ABSTRACT Developing efficient and durable Fe‐based electrocatalysts for the hydrogen evolution reaction (HER) across a broad pH range remains challenging because of sluggish interfacial charge transfer, inefficient water activation, limited active‐site accessibility, and insufficient structural stability. Herein, hierarchical porous S‐ FeS 2 /Fe 3 O 4 ‐CNT microspheres are constructed to integrate FeS 2 /Fe 3 O 4 heterointerfaces, interconnected carbon nanotube networks, and penetrative mass‐transport channels. Spectroscopic characterization, operando Raman analysis, and density functional theory calculations reveal that interfacial electronic redistribution at the FeS 2 /Fe 3 O 4 heterojunction facilitates water adsorption and dissociation while optimizing H * adsorption energetics. The CNT framework provides continuous electron‐transport pathways, whereas three‐dimensional tomography and permeability simulations demonstrate that accessible heterointerfaces are distributed throughout the microspheres and connected pores promote electrolyte transport to the internal active sites. Consequently, S‐FeS 2 /Fe 3 O 4 ‐CNTs exhibit competitive HER activity across acidic, alkaline, and neutral seawater, requiring overpotentials of 273.52, 82.97, and 248.04 mV, respectively, to reach 10 mA cm −2 , together with long‐term operational stability. Moreover, the S‐FeS 2 /Fe 3 O 4 ‐CNTs||RuO 2 electrolyzer delivers lower cell voltages than the Pt/C||RuO 2 benchmark under identical seawater electrolysis conditions. This work establishes a multiscale design strategy for earth‐abundant electrocatalysts by coupling interfacial electronic regulation, conductive‐network construction, active‐site accessibility, and mass‐transport engineering.

Anaerobic digestion of sewage sludge is a cornerstone technology for energy recovery, yet the CO2-rich biogas stream constrains deep carbon recovery. Here, we developed a coupled microbial electrosynthesis (MES)-chain elongation platform as a tunable post-treatment strategy to simultaneously upgrade biomethane (bio-CH4) and valorize CO2 into medium-chain carboxylates (MCCAs). Using defined synthetic matrices to systematically isolate metabolic drivers, operation revealed a kinetic transition from electron-supply limitation to mass-transfer limitation (kLa) beyond 3.0 V. An operating window at 3.0 V with 260 mmol L-1 ethanol balanced these constraints, delivering 95.0 % CH4 and 36.3 mmol L-1 MCCAs. Thermodynamic analysis and 16S rRNA profiling support a push and pull metabolic framework, where cathodic H2 pushes homoacetogenesis while ethanol-driven chain elongation pulls carbon toward MCCAs. Techno-economic analysis suggested a positive operating margin (benefit-to-cost ratio = 1.85), with sensitivity analysis confirming that the high value of MCCAs provides an economic buffer against downstream separation costs. Life cycle assessment further indicated that this operating window minimized cradle-to-gate impacts when bio-CH4 upgrading and MCCAs valorization were assessed jointly. These findings highlight the potential of this electro-biological strategy to advance water resource recovery facility carbon management by offering a tunable approach to balance energy recovery and chemical production.

The widespread commercialization of proton exchange membrane fuel cells (PEMFCs) is critically hindered by the lack of catalysts that are simultaneously active and durable for the oxygen reduction reaction (ORR). Herein, we report a robust electrospinning strategy to the synthesis of ultrafine Pt3Co intermetallic nanoparticles (2.6 nm), which are spatially confined within hierarchically porous Co-N-doped carbon nanofibers. The engineered architecture yields superior ORR performance, with a half-wave potential (E1/2) of 0.926 V and a mass activity of 0.63 A mgPt-1, which represents a threefold improvement over commercial Pt/C. Crucially, durability assessments reveal a negligible loss of 8 mV in an E1/2 after 30000 cycles, significantly outperforming the 20 mV degradation observed for Pt/C. A membrane electrode assembly incorporating the Pt3Co-CoNC cathode achieves a peak power density of 1.54 W cm-2 and retains 85% of its performance after accelerated durability testing. This work demonstrates that architectural confinement is a robust and effective strategy for designing catalysts that simultaneously achieve high activity and long-term stability, paving the way for advanced fuel cell applications.

