Search Results (1,292)

Side-boss parallel channels can enhance reactant transport and water removal in proton exchange membrane fuel cells, but their local protrusions increase the forming difficulty of ultra-thin metallic bipolar plates. This study numerically investigates the single-step stamping formability of 0.1 mm SS304 bipolar plates using Dynaform. The effects of side-boss number, side-boss height, and punch speed were evaluated through thickness distribution, maximum thinning ratio, and forming-limit-diagram states. The results show that side-boss height is the dominant geometric factor. Increasing the height from 0 to 0.75 mm raises the maximum thinning ratio from 17.69% to 29.87% and shifts the critical deformation regions from the conventional channel bottom toward the side-boss roots, boss tops, transition fillets, and channel corners. The number of side-boss sets produces a non-monotonic thinning response, with maximum thinning ratios ranging from 19.54% to 27.76% for the modified configurations. Punch speeds of 200, 500, and 800 mm/s yield comparable thinning levels of 24.60%, 23.09%, and 23.16%, respectively, whereas the value increases to 26.30% at 1100 mm/s. Under the present forming conditions, these findings establish a quantitative relationship between side-boss geometry, material-flow restriction, and strain localization, and provide practical guidance for geometry selection and stamping-process design of metallic bipolar plates. Full article

Proton exchange membrane (PEM) electrolyzers and fuel cells could substantially increase demand for iridium (Ir) and platinum (Pt), two platinum-group metals (PGMs) with concentrated primary supply chains. This study evaluates secondary Ir and Pt supply from end-of-life PEM technologies using a scenario-based material-flow analysis for global and U.S. markets from 2020 to 2050. Annual metal demand is estimated from U.S. Department of Energy annual PEM manufactured-capacity inputs, which include new and replacement systems, and from catalyst loading rates. Secondary supply is estimated using distributed lifetimes, collection efficiency, technical recovery efficiency, recycling delay, loss accounting, remaining primary requirement, and surplus. Under the central practical case, recovered Ir supplies 16.9% of global and 3.8% of U.S. PEM electrolyzer Ir demand in 2050. Recovered PEM electrolyzer Pt supplies 32.2% of global and 7.3% of U.S. demand, while recovered PEM fuel-cell Pt supplies 75.1% of global and 51.2% of U.S. demand. Sensitivity and uncertainty results show that recovery outcomes depend strongly on collection performance, recycling delay, technical recovery, catalyst loading, and capacity-input assumptions. PEM recycling can reduce future primary PGM requirements, especially for Pt, but cannot eliminate primary Ir demand during rapid PEM electrolyzer scale-up. Full article

Hydrogen has emerged as a promising energy carrier for sustainable, low-carbon energy systems because of its high energy density and compatibility with fuel cell technologies. This study presents a comprehensive investigation of hydrogen production through the integration of steam methane reforming (SMR), solar photovoltaic (PV) power generation, proton exchange membrane (PEM) electrolysis, hydrogen storage, and PEM fuel cells. A three-dimensional computational fluid dynamics (CFD) model was developed to analyze fluid flow, heat transfer, species transport, and chemical reactions within a catalytic steam methane reformer. The simulation predicted a methane conversion of 94.71%, a hydrogen yield of 3.75 mol H₂/mol CH₄, and an overall efficiency of 63.35%, indicating highly efficient hydrogen production. Sensitivity analyses identify catalyst temperature, inlet temperature, and residence time as the dominant parameters affecting hydrogen yield. Integration with renewable energy systems demonstrated that a hybrid configuration consisting of a 120 kW PV array, a 50 kW PEM electrolyzer, a 6 kW PEM fuel cell, and 6–8 kg hydrogen storage can effectively support sustainable hydrogen production and auxiliary power demands. The proposed framework provides a practical pathway for integrating thermochemical and renewable hydrogen technologies into future energy applications worldwide. Full article

