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In recent years, there has been an increasing demand for forest certification and certified forest products in Europe. This trend is related to major worldwide challenges, such as the need to decarbonize the economy and mitigate climate change but also social and consumer demands for wider fair trade. However, whether forest certification influences economic valorization in forestry remains a question. The aim of this study is to analyze forest certification levels across Europe and identify potential relationships between the level of certification in forest areas and relevant economic indicators at country level. This study collected openly available data on total and certified forest areas, economic indicators, and environmental indicators for 28 European countries and explored the correlation between certified forest areas and economic performance in the forestry sector. Findings show that forest certification can significantly improve the economic performance of European forests. It has a more pronounced positive effect on economic incomes than on costs' reduction. While certification costs do rise with the extent of forest area, they tend to stabilize at larger scales, suggesting that the certification process is economically sustainable and scale is relevant. Czechia and the Netherlands stand out for having the highest net values added related to forest certification, reflecting an effective economic exploration of forest resources. This study offers new perspectives to natural and social scientists, as well as to industry and policy makers, by proving contextualized data to support decision making. Additionally, it provides hints for further studies and policy guidelines on sustainable development and the impact of forest certification schemes. [ABSTRACT FROM AUTHOR]

Fibrous carbon has attracted attention for use as a carbon support of polymer electrolyte fuel cells (PEFC). In this study, Marimo carbon (MC), a fibrous carbon, was used as the carbon support. The MC has a higher order structure in which many carbon nanofilaments (CNFs) are grown on the surface of diamond particles (dia.). The MC was synthesized by the contact reaction between a Ni supported oxidized diamond (Ni/O-dia.) and CH 4 gas, the carbon source of the CNFs. The flow rate of the CH 4 gas during the MC synthesis altered the structure of the CNFs. A thick CNFs was observed in the MC with a low CH 4 gas flow rate, which was not observed in the MC with a high CH 4 gas flow rate. The MC with the thicker CNFs had wider interspaces between the CNFs and higher Pt supporting amounts. Electrochemical measurements of the Pt support MC (Pt/MC) were evaluated by cyclic voltammetry (CV), linear sweep voltammetry (LSV) and current–voltage (I–V) measurements. The lower CH 4 gas flow rate of the MC indicated faster charge transfer. The MC structural and charge transfer changed with the flow rate of the CH 4 gas altered the electrochemical active surface area (ECSA), the oxygen reduction reaction (ORR) catalytic activity and the I–V performance of the Pt/MC. • Highly ordered structure of fibers (MC) was used as a catalyst support for PEFC. • Flow rate of the CH 4 gas during MC synthesis altered interspaces between CNFs. • Flow rate of the CH 4 gas during MC synthesis altered charge transfer of Pt/MC. • I–V performance of Pt/MC1000 was high in high current density region. • Maximum power density of Pt/MC1000 was 1.4 times higher than that of Pt/CB. [ABSTRACT FROM AUTHOR]

In recent years, there has been an increasing demand for forest certification and certified forest products in Europe. This trend is related to major worldwide challenges, such as the need to decarbonize the economy and mitigate climate change but also social and consumer demands for wider fair trade. However, whether forest certification influences economic valorization in forestry remains a question. The aim of this study is to analyze forest certification levels across Europe and identify potential relationships between the level of certification in forest areas and relevant economic indicators at country level. This study collected openly available data on total and certified forest areas, economic indicators, and environmental indicators for 28 European countries and explored the correlation between certified forest areas and economic performance in the forestry sector. Findings show that forest certification can significantly improve the economic performance of European forests. It has a more pronounced positive effect on economic incomes than on costs’ reduction. While certification costs do rise with the extent of forest area, they tend to stabilize at larger scales, suggesting that the certification process is economically sustainable and scale is relevant. Czechia and the Netherlands stand out for having the highest net values added related to forest certification, reflecting an effective economic exploration of forest resources. This study offers new perspectives to natural and social scientists, as well as to industry and policy makers, by proving contextualized data to support decision making. Additionally, it provides hints for further studies and policy guidelines on sustainable development and the impact of forest certification schemes.

Next-generation polymer electrolyte fuel cells (PEFCs) require an integral design of the porous structure of electrodes at different scales to improve performance and enlarge durability while reducing cost. One of today's biggest challenges is the stable, high-performance operation at low Pt loading due to the detrimental effect of the local oxygen transport resistance caused by ionomer around catalyst sites. Hindered local oxygen transport arises from sluggish kinetics at the local reaction environment, that comprises adsorption at (wet) ionomer and Pt interfaces, and diffusivity of gas species in ionomer and water. Diverse factors affect oxygen transport, including operating conditions (relative humidity, temperature, and pressure), ionomer content and morphology, ionomer heterogeneity, porosity of carbon support, catalyst dispersity, and flooding. To attain performance and durability targets, it is essential to maximize the oxygen utilization of the catalyst layer by implementing enhanced membrane electrode assembly architectures. This involves employing advanced catalyst layer preparation techniques, including electrospraying, to generate optimized highly porous morphologies. Furthermore, achieving these targets necessitates the development of new materials with tailored properties, such as high permeability and porous ionomers, among other innovative strategies. [ABSTRACT FROM AUTHOR]