This study assessed a CA. We explored its effects on fermentation characteristics, aerobic stability and microbial communities of HMC at 35°C and 5°C. Two treatments were set up: CON and CA group. HMC silage was fermented for 28 days at either 35°C or 5°C. All silages then received a 7-day aerobic exposure. High-throughput sequencing was performed to analyze microbial communities in this stage. CA produced positive effects under both temperatures. It raised lactic acid and CP levels, reduced pH, NH₃-N and NDF. CA suppressed yeasts and enterobacteria, and greatly improved aerobic stability. Storage temperature was the main factor shaping microbial community composition. CA further optimized the community structure of HMC silage. At 35°C, CA completely removed spoilage yeast Nakaseomyces glabratus. It enriched heterolactic strain Levilactobacillus brevis and beneficial Aspergillus spp. At 5°C, CA inhibited cold-resistant spoilage microbes. Beneficial Latilactobacillus curvatus accumulated, while cyanobacteria growth was restrained. Metabolic pathway analysis showed the regulatory function of CA. It upregulated lactic acid synthesis pathways and downregulated pathways related to protein hydrolysis and silage spoilage. In summary, CA reshapes microbial communities and metabolic profiles of HMC silage. It restrains silage deterioration under two storage temperatures. This additive is suitable for HMC preservation across different temperatures.

The durability of proton exchange membrane fuel cells under start-up/shutdown (SUSD) and dynamic load cycling is constrained by a trade-off between carbon support corrosion and Pt ripening. Herein, we report a nitrogen-modified graphitized carbon (N-GC) support mitigating both degradation pathways simultaneously. Graphitization of Ketjenblack EC-300J (EC300) yields graphitized carbon (GC) with a highly ordered framework, while ultralow nitrogen incorporation introduces electron modulation at the metal-support interface. This strengthens metal-support interactions, suppressing Pt nanoparticle migration and coarsening during dynamic load cycling and maintaining corrosion resistance under SUSD. Pt/N-GC exhibits exceptional robustness following U.S. Department of Energy (DOE)-specified accelerated stress tests (ASTs). During carbon support-focused AST, Pt/N-GC limits voltage loss to 27 mV at 1.5 A cm(-2) and retains 61.88% of its initial electrochemical surface area (ECSA), outperforming Pt/EC300 (>140 mV, 23.98%) and meeting DOE targets. Under catalyst-focused AST, Pt/N-GC limits voltage loss to 42 mV at 0.8 A cm(-2) and shows superior ECSA retention of 53.22% compared to Pt/GC (60 mV, 36.21%). In a 100 W air-cooled stack under simulated two-wheeler cycles, Pt/N-GC delivers a 237.2 h lifetime, exceeding both Pt/GC (226.2 h) and Pt/EC300 (143.9 h). This work establishes a support-design strategy that reconciles carbon corrosion and Pt ripening, validating durability from single-cell to engineered stacks.

Atomically dispersed catalysts based on 3d metals have been extensively explored in the catalytic field, but stabilizing 4d and 5d metals like Ru, Pd, and Pt as single atoms remains a challenge due to their high cohesive energies. Herein, we develop a hydrogen-embrittlement-inspired strategy that leverages H2 permeation to weaken metal-metal cohesion in 4d/5d metal clusters during high-temperature synthesis. Hydrogen diffuses into the clusters, driving their dissociation into individual atoms, which are subsequently stabilized by nitrogen dopants in carbon supports, resulting in the formation of stable M-N4 single-atom sites. Taking Ru as a model system, ex-situ microscopy and spectroscopy offer definitive evidence that hydrogen permeation disrupts Ru-Ru bonding interactions, facilitating the conversion of Ru clusters into isolated RuN4 sites during the H2-assisted thermal activation process. Consequently, the prepared NC-Ru-950 catalyst achieves satisfactory activity and stability for acidic oxygen reduction and proton exchange membrane fuel cells. This work introduces a robust and universal strategy for stabilizing 4d and 5d transition metals as single-atom catalysts, offering a promising route to develop high-performance electrocatalysts.

