Cell Current Density Research Articles

Modelling and Optimization of A Light Trapping Scheme in A Silicon Solar Cell Using Silicon Nitride (SiNx) Anti-Reflective Coating

Solar cells system has been gaining remarkable attention in the photovoltaic (PV) industry in recent years. Therefore, many people used solar cells in their life. Hence, from time to time, many industries keep improve it to get the best of efficiency of the solar cell. In this work, it presents ray tracing of light trapping (LT) schemes in thin c-Si to enhance broadband light absorption within 300 - 1,200 nm wavelength region. For the ray tracing simulation, mono c-Si wafer with 100 μm thickness is investigated and solar spectrum (AM1.5G) at normal incidence is used. Random planar and upright pyramid front surface with silicon nitride (SiNx) anti-reflective coatings (ARC) with the difference thicknesses are the LT schemes being studies in this work. The broadband anti-reflective coating can effectively reduce the optical loss and improve the energy efficiency in the solar cells. The optical properties of the thin c-Si are analyzed with incremental LT schemes. Not only that, the current density also calculated from the absorption curve. Optical properties and current density were evaluated to find out the best thickness and refractive index of the silicon nitride (SiNx). The initial simulation results show that the solar cell current density is about 24.81 mA/cm2. A great Jmax enhancement in solar cell was achieved with utilizing the ARC thickness and type of front surface. Among the 6 proposed scheme, the scheme with upright pyramid front surface of 75 nm SiNx ARC thickness realized a good improvement in current density of 41.19 mA/cm2. This leads to Jmax enhancement of 66.02 % when compared to the reference c-Si. HIGHLIGHTS Solar cell energy conversion efficiencies for commercially available multicrystalline silicon solar cells are around 14 - 20 % which still insufficient Energy conversion efficiency of solar cell can be enhanced by adding the anti-reflective coating on the front layer of light trapping scheme SiNx as a single layer anti-reflective coating with a certain thickness shown a good behavior in reducing the light reflection hence, effectively absorbing more light into the scheme and leads to enhancing the energy conversion efficiency GRAPHICAL ABSTRACT

The pinhole effect on proton exchange membrane fuel cell (PEMFC) current density distribution and temperature distribution

The proton exchange membrane (PEM) is a critical portion of a proton exchange membrane fuel cell (PEMFC). However, it is strongly influenced by pinhole defects owing to degradation during its operation or manufacture. Such defects may accelerate chemical polymer decomposition, eventually causing fuel cell failure and other safety issues. Thus, it is necessary to detect and characterize pinhole degradation while determining the effect of pinhole on electrochemical behavior and fuel cell performance. Herein, pinholes of different sizes (10 and 100 µm) were fabricated on a 50-cm2 catalyst-coated membrane (CCM) and characterized using commercial current scan shunt (CSS) S++ Simulation Services (Hephas Energy) to investigate the effects of pinhole size on current density and temperature distributions of the PEMFC. Our analyses show that hydrogen crossover from the anode to the cathode through a pinhole can cause hydrogen diffusion and a hydrogen oxidation reaction (HOR) on the cathode electrode surface under certain conditions. Consequently, local reverse currents and hot spots are detected around the pinhole position under open-circuit voltage (OCV) and the corresponding current and temperature distribution trends are uniform. Conversely, the reverse current immediately disappeared from the current distribution map because water exists under operation conditions, resulting in membrane swelling and pinhole sealing. Thus, hydrogen crossover decreased and local reverse currents reappeared as a result of anode overpressure during fuel cell operation. The local reverse current becomes weaker when using the same-sized pinhole under the same anode overpressure because the overall current density increases. Furthermore, owing to the presence of water, the capillary force for the 100-µm pinhole was higher than that for the 10-µm pinhole, indicating that more anode overpressure is required to generate a local reverse current. Thus, the position and size of the pinhole can be effectively detected using in situ characterization.

