Article
Computer Science, Information Systems
Henrique P. Correa, Flavio H. T. Vieira
Summary: A new method for extracting parameters of the ETPQM model for solar cell I-V characteristics is proposed in this paper, which achieves better accuracy and shorter execution time through introducing a new I-V point condition and low-complexity search procedure.
Article
Physics, Applied
Yen-Pu Chen, Bikram K. Mahajan, Dhanoop Varghese, Srikanth Krishnan, Vijay Reddy, Muhammad A. Alam
Summary: Unlike traditional logic transistors, hot carrier degradation in power transistors involves simultaneous and potentially correlated degradation in multiple regions. Understanding and characterizing the voltage- and temperature-dependence of these region-specific degradations is crucial for developing predictive HCD models. This Letter presents a new three-point I-V spectroscopy technique using a physics-based tandem-FET model to extract mobility and threshold voltage degradations in the channel and drift regions of an LDMOS transistor, which could be generalized to other LDMOS transistor configurations.
APPLIED PHYSICS LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Chien-Ting Tung, Ming-Yen Kao, Chenming Hu
Summary: This paper presents a neural network-based device modeling framework that accurately models advanced FETs. Both I-V and C-V characteristics are studied, and a speed comparison with traditional models shows the potential of neural networks in accelerating circuit simulation.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2022)
Article
Energy & Fuels
Jun Shen, Changqing Du, Fuwu Yan, Ben Chen, Zhengkai Tu
Summary: A novel methodology for fitting polarization curves of PEMFC is proposed based on genetic algorithm, and the results show good agreement with experimental data. Furthermore, a dynamic model is used to investigate the transient response of PEMFC, and the simulation results match well with experimental data, indicating the reliability of the method for polarization curve fitting.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Energy & Fuels
Zhenheng Liu, Li Liu, Yuying Zhou
Summary: As the issues of energy crisis and environmental pollution worsen, research on clean energy is gaining more attention. This study focuses on a closed PEMFC structure in an air-starved environment, establishing mathematical models and conducting simulation verification.
Article
Energy & Fuels
Lei Fan, Jianhua Gao, Yanda Lu, Wei Shen, Su Zhou
Summary: By establishing a novel PEMFC model based on component properties, the effects of component degradation on different indexes were studied. The results showed that the extent of performance degradation varied among different components.
Article
Computer Science, Artificial Intelligence
Xuan Li, Peijun Ye, Juanjuan Li, Zhongmin Liu, Longbing Cao, Fei-Yue Wang
Summary: This article introduces the theoretical framework of scenarios engineering for building trustworthy AI techniques. It proposes six key dimensions, such as intelligence and index, calibration and certification, and verification and validation, to achieve more robust and trusting AI.
IEEE INTELLIGENT SYSTEMS
(2022)
Article
Energy & Fuels
Bing Li, Kechuang Wan, Meng Xie, Tiankuo Chu, Xiaolei Wang, Xiang Li, Daijun Yang, Pingwen Ming, Cunman Zhang
Summary: The durability of the proton exchange membrane fuel cell (PEMFC) stack is crucial for commercial applications. This study analyzed the degradation mechanism and performance consistency of a 3-cell PEMFC stack after a 1600-hour durability test. The voltage degradation rates were found to be 12.2% and 52.2 uV h(-1) at a current density of 1000 mA cm(-2). The performance degradation was attributed to catalyst loss and agglomeration, as well as structural damage to the membrane and catalyst layer. The findings have great potential for promoting the development of PEMFC stacks in automotive applications.
Article
Thermodynamics
Xi Chen, Jianghai Xu, Chen Yang, Ye Fang, Wenbin Li, Yan Zhang, Zhongmin Wan, Xiaodong Wang
Summary: This study established a degradation model to predict the lifetime and degradation progress of PEMFC stack, revealing that high working current accelerates cell degradation and reduces the lifetime of PEMFC stack. Additionally, it was found that the fuel consumption and total cost of PEMFC stack increase with the rise of degradation rate.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Energy & Fuels
Hong Chen, Zhigang Zhan, Panxing Jiang, Yahao Sun, Liwen Liao, Xiongbiao Wan, Qing Du, Xiaosong Chen, Hao Song, Ruijie Zhu, Zhanhong Shu, Shang Li, Mu Pan
Summary: Understanding the degradation mechanism and accurately predicting the remaining useful life of proton exchange membrane fuel cells is crucial for improving durability and reducing operation costs. Through a study on the lifetime of a fuel cell, it was found that catalyst degradation was the main factor contributing to voltage degradation, with membrane degradation and increase in MEA mass transfer resistance playing increasingly significant roles in the latter stage of the lifetime. The influence of evolutions to the internal resistance was determined to be negligible.