Electrochemical reactions in proton exchange membrane fuel cells (PEMFCs) predominantly occur within the membrane electrode assembly (MEA), dictating power output and lifetime. As a key functional component of the catalyst layer (CL), ionomer plays a decisive role in establishing effective three-phase boundaries, maintaining proton-conducting networks. While the impact of ionomer-to-carbon (I/C) ratio on MEA performance has been recognized, its coupled effect on durability remains underexplored. Herein, MEAs with I/C ratios ranging from 0.4 to 1.2 were fabricated, and the influence of ionomer content on performance and durability was systematically investigated through microstructural characterization, electrochemical measurement, and accelerated stress testing. Results reveal distinct trade-offs: insufficient ionomer impairs proton transport and durability, while excess ionomer hinders mass transport and electrochemical performance but helps maintain CL stability. Specifically, an I/C ratio of 1.2 exhibits the highest durability but the lowest performance. An I/C ratio of 0.8 achieves the optimal peak power density (1156 mW cm^–2) while maintaining good durability, superior to lower I/C ratios. Balancing performance and durability, an I/C ratio of 0.8 emerges as the optimal choice. This work provides both experimental evidence and mechanistic insights into the influence of ionomer content in CL, offering guidance for the design of high-performance and durable PEMFCs. Full article

Hungarian legislation—TÉKA 280/2024 and ÉKM 9/2023, effective January 2025—requires hospitality properties to install operational EV charging infrastructure. This study develops a techno-economic scenario model assessing DC Fast Charging (DCFC) powered by formic acid (HCOOH)-based proton-exchange membrane (PEM) fuel cell microgrids as an alternative to conventional grid-tied AC charging in energy-constrained rural tourism destinations. Three containerized HCOOH-PEM configurations (100 kW, 500 kW, 1 MW) are modelled using published technical parameters and secondary market benchmarks, and results are interpreted through Porter’s competitive advantage theory and Ritchie and Crouch’s destination competitiveness framework. All reported values are simulation outputs derived from predefined assumptions rather than empirically validated findings. Under these assumptions, the DC-HCOOH configuration projects annual EBITDA of €72,946 per unit (284% above the modelled AC baseline) with a comparable simple payback period, while ancillary guest spending during DCFC dwell-time (‘Charge and Spend’) is projected at roughly 5.3 times the AC level. Sensitivity scenarios show that payback estimates are highly responsive to CAPEX scope and ancillary-margin assumptions. Findings offer a conceptual basis for destination managers, investors, and policymakers, while underscoring the need for empirical validation with primary operational data. Full article

Bio-inspired metaheuristic algorithms, which emulate natural predatory and evolutionary behaviors, play a crucial role in solving complex engineering problems, such as the accurate parameter extraction of proton exchange membrane fuel cells (PEMFCs). However, many existing optimization algorithms suffer from premature convergence, premature stagnation in local minima, and limited accuracy. Among these algorithms, the Osprey Optimization Algorithm (OOA) has shown promising performance. In this paper, an Enhanced Osprey Optimization Algorithm (EOOA), an improved variant of the conventional OOA, is proposed. The performance of the proposed algorithm is first evaluated using the CEC2022 benchmark functions. Subsequently, the EOOA is applied to the problem of PEMFC parameter extraction for two commercial stacks, namely NedStack PS6 and Ballard Mark V. The results demonstrate that the EOOA outperforms the original OOA and four other metaheuristic algorithms, ranking first in 11 out of 12 CEC2022 benchmark functions. Furthermore, the EOOA shows superior performance in PEMFC parameter identification compared to the OOA and other methods reported in the literature. Specifically, the proposed algorithm achieves a sum of squared errors (SSE) of 2.065 for the NedStack PS6 and 0.81 for the Ballard Mark V. These results indicate that the EOOA has strong potential for application to other optimization problems beyond PEMFC parameter extraction. Full article

