This review systematically analyzes cutting-edge fuel cell technologies, focusing on proton exchange membrane fuel cells (PEMFCs), solid oxide fuel cells (SOFCs), and emerging metal-air systems. It elaborates on material innovations in catalysts and electrolytes, automation-driven manufacturing processes, and digital twin-based health management strategies. Case studies validate the performance enhancements, while current challenges and future development directions are outlined to provide a comprehensive reference for research and industrial applications.

Enhancing the Comprehensive Performance of Proton Exchange Membrane Fuel Cells through a Novel Aramid Nanofiber/Cellulose Nanofibers Grafted with Methyl Methacrylate-Modified Carbon Paper

Developing efficient catalysts for proton exchange membrane fuel cells (PEMFCs) requires minimising platinum (Pt) usage while enhancing oxygen reduction reaction (ORR) activity. While density functional theory (DFT) calculations provide valuable structural insights, understanding complex structure-property relationships often requires extensive manual analysis. We apply the Self-Consistent Attention Neural Network (SCANN) to analyze DFT data for Pt clusters (Pt 4 , Pt 13 ) on single-wall carbon nanotubes (SWNTs) with adsorbed O 2 . SCANN accurately predicts deformation energies (MAE < 1 meV/atom) and frontier orbital energies (MAE < 12 meV), while its attention scores suggest that p–d hybridisation between Pt and SWNT atoms may influence adsorption behaviour. Our minimum energy path analysis examines O–O bond dissociation, with attention scores revealing potential electronic redistribution patterns that could influence this critical catalytic step. These computational findings demonstrate how interpretable machine learning approaches may advance the understanding and design of Pt–SWNT catalytic systems for sustainable energy applications.

ABSTRACT Promotion of atomic ordering in Pt‐based intermetallic compounds (IMCs) is a proven strategy to enhance catalytic activity and durability, for the cathode catalysts in proton exchange membrane fuel cells (PEMFCs). However, achieving higher atomic ordering typically requires elevated temperature annealing, which induces nanoparticles (NPs) sintering and surface area loss, resulting in a challenge for catalyst design. Here, we demonstrate that Zn incorporation in L1 0 ‐PtCo IMCs promotes the ordering, endowing the enhanced stability and activity. Machine learning interatomic potential (MLIP) simulations reveal that Zn lowers vacancy formation energies and modifies atomic migration, thereby accelerating ordering during annealing. These results are validated experimentally by X‐ray‐based analyses. Electrochemical measurements show that L1 0 ‐Zn‐PtCo/ZnNC achieves a mass activity (MA) of 1.76 A mg Pt −1 at 0.9 V RHE , outperforming Pt/C (0.24 A mg Pt −1 ). In single‐cell tests, it delivers 438 mA cm −2 at 0.7 V, surpassing Pt/C (293 mA cm −2 ). After 30 000 cycles, it retains 89.7% initial current density, compared with only 54.6% retention for Pt/C. By integrating ML‐guided design with experimental validation, this work establishes a rational strategy to engineer atomically ordered Pt‐based IMCs under practical conditions, advancing the development of efficient electrocatalysts.

Abstract Polymer Electrolyte Membrane Fuel Cells (PEMFCs) have emerged as a promising sustainable energy technology capable of efficiently converting hydrogen and oxygen into electricity. Their adoption plays a vital role in reducing carbon emissions and dependence on fossil fuels for transportation and stationary power generation. However, maintaining an optimal balance between thermal regulation and electrical performance remains a critical engineering challenge. Excessive temperature gradients can deteriorate membrane integrity, leading to reduced durability and overall system efficiency. This study aims to determine the optimal combination of flow channel number and configuration in Polymer Electrolyte Membrane Fuel Cells (PEMFCs) to achieve balanced thermal management and electrical performance. The research addresses the gap in systematically evaluating both parameters together for practical, high-efficiency applications. Three parallel flow field designs with 8, 11, and 15 channels were modeled under co-flow, counter-flow, and cross-flow configurations. Computational Fluid Dynamics (CFD) simulations were performed using Nafion as the electrolyte membrane and carbon as the gas diffusion layer. Temperature distribution and current density were analyzed to assess thermal uniformity and electrochemical output. The 15-channel cross-flow design achieved the most uniform temperature profile, with a minimal temperature difference of 0.048 %. The 8-channel counter-flow configuration generated the highest current density of 5582.33 A/m 2 but exhibited less uniform thermal distribution. The 11-channel cross-flow configuration provided the best balance, attaining a current density of 4103.92 A/m 2 while maintaining a uniform temperature contour. The 11-channel cross-flow configuration optimizes PEMFC performance by combining effective thermal management with strong electrical output and reducing the risk of hot spots. These findings offer a scalable design strategy for enhancing PEMFC durability and efficiency in transportation and stationary power applications.

