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OpenAlex Citation Counts

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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:

Kinetics parameter optimization of hydrocarbon fuels via neural ordinary differential equations
Xingyu Su, Weiqi Ji, Jian An, et al.
Combustion and Flame (2023) Vol. 251, pp. 112732-112732
Closed Access | Times Cited: 16

Showing 16 citing articles:

FlamePINN-1D: Physics-informed neural networks to solve forward and inverse problems of 1D laminar flames
Jiahao Wu, Su Zhang, Yuxin Wu, et al.
Combustion and Flame (2025) Vol. 273, pp. 113964-113964
Closed Access | Times Cited: 2
Global reaction neural networks with embedded stoichiometry and thermodynamics for learning kinetics from reactor data
Tim Kircher, Felix Döppel, Martin Votsmeier
Chemical Engineering Journal (2024) Vol. 485, pp. 149863-149863
Open Access | Times Cited: 8
Exploring surface reaction mechanism using a surface reaction neural network framework
Lin Luo, Qimin Liu, Junhao Sun, et al.
Chemical Engineering Science (2025), pp. 121307-121307
Closed Access
Development of compact mechanism for lithium-ion battery venting gas fires using Cantera ordinary differential equation neural network algorithm
Mengjie Li, Hao Hu, Li Lü, et al.
Applications in Energy and Combustion Science (2025), pp. 100326-100326
Open Access
Analysis of structure and interactions between chemical reactions, species transport and heat release in laminar flames
Liang Ji, K. Seshadri
Combustion and Flame (2025) Vol. 275, pp. 114030-114030
Closed Access
A Two‐Stage Training Method for Modeling Constrained Systems With Neural Networks
C. Coelho, M. Fernanda P. Costa, L. L. Ferrás
Journal of Forecasting (2025)
Closed Access
Training stiff neural ordinary differential equations with explicit exponential integration methods
Colby Fronk, Linda Petzold
Chaos An Interdisciplinary Journal of Nonlinear Science (2025) Vol. 35, Iss. 3
Closed Access
A data-driven method to optimize soot kinetics based on uncertainty quantification and the active subspace approach
Xingyu Su, Andrea Nobili, Feixue Cai, et al.
Combustion and Flame (2025) Vol. 276, pp. 114137-114137
Closed Access
A HyChem Model of Polyoxymethylene Dimethyl Ether 5 Optimized with a Differential Evolution Algorithm
Guohua Li, Yujie Tao
ACS Omega (2025)
Open Access
Bayesian polynomial neural networks and polynomial neural ordinary differential equations
Colby Fronk, Jae-Woong Yun, Prashant Singh, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 10, pp. e1012414-e1012414
Open Access | Times Cited: 3
An extended neural ordinary differential equation network with grey system and its applications
Fangxue Zhang, Xinping Xiao, Mingyun Gao
Neurocomputing (2024) Vol. 576, pp. 127343-127343
Closed Access | Times Cited: 2
Training stiff neural ordinary differential equations with implicit single-step methods
Colby Fronk, Linda Petzold
Chaos An Interdisciplinary Journal of Nonlinear Science (2024) Vol. 34, Iss. 12
Open Access | Times Cited: 2
A neural network with embedded stoichiometry and thermodynamics for learning kinetics from reactor data
Tim Kircher, Felix Döppel, Martin Votsmeier
(2023)
Open Access | Times Cited: 5
Artificial intelligence as a catalyst for combustion science and engineering
Matthias Ihme, Wai Tong Chung
Proceedings of the Combustion Institute (2024) Vol. 40, Iss. 1-4, pp. 105730-105730
Closed Access | Times Cited: 1
Development of a Global Mechanism for Ammonia Combustion Assisted by Machine Learning
Jieun Kang, Seong-kyun Im
Journal of the Korean Society of Combustion (2024) Vol. 29, Iss. 2, pp. 37-43
Closed Access
Model-Optimization-guided Neural Network (MOGNN) Applied to Chemical Processes
Felipe Macedo Freitas Siqueira, Lizandro de Sousa Santos
Applied Soft Computing (2024), pp. 112285-112285
Closed Access
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