Abstract The growing energy demand and population raising require alternative, clean, and sustainable energy systems. During the last few years, hydrogen energy has proven to be a crucial factor under the current conditions. Although the energy conversion process in polymer electrolyte fuel cells (PEFCs) is clean and noiseless since the only by-products are heat and water, the inside phenomena are not simple. As a result, correct monitoring of the health situation of the device is required to perform efficiently. This paper aims to explore and evaluate the machine learning (ML) and deep learning (DL) models for predicting classification fault detection in PEFCs. It represents a support for decision-making by the fuel cell operator or user. Seven ML and DL model classifiers are considered. A database comprising 182,156 records and 20 variables arising from the fuel cell's energy conversion process and operating conditions is considered. This dataset is unbalanced; therefore, techniques to balance are applied and analyzed in the training and testing of several models. The results showed that the logistic regression (LR), k-nearest neighbor (KNN), decision tree (DT), random forest (RF), and Naive Bayes (NB) models present similar and optimal trends in terms of performance indicators and computational cost; unlike support vector machine (SMV) and multi-layer perceptron (MLP) whose performance is affected when the data is balanced and even presents a higher computational cost. Therefore, it is a novel approach for fault detection analysis in PEFC that combines the interpretability of different ML and DL algorithms while addressing data imbalance, so common in the real world, using resampling techniques. This methodology provides clear information for the model decision-making process, improving confidence and facilitating further optimization; in contrast to traditional physics-based models, paving the way for data-driven control strategies.

The growing energy demand and population raising require alternative, clean, and sustainable energy systems. During the last few years, hydrogen energy has proven to be a crucial factor under the current conditions. Although the energy conversion process in polymer electrolyte fuel cells (PEFCs) is clean and noiseless since the only by-products are heat and water, the inside phenomena are not simple. As a result, correct monitoring of the health situation of the device is required to perform efficiently. This paper aims to explore and evaluate the machine learning (ML) and deep learning (DL) models for predicting classification fault detection in PEFCs. It represents a support for decision-making by the fuel cell operator or user. Seven ML and DL model classifiers are considered. A database comprising 182,156 records and 20 variables arising from the fuel cell's energy conversion process and operating conditions is considered. This dataset is unbalanced; therefore, techniques to balance are applied and analyzed in the training and testing of several models. The results showed that the logistic regression (LR), k-nearest neighbor (KNN), decision tree (DT), random forest (RF), and Naive Bayes (NB) models present similar and optimal trends in terms of performance indicators and computational cost; unlike support vector machine (SMV) and multi-layer perceptron (MLP) whose performance is affected when the data is balanced and even presents a higher computational cost. Therefore, it is a novel approach for fault detection analysis in PEFC that combines the interpretability of different ML and DL algorithms while addressing data imbalance, so common in the real world, using resampling techniques. This methodology provides clear information for the model decision-making process, improving confidence and facilitating further optimization; in contrast to traditional physics-based models, paving the way for data-driven control strategies. [ABSTRACT FROM AUTHOR]

In recent years, sustainable forest management has proved to be a crucial issue for forestry companies becoming more and more sensitive to environmental problems. This resulted in the inherent expansion in forest certifications formally promoting long-term environmental sustainability and a wider spectrum of forest ecosystems. In this context this study aims to assess the main motivations that encourage the adoption of sustainable forest management certification for PEFC and FSC standards and how these motivations vary depending on the characteristics of the companies. Specifically, online questionnaire surveys were submitted to a sample of Italian and German forest owners and managers considering five main motivational factors offered by the economic literature: three external mechanisms represented by the market, signalling and legal mechanism and two internal mechanisms consisting of the moral and learning mechanism. Results highlighted that the main drivers are represented for both countries by the reporting mechanism, in particular certification is seen as a tool to demonstrate externally the implementation of sustainable forest management practices. Other mechanisms that guide the intentions of forest owners and managers include the legal mechanism, in particular in the Italian case, especially for publicly owned forest areas, more driven by the interest of complying with forestry regulations and the moral mechanism, in the case of Germany. The implications of this research are seen in development of forest certification, through understanding forest owners' reasons for adopting it and providing background information to improve the design of certification programs to attract greater adoption by forest companies. [ABSTRACT FROM AUTHOR]

Next-generation polymer electrolyte fuel cells (PEFCs) require an integral design of the porous structure of electrodes at different scales to improve performance and enlarge durability while reducing cost. One of today’s biggest challenges is the stable, high-performance operation at low Pt loading due to the detrimental effect of the local oxygen transport resistance caused by ionomer around catalyst sites. Hindered local oxygen transport arises from sluggish kinetics at the local reaction environment, that comprises adsorption at (wet) ionomer and Pt interfaces, and diffusivity of gas species in ionomer and water. Diverse factors affect oxygen transport, including operating conditions (relative humidity, temperature, and pressure), ionomer content and morphology, ionomer heterogeneity, porosity of carbon support, catalyst dispersity, and flooding. To attain performance and durability targets, it is essential to maximize the oxygen utilization of the catalyst layer by implementing enhanced membrane electrode assembly architectures. This involves employing advanced catalyst layer preparation techniques, including electrospraying, to generate optimized highly porous morphologies. Furthermore, achieving these targets necessitates the development of new materials with tailored properties, such as high permeability and porous ionomers, among other innovative strategies.