Electrical properties of BaZr0.5Ce0.3Y0.1Yb0.1O3-δ proton conductor for reversible proton-conducting solid oxide electrochemical cells

Proton-conducting oxide-based reversible solid oxide electrochemical cells (protonic-SOEC, P-SOEC) have a great potential to be the most efficient transition technology operating at intermediate temperatures. Here, we have introduced a perovskite-type proton conductor BaZr0.5Ce0.3Y0.1Yb0.1O3-δ (BZCYYb5311) and evaluated its electrochemical and transport properties. The chemical stability of BZCYYb5311 was confirmed by thermo-gravimetric analysis (TGA) under pure CO2 conditions and X-ray diffraction analysis. The total and partial conductivities were obtained using DC four-probe conductivity measurements under various pO2 and pH2O conditions. The ratio of proton conductivity to ionic conductivity including the oxygen-ion conductivity of this material was 98% at 600 °C, indicating that it is a relatively pure proton conductor with most of the ionic conduction almost exclusively carried out by protons. Chemical diffusivities were calculated from Fick's 2nd law by non-linear least squares fitting during oxidation/reduction and hydration/dehydration processes and were faster than other proton conductor BZCY (Y-doped BaCeO3-BaZrO3) series, which have a similar zirconium contents. In addition, the theoretical performance and efficiency of the reversible P-SOEC were determined from the spatial distribution of oxygen and hydrogen partial pressure in BZCYYb5311, calculating the maximum power density (4.5 Wcm−2 at 600 °C, 3% of water vapor pressure) for the fuel cell mode and current density (12.3 Acm−2 at 1.5 V, 600 °C, and 20% of water vapor pressure) for the electrolysis mode. The fuel consumption efficiency is high (99.1% at 0.6 V at 600 °C), while the electrolysis efficiency is low (72.3% at 1.6 V) due to the dominant p-type regime in the electrolyte during electrolysis. This low electrolysis efficiency can be enhanced by recovering the electrolyte regime by increasing pH2O or decreasing pO2 in the air electrode; however, it will still have low efficiency. Consequently, BZCYYb5311 is not an efficient electrolyte material for electrolyzers, but is promising for fuel cells because of its superior chemical stability, exceptional pure proton conductivity, and better bulk diffusion than those of the BZCY system.

Exergy-economic assessment of a hybrid power, cooling and heating generation system based on SOFC

In this research, a combined cycle using a solid oxide fuel cell system, a single-stage H2O–NH3 absorption chiller and a residential hot water HX, is developed for the electricity production, hot water and cooling all at the same time, and it is studied from an exergy, energy, and exergoeconomic standpoint. Performance of system under the design condition is analyzed and the mathematical model is simulated. After analyzing the results in the initial input mode, changing the fuel cell current density effect and fuel utilization factor on the system efficiency is evaluated. The result indicates that total energy is 4.418 kW, the total exergy efficiency is 37.8%. And the overall irreversibility is 1.650 kW. On the other hand, the air HX, fuel cell and water HX are designed as elements that must be given more attention than others from the exergoeconomic perspective, because they have nearly the most amount of price compared to other parts.

An innovative biomass-driven multi-generation system equipped with PEM fuel cells/VCl cycle: Throughout assessment and optimal design via particle swarm algorithm

This work proposes a new, efficient, economically, and environmentally viable approach for developing cutting-edge energy systems and assisting the anticipated global green transition with maximal renewable integration. The cogeneration of hydrogen and power is driven by biomass, which in turn drives the vanadium chloride cycle and the proton exchange membrane fuel cells. A cooling absorption unit is powered by waste heat recovered using a passive energy improvement technique to improve performance and cut costs. Energy, exergy, exergo-economic, exergo-environmental impacts, and CO2 emission rate of the suggested renewable-based model are analyzed using an engineering equation solver tool. Parametric analysis is also used to assess the impact of key operational factors on main performance indicators. With machine learning, a particle swarm method is implemented in MATLAB to find the optimal operating state with high precision and low computing cost. The results show the importance of multi-objective optimization by pointing out a conflicting change in the performance metrics from different angles by picking up the biomass moisture content and fuel cell current density. According to the optimization results, an acceptable total cost, environmental damage effectiveness, and exergy efficiency of 5 $/h, 0.86, and 55% are achieved through the integration of particle swarm optimizer and artificial neural network method. The results further reveal that the gasification temperature is not sensitive; however, changing the fuel cell utilization factor significantly impacts the system's performance from all sides. Finally, the chord diagram of the irreversibility rate indicates that the fuel cell and gasifier have the highest destruction of 6.4 kW and 2.6 kW under the optimum condition, owing to mixing and chemical reactions. As for the environmental aspect, by optimizing the system, the system's CO2 emission are greatly reduced.

