Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Recent advances in knowledge discovery for heterogeneous catalysis using machine learning
M. Erdem Günay, Ramazan Yıldırım
Catalysis Reviews (2020) Vol. 63, Iss. 1, pp. 120-164
Closed Access | Times Cited: 86

Showing 1-25 of 86 citing articles:

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery
Haoxin Mai, Tu C. Le, Dehong Chen, et al.
Chemical Reviews (2022) Vol. 122, Iss. 16, pp. 13478-13515
Closed Access | Times Cited: 270
Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage
Daniel Rangel-Martínez, K.D.P. Nigam, Luis Ricardez‐Sandoval
Process Safety and Environmental Protection (2021) Vol. 174, pp. 414-441
Closed Access | Times Cited: 177
Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation
Çiğdem Altıntaş, Ömer Faruk Altundal, Seda Keskın, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 5, pp. 2131-2146
Open Access | Times Cited: 172
Machine learning for advanced energy materials
Liu Yun, Oladapo Christopher Esan, Zhefei Pan, et al.
Energy and AI (2021) Vol. 3, pp. 100049-100049
Open Access | Times Cited: 152
Data‐Driven High‐Throughput Rational Design of Double‐Atom Catalysts for Oxygen Evolution and Reduction
Lianping Wu, Tian Guo, Teng Li
Advanced Functional Materials (2022) Vol. 32, Iss. 31
Open Access | Times Cited: 77
Advancement of modification engineering in lean methane combustion catalysts based on defect chemistry
Ruishan Qiu, Wei Wang, Zhe Wang, et al.
Catalysis Science & Technology (2023) Vol. 13, Iss. 8, pp. 2566-2584
Closed Access | Times Cited: 53
Machine Learning Descriptors for Data‐Driven Catalysis Study
Li‐Hui Mou, TianTian Han, Pieter E. S. Smith, et al.
Advanced Science (2023) Vol. 10, Iss. 22
Open Access | Times Cited: 51
Recent developments and current trends on catalytic dry reforming of Methane: Hydrogen Production, thermodynamics analysis, techno feasibility, and machine learning
Mohammed Mosaad Awad, Esraa Kotob, Omer Ahmed Taialla, et al.
Energy Conversion and Management (2024) Vol. 304, pp. 118252-118252
Closed Access | Times Cited: 27
From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design
Jorge Benavides-Hernández, Franck Dumeignil
ACS Catalysis (2024) Vol. 14, Iss. 15, pp. 11749-11779
Closed Access | Times Cited: 24
Combining machine learning and metal–organic frameworks research: Novel modeling, performance prediction, and materials discovery
Chunhua Li, Luqian Bao, Yixin Ji, et al.
Coordination Chemistry Reviews (2024) Vol. 514, pp. 215888-215888
Closed Access | Times Cited: 18
AI in single-atom catalysts: a review of design and applications
Qijun Yu, Ninggui Ma, Chihon Leung, et al.
Journal of Materials Informatics (2025) Vol. 5, Iss. 1
Open Access | Times Cited: 2
Machine Learning for Transition-Metal-Based Hydrogen Generation Electrocatalysts
Min Wang, Hongwei Zhu
ACS Catalysis (2021) Vol. 11, Iss. 7, pp. 3930-3937
Closed Access | Times Cited: 70
Machine learning for design principles for single atom catalysts towards electrochemical reactions
Mohsen Tamtaji, Hanyu Gao, Md Delowar Hossain, et al.
Journal of Materials Chemistry A (2022) Vol. 10, Iss. 29, pp. 15309-15331
Open Access | Times Cited: 69
Quo vadis multiscale modeling in reaction engineering? – A perspective
Gregor D. Wehinger, Matteo Ambrosetti, Raffaele Cheula, et al.
Process Safety and Environmental Protection (2022) Vol. 184, pp. 39-58
Open Access | Times Cited: 51
Automation and machine learning augmented by large language models in a catalysis study
Yuming Su, Xue Wang, Yuanxiang Ye, et al.
Chemical Science (2024) Vol. 15, Iss. 31, pp. 12200-12233
Open Access | Times Cited: 13
Microalgal biorefineries: Advancement in machine learning tools for sustainable biofuel production and value-added products recovery
S. Kavitha, Yukesh Kannah Ravi, Gopalakrishnan Kumar, et al.
Journal of Environmental Management (2024) Vol. 353, pp. 120135-120135
Closed Access | Times Cited: 11
Application of density functional theory and machine learning in heterogenous-based catalytic reactions for hydrogen production
Lord Ugwu, Yasser Morgan, Hussameldin Ibrahim
International Journal of Hydrogen Energy (2021) Vol. 47, Iss. 4, pp. 2245-2267
Closed Access | Times Cited: 47
Transmission x-ray microscopy and its applications in battery material research—a short review
Stephanie Spence, Wah-Keat Lee, Feng Lin, et al.
Nanotechnology (2021) Vol. 32, Iss. 44, pp. 442003-442003
Open Access | Times Cited: 42
Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities
Idil Ismail, Raphael Chantreau Majerus, Scott Habershon
The Journal of Physical Chemistry A (2022) Vol. 126, Iss. 40, pp. 7051-7069
Open Access | Times Cited: 31
Identifying Descriptors for Promoted Rhodium-Based Catalysts for Higher Alcohol Synthesis via Machine Learning
Manu Suvarna, Phil Preikschas, Javier Pérez‐Ramírez
ACS Catalysis (2022) Vol. 12, Iss. 24, pp. 15373-15385
Open Access | Times Cited: 29
Analysis of PEM and AEM electrolysis by neural network pattern recognition, association rule mining and LIME
M. Erdem Günay, Niyazi Alper Tapan
Energy and AI (2023) Vol. 13, pp. 100254-100254
Open Access | Times Cited: 21
A critical review of machine learning for lignocellulosic ethanol production via fermentation route
Ahmet Coşgun, M. Erdem Günay, Ramazan Yıldırım
Biofuel Research Journal (2023) Vol. 10, Iss. 2, pp. 1859-1875
Open Access | Times Cited: 21
Machine learning for algal biofuels: a critical review and perspective for the future
Ahmet Çoşgun, M. Erdem Günay, Ramazan Yıldırım
Green Chemistry (2023) Vol. 25, Iss. 9, pp. 3354-3373
Closed Access | Times Cited: 18
Machine learning-based exploration of biochar for environmental management and remediation
Burcu Oral, Ahmet Coşgun, M. Erdem Günay, et al.
Journal of Environmental Management (2024) Vol. 360, pp. 121162-121162
Closed Access | Times Cited: 8
Multiscale Physics-Informed Neural Network Framework to Capture Stochastic Thin-Film Deposition
Donovan Chaffart, Yue Yuan, Luis Ricardez‐Sandoval
The Journal of Physical Chemistry C (2024) Vol. 128, Iss. 9, pp. 3733-3750
Closed Access | Times Cited: 7
Page 1 - Next Page

Scroll to top