bluuebunny/crossref_metadata_2025_split huggingface dataset:
High Reliability Tungsten-Doped Indium Zinc Oxide Thin Film Transistors for Display Applications
Authors: Deng Jing-Zhong , Chiang Tsung-Che , Li Zhen-Hao , Liu Po-Tsun , Kuo Yue 
Published: February 2024

Abstract

Recently, flat panel display technologies are based on amorphous silicon (a-Si), polycrystalline silicon (poly-Si) or amorphous oxide semiconductor (AOS) thin film transistors (TFTs) technology. In order to reach higher performance for ultra-high resolution display applications, the material selection for the channel layer is vital. AOS TFTs drawn lots of attention because of its advantages such as low leakage current, high driving current and high uniformity [1,3]. In this work, we presented a novel amorphous oxide semiconductor (AOS) material of gallium-free a-InWZnO thin film transistors (IWZO TFTs) which is very promising to be applied for ultra-high resolution display technology.

Experiment

In this work, we demonstrated the structure of a-IWZO TFTs processes. Figure 1 shows the schematic of the TFT cross-section. After growing a 550 nm thermal oxide layer as buffer layer, a 25-nm-thick of molybdenum was deposited by DC-sputter as the bottom gate electrode. A 10-nm-HfO2 was deposited by plasma-enhanced atomic layer deposition (PEALD) system as high-κ gate dielectric (GI). Then, post deposition annealing (PDA) was carried out to enhance the quality of the insulator layer. Next, an ultra-thin body a-IWZO was deposited by RF-sputter as channel layer. Finally, source and drain were defined by lift-off process and the gate contact via was etched by dry etching to finish the device fabrication.

Result and Discussion

Figure 1(b) shows the negative gate bias stress (NGBS) transfer curve (ID-VG) of a-IWZO TFTs with passivation layer. The experimental results have shown that passivation layer could keep the back channel of IWZO channel from exposing to oxygen and hydrogen from the atmosphere. Without the passivation layer, the back channel would contact moisture leading the diffused hydrogen atoms to fill oxygen vacancy sites and de-trap free carriers, causing the VTH shifts negatively. The ultra-thin a-IWZO TFTs with passivation layer exhibited a low subthreshold swing (S.S.) of 89.7 mV/dec, high on/off current ratio (ION/IOFF) of 2.1×107 and small threshold voltage shift (ΔVth) of -0.097 V during NGBS of -2MV/cm with 2000s. To sum up, the passivation layer could enhance the a-IWZO TFTs reliability.

Reference

[1] Kamiya, H. Hosono, NPG Asia Mater., vol. 2, pp. 15, 2010.
[2] Nomura, H. Ohta, A. Takagi, T. Kamiya, M. Hirano, and H. Hosono, nature, vol. 432, no. 7016, pp. 488-492, 2004.
[3] Y. Kuo, C. M. Chang, I. H. Liu, and P. T. Liu, Scientific reports, vol. 9, no. 1, pp. 1-7, 2019.

Figure 1
Integration of Machine Learning Models into Three-Dimensional Numerical Simulation of Polymer Electrolyte Membrane Fuel Cells
Authors: Matsumoto Ryuki , Takayama Tsutomu , Tsukamoto Takayuki , Tsujimura Ippei 
Published: February 2024

Numerical simulations are powerful tools for understanding phenomena in Polymer Electrolyte Membrane Fuel Cells (PEMFCs) and developing PEMFCs with high performance and durability. We have been developing a three-dimensional (3D) PEMFC simulator P-Stack [1]. P-Stack can perform 3D cell/stack simulations for long-time operation about 10 ~ 100 hours at most. However, fuel cell degradation occurs on longer time scales. To simulate such very long time scales within acceptable computational time, the computational speed need to be improved innovatively. As one of the approaches, we have integrated machine learning models into the simulation.
In the power generation calculation of P-Stack, an in-plane current density distribution is determined by calculating a one-dimensional (1D) electrochemical reaction model at each point. In the present study, the 1D electrochemical reaction model is replaced with a machine learning model. The learning data is the result of “pseudo-1D” power generation calculation of 500 cases generated by P-Stack. Here, “pseudo-1D” means the power generation calculation for sampling is performed for small cell geometry, guaranteeing that in-plane distribution is almost homogeneous. It also suitable for sampling calculation because computational cost is very low. In the data generation by P-Stack, the input parameters of P-Stack were determined by Latin hypercube sampling. The input parameters for the machine learning model are the potential, the concentration of each gas species in the anode and cathode catalyst layers, and the temperature. The prediction parameters are current density, cell resistance, overvoltages, molar flux of each gas species and heat flux.
As shown in Figure 1, the machine learning model well predicts the target parameters, and the coefficient of determination was about 0.9 for various prediction targets of the verification data. As a result, machine learning could be used to predict power generation. We have implemented this machine learning model into P-Stack. We will also discuss the stability and accuracy of computation coupled with machine learning model and P-Stack, and how much the calculation can be accelerated by our approach.
Reference
[1] T. Tsukamoto, T. Aoki, H. Kanesaka, T. Taniguchi, T. Takayama, H. Motegi, R. Takayama, S. Tanaka, K. Komiyama, M. Yoneda, J. Power Sources 488 (2021) 229412