Lithium plating during low-temperature charging critically limits the safety, durability, and reliability of lithiumion batteries, posing a major obstacle to their large-scale deployment in electric vehicles and energy storage systems in cold regions. This study integrates modeling and experimental approaches to investigate lithium plating in cylindrical LiCoO2/graphite batteries under subzero charging conditions (-10 degrees C to -30 degrees C). By incorporating a lithium-plating side reaction into a simplified electrochemical-thermal model, the onset and progression of plating are predicted based on overpotential evolution. A combination of non-destructive (dV/dQ and Coulombic efficiency) and destructive (SEM and ICP) methods validates the model's accuracy and quantifies the extent of lithium deposition. Model-based strategy analysis further evaluates two mitigation routes-cell preheating and adjustment of the negative-to-positive (N/P) capacity ratio. The results demonstrate that preheating and N/P optimization both reduce lithium plating, but preheating is markedly more effective: at -10 degrees C and 1.0C, raising the N/P ratio from 1.08 to 1.2 decreases plating time from 90.3% to 43.0%, whereas preheating to 10 degrees C lowers it to 10.1%. The proposed framework accurately predicts lithium-plating behavior and provides practical guidance for safe, energy-efficient battery operation under extreme conditions. These findings contribute to the sustainable and secure utilization of electrochemical energy storage technologies in a lowcarbon energy future.

Rechargeable zinc-copper (Zn-Cu) batteries exhibit significant potential in energy storage systems due to their high capacity, cost-effectiveness, and environmental friendliness. However, capacity degradation occurs due to severe Cu dissolution and Zn side reactions during charging/discharging cycles. Herein, we propose incorporating covalent organic framework layers containing naphthalenediimide and triphenylamine units (NTCOF) onto the surfaces of both the Cu cathode and the Zn@Cu anode, thereby constructing an advanced Zn-Cu battery. On the cathode side, NTCOF promotes the formation of zinc hydroxide sulfate (ZHS) by creating a localized alkaline environment. This enhances the reversibility of Cu and Cu2O transitions while preventing Cu dissolution. On the anode side, NTCOF acts as a stable protective layer that inhibits side reactions and provides favorable ionic transport pathways, thereby effectively suppressing dendrite growth. Consequently, the NTCOF+Zn@Cu symmetric battery exhibits exceptional cycling stability for over 500 h, maintaining a low polarization voltage of 75 mV at 0.2 mA cm-2. The NTCOF+Cu//NTCOF+Zn@Cu full battery demonstrates a stable discharge voltage plateau at 0.9 V and maintains a high-capacity retention of 90.4% over 400 cycles. This work presents an effective approach to simultaneously stabilize both the Cu and Zn electrodes using a single material, thereby enhancing their performance in energy storage applications.

In the field of oxygen electrocatalysis, interface engineering was regarded as a pivotal technique for developing cost-effective catalysts with well-defined structures and enhanced stability. Here, varying ratios of ZIF-8/67 were employed to synthesize an N-doped C-coated Co3ZnC/Co heterojunction structure (Co3ZnC/Co@NC). The formation of heterojunctions facilitated the transfer of charge from Co nanoparticles to Co3ZnC, altering the surface structure to accelerate the cleavage of the O-O bond in the *OOH intermediate. The optimized Co3ZnC/Co@NC catalyst exhibited a half-wave potential (E1/2) of 0.763 V in PBS electrolyte, which was 77 mV more positive than that of commercial Pt/C (0.686 V). Meanwhile, Co3ZnC/Co@NC displayed excellent methanol tolerance (86.27%) and operational stability, with a mere 3 mV reduction after 5000 cyclic voltammetry (CV) cycles. It was noteworthy that the material exhibits high performance as an air cathode in microbial fuel cells (MFCs), displaying high power density (1.28 W m-2) and outstanding stability (60 days). This work presented novel insights into the preparation of durable ORR catalysts for AC-MFC applications.

