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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:

Toward autonomous materials research: Recent progress and future challenges
Joseph H. Montoya, Muratahan Aykol, Abraham Anapolsky, et al.
Applied Physics Reviews (2022) Vol. 9, Iss. 1
Closed Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Emerging Trends in Machine Learning: A Polymer Perspective
Tyler B. Martin, Debra J. Audus
ACS Polymers Au (2023) Vol. 3, Iss. 3, pp. 239-258
Open Access | Times Cited: 74
Accelerated chemical science with AI
Seoin Back, Alán Aspuru-Guzik, Michele Ceriotti, et al.
Digital Discovery (2023) Vol. 3, Iss. 1, pp. 23-33
Open Access | Times Cited: 41
What is missing in autonomous discovery: open challenges for the community
Phillip M. Maffettone, Pascal Friederich, Sterling G. Baird, et al.
Digital Discovery (2023) Vol. 2, Iss. 6, pp. 1644-1659
Open Access | Times Cited: 25
Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept
Stanley Lo, Sterling G. Baird, Joshua Schrier, et al.
Digital Discovery (2024) Vol. 3, Iss. 5, pp. 842-868
Open Access | Times Cited: 10
New challenges in oxygen reduction catalysis: a consortium retrospective to inform future research
Michaela Burke Stevens, Megha Anand, Melissa E. Kreider, et al.
Energy & Environmental Science (2022) Vol. 15, Iss. 9, pp. 3775-3794
Closed Access | Times Cited: 27
What is a minimal working example for a self-driving laboratory?
Sterling G. Baird, Taylor D. Sparks
Matter (2022) Vol. 5, Iss. 12, pp. 4170-4178
Open Access | Times Cited: 27
Orchestrating nimble experiments across interconnected labs
Dan Guevarra, Kevin Kan, Yungchieh Lai, et al.
Digital Discovery (2023) Vol. 2, Iss. 6, pp. 1806-1812
Open Access | Times Cited: 20
Density Functional Waltz: Molecular Theory of Spin Dynamics
Jyoti Bhattacharjee, Subhasis Roy
Journal of Physics & Optics Sciences (2024), pp. 1-4
Open Access | Times Cited: 5
Transforming research laboratories with connected digital twins
Simon D. Rihm, Jiaru Bai, Aleksandar Kondinski, et al.
Deleted Journal (2024) Vol. 1, Iss. 1, pp. 100004-100004
Open Access | Times Cited: 4
A multiobjective closed-loop approach towards autonomous discovery of electrocatalysts for nitrogen reduction
Lance Kavalsky, Vinay I. Hegde, Bryce Meredig, et al.
Digital Discovery (2024) Vol. 3, Iss. 5, pp. 999-1010
Open Access | Times Cited: 4
Autonomous laboratories for accelerated materials discovery: a community survey and practical insights
Linda Hung, Joyce A. Yager, Danielle R. Monteverde, et al.
Digital Discovery (2024) Vol. 3, Iss. 7, pp. 1273-1279
Open Access | Times Cited: 3
Autonomous (AI-driven) materials science
Martin L. Green, Benji Maruyama, Joshua Schrier
Applied Physics Reviews (2022) Vol. 9, Iss. 3
Open Access | Times Cited: 15
Integrating autonomy into automated research platforms
Richard B. Canty, Brent A. Koscher, Matthew A. McDonald, et al.
Digital Discovery (2023) Vol. 2, Iss. 5, pp. 1259-1268
Open Access | Times Cited: 8
Transforming science labs into automated factories of discovery
Angelos Angelopoulos, James F. Cahoon, Ron Alterovitz
Science Robotics (2024) Vol. 9, Iss. 95
Closed Access | Times Cited: 2
Machine learning in advancing anode materials for Lithium-Ion batteries – A review
Mohammad Aminul Islam, Zahid Ahsan, Mohammad Mustafizur Rahman, et al.
Inorganic Chemistry Communications (2024), pp. 113577-113577
Closed Access | Times Cited: 2
Early Prediction of Ion Transport Properties in Solid Polymer Electrolytes Using Machine Learning and System Behavior-Based Descriptors of Molecular Dynamics Simulations
Arash Khajeh, Daniel Schweigert, Steven B. Torrisi, et al.
Macromolecules (2023) Vol. 56, Iss. 13, pp. 4787-4799
Closed Access | Times Cited: 6
The materials experiment knowledge graph
Michael J. Statt, Brian A. Rohr, Dan Guevarra, et al.
Digital Discovery (2023) Vol. 2, Iss. 4, pp. 909-914
Open Access | Times Cited: 6
Targeted materials discovery using Bayesian algorithm execution
Sathya R. Chitturi, Akash Ramdas, Yue Wu, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 1
Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility
Ryan Jacobs, L. Schultz, Aristana Scourtas, et al.
Machine Learning Science and Technology (2024) Vol. 5, Iss. 4, pp. 045051-045051
Open Access | Times Cited: 1
Autonomous sputter synthesis of thin film nitrides with composition controlled by Bayesian optimization of optical plasma emission
Davi Fébba, Kevin R. Talley, K.E. Johnson, et al.
APL Materials (2023) Vol. 11, Iss. 7
Open Access | Times Cited: 4
Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models
Venkateswaran Shekar, Vincent F. Yu, Benjamin J. Garcia, et al.
(2022)
Open Access | Times Cited: 7
Networks and interfaces as catalysts for polymer materials innovation
Michael E. Deagen, Dylan J. Walsh, Debra J. Audus, et al.
Cell Reports Physical Science (2022) Vol. 3, Iss. 11, pp. 101126-101126
Closed Access | Times Cited: 7
Review of Low-cost Self-driving Laboratories: The "Frugal Twin" Concept
Stanley Lo, Sterling G. Baird, Joshua Schrier, et al.
(2023)
Open Access | Times Cited: 3
Realizing the cooking recipe of materials synthesis through large language models
Jaydeep Thik, Siwen Wang, Chuhong Wang, et al.
Journal of Materials Chemistry A (2023) Vol. 11, Iss. 47, pp. 25849-25853
Closed Access | Times Cited: 3
Role of multifidelity data in sequential active learning materials discovery campaigns: case study of electronic bandgap
Ryan Jacobs, Philip E. Goins, Dane Morgan
Machine Learning Science and Technology (2023) Vol. 4, Iss. 4, pp. 045060-045060
Open Access | Times Cited: 2
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