Figure 1
A Machine Learning Accelerated Hierarchical 3D+1D Model for Proton Exchange Membrane Fuel Cells
Authors: Pan Yuwei , Ruan Haijun , Regmi Yagya N , Wu Billy , Wang Huizhi , Brandon Nigel 
Published: February 2024

Physics-based continuum models for proton exchange membrane fuel cells (PEMFCs) are an essential tool for fuel cell design and management. To date, many continuum models, ranging from 1D to 3D, have been developed for PEMFCs. Although computationally efficient, 1D models do not account for heterogeneity in flow fields, which negatively impact their accuracy. In contrast, 2D and 3D models are usually more representative of actual operating conditions but computationally intensive due to the coupled partial differential equations and large number of mesh elements involved. To overcome these issues, a hierarchical approach that combines a 2D/3D description of flow fields, gas diffusion layers (GDLs) and a simplified microporous layer (MPL)/catalyst layer (CL)/membrane sub-model has been proposed in the literature. However, studies based on this method often use a simplified or 0D MPL/CL/membrane sub-model, whose results may deviate from a full 1D description due to the neglected nonlinearity, especially at higher loads.
In this study, we present a computationally efficient 3D+1D hierarchical model for PEMFCs accelerated by machine learning. The 3D model, which captures the two-phase flow in the gas channels and GDLs, is coupled with a full 1D description of the MPLs, membrane, CLs, and CL agglomerates by exchanging boundary values and fluxes, as shown in the figure. To avoid the high computing cost increase associated with the full 1D description, we develop a physics-informed neural network to replace the 1D sub-model for coupling with the 3D model, while maintaining the full description of fuel cell internal states. Large synthetic datasets are generated using the 1D model for training the neural network, ensuring the accuracy of the model. The proposed 3D+1D model is validated against experimentally obtained polarization curves and high frequency resistances under different relative humidities. The proposed model is then used to study the nonlinear distribution of the internal states along the thickness direction of the membrane electrode assembly as well as in the 3D flow field. The model is also highly effective in elucidating the dominant voltage loss factor under different operating conditions. Our developed model offers high accuracy at low computing cost under a wide range of operating conditions, potentially aiding the rapid optimization of both the membrane electrode assembly and the gas channel geometry and advance the water and thermal management of existing fuel cell designs.

Figure 1
Influence of Ionomer Chemistry on Oxygen Permeability in Hydrocarbon-Based Proton-Exchange Membrane Fuel Cells
Authors: Liepold Hannes , Nguyen Hien , Münchinger Andreas , Vierrath Severin 
Published: February 2024