Photothermoelectric (PTE) detectors, which operate relying on the photothermal and thermoelectric effects, can overcome the intrinsic spectral limitations originated from material bandgaps in photon-driven detectors. However, the hardware implementation of devices leveraging light-heat-electricity cascade conversion remains challenging. Here, we report the construction of MoS2/SiO2 semiconductor/dielectric superlattice films with features of nanoscale layer definition, high crystalline quality, and wafer-level manufacturability. Benefiting from the interlayer interference and electric-field localization, the MoS2/SiO2 superlattices exhibit remarkably enhanced optical absorption across the visible to infrared spectrum, which enables the high photothermal energy conversion efficiency and substantial temperature rise exceeding 70 K. The PTE detection, implemented by integrating superlattice absorber with a microscale thermoelectric (μ-TE) platform based on Bi2Te3/Sb2Te3 P-N pairs, enables high-efficiency photodetection through strong light-matter interaction and optimized thermal management. The self-powered detector can stably operate over a broad-spectrum range extending to 1550 nm, demonstrating a temporal response (∼16 ms), high responsivity (17.6 V W-1), and detectivity exceeding 1.20 × 1010 Jones, comparable to state-of-the-art broadband PTE detectors. Array-level integration facilitates high-fidelity 1550 nm imaging with a 256-pixel prototype, while wafer-scale fabrication of over 3000 units on a 2-inch substrate confirms excellent uniformity, reproducibility and scalability, unlocking the potential for advanced large-scale imaging applications.

Resistive elements consume Joule heat in the electric circuits, while the capacitors and inductors can save field energy, which is crucial for further energy exchange and maintaining channel currents. Incorporation of specific electric components into the branch circuits of an electric circuit can adjust the energy conversion between capacitive and inductive elements, and continuous energy flow supports continuous oscillations in the electric circuits. In this article, a neural circuit is proposed by connecting a capacitor, inductor and ideal Josephson junction in three paralleled branch circuits, and then two excited neural circuits are coupled via a Josephson junction for maintaining synchronous firing. The energy function is calculated and proved from physical aspect, and coherence resonance is induced under noisy disturbance. The incorporation of Josephson junction just introduces nonlinear modulation on the channel current across the capacitor and inductor, and the neural circuit is excited to present rich firing patterns under external stimulus. The neural circuit is simple but it shows some advantages than most of the known neural circuit because lower Joule heat is consumed in absence of resistor.

ABSTRACT The conventional triple‐phase interface (TPI) in proton exchange membrane fuel cells (PEMFCs) relies on dense ionomer encapsulation to conduct protons, but this inevitably poisons platinum (Pt) catalysts and blocks oxygen transport. Here, we replace this closed architecture with an open, scaffolded TPI constructed by introducing sulfonated covalent organic framework (SCOF) nanosheets as a rigid, porous scaffold within the Pt‐ionomer matrix. Unlike the conventional ionomer film that intimately coats Pt, the SCOF scaffold acts as a physical spacer that suppresses direct ionomer adsorption, while its ordered nanochannels serve as dedicated proton highways and its intrinsic porosity facilitates oxygen diffusion. This open architecture decouples the competing requirements of proton conduction and catalyst accessibility, concurrently mitigating Pt poisoning and enhancing mass transport. Accordingly, the engineered cathode exhibits substantially reduced sulfonate‐group coverage and improved proton conduction, alongside a significantly decreased pressure‐independent oxygen transport resistance. At an ultralow Pt loading of 0.05 mg Pt cm −2 , the system delivers a peak power density of 0.86 W cm −2 under H 2 /air, representing a 24% improvement over the conventional counterpart. This work establishes an open‐scaffold design paradigm that fundamentally breaks away from the traditional ionomer‐encapsulated TPI, offering a generalizable route to high‐performance, low‐Pt‐loading PEMFCs.

