Prediction of fuel cell performance degradation using a combined approach of machine learning and impedance spectroscopy
Accurate prediction of performance degradation in complex systems such as solid oxide fuel
cells is crucial for expediting technological advancements. However, significant challenges …
cells is crucial for expediting technological advancements. However, significant challenges …
Machine learning based analysis of metal support co-sintering process for solid oxide fuel cells
Porous metals are promising substrate supports of solid oxide fuel cell for the applications of
mobile and high-power density. The process conditions for a suitable mixture of pore former …
mobile and high-power density. The process conditions for a suitable mixture of pore former …
Prediction of electrode microstructure evolutions with physically constrained unsupervised image-to-image translation networks
Microstructure of electrodes determines the performance of electrochemical devices such as
fuel cells and batteries. The efficiency and economic feasibility of these technologies …
fuel cells and batteries. The efficiency and economic feasibility of these technologies …
Enhanced temporal prediction of electrochemical impedance spectroscopy using long short-term memory neural networks
Large-scale applications of many electrochemical energy devices, such as batteries, fuel
cells, and electrolyzers, are hindered by insufficient lifetime and durability. Traditional …
cells, and electrolyzers, are hindered by insufficient lifetime and durability. Traditional …
[HTML][HTML] The exploitation of eigenspectra in electrochemical impedance spectroscopy: Reconstruction of spectra from sparse measurements
Abstract Electrochemical Impedance Spectroscopy (EIS) represents one of the most widely
utilized techniques for the characterization of solid oxide cells (SOCs) and stacks in …
utilized techniques for the characterization of solid oxide cells (SOCs) and stacks in …
Automatic data curation and analysis pipeline for electrochemical impedance spectroscopy measurements conducted on solid oxide cell stacks
In this work, we apply data from Electrochemical Impedance Spectroscopy (EIS)
measurements, conducted on a Solid Oxide Cell (SOC) stack, to an automatic data curation …
measurements, conducted on a Solid Oxide Cell (SOC) stack, to an automatic data curation …
Impact of Electrochemical Impedance Spectroscopy Dataset Curation on Solid Oxide Cell Degradation Assessment
Electrochemical impedance spectroscopy (EIS) has become a standard measurement
technique for detecting degradation in single cells and stacks of solid oxide cells (SOCs) …
technique for detecting degradation in single cells and stacks of solid oxide cells (SOCs) …
Communication—Prediction of Area Specific Resistance of Solid Oxide Cell Stacks from Electrochemical Impedance Spectra
A support vector regression model was trained to predict the area specific resistance of solid
oxide cell stacks from electrochemical impedance spectroscopy measurements. In …
oxide cell stacks from electrochemical impedance spectroscopy measurements. In …
Monitoring of operational conditions of fuel cells by using machine learning
AB Shrote, KK Kumar, C Kaur… - … on Internet of Things, 2024 - publications.eai.eu
The reliability of fuel cells during testing is crucial for their development on test benches. For
the development of fuel cells on test benches, it is essential to maintain their dependability …
the development of fuel cells on test benches, it is essential to maintain their dependability …
A machine learning approach to predict gene expression levels based on stochastic simulation
R King - 2024 - researchsquare.com
Purpose: Genes are key players in cellular systems as they control different aspects of cell
behaviour and progression. Abnormalities in gene activities are indicators of cancer …
behaviour and progression. Abnormalities in gene activities are indicators of cancer …