The through-plane gas permeability and morphology of PEFC gas diffusion media (GDM) is investigated for different microporous layer (MPL) ink homogenisation techniques (bath sonication and magnetic stirring) for low- (Vulcan XC-72R) and high (Ketjenblack EC-300J)-surface-area carbon powders. The MPL composition is held constant at 80 wt.% carbon powder and 20 wt.% PTFE for a carbon loading of 1.0 mg cm−2. The MPL ink homogenisation time is held constant at two hours for both techniques and increased by one hour for bath sonication to compare with previous investigations. The results show that the through-plane gas permeability of the GDM is approximately doubled using magnetic stirring when compared with bath sonication for MPLs composed of Vulcan XC-72R, with a negligible change in surface morphology between the structures produced from either homogenisation technique. The variation in through-plane gas permeability is almost negligible for MPLs composed of Ketjenblack EC-300J compared with Vulcan XC-72R; however, MPL surface morphology changes considerably with bath sonication, producing smoother, less cracked surfaces compared to the large cracks produced via magnetic stirring for a large-surface-area carbon powder. An MPL ink sonication time of three hours results in a percentage reduction in through-plane gas permeability from the GDL substrate permeability by ~72% for Ketjenblack EC-300J compared to ~47% for two hours. [ABSTRACT FROM AUTHOR]

Surface coverages of ionomer on Pt and carbon support are key properties to clarify the ionomer distribution in cathode catalyst layer of polymer electrolyte fuel cells. However, their measurement is highly challenging especially for carbon, where Faradaic charge is not visible in voltammograms. Conventionally, the capacitance measured by voltammetry or electrochemical impedance spectroscopy is used to determine the ionomer coverage. In these methods, surface coverages are obtained by comparing the double layer capacitance at wet condition with that at dry condition; Pt and carbon surfaces covered by ionomer and water contributes to the capacitance at wet condition, while surfaces covered only by the ionomer contributes at the dry condition because of the absence of water. However, when measured capacitance is converted to surface area, the methods assume that the specific capacitance (capacitance per surface area) is independent of the humidity although it significantly changes in reality, because the double layer structure of ionomer changes. Here, we propose an alternative method that significantly suppresses the change in specific capacitance. The method was applied to porous and nonporous carbon supports with Pt nanoparticle catalyst. The measurement also indicates that the surface coverages on both Pt and carbon are reduced in the case of the porous carbon. [ABSTRACT FROM AUTHOR]

In the past, platinum–copper catalysts have proven to be highly active for the oxygen reduction reaction (ORR), but transferring the high activities measured in thin-film rotating disk electrodes (TF-RDEs) to high-performing membrane electrode assemblies (MEAs) has proven difficult due to stability issues during operation. High initial performance can be achieved. However, fast performance decay on a timescale of 24 h is induced by repeated voltage load steps with H2/air supplied. This performance decay is accelerated if high relative humidity (>60% RH) is set for a prolonged time and low voltages are applied during polarization. The reasons and possible solutions for this issue have been investigated by means of electrochemical impedance spectroscopy and distribution of relaxation time analysis (EIS–DRT). The affected electrochemical sub-processes have been identified by comparing the PtCu electrocatalyst with commercial Pt/C benchmark materials in homemade catalyst-coated membranes (CCMs). The proton transport resistance (Rpt) increased by a factor of ~2 compared to the benchmark materials. These results provide important insight into the challenges encountered with the de-alloyed PtCu/KB electrocatalyst during cell break-in and operation. This provides a basis for improvements in the catalysts' design and break-in procedures for the highly attractive PtCu/KB catalyst system. [ABSTRACT FROM AUTHOR]

A new method for measuring membrane degradation in polymer electrolyte fuel cells (PEFCs) is proposed. The method is based on the detection of fluoride ions in effluent water from the cathode- and anode outlet of the PEFC using photometry (PM). The fluoride emission rate (FER) is an indicator of the membrane's state of health (SoH) and can be used to measure the chemical membrane degradation. Commercial catalyst-coated membranes (CCMs) have been tested at 80 °C and 90 °C at 30% relative humidity (RH) to investigate the reliability of the developed method for fuel cell effluent samples. To verify the measurement, a mean-difference plot was created by measuring the same data with a fluorine selective electrode. The average difference was at ±0.13 nmol h−1 cm−2, which indicates good agreement between the two methods. These new findings imply that PM is a promising method for quick and simple assessment of membrane degradation in PEM technology. [ABSTRACT FROM AUTHOR]