Article
Chemistry, Physical
Tiankuo Chu, Meng Xie, Jia Hao, Zichun Xu, Yantao Li, Daijun Yang, Bing Li, Pingwen Ming, Cunman Zhang
Summary: The durability of metal plate proton exchange membrane fuel cell (PEMFC) stack is a crucial factor influencing its widespread commercial application. In this study, a 1000 h durability test was conducted on a 1 kW metal plate PEMFC stack to investigate the degradation of its core components. The results revealed that the stack exhibited a voltage decay percentage of 5.67% after 1000 h of dynamic load cycles at a current density of 1000 mA cm-2. SEM analysis showed contamination on the surfaces of the metal plates due to organic matter precipitation from the membrane electrode assembly (MEA). Additionally, severe degradation in the MEA, including catalyst layer agglomeration, thinning, and perforation of the proton exchange membrane (PEM), were identified as the main factors contributing to the increased hydrogen crossover flow rate and performance decay of the PEMFC stack.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Chemistry, Physical
Huipeng Niu, Changwei Ji, Shuofeng Wang, Chen Liang
Summary: This study analyzes the resistance relaxation characteristic of polymer electrolyte membrane fuel cells (PEMFC) under different pretreatment methods before low-temperature storage. The impact of residual water in different locations of PEMFC on its storage performance after thermal cycles is investigated. The results suggest that the relaxation of resistance may be caused by reorganization of the water structure in the membrane, and the performance degradation after freeze/thaw cycles is associated with water freezing between ionomers and Pt particles.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Chemistry, Physical
Lixin Fan, Junjie Zhao, Xiaobing Luo, Zhengkai Tu
Summary: This paper investigates the degradation characteristics of PEMFCs with Pt black and Pt/C catalysts, and finds that the performance degradation of Pt black catalyst is more severe than that of Pt/C catalyst, mainly due to the different decay mechanisms of these two catalysts.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Nanoscience & Nanotechnology
Raghunandan Sharma, Per Morgen, Serguei Chiriaev, Peter Brilner Lund, Mikkel Juul Larsen, Bertil Sieborg, Laila Grahl-Madsen, Shuang Ma Andersen
Summary: This study investigated the structural characteristics of a low-temperature polymer electrolyte membrane fuel cell subjected to long-term durability testing. The results showed that while the electrocatalysts did not significantly degrade, the degradation of Nafion was the primary mechanism for performance degradation. Mitigating the degradation of the ionomer is an important strategy for improving the durability of PEMFCs.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Thermodynamics
Nicolas Sbirrazzuoli
Summary: This study simulated three different complex multi-step reaction mechanisms, including parallel-competing, consecutive, and parallel-independent reactions, using two sets of different kinetic parameters. The analysis of thermoanalytical curves and E alpha-dependencies, combined with model-fitting approach, can elucidate reaction mechanisms and estimate kinetic parameters for each step.
THERMOCHIMICA ACTA
(2023)
Article
Construction & Building Technology
L. Mao, S. J. Barnett, A. Tyas, J. Warren, G. K. Schleyer, S. S. Zaini
CONSTRUCTION AND BUILDING MATERIALS
(2015)
Article
Electrochemistry
L. Mao, L. Jackson, S. Dunnett
Article
Chemistry, Physical
Lei Mao, Lisa Jackson
JOURNAL OF POWER SOURCES
(2016)
Article
Acoustics
Lei Mao, Yong Lu
JOURNAL OF SOUND AND VIBRATION
(2016)
Article
Energy & Fuels
Lei Mao, Ben Davies, Lisa Jackson
Article
Engineering, Civil
Lei Mao, Yong Lu
ENGINEERING STRUCTURES
(2017)
Article
Chemistry, Physical
L. Mao, L. Jackson, B. Davies
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2018)
Article
Engineering, Mechanical
L. Mao, S. J. Barnett
INTERNATIONAL JOURNAL OF IMPACT ENGINEERING
(2017)
Article
Chemistry, Physical
Lei Mao, Lisa Jackson, Tom Jackson
JOURNAL OF POWER SOURCES
(2017)
Article
Automation & Control Systems
Lei Mao, Lisa Jackson, Ben Davies
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2018)
Article
Chemistry, Analytical
Lei Mao, Lisa Jackson
Article
Energy & Fuels
Heng Zhang, Zhongyong Liu, Weilai Liu, Lei Mao
Summary: This paper proposes a novel approach for diagnosing improper water content in proton exchange membrane fuel cell (PEMFC) using a two-dimensional convolutional neural network (2D-CNN). The trained 2D-CNN model achieves a diagnostic accuracy of 97.5% for PEMFC membrane improper water content. The proposed method exhibits better noise robustness compared to a one-dimensional convolutional neural network (1D-CNN). Additionally, t-distributed Stochastic Neighbor Embedding (t-SNE) is used to visualize the feature separability. Overall, the effectiveness of using 2D-CNN for diagnosing PEMFC membrane improper water content is explored.
Article
Engineering, Civil
Chuanchuan Hou, Lei Mao, Yong Lu
SMART STRUCTURES AND SYSTEMS
(2017)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Jiang Xie, Junfu Xu, Celine Nie, Qing Nie
HIGH PERFORMANCE COMPUTING AND APPLICATIONS, HPCA 2015
(2016)