Iron and nitrogen co-doped carbon material (Fe-N-C) catalysts hold great promise as cost-effective alternatives to platinum but are fundamentally constrained in catalytic performance by linear scaling relationships among intermediate adsorption energies. Herein, we report a Ga-mediated dynamic charge storage strategy to precisely regulate the Lewis acidity of Fe centers, dynamically enabling *O2 activation and *OH desorption. Ga atoms, characterized by moderate high occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap, establish an electron-transfer channel with Fe, acting as a charge reservoir to neutralize intermediates- triggered charge polarization of Fe sites. This flexible electron regulation allows Fe centers to switch between weak Lewis acid sites with enhanced electron-donating ability and strong Lewis acid sites with reduced electron-donating ability, thereby overcoming the conventional adsorption-desorption trade-off and achieving accelerated reaction kinetics. The as-synthesized catalyst demonstrates outstanding electrocatalytic performance, retaining 92.4% of its current density after 500 h in acidic media. It delivers current densities of 147.09 mA cm-2 @0.8 ViR-free and 670.31 mA cm-2 @0.675 ViR-free, significantly exceeding United States Department of Energy (U.S.DOE) targets by similar to 1.5- and similar to 1.3-fold, and achieving a peak power density of 0.78 W cm-2 at H2-air fuel cells. This work deciphers dynamic charge storage as a conceptual framework for decoupling adsorption energetics and overcoming linear scaling relationships in multi-step reactions.

Correction for ‘Dual modulation of electronic and crystalline structures in PtCo alloys for high-performance fuel cells’ by Si Lin et al. , Green Chem. , 2026, 28 , 9438–9445, https://doi.org/10.1039/d6gc01607c.

Sodium-ion batteries have gained increasing attention due to their advantages, such as abundant raw material reserves and low costs. As a new battery system, the electrochemical and thermal properties of its electrodes and the entire cell, as well as their variations over both short and long periods, still contain many unknowns. Similar to lithium-ion batteries, sodium-ion batteries also experience performance degradation over time. To ensure the long-term, safe, and stable operation of batteries in service, health and safety management are necessary. Modeling and simulation can accurately predict the multi-scale behavior of battery characteristics, and thus, serve as an important theoretical foundation for battery management. Therefore, modeling and simulation of sodium-ion batteries are crucial.This paper first considers the temperature changes during battery operation and, based on the fundamental working principles of the battery, develops an electrochemical-thermal coupling model by retaining the main physical processes while ignoring secondary processes. Then, to identify and optimize the highly sensitive model parameters, a weighted particle swarm optimization algorithm is used, ensuring that the parameters are valid and reasonable. Finally, to address the differences among individual cells and the uncertainties in the measured data, machine learning algorithms are introduced into battery mechanism modeling. Specifically, a dynamic residual forest model (DRF) for sodium-ion batteries is constructed using random forest and incremental learning algorithms, which iteratively learns from errors to reduce simulation errors in voltage and temperature.In the DRF model, the random forest algorithm initially performs a preliminary prediction, followed by the use of incremental learning algorithms to correct prediction errors, thereby continuously optimizing the prediction accuracy of battery terminal voltage and temperature. The key feature of this model is its ability to handle real-time data streams, adapt to dynamic changes in data distribution, and reduce the need for retraining on new data, all while maintaining high prediction accuracy. This allows the model to simulate the complex operating conditions during the actual use of the battery. By using the DRF model to correct the outputs of the electrochemical-thermal coupling model, the final predictions of terminal voltage and temperature are obtained. Validation results show that the hybrid model provides better predictions of terminal voltage and temperature for different individual cells with higher accuracy.

Zinc sulfide (ZnS) has emerged as a promising anode material for sodium-ion batteries (SIBs) due to its high theoretical capacity and cost-effectiveness. However, the intrinsically low conductivity of ZnS leads to poor rate performance, while significant volume variations during charge/discharge cycles cause rapid capacity decay. In this study, a poly(vinylpyrrolidone) (PVP)-assisted synthesis of ZnS hollow nanoparticle has been demonstrated. The addition of PVP would induce lattice expansion, thus decrease the formation energy of sulfur vacancies in the material, giving rise to sulfur-deficient hollow ZnS (H-ZnS1-x). The hollow architecture effectively accommodates volume expansion, while the introduced sulfur vacancies significantly improve the conductivity of HZnS1-x, achieving remarkable kinetic performance, maintaining 454 mAh g- 1 at 5 A g- 1 over 1970 cycles. Furthermore, high capacities of 621 mAh g- 1 and 559 mAh g- 1 have been delivered at 1 A g- 1 and 2 A g- 1, respectively, surpassing many reported sulfur-based anodes.