The pursuit of alternatives to perfluorinated sulfonic acid (PFSA) materials is of particular interest in light of the global and European mid-term goals to avoid fluorinated materials, and the technical target to operate proton-exchange membrane (PEM) fuel cells at temperatures of 120°C. Non-fluorinated hydrocarbon ionomers offer improved chemical stability at temperatures above 100°C, are less environmentally hazardous, exhibit lower gas crossover, and have the potential to reduce production costs.1 Recent years have seen significant progress in the development of hydrocarbon-based membranes and electrodes, with performance on par with that of state-of-the-art PFSA-based fuel cells under optimized conditions.2 However, a performance gap between hydrocarbon- and PFSA-based PEM fuel cells persists under application-relevant conditions, necessitating an understanding of the limitations that arise. Mass transport-related phenomena, particularly at the ionomer/catalyst interfaces, play a crucial role in controlling PEM fuel cell performance.3 While extensive studies have been conducted for PFSA-based fuel cells to deconvolute the local from the total transport resistance of the cathode catalyst layer, no such studies have been conducted for hydrocarbon ionomers. In this study, we investigated gas transport resistance and its components in hydrocarbon-based PEM fuel cells using H2- and O2 limiting current methods and ex-situ investigations in ionomer thin film behavior, while varying the ionomer's ion-exchange capacity. Our results show that local transport resistances are similar to those measured with PFSA-based cells with respect to different ionomer to carbon mass ratios (I/C). However, higher transport-induced resistances are observed under the potential formation of liquid water in the range of high current densities. We attribute these effects to the more pronounced water uptake of the ionomer thin film compared to the PFSA based reference. Thus, reducing ionomer swelling while maintaining the necessary proton conductivity of the ionomer thin film is crucial for next-generation hydrocarbon PEM fuel cells.
References
(1) H. Nguyen, C. Klose, L. Metzler, S. Vierrath and M. Breitwieser, Adv.
Energy Mater., 2022, 12, 2103559.
(2) H. Nguyen, F. Lombeck, C. Schwarz, P. Heizmann, M. Adamski, H. F. Lee, B. Britton, S. Holdcroft, S. Vierrath and M. Breitwieser, Sustainable Energy Fuels, 2021, 5, 3687–3699.
(3) T. Schuler, A. Chowdhury, A. T. Freiberg, B. Sneed, F. B. Spingler, M. C. Tucker, K. L. More, C. J. Radke and A. Z. Weber, J. Electrochem. Soc
., 2019, 166(9), F3020.
(Poster Award - Honorable Mention) Probing the Catalyst-Ionomer Interface in Catalyst Layers with Sulfo-Phenylated Polyphenylene Ionomers Using CO-Displacement and Stripping Techniques
Authors: Anton Robert James , Sun Shikai , Swider-Lyons Karen , Mittelsteadt Cortney , Adamski Michael , Britton Benjamin , Morimoto Yu , Zenyuk Iryna 
Published: February 2024

Sulfo-phenylated polyphenylene ionomers (sPPP) are a class of hydrocarbon Ionomer being explored as a replacement for the perfluorinated sulfonic acid (PFSA) ionomer in fuel cell membranes and catalyst layers because they do not contain fluorinated compounds. Integration of sPPP ionomers into catalyst layers is challenging, as they have significantly different morphology compared to PFSA-based ionomers. Furthermore, little is known about the resulting ionomer-catalyst interface and whether characterization techniques developed for catalysts layers with PFSA-based ionomers will perform well for catalyst layers containing an sPPP ionomer. In this work, we examine the usefulness of CO displacement and stripping techniques to probe both the electrochemically active surface area (ECSA) of Pt/C in the catalyst layer and adsorbed species on the Pt catalyst sites. For catalyst layers containing PFSA, we measure a strong CO displacement reduction peak at potentials above potential of zero charge, when CO is introduced to the system, corresponding to sulfonic acid groups being displaced from active sites. The range of sulfonic acid groups adsorbed on the surface is 15- 25 % depending on the carbon support used. When the catalyst layers contain an sPPP ionomer instead of PFSA, the CO displacement peak is almost entirely suppressed, resulting in less than 10 % of sulfonic acid group adsorption. This is indicative that sPPP ionomer orientation near the Pt surface is very different compared to PFSA-based ionomer and that sulfonic acid groups do not “poison” Pt when in contact with the sPPP ionomer. However, mass activity increase is not observed for the sPPP ionomer-based catalyst layers, indicating there might be different “poisoning” mechanisms present, perhaps associated with the phenyl rings adsorption [1]. ECSA measurements for MEAs containing the non-fluorinated ionomer catalyst layers align with those measured for PFSA MEAs with the same catalysts type, loading, and comparable ionomer content, indicating that CO stripping is still a useful tool for assessing the ECSA for MEAs.
[1] Zhai, Y., Baturina, O., Ramaker, D., Farquhar, E., St-Pierre, J., & Swider-Lyons, K. (2015). Chlorobenzene Poisoning and Recovery of Platinum-Based Cathodes in Proton Exchange Membrane Fuel Cells. Journal of Physical Chemistry C, 119(35), 20328–20338. https://doi.org/10.1021/acs.jpcc.5b06362
The Porous Structure Design of Catalyst Layer by Controlling Particle Size Distribution of PEMFC Catalyst Ink
Authors: Cho Minju , Cho Sung Yong , Cho Youngick , Lee Ji-Eun , Lee Sungchul , Park Eun-Byeol , Kim Young-Min , Kang Eun Heui 
Published: February 2024