Neurofuzzy modelling on the influence of Pt–Sn catalyst properties in direct ethanol fuel cells performance: Fuzzy inference system generation and cell power density optimization

Pt-based materials are commonly employed as catalysts in the electrooxidation of ethanol in direct ethanol fuel cells (DEFC). However, due to the complex nature of electrooxidation, the effect of catalyst properties on fuel cell power generation is not easily described by mechanistic models. Fuzzy systems can be used instead precisely for their ability to provide a more direct and qualitative/semiquantitative cause-effect relationship. In this study, a neurofuzzy model was developed to relate the effect of 5 input variables (4 catalyst properties, namely, crystal size, surface area, presence of PtSn phase and Pt L3-edge whiteline integrated intensity, and the cell potential) on cell current density. The fuzzy inference system (FIS) structure was constructed in MATLAB with ANFIS (Adaptive network-based FIS) based on experimental data used for training and validation. A 4-variable FIS (not including integrated intensity) was initially created and used as a basis for developing the 5-variable FIS, thus addressing the issue of fewer experimental data points available for integrated intensity. Both FIS structures exhibited very good fits to experimental data. The addition of integrated intensity as an input variable did not affect the fitted fuzzy model parameters for the other input variables and, therefore, a broader and more relevant model that included an electronic property of the catalyst was created. Response surface analyses, corroborated by particle swarm optimization, indicated that decreasing crystal size has the greatest effect in maximizing power density. Medium potentials and medium integrated intensity are also favorable. In addition, presence of the PtSn phase in moderate amounts is not unfavorable. With these values it was possible to predict the optimization of the power density value to 24.3 mW/cm2, compared to the best experimental value of 19.6 mW/cm2.

Performance analysis and optimization of combined heat and power system based on PEM fuel cell and [formula omitted] type Stirling engine

In this study, a new arrangement of a combined heat and power (CHP) system is proposed, which is designed based on a dual-prime mover of proton exchange membrane (PEM) fuel cell and β type Stirling engine. By using this CHP system based on Stirling engine and fuel cell in hybrid form, the potential of performance improbvement of the system can be analyzed and the appropriate operation condition compared to using the CHP system based on one prime mover can be achieved.Also, two suitable thermodynamic models have been used for modeling the fuel cell and Stirling engine from energy, environmental and economic issues. In addition, the effects of Stirling engine speed, temperature, and fuel cell current density on power, electrical efficiency, CHP efficiency, fuel cost savings, the amount of annual CO2 emission reduction (ACO2ER) and payback period have been investigated for the CHP system. Then, an optimization method has been performed with the help of a two-objective genetic algorithm and the TOPSIS methods, and several optimal cases from different viewpoints of the CHP system are presented. The modeling results showed that to increase the CHP system's efficiency, the engine speed should be in the range of 1500 rpm and to increase the system's capacity, a higher engine speed should be used. Also, based on the payback period analysis, the system has higher economic performance at a higher rotational speed.I addition, increasing the fuel cell's temperature increases the system's power and electrical efficiency. The system's capacity increases with the current density, but the system's efficiency decreases. The optimization results showed that the engine speed, the fuel cell temperature, and the current density are recommended to be 3000 rpm, 94.5 °C, and 0.67 A cm−2, respectively. Suppose the main goal is to maximize the CHP efficiency and ACO2ER simultaneously, the CHP system should be started with a slightly lower engine speed of around 2126 rpm, a lower temperature of around 70.11 °C and a higher current density of around 0.93 A cm−2.