To address the challenges of restricted renewable energy accommodation, high carbon emissions, and elevated operating costs in integrated energy systems (IES), this paper proposes a stochastic optimization scheduling method that incorporates the synergy between carbon–green certificate trading and the multi-use applications of hydrogen energy. First, an integrated “electricity–carbon–hydrogen–methanol” model is constructed, incorporating proton exchange membrane (PEM) electrolyzers (ELs), methanol synthesis reactors, hydrogen storage systems, and hydrogen fuel cells (HFCs). Second, a concentrating solar power (CSP) plant coupled with an electric heater (EH) is integrated based on an “electricity–heat–electricity” mechanism. Concurrently, a joint carbon emission trading (CET) and green certificate trading (GCT) mechanism is incorporated into a low-carbon economic dispatch model to minimize total operational costs. On this basis, Information Gap Decision Theory (IGDT) is applied to address source–load uncertainties via risk-averse (RAS) and opportunity-seeking (OSS) strategies. Simulation results demonstrate that the proposed strategy achieves full accommodation of renewable energy. The EH-coupled CSP plant increases thermal output by 4.96%, reducing system carbon emissions by 8.07% compared with the non-EH scenario and decreasing natural gas procurement costs by 14.1%. Furthermore, the joint CET-GCT mechanism overcomes single-market limitations, increasing carbon trading revenues by 298.01% and lowering total operating costs by 39.6% compared with uncoordinated mechanisms. Finally, under IGDT uncertainty analysis, the opportunity-seeking strategy further reduces operating costs by 9.5% compared with the risk-averse strategy, enhancing the system’s low-carbon economic performance and operational flexibility. From the perspective of sustainable development, this study provides a practical dispatch framework for regional integrated energy systems to balance energy security, low-carbon transition and economic cost, offering methodological support for advancing the sustainable transformation of multi-energy systems amid the dual-carbon drive. Full article

Proton exchange membrane fuel cells (PEMFCs) are critical parts of new-age green hydrogen energy systems where reactant distribution and water management determine performance and reliability. A three-dimensional, steady-state, and single-phase model of a self-humidified low-temperature PEMFC was developed in COMSOL Multiphysics to compare parallel, single-serpentine and double-serpentine bipolar plate flow fields under identical active area membrane electrode assembly, material properties and operating conditions, so that flow field geometry was the only variable. The model is verified via grid independence and validated in terms of published experimental polarization data with mean absolute deviation under 2%. At 0.1 relative humidity of the cathode inlet, the single-serpentine flow field provides 717 mA cm⁻² current density at 0.6 V and 595.7 mW cm⁻² peak power density in contrast to 582 mA cm⁻² and 492.3 mW cm⁻² for the double-serpentine and 577 mA cm⁻² and 463.2 mW cm⁻² for the parallel flow field. These two designs therefore behave almost identically in electrochemical terms but differ hydraulically; their peak channel pressure drops, being 3.8 and 0.8 kPa against 14 kPa for the single-serpentine design. Once pumping power is included, the single-serpentine design remains the best net power choice below an active area of approximately 54 cm². Full article

The rapid expansion of hydrogen technologies has intensified the demand for platinum group metals (PGMs), particularly platinum (Pt) and iridium (Ir). Proton exchange membrane fuel cells (PEMFCs) and proton exchange membrane water electrolyzers (PEMWEs) rely on PGMs and fluoropolymer membranes such as Nafion, generating increasing volumes of end-of-life (EoL) membrane electrode assemblies (MEAs). Conventional recycling routes are often energy-intensive, hazardous and limited in polymer recovery. In this study, a closed-loop hydrometallurgical recycling route is assessed through a life cycle assessment (LCA), supported by primary experimental data from optimized recycling trials. Mechanical delamination enabled separation of catalyst layers while preserving membranes, followed by a chlorine-based hydrometallurgical process operating under mild conditions. Leaching efficiencies exceeded 99% for Pt and 80% for Ir, demonstrating the feasibility of metal recovery. Two LCA models were developed: (i) a gate-to-gate recycling model for EoL MEAs and (ii) a cradle-to-gate manufacturing model comparing virgin and recycled Pt. Results showed that substituting virgin Pt with recycled Pt reduced the global warming potential of MEA manufacturing by up to 70%. The analysis also identified electricity demand and Nafion membrane waste as key environmental hotspots. Overall, the study highlights the potential of closed-loop recycling to enhance circularity in hydrogen technologies. Full article