In hydrogen energy systems, the polymer electrolyte fuel cell (PEFC) is an important component. The purpose of this study is to clarify the effect of separator thickness (s.t.) in PEFC on the distributions of mass such as H2, O2, H2O and current density when PEFC is operated at 363 K and 373 K. The relative humidity (RH) of supply gases also impacts the operation. The numerical simulation (using a 3D model) with COMSOL Multiphysics has been conducted to analyze the characteristics of PEFC. It has been observed that the molar concentration of H2 using s.t. of 2.0 mm is smaller compared with the thinner s.t. cases at the initial operation temperature of a cell (Tini) = 363 K and 373 K. The molar concentration of O2 using s.t. of 2.0 mm is smaller compared with the thinner s.t. cases at Tini = 373 K, as well as the case for the RH of supply gases at the anode of 40%RH and cathode of 40%RH (A40%RH/C40%RH) irrespective of Tini. Additionally, it has been clarified that the molar concentration of H2O maintains a low value along with the gas channel at Tini = 373 K using s.t. of 1.5 mm and 1.0 mm. Moreover, it has been clarified that the current density using s.t. of 2.0 mm is the highest among the different s.t. irrespective of Tini, which is the most remarkable in the case of A40%RH&C40%RH. [ABSTRACT FROM AUTHOR]

The material characteristics of gas diffusion layers are relevant for the efficient operation of polymer electrolyte fuel cells. The current state-of-the-art calculates these using transport simulations based on their micro-structures, either reconstructed or generated by means of stochastic geometry models. Such transport simulations often require high computational resources. To support material characterization using artificial-intelligence-based methods, in this study, a convolutional neural network was developed. It was trained with results from previous transport simulations and validated using five-fold cross-validation. The neural network enables the permeability of paper-type gas diffusion layers to be predicted. A stochastic arrangement of the fibers, four types of binder distributions, and compression of up to 50% are also considered. The binder type and compression level were features inherent to the material but were not the subject of the training. In this regard, they can be seen as features hidden from the training process. Nevertheless, these characteristics were reproduced with the proposed machine learning model. With a trained machine learning model, the prediction of permeability can be performed on a standard computer. [ABSTRACT FROM AUTHOR]

This paper explores the process of sustainability transformation on pulp and paper industry in Indonesia, including the factors driving sustainability, challenges of integrating sustainability, and current best practices in the industry. We used a qualitative research methodology, interview and examine sustainability reports of APP and APRIL, two leading pulp and paper companies in Indonesia. We find a total of 4 drivers and 2 main challenges in the transformation process. The four drivers are: risk and risk reduction, expectation of key stakeholders, i.e., market, consumers, investors, society; competitive advantage, and top management. The two main challenges are the initial investment required and the lack of competence to manage the alleged paradox of improving environmental, social, and economic goals at the same time. However, despite the challenges presented, we find that the transformational process has resulted in a positive impact for the companies’ triple bottom line.

The through-plane gas permeability and morphology of PEFC gas diffusion media (GDM) is investigated for different microporous layer (MPL) ink homogenisation techniques (bath sonication and magnetic stirring) for low- (Vulcan XC-72R) and high (Ketjenblack EC-300J)-surface-area carbon powders. The MPL composition is held constant at 80 wt.% carbon powder and 20 wt.% PTFE for a carbon loading of 1.0 mg cm−2. The MPL ink homogenisation time is held constant at two hours for both techniques and increased by one hour for bath sonication to compare with previous investigations. The results show that the through-plane gas permeability of the GDM is approximately doubled using magnetic stirring when compared with bath sonication for MPLs composed of Vulcan XC-72R, with a negligible change in surface morphology between the structures produced from either homogenisation technique. The variation in through-plane gas permeability is almost negligible for MPLs composed of Ketjenblack EC-300J compared with Vulcan XC-72R; however, MPL surface morphology changes considerably with bath sonication, producing smoother, less cracked surfaces compared to the large cracks produced via magnetic stirring for a large-surface-area carbon powder. An MPL ink sonication time of three hours results in a percentage reduction in through-plane gas permeability from the GDL substrate permeability by ~72% for Ketjenblack EC-300J compared to ~47% for two hours.

The aim of this study is to clarify the impact of the thickness of a gas diffusion layer (GDL) and a micro porous layer (MPL) on the distributions of gas, H2O, and current density in a polymer electrolyte fuel cell (PEFC) which is operated at 363 K and 373 K and with various thicknesses of polymer electrolyte membrane (PEM) as well as a relative humidity (RH) of supply gas. These investigations are carried out by numerical simulation using the 3D model with COMSOL Multiphysics. In the case of Nafion 115, which is the thicker PEM, the change in the molar concentration of H2O from the inlet to the outlet with MPL is larger than that without MPL irrespective of the thickness of GDL, Tini and RH condition. In the case of Nafion NRE-212, which is the thinner PEM, the change in the molar concentration of H2O from the inlet to the outlet is larger with MPL than that without MPL in the case of TGP-H-060 (the thicker commercial GDL), while that is smaller with MPL than that without MPL in the case of TGP-H-030 (the thinner commercial GDL). These results exhibit the same tendency as the results of the numerical simulation on the current density. [ABSTRACT FROM AUTHOR]