In this study, high-aspect-ratio cellulose nanofibers (CNFs) are extracted from sea squirt tunic via acid hydrolysis and use as nanofillers in the cathode catalyst layers (CLs) of polymer electrolyte membrane fuel cells (PEMFCs). Because of the aqueous-based extraction process, CNFs possess numerous hydrophilic functional groups on their surfaces, enabling their excellent dispersibility in organic solvents. By leveraging both the high aspect ratio and hydrophilic surface characteristics of CNFs, membrane electrode assemblies (MEAs) incorporating 9 wt.% CNFs exhibit significantly enhanced power performance at low current densities compared to pristine MEAs. This improvement is attributed to the reduction in the agglomerate size within the cathode CL, which facilitates oxygen transport to the catalyst surface and consequently enhances the catalytic activity. Furthermore, surface and interfacial cutting analysis system (SAICAS) measurements confirm that the incorporation of CNFs improves the mechanical integrity of the cathode CLs. Geodict simulation results further reveal that CNFs promote favorable changes in the pore structure, improving gas diffusion and thus supporting efficient catalyst activation. Collectively, these findings suggest that the introduction of properly functionalized 1D nanofibers is a highly effective approach for developing high-performance CLs for PEMFCs.

GNMSA: An Accurate Parameter Estimation of Semi-empirical Proton Exchange Membrane Fuel Cells Model using A Hybrid Artificial Intelligence–Based Optimization Approach

An Enhanced Optimization Algorithm for Estimating PEM Fuel Cells Parameters: Performance Comparison and Real-World Applicability

Achieving excellent water management capabilities under wide humidity ranges plays a crucial role in enhancing the performance of proton exchange membrane fuel cells (PEMFCs). Modifying the structure of the microporous layer (MPL) is one of the important strategies. In this study, a hierarchical interface structure MPL featuring a flat, dense surface and perforations is prepared. The results indicate that the MPL with a hierarchical interface structure demonstrates superior performance across a wide range of humidity. Its power density at 2 A/cm2 is 12% higher than that of the normal MPL. The hierarchical interface structure significantly decreases the oxygen transport resistance (OTR) and expands the dry region from 1 A/cm2 to 1.5 A/cm2. A millimeter-scale Lattice Boltzmann Method (LBM) simulation, in conjunction with experiments, systematically demonstrated the water management mechanisms of the hierarchical interface structure across a wide range of humidity. At low humidity, the dense regions retain moisture within the membrane, while the perforation promotes the molecular diffusion of gases. At high humidity, perforations become the preferred conduction pathways for liquid water, and the dense regions enhance this effect, thereby reducing the water saturation in each layer within the gas diffusion layer (GDL). This work proposes a design strategy for MPLs aimed at achieving effective water management. The findings enhance our understanding of gas-liquid transport behavior within pores of varying sizes across a wide humidity range.