A novel high coefficient of performance electrochemical cooling system developed based on the combined chlorine/bromine‐hydrogen fuel cell and electrolyzer

This paper suggests combining a fuel cell and an electrolyzer to create an electrochemical cooling system. Previously, a cooling system based on hydrogen and oxygen are analyzed, and a low coefficient of performance (COP) is attained. Therefore, in the present investigation, in order to improve the COP of the cooling system, we replace sluggish oxygen reaction with chlorine and bromine, which have faster kinetics. For this purpose, a numerical simulation of the fuel cell and electrolyzer is presented, and then the whole system is analytically modeled. Furthermore, the effects of different critical operating parameters, including electrolyzer current density, the operating temperature of electrolyzer and fuel cell, operating pressure, and exchange current density, are assessed on the cooling system's performance. Results show that increasing the operating temperature of the electrolyzer increases the COP of the cooling system, while the fuel cell temperature has a reverse effect on the COP. Also, increasing the exchanged current density of chlorine and bromine increases the COP; however, beyond a certain, COP does not improve further. The H2/Cl2 and H2/Br2 cooling systems reach COP of about 1.43–2.05 and 1.37–2.94, respectively, which are about 3.3 and 4.1 times the COP of the previously studied H2/O2 cooling system. The recommended cooling system is also competitive with cooling technologies, including vapor compression refrigeration, triple effect absorption, ejector refrigeration cycle, and Malone cycle.

Oxygen transport in the low–Pt catalyst layer of a PEM fuel cell: Impedance spectroscopy study

A model for PEM fuel cell impedance taking into account the pore size distribution (PSD) in the cathode catalyst layer is developed. Experimental PSD is approximated by pores of three sizes (small, medium and large) and in each kind of pores, the oxygen diffusion coefficient is allowed to have a separate value. The model is fitted to experimental impedance spectra of a low–Pt PEM fuel cell. The oxygen diffusivities of small and medium pores exhibit rapid growth with the cell current density, while in large pores, this parameter remains nearly constant. We show that oxygen reduction occurs mainly in the small and medium pores, leaving the large pores for mass transport only. This effect explains the discrepancy between small effective oxygen diffusivity of PEMFC catalyst layer measured in situ in operating cells by limiting current method, and much larger value of this parameter determined from ex situ experiments using Loschmidt cell.

Numerical study of PEMFC heat and mass transfer characteristics based on roughness interface thermal resistance model

The thermal contact resistance (TCR) is the main component of proton exchange membrane fuel cell (PEMFC) thermal resistance due to the existence of surface roughness between the components of PEMFC, and the influence of TCR is often ignored in traditional three dimensional PEMFC simulations. In this paper, the heat and mass transfer characteristics including polarization curve, power density curve, temperature distribution, membrane water content distribution, membrane current density are studied under different component surface roughness conditions, and finally the effect of each TCR on the PEMFC performance is studied. It is found that under the same operating conditions, the TCR makes the radial heat transfer of the PEMFC decrease, and the temperature of the membrane electrode and the temperature difference of each component of the PEMFC is higher than that of the model without TCR. When the surface roughness of components in the PEMFC equals 1 μm, 2 μm, 3 μm, the cell current density decreases by 6.56%, 12.46% and 17.17% respectively when the output cell voltage equals 0.3 V, and the cell power density decreases by 3.64%, 7.54%, 13.14% respectively when the cell current density equals 1.2 A·cm−2. When the TCR between the CL and PEM equals 0.003 K·m2·W−1, 0.005 K·m2·W−1, 0.01 K·m2·W−1, the cell current density is increased by 2.30%, 3.65%, 6.74% respectively under the condition that the output cell voltage equals 0.3 V, and the cell power density is increased by 1.24%, 1.85%, 3.10% respectively when the cell current density equals 1.2 A·cm−2. The results show that the numerical simulation of PEMFC cannot ignore the effect of TCR.