In the past, platinum–copper catalysts have proven to be highly active for the oxygen reduction reaction (ORR), but transferring the high activities measured in thin-film rotating disk electrodes (TF-RDEs) to high-performing membrane electrode assemblies (MEAs) has proven difficult due to stability issues during operation. High initial performance can be achieved. However, fast performance decay on a timescale of 24 h is induced by repeated voltage load steps with H2/air supplied. This performance decay is accelerated if high relative humidity (>60% RH) is set for a prolonged time and low voltages are applied during polarization. The reasons and possible solutions for this issue have been investigated by means of electrochemical impedance spectroscopy and distribution of relaxation time analysis (EIS–DRT). The affected electrochemical sub-processes have been identified by comparing the PtCu electrocatalyst with commercial Pt/C benchmark materials in homemade catalyst-coated membranes (CCMs). The proton transport resistance (Rpt) increased by a factor of ~2 compared to the benchmark materials. These results provide important insight into the challenges encountered with the de-alloyed PtCu/KB electrocatalyst during cell break-in and operation. This provides a basis for improvements in the catalysts’ design and break-in procedures for the highly attractive PtCu/KB catalyst system.

In practical applications of polymer electrolyte fuel cells (PEFC), the wide variations of local structures and environment of electrocatalysts bring about complex reaction behaviours inside a membrane electrode assembly (MEA). The variations of local coordination structure and redox response of a Pt/C cathode catalyst in an MEA before and after a typical accelerated degradation test (ADT) were three‐dimensionally visualized by operando Pt LIII‐edge computed‐tomography X‐ray absorption fine structure (CT‐XAFS) imaging under PEFC operating conditions for the first time. The set of operando CT‐XANES and CT‐EXAFS analyses visualized changes in the local coordination structure and redox reactivity of the Pt catalyst by a typical ADT process. [ABSTRACT FROM AUTHOR]

Pd–Y 2 O 3 on carbon (Pd–Y 2 O 3 /C) in different mass ratios of Pd to Y 2 O 3 (1:1, 2:1, 3:1) were prepared and subjected as cathode electrocatalyst for polymer electrolyte fuel cells (PEFC). X-ray diffraction (XRD) and transmission electron microscopy (TEM) were used to determine the structure, crystalline size and dispersion of Pd–Y 2 O 3 /C respectively. The electrochemical characterizations of the electrocatalysts were evaluated from Cyclic Voltammetry (CV) and Linear Sweep Voltammetry (LSV). These electrocatalysts were evaluated for their catalytic activity towards oxygen reduction reaction (ORR) in fuel cell. Pd 2 –Y 2 O 3 /C catalyst shows higher power density of 325 mW cm−2 than Pd 1 –Y 2 O 3 /C, Pd 3 –Y 2 O 3 /C and Pd/C. • Various atomic ratios of Pd–Y 2 O 3 /C prepared and evaluated as ORR catalyst for PEFC. • Pd 2 –Y 2 O 3 /C as a cathode catalyst shows high peak power density of 325 mW cm−2. • Pd 2 –Y 2 O 3 /C exhibits higher ORR activity due to SMSI effect. [ABSTRACT FROM AUTHOR]

A new method for measuring membrane degradation in polymer electrolyte fuel cells (PEFCs) is proposed. The method is based on the detection of fluoride ions in effluent water from the cathode- and anode outlet of the PEFC using photometry (PM). The fluoride emission rate (FER) is an indicator of the membrane’s state of health (SoH) and can be used to measure the chemical membrane degradation. Commercial catalyst-coated membranes (CCMs) have been tested at 80 °C and 90 °C at 30% relative humidity (RH) to investigate the reliability of the developed method for fuel cell effluent samples. To verify the measurement, a mean-difference plot was created by measuring the same data with a fluorine selective electrode. The average difference was at ±0.13 nmol h−1 cm−2, which indicates good agreement between the two methods. These new findings imply that PM is a promising method for quick and simple assessment of membrane degradation in PEM technology.

In hydrogen energy systems, the polymer electrolyte fuel cell (PEFC) is an important component. The purpose of this study is to clarify the effect of separator thickness (s.t.) in PEFC on the distributions of mass such as H2, O2, H2O and current density when PEFC is operated at 363 K and 373 K. The relative humidity (RH) of supply gases also impacts the operation. The numerical simulation (using a 3D model) with COMSOL Multiphysics has been conducted to analyze the characteristics of PEFC. It has been observed that the molar concentration of H2 using s.t. of 2.0 mm is smaller compared with the thinner s.t. cases at the initial operation temperature of a cell (Tini) = 363 K and 373 K. The molar concentration of O2 using s.t. of 2.0 mm is smaller compared with the thinner s.t. cases at Tini = 373 K, as well as the case for the RH of supply gases at the anode of 40%RH and cathode of 40%RH (A40%RH/C40%RH) irrespective of Tini. Additionally, it has been clarified that the molar concentration of H2O maintains a low value along with the gas channel at Tini = 373 K using s.t. of 1.5 mm and 1.0 mm. Moreover, it has been clarified that the current density using s.t. of 2.0 mm is the highest among the different s.t. irrespective of Tini, which is the most remarkable in the case of A40%RH&C40%RH.

