Cell Performance Research Articles

Coarse-Grained Molecular Dynamics Simulation of Ionomer-Mediated Carbon Cluster Bonding in Polymer Electrolyte Fuel Cell Catalyst Layers

This study examines the impact of ionomer to carbon mass ratio and the number of platinum particle clusters on the structural dynamics and organization of Pt-C-Nafion catalyst layers during the evaporation process. Using Coarse-Grained Molecular Dynamics (CGMD) simulations, we analyzed the center of mass position and ionomer coverage on Pt surface. The results show that a higher ionic polymer to carbon mass ratio (0.6) increases lateral mobility and short-range ordering along with the coverage of the Pt surface with ionomers, whereas increasing the number of Pt particle clusters (from 1 to 4 ) enhances lateral diffusion as well as leading to more difficult adsorption of ionomers. These findings highlight the importance of optimizing these parameters to obtain a homogeneous and stable catalyst layer, which is critical for fuel cell performance. Future work will include tuning the Pt/C mass ratio, hydrophilicity, and IC ratio in conjunction with energy and force analyses to further understand the effect of Nafion on Pt/C clusters.

Experimental Investigation on the Backpressure Effect on the Performance of a High Temperature Proton Exchange Membrane Fuel Cell Stack

This study investigated the impact of backpressure of anode and cathode on the performance of a high-temperature proton exchange membrane fuel cell stack consisting of 30 cells, initially operating at a current density of 0.4 A/cm², temperature of 160 ℃, and 0 bar with pure H2. Subsequently, the backpressure on both sides was varied from 0 bar to 1.5 bar, and the changes in stack performance were recorded throughout the testing period. Additionally, the impact of backpressure was also investigated with reformates (H2/CO2/CO/N2 = 69.4%/22.3%/1.40%/6.9%) as anode feed for the stack. The results showed that increase in operating backpressure improves the fuel cell performance. A stack voltage increase of 20 mV per cell and 40 mV per cell were achieved for the pure hydrogen operation and reformate gas operation respectively when increasing backpressure from 0 bar to 0.5 bar. This signifies potential to improve the system’s overall efficiency with only minor penalty in terms of auxiliary power loss to increase the back pressure.

Improving the performance of organic solar cell via tuning the interfacial n-doping of cathode-modifying layer

Organic solar cells have been fabricated using thermally evaporated bathocuproine (BCP) and ytterbium n-doped BCP (BCP:Yb) to modify the interfaces of active layer and cathode. The device with 10 nm BCP presents open-circuit voltage of 0.791 V and fill factor of 0.670, greater than those (0.785 V and 0.636) of the device with 10 nm BCP:Yb, mostly due to that the BCP:Yb causes severe nonradiative recombination in active layer. The device with 1 nm BCP/9 nm BCP:Yb offers open-circuit voltage of 0.793 V, almost same as that of the device with 10 nm BCP, due to the two following reasons. Firstly, the interlayer of 1 nm BCP is able to separate active layer from BCP:Yb, thereby preventing the nonradiative recombination. Secondly, the BCP interlayer is so thin that the interfacial n-doping of Yb in it raises the Fermi level close to its lowest unoccupied molecular orbital level, whereby it forms ohmic contacts with active layer and BCP:Yb. Despite showing decreased fill factors, the devices with 10 nm BCP:Yb and 1 nm BCP/9 nm BCP:Yb give short-circuit current densities of 15.43 and 15.62 mA cm−2, respectively, larger than that (14.47 mA cm−2) of the device with 10 nm BCP. The power conversion efficiency based on 1 nm BCP/9 nm BCP:Yb is 8.11 %, higher than those based on 10 nm BCP (7.67 %) and 10 nm BCP:Yb (7.71 %). The current research indicates that tuning the interfacial n-doping of cathode-modifying layers is a facial and effective method to improve the performance of organic solar cells.

The interplay between optoelectronic and magnetic properties in Co-doped Cu2ZnSnS4 for next-generation solar cell devices

Abstract A search for next-generation solar cell devices to massively actualize renewable energy is being exponentially conducted. It includes the development of Cu2ZnSnS4 (CZTS)-based solar cells, which are known as cost-effective and highly stable solar cell devices. In this present research, we develop a CZTS solar cell by adding a magnetic degree of freedom using cobalt (Co) doping. We find that the Co doping can induce modulation of the crystalline structure and bandgap of CZTS, which further influences its photovoltaic performance. The increase in the grain size of the CZTS with the addition of Co doping could further induce the reduction of detrimental grain boundaries, which benefits the photovoltaic performance of CZTS-based solar cells. Co doping also generates magnetic behavior in CZTS, which supports its magnetically controlled optoelectronic properties and thus, in turn, enhances the photovoltaic performance. We believe that this study could open up opportunities to obtain next-generation solar cell devices with excellent performances by using magnetic-field induction.