A general catalyst ink of proton exchange membrane fuel cells(PEMFC) consists of a catalyst, its support, an ionomer, and a solvent. These elements are made in the form of membrane electrode assembly(MEA) through grinding, dispersing, and coating processes. Therefore, the preparation of catalyst ink is an important step that directly affects the structure formation of the catalyst layer and the cell performance.
In this study, by controlling the particle size distribution of the catalyst ink, we aim to achieve optimized pore structure in the catalyst layer that leads to improved performance of the fuel cell. Particle size and its distribution of the catalyst ink were confirmed by using particle size analyzer(PSA). Mercury intrusion porosimetry(MIP) was used to determine porous structure, including the pore diameter and total pore volume of MEA. Segmented tomographic evaluation is utilized to evaluate the 3D porous carbon structure in terms of local surface area, pore size distribution, and their 3D networking. MEA were tested to ascertain the influence of the catalyst ink properties on electrochemical character such as H2/air polarization curves, electrochemical impedance spectroscopy(EIS). Also, to analyze the resistance contributed by the molecular and Knudsen diffusion and permeation through the ionomer film, we tested MEA using limiting-current measurements.
As a result, We are able to confirm that the particle size has a high correlation with the pore characteristics of the electrode layer that affect the cell performance. The enhanced electrochemical performance is attributed by decreasing fine particles about 0.1um in size. We figured out that the gas diffusion resistance in the catalyst layer increases as the fine particles increase. The results of this study will provide important insights into the design and fabrication of the catalyst layers in PEMFCs and could potentially lead to improvements in the efficiency of fuel cells.
Observation of Catalyst Layer Structure Formation from Electrode Slurry By White Light Confocal Microscopy
Authors: Suzuki Takahiro , Kirigaya Ryo , Tsushima Shohji 
Published: February 2024

Mass transport in the catalyst layers (CLs) is an important factor to improve the cell performance of polymer electrolyte fuel cells (PEFCs). Transport properties in the CLs are determined by their structure and material distributions. The CLs are usually fabricated from electrode slurry in which Pt/C and ionomer are contained through applying and drying processes. Therefore, the structure and material distributions in the CLs are determined in these fabrication processes. However, these fabrication processes have been developed through trial-and-error approaches. A fundamental understanding of the structure formation mechanisms during the fabrication processes is required.
The authors have performed impedance measurement and surface displacement measurement of electrode slurry during the drying process at the same time and detected the particle packing process (1, 2). For a further understanding of the fabrication process, observation of the structure formation of electrode slurry during drying by white light confocal microscopy was conducted in this study to break down the structure formation regimes. The observation of flow mode on the surface of the slurry and measurement of surface displacement were performed at the same time.
Figure 1 shows confocal images of the electrode slurry during drying. Three different regimes were observed. At the initial state of drying, convection flow was observed. Then, the shrinking of the slurry was observed. After shrinking stopped, the solvent was evaporated from the porous media and finally, the structure of the catalyst layer was formed. Understanding the relationships between the variation of the flow regimes during the drying of electrode slurry and fabrication conditions including materials and process parameters can contribute to revealing the methodology for controlling porous structure and material distributions in the catalyst layers.
Acknowledgments
A part of this work was supported by JST PRESTO JPMJPR22O4.
References
(1) T. Suzuki et al., ECS Trans., 67(17), 465 (2015).
(2) T. Suzuki et al., J. Therm. Sci. Technol., 16(1), 20-00259 (2021).

Figure 1
Analysis of Transmission Line Models for PEMFC Impedance Modelling
Authors: Schwab Kersten , Weber Andre 
Published: February 2024