The polymer electrolyte fuel cell (PEFC) is one of the strongest candidates for a next-generation power source for vehicles which do not emit CO2 gas as exhaust gas. The key factor in PEFCs is the nano-scaled electrochemical reactions that take place on the catalyst material and an ionomer supported by a carbon support. However, because the nano-scaled morphological features of the key materials in the catalyst compound cannot be observed clearly by transmission electron microscopy, improvement of PEFC performance had been approached by an imaginal schematic diagram based on an electrochemical analysis. In this study, we revealed the nano-scaled morphological features of the PEFC electrode in three dimensions and performed a quantitative analysis of the nanostructure by the newly developed 'Combined ADF-STEM tomography technique'. This method combines information from plural annular darkfield detectors with different electron collection angles and can emphasize the difference of the electron scattering intensity between the ionomer and carbon in the cross-sectional image of the reconstructed three-dimensional (3D) data. Therefore, this segmentation method utilizing image contrast does not require a high electron beam current like that used in energy dispersive X-ray analysis, and thus is suitable for electron beam damage-sensitive materials. By eliminating the process of manually determining the thresholds for obtaining classified component data from grayscale data, the obtained 3D structures have sufficient accuracy to allow quantitative analysis and specify the nano-scaled structural parameters directly related to power generation characteristics., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Japanese Society of Microscopy.)

The material characteristics of gas diffusion layers are relevant for the efficient operation of polymer electrolyte fuel cells. The current state-of-the-art calculates these using transport simulations based on their micro-structures, either reconstructed or generated by means of stochastic geometry models. Such transport simulations often require high computational resources. To support material characterization using artificial-intelligence-based methods, in this study, a convolutional neural network was developed. It was trained with results from previous transport simulations and validated using five-fold cross-validation. The neural network enables the permeability of paper-type gas diffusion layers to be predicted. A stochastic arrangement of the fibers, four types of binder distributions, and compression of up to 50% are also considered. The binder type and compression level were features inherent to the material but were not the subject of the training. In this regard, they can be seen as features hidden from the training process. Nevertheless, these characteristics were reproduced with the proposed machine learning model. With a trained machine learning model, the prediction of permeability can be performed on a standard computer.

The study investigates the freezing behavior of supercooled water in gas diffusion layers (GDLs) of polymer electrolyte fuel cells (PEFCs). Using an innovative advanced in situ differential scanning calorimetry (advanced DSC) technique, we analyze phase transitions within GDLs at a single-cell scale, excluding impacts of catalyst layers and membranes. This method overcomes the limitations of traditional DSC, allowing variable water saturation and distribution. We find that freezing-thawing and drying-saturating cycles contribute to noticeable variations in the freezing temperature (T o n s e t ) of supercooled water, ranging from −6 °C to −15 °C, attributed to the heterogeneous surface of GDL and water redistribution. Repeated drying-saturating cycles remove nucleation seeds, lowering the freezing point of water − a "cleaning effect." The freezing probability reduces at lower saturation levels, influenced by waterproof treatment uniformity on GDLs. Residual ice can be detrimental to the cold-start capability of PEFCs, as it promotes freezing of supercooled water around −1 °C. Our findings enhance understanding of water behavior in GDLs and its impact on PEFC cold-start performance. Applying this technique to other cell components, such as the catalyst layer, could further elucidate water freezing dynamics in PEFCs and guide the innovation of more reliable cell components for PEFC applications in broader climates. • In situ differential calorimetric observation of water freezing behavior in GDLs. • Noticeable inter-cycle variations explains the stochastic cold-start operation time. • Freezing temperature decreases with lower saturation level. • Understanding of how GDL property influences crystallization. • Discovery of the presence "0 °C freezing" and "cleaning effect" in GDL. [ABSTRACT FROM AUTHOR]

The aim of this study is to clarify the impact of the thickness of a gas diffusion layer (GDL) and a micro porous layer (MPL) on the distributions of gas, H2O, and current density in a polymer electrolyte fuel cell (PEFC) which is operated at 363 K and 373 K and with various thicknesses of polymer electrolyte membrane (PEM) as well as a relative humidity (RH) of supply gas. These investigations are carried out by numerical simulation using the 3D model with COMSOL Multiphysics. In the case of Nafion 115, which is the thicker PEM, the change in the molar concentration of H2O from the inlet to the outlet with MPL is larger than that without MPL irrespective of the thickness of GDL, Tini and RH condition. In the case of Nafion NRE-212, which is the thinner PEM, the change in the molar concentration of H2O from the inlet to the outlet is larger with MPL than that without MPL in the case of TGP-H-060 (the thicker commercial GDL), while that is smaller with MPL than that without MPL in the case of TGP-H-030 (the thinner commercial GDL). These results exhibit the same tendency as the results of the numerical simulation on the current density.