Hydrogen-based technologies are widely considered promising pathways for decarbonizing power generation and industrial energy systems; however, their overall sustainability depends strongly on both production routes and conversion efficiencies. This study presents a comparative energy and exergy analysis of hydrogen-based decarbonization pathways under a consistent 1 MW net electrical output boundary, including natural gas combustion (S0), grey hydrogen combustion (S1), grey hydrogen fuel cell (S2), green hydrogen combustion (S3), and green hydrogen fuel cell (S4) systems. The results indicate that combustion-based pathways (S0, S1, and S3) exhibit relatively low energy efficiencies of approximately 30–40% and exergy efficiencies of 25–40%, accompanied by high exergy destruction levels generally exceeding 60%. In contrast, fuel cell-based configurations (S2 and S4) demonstrate improved conversion-stage thermodynamic performance, achieving energy efficiencies of 50–60% and exergy efficiencies of 45–65%, while reducing exergy destruction due to electrochemical conversion and lower irreversibilities. A detailed comparison shows that the natural gas reference system reaches an exergy efficiency of 33.7%, whereas the hydrogen fuel cell system achieves 46.5%, corresponding to approximately 42% lower exergy destruction and about 36% reduced fuel input. From an environmental perspective, the simplified carbon assessment indicates that natural gas combustion generates approximately 577 kg CO₂/h. Grey hydrogen pathways remain associated with substantial upstream emissions, generating approximately 857 kg CO₂/h for grey hydrogen combustion and 545 kg CO₂/h for grey hydrogen fuel cell operation under the 1 MW net electrical output basis. In contrast, green hydrogen-based pathways are assumed to have near-zero direct/upstream operational CO₂ emissions under renewable-powered production assumptions. Overall, the findings show that hydrogen use alone does not guarantee decarbonization; rather, both the hydrogen production route and the final conversion technology must be considered to achieve thermodynamically efficient and low-carbon power generation. Full article

Efficient thermal management is critical for proton exchange membrane fuel cells (PEMFCs). This study develops a bio-inspired active liquid cooling architecture to overcome the limitations of conventional flow channels, where convective heat transfer augmentation significantly increases pressure drop. The proposed configuration adheres to constructal theory and Murray’s law. A three-dimensional conjugate heat transfer model was formulated to evaluate the thermo-hydrodynamic performance against parallel and serpentine flow channels. Under identical conditions, the proposed configuration exhibits superior thermal uniformity and hydrodynamic behavior, alongside minimized parasitic pumping power. At an inlet Reynolds number (Re) of 400, this configuration stabilizes the average bipolar plate temperature at 349.63 K. It reduces the index of uniform temperature (IUT) to 1.49 K, representing a 52.8% thermal uniformity improvement over the parallel flow channel. Furthermore, at an inlet Re of 600, the overall pressure drop is restricted to 68.44 Pa, reducing the single-plate parasitic pumping power to 1.27 × 10⁻⁴ W, which represents reductions of 93.5% and 12.5% relative to the serpentine and parallel flow channels, respectively. This study provides an alternative architectural scheme for the design of active liquid cooling flow channels in PEMFCs. Full article

Proton exchange membrane fuel cells (PEMFCs) offer high efficiency and zero emissions, but durability remains a major barrier to commercialization. Degradation arises from coupled thermal, mechanical, and chemical stresses, yet these processes are often studied in isolation, reducing the accuracy of lifetime prediction. This paper systematically reviews PEMFC degradation, focusing on the coupling between thermal management failure and hydrogen crossover. Most importantly, it identifies a self-reinforcing thermal–hydrogen feedback in which localized overheating and permeated-hydrogen oxidation mutually amplify membrane defect propagation. Mitigation strategies spanning temperature control, hydrogen crossover suppression, intelligent prediction, and current challenges are then discussed. Mechanistically, thermal mismanagement promotes localized hot spots, while elevated temperature increases hydrogen diffusivity and accelerates defect growth, thereby sharply increasing crossover flux. Permeated hydrogen can be catalytically oxidized near defect sites, releasing additional heat and intensifying local membrane damage. Because the two stressors are coupled rather than independent, single-factor mitigation is insufficient; temperature control and hydrogen crossover suppression must be co-optimized. Future progress requires multiscale frameworks across scales, in situ multiphysics characterization, and artificial intelligence (AI)-driven control, moving from mechanistic understanding to engineering application. Full article

