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:
Applications and training sets of machine learning potentials
Chang‐Ho Hong, Jaehoon Kim, Jaesun Kim, et al.
Science and Technology of Advanced Materials Methods (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 8
Chang‐Ho Hong, Jaehoon Kim, Jaesun Kim, et al.
Science and Technology of Advanced Materials Methods (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 8
Showing 8 citing articles:
Disorder-Dependent Li Diffusion in Li6PS5Cl Investigated by Machine-Learning Potential
Jiho Lee, Suyeon Ju, Seungwoo Hwang, et al.
ACS Applied Materials & Interfaces (2024) Vol. 16, Iss. 35, pp. 46442-46453
Closed Access | Times Cited: 7
Jiho Lee, Suyeon Ju, Seungwoo Hwang, et al.
ACS Applied Materials & Interfaces (2024) Vol. 16, Iss. 35, pp. 46442-46453
Closed Access | Times Cited: 7
Atomistic Simulation of HF Etching Process of Amorphous Si3N4 Using Machine Learning Potential
Chang‐Ho Hong, Sangmin Oh, Hyungmin An, et al.
ACS Applied Materials & Interfaces (2024) Vol. 16, Iss. 36, pp. 48457-48469
Closed Access | Times Cited: 5
Chang‐Ho Hong, Sangmin Oh, Hyungmin An, et al.
ACS Applied Materials & Interfaces (2024) Vol. 16, Iss. 36, pp. 48457-48469
Closed Access | Times Cited: 5
Local Structures of Ex-Solved Nanoparticles Identified by Machine-Learned Potentials
Sungwoo Kang, Jun Kyu Kim, Hyun‐Ah Kim, et al.
Nano Letters (2024) Vol. 24, Iss. 14, pp. 4224-4232
Closed Access | Times Cited: 4
Sungwoo Kang, Jun Kyu Kim, Hyun‐Ah Kim, et al.
Nano Letters (2024) Vol. 24, Iss. 14, pp. 4224-4232
Closed Access | Times Cited: 4
Fine-Tuned Global Neural Network Potentials for Global Potential Energy Surface Exploration at High Accuracy
X. H. Xie, Tong Guan, Zhengxin Yang, et al.
Journal of Chemical Theory and Computation (2025)
Closed Access
X. H. Xie, Tong Guan, Zhengxin Yang, et al.
Journal of Chemical Theory and Computation (2025)
Closed Access
Applications of machine learning in surfaces and interfaces
Shaofeng Xu, Jing‐Yuan Wu, Ying Guo, et al.
Chemical Physics Reviews (2025) Vol. 6, Iss. 1
Open Access
Shaofeng Xu, Jing‐Yuan Wu, Ying Guo, et al.
Chemical Physics Reviews (2025) Vol. 6, Iss. 1
Open Access
Data-Efficient Multifidelity Training for High-Fidelity Machine Learning Interatomic Potentials
Jaesun Kim, Jisu Kim, Jaehoon Kim, et al.
Journal of the American Chemical Society (2024)
Closed Access | Times Cited: 2
Jaesun Kim, Jisu Kim, Jaehoon Kim, et al.
Journal of the American Chemical Society (2024)
Closed Access | Times Cited: 2
Fluoride-Ion Conduction by Synergic Rotation of the Anion Sublattice for Tl4.5SnF8.5 Analogues
Tsuyoshi Takami, Nozomu Yasufuku, Mariia V. Ivonina, et al.
Chemistry of Materials (2024) Vol. 36, Iss. 17, pp. 8488-8495
Closed Access | Times Cited: 1
Tsuyoshi Takami, Nozomu Yasufuku, Mariia V. Ivonina, et al.
Chemistry of Materials (2024) Vol. 36, Iss. 17, pp. 8488-8495
Closed Access | Times Cited: 1
Modified Activation-Relaxation Technique (ARTn) Method Tuned for Efficient Identification of Transition States in Surface Reactions
Jisu Jung, Hyungmin An, Jinhee Lee, et al.
Journal of Chemical Theory and Computation (2024)
Closed Access | Times Cited: 1
Jisu Jung, Hyungmin An, Jinhee Lee, et al.
Journal of Chemical Theory and Computation (2024)
Closed Access | Times Cited: 1
