption, mismatch between low-grade waste heat and HDH energy requirements, and low thermal recovery efficiency in single-stage configurations. To overcome these challenges, this study proposes a novel three-stage concentrated photovoltaic/thermalhumidification-dehumidification (CPV/T-HDH) seawater desalination system integrated with spectral beam filter (SBF) technology. The proposed system enables full-spectrum cascade utilization of solar energy through the coupling of spectral splitting and three-stage thermal energy recovery. A comprehensive modeling framework was developed by integrating optical ray tracing, thermodynamic analysis of the CPV/T subsystem, and a threestage HDH model with closed-air and open-water circulation. The effects of key external factors (solar irradiance and tracking accuracy) and operating parameters (saline water flow rate, air flow rate, and extraction rate) were systematically investigated. In addition, the operational feasibility of the system in tropical coastal regions was assessed using hourly solar irradiance data from Sanya, China, and a two-stage flow regulation strategy was proposed to improve operational stability. Results show that the designed SBF achieves an average transmittance of 90.56% in the 380-1100 nm band and a reflectance of 97.23% in the 1100-2500 nm band. Under optimal operating conditions, the system achieves a freshwater production rate of 2.3 g/s and a gain output ratio (GOR) of 3.7. These findings demonstrate the potential of the proposed system for distributed solar-driven desalination in off-grid island communities. It should be noted that the present analysis is based on an idealized steady-state model that neglects parasitic power consumption, pressure losses, and ambient heat losses. Consequently, the reported results represent an upper-bound performance benchmark, while actual system performance under transient real-world operating conditions is expected to be lower.

As carbon-free energy carrier, combustion of ammonia suffers from low burning rates, poor flame stability, and excessive nitrogen oxide (NOx) emissions. Although blending with hydrocarbon fuels such as methane alleviates some drawbacks, NOx formation remains a critical barrier. To address these challenges, we propose a hybrid framework combining reactive force field molecular dynamics (ReaxFF-MD) simulations with machine learning (ML). MD simulations at 2000-3000 K were performed for ammonia-methane blended combustion with 0-10% addition of ethanol or methanol. Adding alcohols suppressed the NOx formation by altering charge redistributions and redirecting nitrogen intermediates into stabilising pathways. Particularly at 3000 K, 10% ethanol and methanol reduced NOx by ∼39.5% and ∼30.1%, respectively. Both chemical and physical descriptors derived from MD were used to train ML models and successfully predicted NOx trends at intermediate compositions (2%, 7%, 12%) with <5% error for ethanol-rich mixtures, though predictions beyond 12% require further validation. This framework reduces reliance on costly simulations while providing mechanistic insights and predictive capability of designing alternative fuels.

Methanol is central to the decarbonisation of chemicals and fuels, yet current production is almost entirely reliant on fossil syngas. This review contrasts mature thermocatalytic routes with three emerging green pathways that incorporate electrolysers: 1). one-step direct electrochemical reduction of CO2 to methanol, 2). two-step schemes in which CO2 is hydrogenated using electrolytic hydrogen, and 3). three-step syngas-based system design in which CO2 is first converted to CO with co-produced H-2, then supplemented with electrolytic H-2 for conventional methanol synthesis. Published data are reconciled consistently across technology readiness, energy and carbon efficiency, levelised methanol cost, and life cycle impacts to identify robust trends rather than case-specific results. The analysis shows that conventional steam reforming remains the lowest-cost option at present, while green electrochemical routes can reduce cradle-to-gate greenhouse gas emissions by >80% at the expense of significantly higher production costs, dominated by electricity prices, electrolyser performance, and capacity factors. Direct electrochemical pathways are at a low level of technological readiness but offer the prospect of compact, modular plants that avoid intermediate hydrogen handling. In contrast, the two- and three-step concepts are closer to deployment but incur the energy penalties associated with separate hydrogen generation and CO2 capture. By integrating techno-economic, life-cycle, and scale-up considerations, the review delineates the operating windows, renewable energy prices, and methanol premiums required for economic competitiveness. It highlights research priorities in catalyst durability, large-area stack design, system integration, and policy support that are most likely to close the remaining performance and cost gaps.

Deep eutectic solvents (DESs) are promising electrolyte media for solar redox flow batteries, but their high viscosity and sluggish ion transport can limit redox-species diffusion, interfacial charge transfer, and photocharging performance. This study aimed to regulate a TEMPO/VCl3-based DES electrolyte by controlled water addition for a Yb,Er-doped TiO2–g-C3N4 photoanode solar redox flow battery. DES electrolytes containing 0, 5, 10, and 15 wt% added water were evaluated by physicochemical, electrochemical, and photoelectrochemical measurements, while full-cell tests compared pristine DES with the half-cell-selected 10 wt% electrolyte. While water incorporation systematically enhanced bulk redox-species transport, the optimal photoelectrochemical performance was achieved at 10 wt% water, rather than 15 wt%. Although the 15 wt% electrolyte exhibited the highest bulk diffusivity, the 10 wt% composition provided the most favorable balance between mass transport and interfacial charge transfer kinetics. The Raman spectra supported water-induced reorganization of the bulk DES hydrogen-bonding network. Full-cell tests confirmed that the 10 wt% water-containing electrolyte delivered higher and more stable photocharging responses than pristine DES over 20 cycles. These results indicate that moderate water regulation is an effective strategy for improving DES-based solar redox flow batteries.