Structural and Electrochemical Optimization of Platinum-Saving Pt-CoNiO/C Catalysts Synthesized Via Green Methods for High-Performance PEM Fuel Cells

As a crucial component of new energy vehicles, fuel cells rely heavily on the performance of their bipolar plates, which are among the core parts determining their overall efficiency. The flow field design of metallic bipolar plates plays a significant role in optimizing gas distribution, improving fuel utilization, and enhancing battery performance. Stamping is a key technology that determines the forming quality, cost-effectiveness, and industrial production of metallic bipolar plates. Drawbeads are widely used in the stamping industry, yet research on how drawbead parameters affect the forming quality of bipolar plates remains limited. Therefore, this study conducts an in-depth investigation into the stamping formability of metallic bipolar plates in Proton Exchange Membrane Fuel Cells (PEMFC). The most common parallel flow field is selected for stamping simulation, and the forming quality of metallic bipolar plates is analyzed based on parameters such as the distance between the drawbead and the flow channel area, drawbead depth, blank holder force, and friction coefficient. The results indicate that as the distance between the drawbead and the flow channel increases, the wrinkling area expands, but the occurrence of fracture is alleviated. Increasing the drawbead depth and blank holder force can reduce the incidence of wrinkling, while the friction coefficient has a relatively minor effect on wrinkling. However, reducing the friction coefficient can significantly mitigate the occurrence of fracture.

This study presents a comprehensive performance analysis of aluminum titanium nitride (AlTiN) and aluminum chromium nitride (AlCrN) coatings applied to stainless steel 316L (SS316L) stainless steel substrates, evaluating their potential as metallic bipolar plates in proton exchange membrane fuel cells (PEMFCs). The coatings were deposited using the cathodic arc physical vapor deposition (CA-PVD) technique. Extensive material characterization revealed significant improvements in key properties, including a reduction in interfacial contact. The corrosion resistance of AlTiN- and AlCrN-coated SS316L bipolar plates was evaluated under simulated PEMFC conditions. Both coatings exhibited corrosion current densities below the US DOE 2025 target of 1 µA cm−2, confirming excellent electrochemical stability, alongside increased hydrophobicity. Adhesion tests confirmed the stability of both coatings, achieving a top rating of grade 5B. Single-cell fuel cell testing demonstrated a notable improvement in performance, with AlTiN-coated plates exhibiting an 18.59% increase in peak power density 12.452 mW per cm2 compared to uncoated SS316L plates at 10.5 mW per cm2, outperforming the AlCrN-coated plates. These findings highlight AlTiN as a promising coating material for enhancing the durability and efficiency of PEMFCs, suggesting potential for further optimization through advanced membrane electrode assembly MEA configurations.

Proton Exchange Membrane Fuel Cells (PEMFCs) is one of the best promising clean technologies in future. Numerous research activities are going on regarding to stability and thermal management of PEMFC. This reserch aim to study the scattering dynamic inside PEMFC in self-generated heat, laser field and scattering particles. To fulfil this objective first, authors developed theoretical model and then verified some parameters of theoretical model with experimental methods. For theoretical model authors formulated transition matrix using thermal Volkov wave function and thermal potential of hydrogen to study scattering dynamic. For experimental method, authors developed a PEMFC prototypes and applied diffident condition (heat and laser) to observed the data for verification of theoretical model. The developed differential cross section (DCS) model shows that with increasing temperature DCS increase theoretically and experimentally found that increasing in temperature decreasing in voltage. So, the DCS increasing with decreasing in voltage which is verified both theoretically and experimentally. In addition, we also observed that DCS effect by different parameters of PEMFC like charge transfer, charge density, efficiency, voltage, activation potential etc. and scattering parameters like momentum, scattering angle, incidence energy, distance separation etc. This finding help both academic field and non-academic field like scanning tunneling microscopy, laser-induced fluorescence, quantum computing and nanophotonic sensors perform. The finding finds that the supply temperature negatively influences PEMFC performance, which is attributed to higher particles’ resistance and entropy, hence indicating how stringent is the requirement for an accurate thermal management for enhancing fuel cell efficiency.

Atomically dispersed Fe-N-C catalysts are regarded as promising alternatives to platinum-group-metal (PGM) catalysts for proton exchange membrane fuel cells (PEMFCs). However, their further development is hindered by inadequate utilization of active sites in membrane electrode assembly (MEA). Herein, we developed a high mass activity O-FeNC catalyst with high site density and enhanced site utilization. C═O groups function as hard base linkers, promoting the densification of FeN4 sites through Lewis acid-base interactions. Moreover, they also direct interfacial alignment within triple-phase boundaries, leading to concentrated hydronium ions and accelerated oxygen permeation via regulated ionomer nanophase segregation. As a result, the obtained O-FeNC cathode delivered a current density of 66.45 mA cm-2 at 0.90 ViR-free, surpassing the US Department of Energy 2025 target (44 mA cm-2 at 0.9 ViR-free), with a mass activity that is 59% higher than commercial Pt/C. The peak power densities reached 1.8 W cm-2 under H2-O2 and 0.93 W cm-2 under H2-air, alongside demonstrated industrial scalability through gram-scale synthesis and a 500 W PGM-free cathode stack prototype.