Perfluorinated sulfonic acid (PFSA) polymers such as Nafion® are widely used for both electrolyte membranes and ionomers in the catalytic layer of membrane-electrode assemblies (MEAs) because of their high protonic conductivity, σH, as well as chemical and thermal stability. The use of PFSA polymers with shorter side chains and lower equivalent weight (EW) than Nafion®, such as Aquivion® PFSA ionomers, is a valid approach to improve fuel cell performance and stability under drastic operative conditions such as those related to automotive applications. In this context, it is necessary to optimize the composition of the catalytic ink, according to the different ionomer characteristics. In this work, the influence of the ionomer amount in the catalytic layer was studied, considering the dispersing agent used to prepare the electrode (water or ethanol). Electrochemical studies were carried out in a single cell in the presence of H2-air, at intermediate temperatures (80–95 °C), low pressure, and reduced humidity ((50% RH). %). The best fuel cell performance was found for 26 wt.% Aquivion® at the electrodes using ethanol for the ink preparation, associated to a maximum catalyst utilization.

[Display omitted] • The mass of carbon-free Ti 4 O 7 synthesized in a single reaction, the production batch size increased with vanadium doping. • The production batch size increased with an increase in the vanadium-to-titanium atomic ratio up to 0.10. • Tetravalent/trivalent vanadium cations compensated charge imbalance for the creation of Ti 4 O 7 phase. • Strong metal-support interactions between platinum nanoparticles and the optimized (Ti 0.91 V 0.09) 4 O 7 was observed. The most conductive Magnèli phase titanium suboxide, Ti 4 O 7 , has attracted increasing attention as a carbon-free conductive material due to its high electrical conductivity and electrochemical stability. However, this material has not been widely used in applications as a result of the difficulty of its mass production to limit the number of suppliers. In this study, a new and inexpensive route to increase the production batch size, i.e., the mass of carbon-free Ti 4 O 7 synthesized in a single reaction, was developed. By simply doping vanadium into Ti 4 O 7 via a conventional high-temperature synthesis route, the production batch size was successfully increased to 2 g. Vanadium (V) cations were found to not exist in the V5+ form, instead being reduced to V4+/V3+ in the Ti 4 O 7 lattice without segregating to form other phases, and the production batch size increased with an increase in the vanadium-to-titanium atomic ratio up to 0.10. The optimized (Ti 0.91 V 0.09) 4 O 7 material can be used in polymer electrolyte fuel cell cathodes and is promising for use in many other applications. [ABSTRACT FROM AUTHOR]

Evaporative cooling has the potential to reduce stack and system volume of polymer electrolyte fuel cells by up to 30% and to cut costs significantly by simplifying the multi-layered structure of bipolar plates and eliminating the need for external humidification. This study provides an experimental proof of concept by analyzing the evaporation behavior, cooling power, internal humidification, electrochemical performance and operational stability of evaporative cooling under technical cell boundary conditions. Isothermal in situ as well as operando studies are carried out in an evaporatively cooled fuel cell (15 cm2 active area, 80 °C, ambient pressure). Relative humidity boundary conditions imitate the inlet, center and outlet of a technical cell. Main findings show that the evaporation rate is saturation limited at low gas velocities, whereas it is transport limited at higher gas speed. Operando measurements prove that evaporative cooling works at a technical cell level with multiple water supply lines. The entire waste heat is removed and sufficient membrane humidification is achieved when dry inlet gases are used. Furthermore, it is shown that optimal performance is achieved in a counter-flow arrangement. The observed electrochemical performance is comparable to conventional cooling with humidified gases at inlet, center and outlet of the cell. • Operando evaporative cooling analysis in a technical single cell. • Evaporation is saturation limited at low and transport limited at high gas speed. • Counter-flow is identified as optimal arrangement for evaporative cooling. • Sufficient membrane humidification is provided by evaporative cooling. • The performance is comparable to conventional cooling with humidified gases. [ABSTRACT FROM AUTHOR]

Forest certification has become a strategic instrument for businesses, particularly for accessing sensitive environmental markets and within sustainability commitments. This trend is also visible in Spain, where PEFC (Program for the Endorsement of Forest Certification) certification has increased by 91% in the past five years. However, there is a weak understanding of the certification impacts at the level of companies, especially when it comes to economic impacts. This study applies a longitudinal methodology to measure financial performance before and after obtaining PEFC-certification in Spain by analysing treatment and selection effects. The results show significant differences in economic profitability and turnover between certified and non-certified companies prior to certification. However, these differences are not significant in subsequent periods. Therefore, we could not confirm a treatment effect between forest certification and improved financial performance. Instead, we find a positive selection effect: companies with better financial performance have a greater propensity for certification, as has been previously detected for standards such as ISO 9001/14001. Compared to previous studies that predominantly assess economic impacts qualitatively, we use economic-financial data to avoid possible distortion emerging from perceptions and opinions. The main contribution of this study lies in the quantitative assessment of the impacts of forest certification on economic profitability and turnover. [ABSTRACT FROM AUTHOR]