Investigating the influence of the Ag and Al co-doping in ZnO electron transport layer on the performance of organic-inorganic perovskite solar cells using experimentation and SCAPS-1D simulation

The sufficient material selection of electron transport layer (ETL) enormously promises exceptional conversion efficiency from perovskite (PVT) solar cells (PSCs), which in turn give rise to their rapid establishment in world-wide photovoltaic (PV) market. Among the tactics exerted on ETLs, and thus, intensifies the adequacy of associated PSCs, the methodology of doping stands productive. Therefore, this research validates the implementation of such effectual ETLs on widely approved methyl ammonium lead triiodide (MAPbI3)–based PSCs. The work brings together two versions of zinc oxide (ZnO) ETLs: one in its pristine form, and the other is aluminum (Al) co-doped with silver (Ag) represented as Ag-AZO. The investigation launches the PV capabilities of Ag-AZO ETL against its undoped correspondent. Accordingly, the earlier part of the investigation centers on the experimental assessment of ZnO and Ag-AZO nanoparticles (NPs) affirming their material and morphological aspects. Later, the research deals with the involvement of both NPs as ETLs signifying the PV potential of MAPbI3–based PSCs through comprehensive numerical analysis. The judgements of investigation declare that MAPbI3–based PSC with Ag-AZO ETL yields a desirable power conversion efficiency (PCE) of 27.26% against 25.98% from control cell. The investigation will definitely enlighten the development of forthcoming efficient PSCs incorporated with appropriate multiple metals co-doped ETLs.

Research on performance optimization of electrolytic cell: Non-parameter topology and parameter optimization

The technology of water electrolysis for hydrogen production converts renewable energy into hydrogen, enabling efficient storage and utilization of clean energy. The key to enabling the large-scale development of water electrolysis technology lies in enhancing the performance of electrolytic cells and minimizing energy consumption. The mastoid process structure obviously influences the electrolytic cell's flow and electrochemical performance. Therefore, this paper studied the sensitivity of the mastoid process structure to the optimization target, designed the shape topology and the parameter optimization structure, and further analyzed the influence of the two optimization methods on the flow and electrochemical performance of the electrolytic cell based on the multi-physics coupling model. The results show that under the same deformation area, the pressure drop of the topology and the parameter optimization structure is reduced by 17.17 % and 11.89 % compared with that of the original structure. The electrochemical properties were almost unaffected, and the change value was less than 0.1 %. Topology optimization design can achieve optimal performance within limited deformation constraints, and parameter optimization design is more conducive to industrial processing.

Alternative Strategy for Development of Dielectric Calcium Copper Titanate-Based Electrolytes for Low-Temperature Solid Oxide Fuel Cells

HighlightsDielectric CaCu3Ti4O12 (CCTO) was used as electrolyte in low-temperature solid oxide fuel cells for the first time.A new heterostructure electrolyte was designed based on CCTO and Ni0.8Co0.15Al0.05LiO2−δ (NCAL). Promising ionic conductivity and high fuel cell performance were achievedCCTO–NCAL realized an electrolyte function due to its good dielectric property and a heterojunction effect.

Modeling and experimental testing of a UAV liquid hydrogen propulsion set

In this paper, an analytical model of an Unmanned Aerial Vehicle (UAV) propulsion system using liquid hydrogen to supply a fuel cell is presented. The article also describes experimental tests of the performance of a liquid hydrogen (LH2) tank at different ambient temperatures and ground tests of the UAV propulsion system using LH2. These tests were used to validate and calibrate the analytical model. The model is of reduced order and is based on the literature. Despite the simplicity of the model, the tank Boil-Off Gas (BOG) rate and pressure drop, the time for complete evaporation of LH2, the fuel cell performance, and the coolest temperature that the hydrogen can reach, were predicted with deviations not exceeding 0.3%, 0.5%, 2.2%, 0.6%, and 0.5% respectively. The final proposed model allows the incorporation of different conditions, materials, and geometries to suit each mission, all at low operational cost.