Herein, we report the rational balancing of hydrogen adsorption/desorption dynamics by employing a synergistic Co and V dual-doping strategy to enhance the hydrogen evolution reaction (HER) performance of MoS2. The Co and V dual-doping MoS2 (Co, V-MoS2) was successfully synthesized in situ on carbon cloth (CC) substrates via one-pot hydrothermal route, and the XRD, Raman, TEM, XPS, EDS and ICP characterizations validate the substitutional doping of Co and V into the MoS2 lattice. The optimized Co, V-MoS2/CC exhibits significantly enhanced HER performance, requiring only 220.0 mV overpotential to reach-100 mA/cm2 with a 61.9 mV/dec Tafel slope, surpassing both the Co/V mono-doped MoS2/CC and undoped MoS2/CC. Moreover, the polarization curve of Co, V-MoS2/CC exhibits a negligible potential decay of 8.4 mV at 50 mA/cm2 after 3000 repeated cyclic voltammogram cycles, demonstrating superior durability. DFT calculations reveal that synergistic Co and V dual doping in MoS2 can balance the hydrogen adsorption/desorption kinetics at S sites near dopants, thereby optimizing the hydrogen adsorption free energy and accelerating the charge transfer, thus achieving far super HER performance. Our balancing hydrogen adsorption/desorption strategy enabled by Co, V dual-doping provides a promising avenue for improving the HER performance of TMDs-based electrocatalysts.

Lithium-ion batteries experience complex degradation governed by multiple interacting mechanisms, posing challenges for real-time aging-mode identification. To overcome this issue, we propose a mechanism-data fusion framework that couples an extended single-particle model (SPM) with a multi-task learning (MTL) architecture. The electrochemical model explicitly incorporates solid-electrolyte interphase (SEI) growth and lithium plating side reactions, and employs a multi-swarm cooperative adaptive particle swarm optimization (MSCPSO) algorithm to achieve accurate parameter identification across different temperatures and C-rates. A three-branch MTL framework is then constructed to jointly predict key degradation indicators-including the loss of lithium inventory (LLI), loss of active material (LAM), SEI and plating layer thicknesses, and plating-induced capacity loss-while also classifying the occurrence of lithium plating. Experimental validation demonstrates strong physical consistency and robustness of the proposed framework under various operating conditions. Among the tested architectures, the MT-LSTM model exhibits the best overall performance, achieving a lithium-plating detection accuracy of 99.63 % and an R2 exceeding 0.97 for multi-target regression tasks. This unified and scalable framework enables quantitative identification of multiple degradation mechanisms directly from charge-discharge data, offering a practical, real-time, and physically interpretable tool for next-generation battery health management systems.

Chemically self-charging aqueous batteries are a promising class of off-grid energy storage systems capable of delivering sustained electrical power. However, conventional O2 self-charging batteries often suffer from long charging times (typically exceeding 10 h) and limited capacity, which severely hinder their practical applicability. Herein, we report an ultrafast H2O2-driven self-charging aqueous Zn/1,4,5,8-naphthalenetetracarboxylic dianhydride (NTDA) battery. Benefiting from the high redox potential difference and strong chemical reactivity between H2O2 and the discharged NTDA, the system can simultaneously achieve the rapid conversion of the chemical energy of H2O2 into electrical energy and the efficient storage of the generated power. Notably, the incorporation of Mn2+ as an electrolyte additive effectively lowers the reaction energy barriers for the H2O2 self-charging process, thereby improving the overall reaction kinetics. As a result, the fully discharged Zn/NTDA battery can spontaneously recharge to 1.32 V within 60 s after H2O2 introduction. It subsequently delivers a discharge-specific capacity of 430.1 mAh g-1 at 0.2 A g-1, with a stable discharge plateau at 0.8 V. Importantly, these self-charging batteries support multiple charging modes, and they exhibit stable self-charging capability as well as consistent galvanostatic discharge performance even under repeated mechanical bending, demonstrating their potential for practical applications. This work presents an effective strategy for designing chemically self-charging batteries with rapid charging capabilities and high specific capacities.