Evaporative cooling is a promising concept to reduce the fuel cell system volume and mass significantly. This paper investigates the interactions between the fuel cell stack and the balance of plant in an evaporatively cooled polymer electrolyte fuel cell system (PEFCS). For this, a zero-dimensional PEFCS model, comprising the fuel cell stack, air compressor, charge air cooler, humidifier, hydrogen recirculation blower, condensing radiator and water separator has been developed and analyzed. Two evaporative cooling system architectures are compared to conventional, liquid cooling. Optimal operating conditions are determined by a numerical optimization of the net system power output. Main results show that evaporative cooling works on the system level over a wide range of operating conditions. The optimum system power and highest efficiencies are achieved at high temperatures (80–90 °C), low pressure (125–150 kPa) and a corresponding cathode stoichiometry between 1.5 and 3, allowing for a closed water loop at the same time. The air compressor shows an increased power demand, compared to conventional cooling and the exhaust gas condenser is identified as the one critical component for evaporative cooling. Its performance is key to an efficient operation and closed water loop at all ambient conditions. • Interactions between evaporatively cooled PEFC stack and auxiliaries are analyzed. • Optimized operating conditions for evaporatively cooled systems are quantified. • A closed water loop is possible over a wide range of operating conditions. • An efficiency map for evaporative cooling is proposed. • The condenser is identified as the one critical component for evaporative cooling. [ABSTRACT FROM AUTHOR]

• A multiscale strategy of the agglomerate-scale and 1D half-cell model is proposed. • Reactive transport process of oxygen and water vapor in agglomerates is modelled. • Partition coefficient is vital to achieve local resistance and concentration drop. • Local transport resistance is sensitive to the electrode structural parameters. • Uniformly dispersed platinum on carbon is favored to minimize local resistance. The reactive transport processes occurred in catalyst layer of a polymer electrolyte fuel cell (PEFC) are essential to characterize the local transport resistance, which acts as an essential barrier for cost reduction. A multiscale strategy was developed to model the coupled transport behaviors of oxygen and water in different reconstructed agglomerates and the transport phenomenon of reactant species and charges in a 1-D cathode catalyst layer. The local transport resistances sensitive to the electrode structural parameters were well captured and compared with existing experimental studies and analytical expressions. Results show that the agglomerate morphology characterizing the heterogenous carbon particles and ionomer distributions can well reproduce the structure-dependent local transport resistance. The local transport resistance increases linearly with the ionomer content and ω /(1- ω) value, where ω is the platinum mass fraction in catalyzed Pt/C mixtures, and increases exponentially with the uncatalyzed volume fraction of carbon. Contribution of pores to the total electrode resistance and the oxygen transport resistance in gas diffusion layer and gas channel are critical to determine the limiting current density at high platinum loading. The mean size of primary pores increases with the proportion of primary porosity in agglomerates, which is favored to minimize the local transport resistance. [ABSTRACT FROM AUTHOR]

Perfluorinated sulfonic acid (PFSA) polymers such as Nafion® are widely used for both electrolyte membranes and ionomers in the catalytic layer of membrane-electrode assemblies (MEAs) because of their high protonic conductivity, σH, as well as chemical and thermal stability. The use of PFSA polymers with shorter side chains and lower equivalent weight (EW) than Nafion®, such as Aquivion® PFSA ionomers, is a valid approach to improve fuel cell performance and stability under drastic operative conditions such as those related to automotive applications. In this context, it is necessary to optimize the composition of the catalytic ink, according to the different ionomer characteristics. In this work, the influence of the ionomer amount in the catalytic layer was studied, considering the dispersing agent used to prepare the electrode (water or ethanol). Electrochemical studies were carried out in a single cell in the presence of H2-air, at intermediate temperatures (80–95 °C), low pressure, and reduced humidity ((50% RH). %). The best fuel cell performance was found for 26 wt.% Aquivion® at the electrodes using ethanol for the ink preparation, associated to a maximum catalyst utilization. [ABSTRACT FROM AUTHOR]

• Analysis of inductive loops in EIS measurements of an open-cathode PEFC stack. • Impedance model to predict inductive loops in PEFC-EIS measurements. • Inductive loops associated to water vapour diffusion in cathode catalyst layer. • Relation between trend of inductive loops and phase angle in EIS measurements. In this study, an impedance model of a polymer electrolyte fuel cell (PEFC) is considered to simulate inductive loops at low frequencies from electrochemical impedance spectroscopy (EIS) measurements carried out in an open-cathode PEFC stack. The new impedance model proposed in this study is derived from the hypothesis that water vapour transport in the cathode catalyst layer (CCL) yields the formation of inductive loops at low frequencies. The impedance model of the PEFC considers the impedance model of the CCL reported in a previous study and considers an analytical expression for the impedance of water vapour diffusion in the CCL. The developed PEFC impedance model is validated with EIS measurements featuring inductive loops at low frequencies and carried out in the individual cells comprising an open-cathode PEFC stack at two current densities. The parameters related to the impedance of water vapour diffusion simulate the inductive loops at low frequencies and simulate a change of the size of the impedance spectrum of the PEFC. Therefore, the formation of inductive loops at low frequencies can be attributed to not only water vapour transport, but also ionomer swelling/shrinking (hydration/dehydration) in the CCL. The impedance model can provide an insight into the relation between the trend of the inductive loops at low frequency and the change in the phase angle in the EIS measurements which can indicate the hydrated state in the membrane-electrode assembly of the individual cells of the open-cathode PEFC stack. [ABSTRACT FROM AUTHOR]