Defects passivation in chloride-iodide perovskite solar cell with chlorobenzylammonium halides

Despite promising optoelectronic properties, it is a matter of fact that ion migration is unavoidable in chloride-iodide-based perovskite solar cells due to a radius mismatch between chlorine and iodine. Local defects like atomic vacancies or accumulation of atoms might occur due to ion migration in chloride-iodide-based perovskite thin film. Again, atomic vacancies are prevalent in solution-processed perovskite thin film. Here we have investigated the passivation of these defects with two organic halide passivators named 4-chlorobenzylammonium chloride and 4-chlorobenzylammonium bromide. They passivate both the surface and bulk of the perovskite thin film. The surface of the perovskite thin film is passivated with the bulky organic benzylammonium cations. The bulk of the perovskite thin film is passivated with the diffusion of chlorine or bromine. With different combinations of the two passivators, we vary the chlorine range from 50% to 100% and the bromine range from 25% to 50%. We have found the champion cell performance for 75% chlorine and 25% bromine combination. The enhancement of device efficiency was around 15% compared to the control device and the device stability was also considerably enhanced.

Generative adversarial networks for stack voltage degradation and RUL estimation in PEMFCs under static and dynamic loads

Accurately predicting the degradation and remaining useful life (RUL) of Proton Exchange Membrane Fuel Cells (PEMFCs) is crucial for enhancing their reliability, particularly in automotive and energy sectors. Traditional models often fail to capture the complex, non-linear degradation patterns of PEMFCs, resulting in suboptimal predictions. This study addresses these technological gaps by introducing a novel approach, the Self-Attention Temporal Dual Discriminator Generative Adversarial Network (SAT-DD-GAN). This model is designed to overcome the limitations of existing methods by integrating advanced Long Short-Term Memory (LSTM) networks for time-series analysis, a self-attention mechanism to focus on critical degradation signals, and dual discriminators to improve prediction accuracy and robustness. By addressing the gap in handling long-term dependencies and complex degradation patterns, the proposed SAT-DD-GAN bridges the disconnect between traditional models and the real-world degradation behavior of PEMFCs. The SAT-DD-GAN achieved groundbreaking predictive performance, with the lowest RMSE (0.983E-3 for static load, 1.012E-3 for dynamic load), MAPE (0.036E-1 and 0.253E-1), MAE (0.776E-3 and 0.806E-3), and the highest R2-score (0.9998 and 0.9983), alongside zero relative error for both datasets. These results demonstrate the model's ability to capture the intricate degradation dynamics more effectively than existing state-of-the-art methods. By filling the technology gap of accurately modeling PEMFC degradation under varying load conditions, this study establishes a new standard for PEMFC prognostics and paves the way for future innovations in optimizing fuel cell performance and longevity.

Dual-Functional Metal-Organic Framework Freestanding Aerogel Boosts Sulfur Reduction Reaction for Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) technology stands out as a promising energy storage system. However, its journey toward practical implementation is hindered by sluggish sulfur reduction reaction (SRR) kinetics. A free-standing graphene aerogel (GA) combined with a copper-based metal-organic framework (MOF-GA) is fabricated as the sulfur host material for Li-S battery cathodes. The presence of MOF particles assumes a dual role, demonstrating its efficacy not only as a catalyst for the reduction reaction of graphene oxide (GO) but also as an electrochemical catalyst to promote sluggish SRR kinetics. The former amplifies electron transfer kinetics within the electrode, and the latter elevates the overall cell performance. Experimental results and theoretical calculations have proven the catalytic activity of MOF-GA electrodes, leading to a higher sulfur utilization of over 80% and a lower capacity decay of 0.082% per cycle. Under extreme conditions, the Li-S cells show a high initial specific capacity of 1113.0 mAh·g-1 under an elevated loading of 4.25 mg·cm-2 and a high sulfur fraction >70%. This study shows the effectiveness of the synergist effects of MOF particles within the GA framework in promoting the sulfur redox reaction in Li-S batteries.