The behaviour of Polymer Electrolyte Membrane Fuel Cells (PEMFC) shows a complex, non-linear dependence on material properties and operation conditions. Therefore, modelling and model parameterization by electrochemical characterization of PEMFCs is challenging. To deconvolute the different loss mechanisms in PEMFCs, impedance spectra are recorded and modelled by equivalent circuit models. Transmission Line Models (TLMs) are a well-established, physicochemical approach for modelling the impedance of PEMFC electrodes. TLMs consider the processes occurring in an electrode and the model parameters are directly related to material and microstructural characteristics. PEM electrodes have inhomogeneous distributions of the material, the current density, stored water, etc. Assuming a homogeneous electrode with homogeneous current distribution, the basic TLM shown in [1] turned during impedance fitting out to be inaccurate in operation conditions where these assumptions do not hold.
To increase the fit accuracy, literature proposes a number of adapted TLMs. These TLMs have additional components and therefore degrees of freedom. This enables these models to take additional processes and the microstructure into consideration.
In this contribution an incremental 1 cm² PEMFC ensuring zero gradient operation is characterized by means of impedance spectroscopy. Different operating conditions are varied within wide ranges and additional characterization methods, like H2/N2 operation were applied.
Different TLMs proposed in literature are evaluated by fitting them to the measured spectra with and without considering the information gained from additional measurements. The DRT was applied as additional criteria in the fitting.
In general, the accuracy of a fit increased with the number of free fitting parameters. Thus more complex TLMs accounting for additional physicochemical processes provide a lower error in the fit. Nevertheless the physicochemical meaningfulness of the determined model parameters is sometimes uncertain. It will be shown that for a meaningful parameterization by CNLS-fitting such TLMs require additional tests and characterization methods.
[1] Heinzmann Marcel; Weber André; Ivers-Tiffée Ellen. „Impedance modelling of porous electorde structures in polymer electrolyte membrane fuel cells“. In: Journal of Power Sources (2019).
Mass Transport Impedance in a PEMFC with Superhydrophobic Catalyst Layers
Authors: Duque Luis , Molinero Antonio , Oller Juan Carlos , Barcala José Miguel , Díaz-Álvarez Ester , Folgado M. Antonia , Chaparro Antonio M 
Published: February 2024

Electrosprayed catalyst layers improve liquid water management in PEMFCs thanks to their superhydrophobic character [1]. Using appropriate parameters, the electrospray deposition of a suspension of Pt/C powder and ionomer (Nafion solution) gives rise to a macroporous layer with superhydrophobic pores. Under current generation in a PEMFC, superhydrophobicity of the cathodic catalyst layer minimizes water interaction with pores walls, and enhances water transport towards the anode. As a consequence, water distribution inside the cell is more homogeneous, which makes cathode flooding less severe and improves anode humidification. PEMFCs with cathodic electrosprayed catalyst layer have shown higher power production rate at intermediate and high current densities, with peak power densities above 20%-25% compared with conventional, more hydrophilic, catalyst layer under standard testing conditions. We have studied in previous works the transport properties of electrosprayed catalyst layers with a number of techniques, like polarization curves, electrochemical impedance spectroscopy, and hydrogen transport.
In this communication, catalyst layer transport properties in a PEMFC with electrosprayed electrodes are studied with 'Current Modulated Hydrogen Flow Rate Spectroscopy' (CH2S) [2], which is a transport impedance technique relating hydrogen flow rate with faradaic current. With this aim, PEMFCs have been mounted with electrosprayed catalyts layers in anode and in cathode. When in anode, the electrosprayed catalyst layer gives rise to significant differences in the CH2S Nyquist plots and dependent on cell humidification (Fig. 1). The CH2S signals resolve transport kinetics having different characteristic times, that can be assigned to transport in different parts of the anode, like flow-field, gas diffusion layer, microporous layer and catalyst layer. The study is completed with CH2S measurements on PEMFCs with different configurations, having electrosprayed electrodes in anode and cathode. It is concluded that CH2S provides new insights into mass transport properties of gas diffusion electrodes.
Acknowledgements
Funding by PORHYDRO2 project (TED2021-131620B-C22, ‘Preparation and characterisation of catalyst layers fabricated by electrospray for proton exchange fuel cells with passive gas feed’) by the Spanish Ministry of Science and Innovation.
[1] M.A. Folgado, J.J. Conde, P. Ferreira-Aparicio, A.M. Chaparro, Single Cell Study of Water Transport in PEMFCs with Electrosprayed Catalyst Layers, Fuel Cells. 18 (2018) 602–612. https://doi.org/10.1002/fuce.201700217.
[2] L. Duque, A. Molinero, J.C. Oller, J.M. Barcala, M.A. Folgado, A.M. Chaparro, Analysis of Hydrogen Feeding to the Anode of a PEMFC By a Transport Impedance Technique, ECS Meet. Abstr. MA2022-02 (2022) 1406–1406. https://doi.org/10.1149/ma2022-02391406mtgabs.

Figure 1