Preparation and characterization of highly active and stable NdBaCo0.8Fe0.8Ni0.4O5+δ oxygen electrode for solid oxide fuel cells

In order to develop high active and stable oxygen electrode for intermediate temperature solid oxide fuel cells (IT-SOFCs), NdBaCo0.8Fe0.8Ni0.4O5+δ (NBCFN) oxygen electrode was successfully prepared by sol-gel method. The NBCFN sample formed a double perovskite structure after calcination at 1100 °C for 10 h. The NBCFN electrode and La0.9Sr0.1Ga0.83Mg0.17O3-δ (LSGM) electrolyte has good chemical compatibility below 950 °C. Compared with NdBaCo2O5+δ, the average thermal expansion coefficient (TEC) of NBCFN sample was 17.2 × 10−6 K-1 at 30 °C - 850 °C in air and decreased by 30%. The conductivity of NBCFN sample exhibited p-type semiconductor conduction and reached 441.8 S cm−1 at 800 °C. The polarization impedance (RP) of NBCFN oxygen electrode on LSGM electrolyte reached 0.055 Ω cm2 at 700 °C. The charge transfer process of NBCFN oxygen electrode was mainly rate-limiting step. The RP of NBCFN oxygen electrode exhibited good stability in air during 200 h test. At 800 °C, the NBCFN oxygen electrode on 300μm-thick LSGM electrolyte reached 1042 mWcm−2 at fuel cell mode and current density was 0.9 A cm−2 at 1.3 V under the electrolysis cell mode, respectively. These results primarily indicated that NBCFN oxygen electrode had good electrochemical performance for IT-SOFCs.

High-current density alkaline electrolyzers: The role of Nafion binder content in the catalyst coatings and techno-economic analysis.

We report high-current density operating alkaline (water) electrolyzers (AELs) based on platinum on Vulcan (Pt/C) cathodes and stainless-steel anodes. By optimizing the binder (Nafion ionomer) and Pt mass loading (mPt) content in the catalysts coating at the cathode side, the AEL can operate at the following (current density, voltage, energy efficiency -based on the hydrogen higher heating value-) conditions (1.0A cm-2, 1.68 V, 87.8%) (2.0A cm-2, 1.85 V, 79.9%) (7.0A cm-2, 2.38 V, 62.3%). The optimal amount of binder content (25wt%) also ensures stable AEL performances, as proved through dedicated intermittent (ON-OFF) accelerated stress tests and continuous operation at 1A cm-2, for which a nearly zero average voltage increase rate was measured over 335h. The designed AELs can therefore reach proton-exchange membrane electrolyzer-like performance, without relying on the use of scarce anode catalysts, namely, iridium. Contrary to common opinions, our preliminary techno-economic analysis shows that the Pt/C cathode-enabled high-current density operation of single cell AELs can also reduce substantially the impact of capital expenditures (CAPEX) on the overall cost of the green hydrogen, leading CAPEX to operating expenses (OPEX) cost ratio <10% for single cell current densities ≥0.8A cm-2. Thus, we estimate a hydrogen production cost as low as $2.06 kgH2 -1 for a 30 years-lifetime 1MW-scale AEL plant using Pt/C cathodes with mPt of 150μg cm-2 and operating at single cell current densities of 0.6-0.8A cm-2. Thus, Pt/C cathodes enable the realization of AELs that can efficiently operate at high current densities, leading to low OPEX while even benefiting the CAPEX due to their superior plant compactness compared to traditional AELs.

Triple-objective optimization and electrochemical/technical/environmental study of biomass gasification process for a novel high-temperature fuel cell/electrolyzer/desalination scheme

To meet demands in agricultural sectors, the way of waste-to-useful products is an alternative to conventional processes capable of generating on-site products. This is an innovative method leading to designing a novel combined system in the current work. By means of a precise chemical and electrochemical simulation, the rice husk (an agricultural biomass fuel) is processed through a gasifier with a steam agent and is utilized in a molten carbonate fuel cell. The fuel cell's waste heat is delivered to thermal-based desalination utilizing humification and dehumidification processes. In addition, a solid oxide electrolyzer cell creates hydrogen by consuming power supplied by the fuel cell. Consequently, the system is able to meet some demands like electricity, irrigation, and chemical fertilizers. Accordingly, the system's applicability is measured by comprehensive electrochemical, technical, and environmental sensitivity analyses along with an advanced triple-objective optimization using the method of artificial neural network (ANN) + multi-objective grey wolf optimization. Regarding the objective functions, i.e., exergetic efficiency (ExEtot), exergoenvironmental impact index (EIItot), and carbon dioxide emission (CDEtot), the optimum state brings ExEtot=29.98%, EIItot=2.28, and CDEtot=391.1kg/MWh. Also, the variability of studied variables is further affected by the fuel cell's current density; its mean sensitivity index equals 0.48.