Microstructural Passivation of Patterned Al2O3 Back Contacts on CdS/CdTe Solar Cells

AbstractPatterned aluminum oxide (Al2O3) back contact on cadmium telluride (CdTe) solar cells can effectively mitigate the loss of the majority carriers while retaining the passivation benefits for minority carriers. This study investigates the impact of the point‐contact geometry on cell performance, where the spacing of the microholes is systematically varied at a constant microhole diameter (≈16 µm). Microhole arrays are created on an evaporated Al2O3 layer (≈30 nm) on CdTe using laser‐beam lithography and selective wet etching processes. Comparative analysis indicates a significant decrease in fill factor (FF) and short‐circuit current (ISC) when the contact fraction falls below 30%, likely due to the Al2O3 barrier impeding majority carriers. Above this fraction, FF and ISC are comparable to those of baseline CdTe cells without Al2O3. Open‐circuit voltage (VOC) shows a gradual decrease as Al2O3 coverage is reduced but exhibits a slight increase (<15 mV) when the contact fraction exceeds 30%. Cathodoluminescence (CL) characterization reveals that significantly improved radiative recombination occurs within the CdTe grain bulk with Al2O3, whereas this effect on grain boundaries is minimal. The findings imply complex local carrier dynamics in the patterned back‐contact region, closely tied to the microstructural properties of CdTe‐based solar cells.

Understanding the heat generation mechanisms and the interplay between joule heat and entropy effects as a function of state of charge in lithium-ion batteries

The thermal performance of lithium-ion battery cells is critical for ensuring their safe and reliable operation across various applications. In this study, we employed an isothermal calorimetry method to investigate the heat generation of commercial 18650 lithium-ion battery fresh cells during charge and discharge at different current rates, ranging from 0.05C to 0.5C, and across various temperatures: 20 °C, 30 °C, 40 °C, and 50 °C. Our findings revealed a direct correlation between heat generation and current rates, indicating that higher current rates lead to increased heat generation within the cells. Conversely, we observed that heat generation remained relatively stable as the temperature rose, suggesting that temperature changes within this range may not significantly impact the heat generation of fresh cells during typical operations. Furthermore, our study explored irreversible heat generation, which depends on the applied current and overpotential, using the galvanostatic intermittent titration technique at 0.05C–0.5C and 30 °C. Additionally, electrochemical impedance spectroscopy was performed on the same cells during charge and discharge at 20 °C, 30 °C, and 40 °C to analyze cell impedance. Our results indicated a consistent dependence of impedance on the state of charge and depth of discharge, with a significant increase in impedance observed at the end of the discharge process.

Optimizing the performance of perovskite-based organic solar cells via graphene integration as the hole transport layer: a comprehensive analysis

Optimizing the performance of perovskite-based organic solar cells via graphene integration as the hole transport layer: a comprehensive analysis

Study on heat and mass transfer behavior of coupled electrochemical reaction in porous structure of proton exchange membrane fuel cell

Proton exchange membrane fuel cell (PEMFC) is widely used in transportation, aviation and energy storage due to its unique advantages. Improving the performance of fuel cells depends largely on effective hydrothermal management. In this work, a multi-physical field coupling model based on the lattice Boltzmann method (LBM) is established to analyze the oxygen transport, liquid water transport, heat transfer and electrochemical reaction, mainly considering the difference between the overpotential of the cell and the surface wettability of the structure. The results show that the overpotential is closely related to the reaction process. The rate of water production is significantly accelerated by increasing the overpotential, and the breakage and merging of water clusters are observed. The increase of overpotential will lead to more energy loss in the form of heat, thus increasing the heat production. Enhancing the hydrophobicity of the structure has a positive effect on the performance of the fuel cell, and the possibility of local hot spots in the low-hydrophobic structure is greater. It is feasible to improve water management and fuel cell performance through wettability design.

Parametric optimization for the performance analysis of novel hybrid organo-perovskite solar cell via SCAPS-1D simulation

The perovskite and organic solar cells are becoming the most cognizant of the photovoltaic communities. The Spiro-OMeTAD organic hole transport layer (HTL) shows a significant impact on the CH3NH3SnI3 perovskite solar cell (PSC) with TiO2 as the electron transport layer (ETL). So, we optimized the physical and electrical parameters of the organic HTL. Electrical optimization shows that the power conversion efficiency (PCE) of the cell can reach up to 18.10% for the electron affinity of the organic HTL material of about 2.5eV. Further, the interpretation of the practical scale of series and shunt resistance reveals the maximum PCE of the cell as 13.30% at 0.5Ωcm2 and 1×106Ωcm2 respectively. Also, the performance of the cell is analyzed for the hole mobility of the organic HTL material, which revealed the best PCE of the cell to 13.31%. Moreover, the physical parameters are also optimized for the cell performance with illumination intensities which pointed out that the performance of the novel organic HTL perovskite solar cell is optimum for illumination intensity around 0.5Sun (500Wm-2). Finally, the overall light harnessing efficiency or PCE of the proposed solar cell is declared to be 13.30%, and the other performance parameters as open circuit voltage (Voc), short circuit current (Jsc), and fill factor (FF) are 0.764V, 25.86mAcm−2 and 67.29%, respectively.

