OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Performance Evaluation of Convolutional Auto Encoders for the Reconstruction of Li-Ion Battery Electrode Microstructure
Mona Faraji Niri, Jimiama Mafeni Mase, James Marco
Energies (2022) Vol. 15, Iss. 12, pp. 4489-4489
Open Access | Times Cited: 13
Mona Faraji Niri, Jimiama Mafeni Mase, James Marco
Energies (2022) Vol. 15, Iss. 12, pp. 4489-4489
Open Access | Times Cited: 13
Showing 13 citing articles:
Leveraging machine learning in porous media
Mostafa Delpisheh, Benyamin Ebrahimpour, Abolfazl Fattahi, et al.
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 32, pp. 20717-20782
Open Access | Times Cited: 8
Mostafa Delpisheh, Benyamin Ebrahimpour, Abolfazl Fattahi, et al.
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 32, pp. 20717-20782
Open Access | Times Cited: 8
Reconstructing Microstructures From Statistical Descriptors Using Neural Cellular Automata
Paul Seibert, Alexander Raßloff, Yichi Zhang, et al.
Integrating materials and manufacturing innovation (2024) Vol. 13, Iss. 1, pp. 272-287
Open Access | Times Cited: 7
Paul Seibert, Alexander Raßloff, Yichi Zhang, et al.
Integrating materials and manufacturing innovation (2024) Vol. 13, Iss. 1, pp. 272-287
Open Access | Times Cited: 7
DA-VEGAN: Differentiably Augmenting VAE-GAN for microstructure reconstruction from extremely small data sets
Yichi Zhang, Paul Seibert, Alexandra Otto, et al.
Computational Materials Science (2023) Vol. 232, pp. 112661-112661
Open Access | Times Cited: 19
Yichi Zhang, Paul Seibert, Alexandra Otto, et al.
Computational Materials Science (2023) Vol. 232, pp. 112661-112661
Open Access | Times Cited: 19
Machine Learning in Lithium‐Ion Battery Cell Production: A Comprehensive Mapping Study
Sajedeh Haghi, Marc Francis V. Hidalgo, Mona Faraji Niri, et al.
Batteries & Supercaps (2023) Vol. 6, Iss. 7
Open Access | Times Cited: 16
Sajedeh Haghi, Marc Francis V. Hidalgo, Mona Faraji Niri, et al.
Batteries & Supercaps (2023) Vol. 6, Iss. 7
Open Access | Times Cited: 16
MFCC Selection by LASSO for Honey Bee Classification
Urszula Libal, Paweł Biernacki
Applied Sciences (2024) Vol. 14, Iss. 2, pp. 913-913
Open Access | Times Cited: 5
Urszula Libal, Paweł Biernacki
Applied Sciences (2024) Vol. 14, Iss. 2, pp. 913-913
Open Access | Times Cited: 5
A Review of the Applications of Explainable Machine Learning for Lithium–Ion Batteries: From Production to State and Performance Estimation
Mona Faraji Niri, Koorosh Aslansefat, Sajedeh Haghi, et al.
Energies (2023) Vol. 16, Iss. 17, pp. 6360-6360
Open Access | Times Cited: 15
Mona Faraji Niri, Koorosh Aslansefat, Sajedeh Haghi, et al.
Energies (2023) Vol. 16, Iss. 17, pp. 6360-6360
Open Access | Times Cited: 15
Intelligent Prediction of Electrode Characteristics Based on Neural Networks in the Lithium-ion Battery Production Chain
Tianxin Chen, Xin Lai, Fei Chen, et al.
Green Energy and Intelligent Transportation (2025), pp. 100294-100294
Open Access
Tianxin Chen, Xin Lai, Fei Chen, et al.
Green Energy and Intelligent Transportation (2025), pp. 100294-100294
Open Access
A Novel Fusion Approach Consisting of GAN and State-of-Charge Estimator for Synthetic Battery Operation Data Generation
Kei Long Wong, Ka Seng Chou, Rita Tse, et al.
Electronics (2023) Vol. 12, Iss. 3, pp. 657-657
Open Access | Times Cited: 11
Kei Long Wong, Ka Seng Chou, Rita Tse, et al.
Electronics (2023) Vol. 12, Iss. 3, pp. 657-657
Open Access | Times Cited: 11
Current trends on the use of deep learning methods for image analysis in energy applications
Mattia Casini, Paolo De Angelis, Eliodoro Chiavazzo, et al.
Energy and AI (2023) Vol. 15, pp. 100330-100330
Open Access | Times Cited: 7
Mattia Casini, Paolo De Angelis, Eliodoro Chiavazzo, et al.
Energy and AI (2023) Vol. 15, pp. 100330-100330
Open Access | Times Cited: 7
Big Data Analytics for the Inspection of Battery Materials
Thomas Lang, Anja Heim, Christoph Heinzl
e-Journal of Nondestructive Testing (2024) Vol. 29, Iss. 3
Open Access | Times Cited: 2
Thomas Lang, Anja Heim, Christoph Heinzl
e-Journal of Nondestructive Testing (2024) Vol. 29, Iss. 3
Open Access | Times Cited: 2
Swift Prediction of Battery Performance: Applying Machine Learning Models on Microstructural Electrode Images for Lithium-Ion Batteries
Patrick Deeg, Christian Weisenberger, Jonas Oehm, et al.
Batteries (2024) Vol. 10, Iss. 3, pp. 99-99
Open Access | Times Cited: 1
Patrick Deeg, Christian Weisenberger, Jonas Oehm, et al.
Batteries (2024) Vol. 10, Iss. 3, pp. 99-99
Open Access | Times Cited: 1
Empowering lithium-ion battery manufacturing with big data: Current status, challenges, and future
Tianxin Chen, Xin Lai, Fei Chen, et al.
Journal of Power Sources (2024) Vol. 623, pp. 235400-235400
Closed Access | Times Cited: 1
Tianxin Chen, Xin Lai, Fei Chen, et al.
Journal of Power Sources (2024) Vol. 623, pp. 235400-235400
Closed Access | Times Cited: 1
Fast descriptor-based 2D and 3D microstructure reconstruction using the Portilla–Simoncelli algorithm
Paul Seibert, Alexander Raßloff, Karl A. Kalina, et al.
Engineering With Computers (2024)
Open Access
Paul Seibert, Alexander Raßloff, Karl A. Kalina, et al.
Engineering With Computers (2024)
Open Access
Fast descriptor-based 2D and 3D microstructure reconstruction using the Portilla-Simoncelli algorithm
Paul Seibert, Alexander Raßloff, Karl A. Kalina, et al.
Research Square (Research Square) (2023)
Open Access
Paul Seibert, Alexander Raßloff, Karl A. Kalina, et al.
Research Square (Research Square) (2023)
Open Access
