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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:

A database of low-energy atomically precise nanoclusters
Sukriti Manna, Yunzhe Wang, Alberto Hernández, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 17

Showing 17 citing articles:

Big Data in a Nano World: A Review on Computational, Data-Driven Design of Nanomaterials Structures, Properties, and Synthesis
Ruoxi Yang, Caitlin A. McCandler, Oxana Andriuc, et al.
ACS Nano (2022) Vol. 16, Iss. 12, pp. 19873-19891
Open Access | Times Cited: 43
Accelerating Structure Prediction of Molecular Crystals using Actively Trained Moment Tensor Potential
Nikita Rybin, Ivan S. Novikov, Alexander V. Shapeev
Physical Chemistry Chemical Physics (2025)
Closed Access | Times Cited: 1
A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery
Suvo Banik, Troy Loefller, Sukriti Manna, et al.
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 13
Non-oxidative calcination enhances the methane dry reforming performance of Ni/CeO2−x catalysts under thermal and photo-thermal conditions
Kristijan Lorber, Vasyl Shvalya, Janez Zavašnik, et al.
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 31, pp. 19910-19923
Open Access | Times Cited: 4
Efficient density functional tight-binding parameterization for accurate modeling of platinum clusters
Rameshwar L. Kumawat, Chelsea M. Mueller, George C. Schatz
Chemical Physics Letters (2025), pp. 141944-141944
Closed Access
Integrating Physical Principles with Machine Learning for Predicting Field-Enhanced Catalysis
Runze Zhao, Qiang Li, Jiaqi Yang, et al.
JACS Au (2025) Vol. 5, Iss. 3, pp. 1121-1132
Open Access
Machine Learning Models to Study Electronic Properties of Metal Nanoclusters
Gia Minh Kieu, Jenica Marie L. Madridejos, Yunpeng Lu
Challenges and advances in computational chemistry and physics (2025), pp. 61-80
Closed Access
The structural resemblance between InSin− and Sin+1 (n = 3–11): Anion photoelectron spectroscopy and density functional calculations
Zhao‐Ou Gao, Xi‐Ling Xu, Umar Farooq, et al.
The Journal of Chemical Physics (2025) Vol. 162, Iss. 11
Closed Access
Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals
Bilvin Varughese, Sukriti Manna, Troy D. Loeffler, et al.
ACS Applied Materials & Interfaces (2024)
Closed Access | Times Cited: 3
Machine-Learned Potential Energy Surfaces for Free Sodium Clusters with Density Functional Accuracy: Applications to Melting
Balasaheb J. Nagare, Sajeev Chacko, D. G. Kanhere
Physica Scripta (2024) Vol. 99, Iss. 5, pp. 056005-056005
Open Access | Times Cited: 2
Multi-reward reinforcement learning based development of inter-atomic potential models for silica
Aditya Koneru, Henry Chan, Sukriti Manna, et al.
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 4
CHILI: Ch emically- I nformed L arge-scale I norganic Nanomaterials Dataset for Advancing Graph Machine Learning
Ulrik Friis-Jensen, Frederik L. Johansen, Andy S. Anker, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 4962-4973
Open Access | Times Cited: 1
Understanding melting behavior of aluminum clusters using machine learned deep neural network potential energy surfaces
Amit Kumar, Balasaheb J. Nagare, R.P. Sharma, et al.
The Journal of Chemical Physics (2024) Vol. 161, Iss. 17
Closed Access | Times Cited: 1
Development of a Machine Learning Potential to Study the Structure and Thermodynamics of Nickel Nanoclusters
Suvo Banik, P.S. Dutta, Sukriti Manna, et al.
The Journal of Physical Chemistry A (2024) Vol. 128, Iss. 47, pp. 10259-10271
Open Access | Times Cited: 1
Phosphine-Stabilized Hidden Ground States in Gold Clusters Investigated via a Aun(PH3)m Database
Caitlin A. McCandler, Jakob C. Dahl, Kristin A. Persson
ACS Nano (2022) Vol. 17, Iss. 2, pp. 1012-1021
Open Access | Times Cited: 7
Clinamen2: Functional-style evolutionary optimization in Python for atomistic structure searches
Ralf Wanzenböck, Florian Buchner, Péter Kovács, et al.
Computer Physics Communications (2023) Vol. 297, pp. 109065-109065
Open Access | Times Cited: 3
On the energetic and magnetic stability of potassium atomic clusters doped by yttrium
Henry Nicole González‐Ramírez, Zeferino Gómez‐Sandoval
Physical Chemistry Chemical Physics (2024) Vol. 26, Iss. 29, pp. 20134-20146
Closed Access
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