Accurate voltage degradation prediction is essential for health management and lifetime extension of proton exchange membrane fuel cell (PEMFC) systems. During long-term constant-current operation, stack voltage evolves nonlinearly and is influenced by coupled variations in temperature, pressure, flow rate, and humidity, while many deep learning-based models lack physical interpretability. This study proposes an interpretable Transformer-based framework for PEMFC voltage degradation prediction under constant-current operation. The framework integrates outlier correction, interpolation, Savitzky–Golay filtering, Z-score normalization, sliding-window reconstruction, Transformer-based prediction, and feature-ablation interpretation. Using multivariate sensor measurements and historical voltage as inputs, the Transformer was compared with RNN, LSTM, and GRU baselines under identical preprocessing and evaluation conditions. The models were evaluated chronologically by continuously applying the sliding-window model over the held-out final 20% of the aging sequence. The Transformer achieved the best performance, with MAE of 8.2 × 10⁻⁴, RMSE of 1.18 × 10⁻³, MAPE of 0.0256%, and R² of 0.9961. Compared with the second-best RNN model, it reduced MAE, RMSE, and MAPE by 9.89%, 7.81%, and 9.86%, respectively. Feature ablation showed that flow- and pressure-related variables contributed 50.08% and 26.78% of the total importance, respectively. Full article

The Zeta-Minimizer Theorem provides a fully deductive variational foundation for the hydrogen oxidation reaction (HOR) and oxygen reduction reaction (ORR) in proton exchange membrane fuel cells. Starting from three primitive thermodynamic axioms and the helical geometry of the phase functional, a multi-extent dynamical system is constructed that simultaneously treats the electrochemical reaction coordinates and the adsorption extents of the participating species at the solid–electrolyte interface. The combined Hessian of the phase functional yields a complete spectrum of relaxation rates whose eigenvalues and eigenvectors emerge directly from the solid blackbox constants $C_k$ and the helical partition functions of the reactive species. Adiabatic elimination of the fast surface modes produces an effective single-extent description in which voltage (or overpotential) appears as the conjugate variable, exactly analogous to the role of pressure in the corresponding gas-phase ammonia synthesis framework. The resulting nonlinear rate law is thermodynamically consistent at all conditions, recovers the Butler–Volmer and Tafel forms as well-defined limiting cases, and incorporates the effects of temperature, dilution, and catalyst-specific interface constants without empirical activation energies or adjustable reaction orders. The framework therefore unifies equilibrium, kinetics, and modal dynamics of HOR and ORR within a single variational structure, offering a parameter-light, first-principles alternative to classical empirical electrocatalytic rate expressions while preserving transparent contact with established limiting laws. Full article

Precise prediction of voltage degradation is critical for the prognostics and health management of proton exchange membrane fuel cells (PEMFCs). The performance degradation of PEMFCs is governed by a complex coupling of multiple physicochemical mechanisms, including catalyst layer and proton exchange membrane degradation. Crucially, these internal degradation processes evolve across highly heterogeneous time scales, ranging from transient high-frequency fluctuations to low-frequency and long-term irreversible performance fade. Conventional predictive models, which typically rely on single-scale architectures or fixed receptive fields, are inherently ill-equipped to simultaneously decouple and capture these cross-scale temporal dynamics. To tackle this challenge, this paper innovatively proposes a multi-scale deep learning framework that integrates a multi-scale degradation trend perception module, a long short-term memory (LSTM)-based encoder–decoder architecture, and a multi-head attention mechanism. One-dimensional convolutional layers with different kernel sizes are employed to simultaneously extract local temporal features at multiple granularities, followed by the LSTM encoder–decoder to model long-range temporal dependencies, while the cross-attention mechanism dynamically allocates attention across the encoded context at each autoregressive decoding step. Experimental outcomes indicate that the proposed model realizes excellent predictive accuracy across five evaluation indices in comparison with standard baselines. In particular, the mean absolute percentage error (MAPE) reaches 1.6696%, and the maximum absolute percentage error (Max-APE) is strictly bounded within 5%, substantiating the reliability of the proposed framework for high precision and long-horizon health prognostics for PEMFCs. Full article