The parameter extraction of proton exchange membrane fuel cells (PEMFCs) has been an active area of study over the past few years, relying on metaheuristic optimizers and experimental datasets to achieve accurate current/voltage (I/V) curves. This work develops a mirage search optimizer (MSO) to precisely estimate the PEMFC model parameters. The MSO employs two search techniques based on the physical phenomena of light bending caused by atmospheric refractive index gradients: a superior mirage for global exploration and an inferior mirage for local exploitation. The MSO employs optical physics to direct search behavior, in contrast to conventional optimization approaches, allowing for a dynamic balance between exploration and exploitation. Convergence efficiency is increased by its iteration-dependent control and fitness-based influence. Using two common PEMFC modules, a comparison study with previously published methodologies and new, recently developed optimizers—the Educational Competition Optimizer (ECO), basketball team optimization (BTO), the fungal growth optimizer (FGO), and the naked mole rat optimizer (NMRO)—was conducted to evaluate the proposed MSO for parameter identification. Furthermore, the two models were tested under various temperatures and pressures. For the three examples studied, the MSO achieved the best sum of squared errors (SSE) values with an intriguing overall standard deviation (STD). It is undeniable that the STD and cropped SSE values, among other difficult techniques, are quite competitive and display the fastest convergence. According to the MSO, the BCS 500W, Ballard Mark V, and Modular SR-12 each have MSO values of 0.011697781, 0.852056, and 1.42098181379214 × 10−4, respectively. Additionally, the comparison results demonstrate that the proposed MSO can be successfully used to quickly and accurately define the PEMFC model.

Uneven ionomer distribution and sulfonate groups (-SO3 -) poisoning at platinum (Pt) sites significantly impede Pt utilization and local mass transport in proton exchange membrane fuel cells (PEMFCs). Herein, we report an electrostatic landscape design on nanocarbon supports that harnesses strong and uniform ionomer adhesion to create a poison-resistant Pt interface, effectively mitigating direct poisoning of Pt sites by -SO3 - groups and enhancing active sites accessibility and local mass transport. The resulting PtFe/FN-C catalyst exhibits an exceptionally low ionomer coverage of only 6.4%, enabling a peak power density of 1.39W cm-2 and an oxygen transport resistance of only 44.5s m-1 in PEMFC testing. Furthermore, it demonstrates impressive durability, with only a 2mV voltage loss after 30 000 cycles at 0.8A cm-2. This work establishes a new principle for interface engineering where overall polymer-support adhesion governs local catalyst-functional group interactions, offering a general strategy for designing high-performance, poison-resistant electrocatalysts for energy conversion technologies.

Proton Exchange Membrane Fuel Cells (PEMFCs) is one of the best promising clean technologies in future. Numerous research activities are going on regarding to stability and thermal management of PEMFC. This reserch aim to study the scattering dynamic inside PEMFC in self-generated heat, laser field and scattering particles. To fulfil this objective first, authors developed theoretical model and then verified some parameters of theoretical model with experimental methods. For theoretical model authors formulated transition matrix using thermal Volkov wave function and thermal potential of hydrogen to study scattering dynamic. For experimental method, authors developed a PEMFC prototypes and applied diffident condition (heat and laser) to observed the data for verification of theoretical model. The developed differential cross section (DCS) model shows that with increasing temperature DCS increase theoretically and experimentally found that increasing in temperature decreasing in voltage. So, the DCS increasing with decreasing in voltage which is verified both theoretically and experimentally. In addition, we also observed that DCS effect by different parameters of PEMFC like charge transfer, charge density, efficiency, voltage, activation potential etc. and scattering parameters like momentum, scattering angle, incidence energy, distance separation etc. This finding help both academic field and non-academic field like scanning tunneling microscopy, laser-induced fluorescence, quantum computing and nanophotonic sensors perform. The finding finds that the supply temperature negatively influences PEMFC performance, which is attributed to higher particles' resistance and entropy, hence indicating how stringent is the requirement for an accurate thermal management for enhancing fuel cell efficiency.