Machine learning-based simulation for proton exchange membrane electrolyzer cell

This paper presents two systematic machine learning (ML) approaches for predicting the hydrogen production rate and cell current density for proton exchange membrane electrolyzer cells (PEMEC) as a function of different design parameters. Management of the hydrogen production rate and current density remains an important research topic for many technologies, including PEM water electrolysis cells, which are the focus of this study; therefore, two applications of ML were proposed to simulate the hydrogen production rate and current density for PEMEC. In this study, five different ML models were trained and tested for each simulation i.e., artificial neural networks, polynomial regression, support vector machine regressor, K-nearest neighbor regressor, and decision tree regressor, using 15 different input parameters and single output parameters. Box and whisker data analysis was applied to obtain the highest activation materials for the current density in the dataset. The box whisker plots revealed that Nafion115 and Nafion117 for the membrane type, titanium for the electrode type (cathode and anode), platinum (Pt) as the cathode catalyst, Pt and ruthenium as anode catalysts, and deionized water and methanol as the electrolyte (catholyte and anolyte) were the highest activation materials for current density. The performance comparison of the ML models was given by calculating the mean absolute error for the training and test data for each model. For both simulations, the ANN model showed the best performance, with a mean absolute error of 5.0006 for training and 6.4383 for testing for hydrogen production simulation, and 0.03819 for training and 0.04036 for testing for the current density simulation. Both applications have minimal error values, which means that the proposed methods simulate the real PEM cell performance well. This study paves the way for a significant method to reduce the cost, effort, and time required to fabricate PEMEC.

Optimal Dynamic Operation of Grid-Integrated Hydrogen Energy System: A Techno-Economic Analysis

Rapidly decreasing costs of solar energy and policies that encourage decarbonization are driving solar photovoltaic (PV) farms to be paired with large scale and longer duration energy storage. Hydrogen generation from renewable energy can provide long-term, clean energy storage and can be used in the power industry through fuel cells or combustion turbines, used as chemical feedstock for industry, or as a fuel for transportation. Production costs of hydrogen via electrolytic methods mainly depends on the electricity price, capital costs, and equipment capacity factors. To be cost effective with other types of energy storage, a desired hydrogen price of $1/kg by 2030 will be needed. This study focuses on a techno-economic analysis of a grid-integrated microgrid that includes hydrogen systems (i.e. electrolyzer, compressor, storage tank, and stationary fuel cell), high penetration of solar PV, and battery energy storage systems. The microgrid is operated in a way to minimize the total operation and investment costs and maximize the revenue of the microgrid owner by exchanging power with the grid. While previous work [1] (one hour steady-state time steps) considered a fixed conversion efficiency for the electrolyzer, this study focuses on dynamic operation of the electrolyzer using polarization curves and non-linear conversion efficiency (modeled based on actual cell voltage, cell current, and Faraday efficiency) for more realistic results.Simulation results show that the hourly conversion efficiency of the electrolyzer highly depends on stack operating conditions (cell voltage and current density, the size of the electrolyzer, the temperature, hydrogen demand, etc.). This results in different microgrid optimization and scheduling of energy assets, and consequently the hydrogen production cost. Sensitivity analysis on the PV penetration, current density of the electrolyzer, and changes in asset capital costs will be presented.[1] Hamed Haggi, Paul Brooker, Wei Sun, James M. Fenton, “Hydrogen and Battery Storage Technologies for Low-Cost Energy Decarbonization in Distributed Networks”, arXiv, 11 (2022). https://doi.org/10.48550/arXiv.2202.02711