Numerical Analysis on Influence of Double-Sided 3D-Patterned Cathode Catalyst Layers on Polymer Electrolyte Fuel Cell Performance

Abstract An optimized cathode catalyst layer (CCL) design can improve fuel cell performance. In this study, we tried to optimize the structure by investigating the electrochemical properties of ion and mass transport through various CCL structures with ionomer layer (IL) added using simulation numerical analysis. In the simulation, an electrochemical calculation was performed on the structure with polymer electrolyte membrane (PEM) and IL of CCL using multi-block model. The simulation was conducted by changing the aspect ratio (AR) structure of width and height of IL to five conditions so that IL is evenly distributed in catalyst layer (CL). The result confirmed that CL 3D IL AR 4.9 structure with the highest aspect ratio showed good performance. In addition, cell performance improved as the uniform reaction area with protons conducting through IL increased and the resistance of protons decreased. Finally, cell performance was predicted based on changes in oxygen concentration (OC), relative humidity (RH), and ionomer/carbon (I/C) ratio. This numerical analysis can show the reaction according to environmental and structural changes and design an optimized structure to improve cell performance.

Machine Learning Prediction of Fuel Cell Remaining Life Enhanced by Variational Mode Decomposition and Improved Whale Optimization Algorithm

In predicting the remaining lifespan of Proton Exchange Membrane Fuel Cells (PEMFC), it is crucial to accurately capture the multi-scale variations in cell performance. This study employs Variational Mode Decomposition (VMD) to decompose performance data into intrinsic modes, elucidating critical multi-scale dynamics vital for understanding the complex degradation processes in fuel cells. In addition to VMD, this research utilizes an Improved Whale Optimization Algorithm (IWOA) to optimize a Back Propagation (BP) Neural Network. The IWOA focuses on precise adjustments of weights and biases, enabling the BP network to effectively interpret complex nonlinear relationships within the dataset. This optimization enhances the predictive model’s reliability and stability. Extensive experimental evaluations demonstrate that the integration of VMD, and the learning capabilities of the IWOA-optimized BP network significantly improves the model’s accuracy and stability across multiple predictions, thereby increasing the reliability of lifespan predictions for PEMFCs. This methodology offers a robust framework for extending the operational life and efficiency of fuel cells.

Development and experimental investigation of a new direct urea fuel cell

This study concerns the development and experimental investigation of Direct Urea-Hydrogen Peroxide Fuel Cells (DUHPFC), with a particular emphasis on electrode preparation using nickel zinc iron oxide coated on stainless steel foil via the electrochemical deposition method, and the performance evaluation of single cells under varying operational conditions is also performed. This electrochemical deposition helps achieve a uniform and stable anode coating, which exhibits the high catalytic activity and stability, resulted in significantly enhanced urea oxidation reaction. The research further identifies an optimal performance for a single cell at 25 °C with 9 M KOH and 0.5 M urea, achieving a peak power density of 46.38 mW/cm2. The single cell demonstrates an open circuit voltage (OCV) of 0.72 V. Both energy and exergy efficiencies are further investigated for the cell performance and found to be 58% and 24%, respectively, at 5 M KOH. The electrochemical impedance spectroscopy (EIS) results reveal a significant reduction in impedance, from 30-Ωcm2 at 25 °C to 15-Ωcm2 at 65 °C, indicating an enhanced ionic conductivity and a reduced resistance. The present study results suggest that optimizing the electrode composition and operational parameters significantly improves the DUHPFC's performance, offering valuable insights for future fuel cell development.

Exploration of the Influences of Electrode Materials and Solutions on the Performances of a Reverse Electrodialysis Cell with a Deduced Equation

Exploration of the Influences of Electrode Materials and Solutions on the Performances of a Reverse Electrodialysis Cell with a Deduced Equation