To enhance the overall performance of proton exchange membrane fuel cells (PEMFCs), this study proposes a novel flow field design featuring hierarchical block structures with non-uniform heights. Four different block geometries—rectangular, wavy, triangular, and trapezoidal—are numerically investigated under both uniform block (UB) and hierarchical top-lowered block (HTLB) configurations using a three-dimensional, two-phase, non-isothermal numerical model. Numerical results reveal that the hierarchical flow fields effectively suppress flow separation and enhance flow reattachment behind blocks, significantly reducing momentum loss. The HTLB configuration achieves a 75.12%–78.46% reduction in pressure drop compared to the traditional uniform case, while maintaining comparable current density levels. Among four geometries, the rectangular block HTLB flow field exhibits the highest net power output due to its superior reactant transport capability, resulting in a 3.95% increase in net power compared to the conventional parallel flow field. Moreover, the HTLB structure improves water management by accelerating liquid water removal and mitigating flooding under low-voltage operation, thereby stabilizing fuel cell performance across a broader range of working conditions. This work demonstrates the broad applicability of hierarchical block structures for optimizing PEMFC flow fields. The design provides an effective balance between reduced flow resistance and enhanced mass transport, showing significant promise for practical engineering applications in advanced fuel cell systems.

This paper proposes a novel model-free control (MFC) strategy for hybrid electric vehicles (EVs) powered by a proton exchange membrane fuel cell (PEMFC) and a supercapacitor (SC). Unlike conventional model-based approaches that depend on accurate system identification and parameter tuning, the proposed framework employs ultra-local models to adapt dynamically to system variations without explicit modeling. The hybrid architecture is implemented using an interleaved boost converter for the PEMFC and a bidirectional buck–boost converter for the SC, coordinated to supply propulsion power and enable regenerative braking. Comprehensive MATLAB/Simulink simulations demonstrate that the proposed MFC achieves &lt;3% current tracking error for both PEMFC and SC, ~750 ms settling time for PMSM speed variations, and &lt;120 ms response for power transitions, while the DC bus voltage remains tightly regulated under dynamic load disturbances. Hardware-in-the-loop (HIL) validation on an OPAL-RT 5600 platform further confirms the method’s feasibility, showing a 20% reduction in execution time and enhanced robustness against parameter uncertainties compared to classical PI control. Experimental results also verify stable current sharing in interleaved converters, accurate voltage regulation in the SC branch, and smooth torque generation in the PMSM drive. Overall, the proposed control strategy provides a computationally efficient, fault-tolerant, and plug-and-play solution for next-generation EVs by reducing calibration effort and ensuring reliable operation under nonlinear and uncertain conditions, while demonstrating clear potential for real-time automotive applications.

A Matlab-Simulink based mathematical model and simulation method is developed by applying appropriate physics and electro-chemistry that adequately describes a proton exchange membrane fuel cell (PEMFC) system. The mathematical model is then simulated for a single low temperature PEMFC with a large, 350cm2, active area. The single cell’s performance was evaluated using different operating conditions and varying values of various crucial system parameters. The Matlab-Simulink model presented in this investigation is used to study various parameters’ effect such as the cell temperature from 50℃ to 90℃, inlet pressure, relative humidity (RH) from 70% to 90%, and the reactant stoichiometry ratio, on the cell performance. Comparison of polarization and power density curves were conducted between the model simulation and experimental data at 60℃ and at 65℃. Except for the higher current densities range (≥1.6 A/cm2), the simulation results match with the experimental results very well. The parametric study was used to determine the optimum value of various parameters. The fuel cell performance with the optimized parameter values show a good improvement using the developed MatLab-Simulink model. Key words. PEMFC, modeling, Matlab-Simulink, fuel cell, experimental validation.