Pairing Gas Diffusion Media for High-Power PEMFC Operation

Proton exchange membrane fuel cell (PEMFC) water management and current density are highly sensitive to the gas diffusion media (GDM) used at both the anode and the cathode. As the gas and mass transport requirements vary at each of these electrodes, the optimal properties for the respective GDM contrast. Utilizing different GDM at the anode and cathode, in an asymmetric GDM pairing, maximizes current densities in a broad range of operating conditions compared to symmetric pairings comprising the same GDM at the anode and cathode. The optimal asymmetric GDM pairing features a highly permeable anode GDM with a high porosity and thick microporous layer (MPL, 80 µm) that is homogeneous in through-plane flux. Alternatively, the cathode GDM is less permeable and has a thinner and less porous MPL (20-45 µm) with a broad flux distribution. Net water drag measurements show that this asymmetric GDM pairing facilitates water retention at the anode and water expulsion from the cathode to realize lower oxygen transport resistance and up to 73% higher current density than PEMFCs with symmetric GDM pairings. Symmetric GDM pairings are insufficient at removing product water from the PEMFC cathode, resulting in greater cathode water saturation. As a result, more product water must back-diffuse across the membrane to be removed from the anode at the expense of significantly greater oxygen transport resistances and concomitantly lower current and power densities than the asymmetric GDM pairing. GDM are characterized by X-ray computed tomography (CT) and scanning electron microscopy (SEM) to reveal differences in MPL carbon type, average pore size, pore character, porosity, pore connectivity, tortuosity, and spatial flux distribution that govern PEMFC gas transport and water management.

Development of ternary Pd-Co-Ir metal nanoparticles decorated on graphene-CNTs hybrid support: An efficient electrocatalyst for hydrogen production from methanol reformation

One of the most effective methods for onsite hydrogen production has been identified as electrochemical methanol reformation (ECMR). However, when it comes to economic viability, it is critical to reduce production costs while improving the specific performance and stability of the electrocatalyst towards hydrogen evolution reaction (HER). To address these issues, we have synthesized Pd2-Co1-Ir1 alloy nanoparticles which were then assembled onto graphene-carbon nanotubes (G-CNTs) through the chemical reduction method. The electrocatalytic activity of the developed electrocatalyst for HER was evaluated through CV, LSV and EIS techniques in an acidic medium. The Pd2-Co1-Ir1/G-CNTs hybrid catalyst showed excellent electrocatalytic activity with high electrochemical surface area (160 m2 g−1), small Tafel slope value (31 mV dec−1), low charge transfer resistance (9 Ω) and long-term stability. Pd2-Co1-Ir1/G-CNTs electrocatalyst showed superior performance at 60 °C cell temperature with a cell voltage and current density of 0.60 V and 250 mA cm−2, respectively, in single ECMR cell as compared to commercially available Pt/C catalyst and other control catalysts in a single ECMR cell. The improvement in electrocatalytic activity could be attributed to the use of G-CNTs as hybrid carbon support and alloying Pd with Co and Ir, which in turn enhanced the electrocatalytic activity of Pd metal.

Performance Enhancement of Inclined Core-Shell Nanowire Solar Cells Using Multivariable Optimization

This paper proposes an optimized high-performance nanowire array solar cell. Three approaches have contributed to achieving the highest possible performance of nanowire solar cells. Inclining the nanowires, adding cores to the nanowires, and finding the optimized design parameters such as inclination angle, core diameter, nanowire length, and the fill factor. Si and GaAs have been used as the core–shell material respectively. A multivariable particle swarm optimization algorithm has been used with the objective of maximizing the efficiency and the nanowire solar cell current density. We could achieve a current density of 58.59 mA/cm2 and a power conversion efficiency (PCE) of 33.52%. The performance parameters of the optimized design such as the absorption, the distribution of the electric field, current density, and efficiency have been calculated and compared with non-optimized structure and other works. According to the obtained results, the superiority of the proposed optimized nanowire solar cell over other designs has been verified.

Design and experimental research of a novel droplet flow field in proton exchange membrane fuel cell

The flow field plays a vital role in the performance and cost of the proton exchange membrane fuel cell (PEMFC). However, the traditional flow field structure cannot meet the high-power density requirements of PEMFC commercialization due to poor mass transport capacity. In addition, new flow field designs have some problems, such as complicated structure, high pressure drop and high manufacturing cost, which make them unsuitable for large-scale applications. In this paper, a novel droplet flow field (DFF) structure is proposed to further improve cell performance and reduce manufacturing cost. In particular, in-situ electrochemical measurement and printed circuit board segmented fuel cell technology are used to investigate the performance of cells with different DFFs. Based on the experimental results, the mass transport mechanism of DFF and its influence on the cell performance and current density distribution are deeply analyzed. The results indicate that DFFs have excellent oxygen transport and water management capabilities, thus improving the cell performance, especially at high current density. By optimizing the droplet placement direction in DFF, we found that the structure with the gas flow direction in contact with the droplet tail (DFF(a)) has the highest cell performance. Compared with the conventional parallel flow field, the maximum power density of the DFF(a) can be increased by 23.7%. Also, the introduction of droplet structure improves the current density distribution uniformity. Furthermore, DFFs have a lower pressure drop, which reduces the pump parasitic power and increases the PEMFC system net output power. Considering the cell performance, current density distribution uniformity and pressure drop, we think that the DFFs (especially the optimized DFF(a)) are more suitable for the practical application of PEMFC.

Shedding Light on Water Management during Operation of AEMFC with Humidity Sensors

The performance of anion exchange membrane fuel cells (AEMFC) has dramatically progressed in the past few years, with initial power performance matching, if not exceeding, those of proton exchange membrane fuel cells (PEMFC). The remaining challenges are i) the replacement of platinum-group-metal catalysts by catalysts based on Earth-abundant elements, ii) improved durability, and iii) the carbonatation issue when the cathode is fed with natural air. Compared to PEMFCs, the water management of AEMFC is more challenging, due to higher flux of water transported from one electrode to the other for a given current density, but also due to the high swelling of anion exchange ionomer (AEI) [1]. An optimized water management was shown to be not only critical for AEMFC power performance [2], but also for the cell stability. The chemical stability of AEM and AEI was recently shown to decrease dramatically with decreasing relative humidity [3]. During AEMFC operation, low humidity is expected on the cathode due to water consumption by the oxygen reduction reaction and due to electroosmotic drag from cathode to anode. While the water management of AEMFC is a recognized challenge, only few works have hitherto investigated it with operando techniques [4-5].In this presentation, we will discuss the application of humidity sensors to measure on-line the relative humidity of the gas outlets of a single-cell AEMFC, allowing us to derive the water balance at each electrode (Figure 1a). The setup was applied to study the water balance and understand how it affects the AEMC power performance, focusing on one type of membrane-electrode assembly, comprising of a state-of-art anode (PtRu/C), cathode (Fe-N-C) and AEM/AEI (low density polyethylene/ethylenetetrafluoroethylene). The effect of dew point, backpressure and flow rates on cell performance and water transport were investigated. As an example of the type of results that can be obtained, Figure 1b shows the water balance at the anode and cathode as a function of time (blue and red curves, respectively), for different galvanostatic holds of 5 min each, from 0.2 to 1.2 A cm-2, at otherwise fixed conditions. As expected, the water balance is positive at the anode, and increases fairly linearly with the current density. Importantly, the water balance at the anode is always lower than the anode water balance expected if all the produced water (through the hydrogen oxidation reaction) would stay in the anode. This implies that the electroosmotic drag effect of water transport from cathode to anode is minor, and that the transport of water from anode to cathode (via back-diffusion, or other mechanism) is significant. As a result, the water balance is also positive at the cathode. Figure 1b shows also the total water balance (green curve), and that it matches with the theoretical total simply derived from the cell current density (black curve). In fact, for all operating conditions tested, the water balance was positive at the cathode, implying that the so-called cathode dry-out seldom occurs in AEMFC. The results also generally show that anode flooding is strongly connected with the maximum current density at which an AEMFC can stably operate. In conclusion, the use of humidity sensors can provide quantified insights on water dynamics in operating AEMFC, providing a tool for understanding optimized operating conditions, or for optimizing materials and components when they are designed to improve water management.