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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:

Machine-learning interatomic potentials enable first-principles multiscale modeling of lattice thermal conductivity in graphene/borophene heterostructures
Bohayra Mortazavi, Evgeny V. Podryabinkin, Stephan Roche, et al.
Materials Horizons (2020) Vol. 7, Iss. 9, pp. 2359-2367
Open Access | Times Cited: 188

Showing 1-25 of 188 citing articles:

The MLIP package: moment tensor potentials with MPI and active learning
Ivan S. Novikov, Konstantin Gubaev, Evgeny V. Podryabinkin, et al.
Machine Learning Science and Technology (2020) Vol. 2, Iss. 2, pp. 025002-025002
Open Access | Times Cited: 429
First‐Principles Multiscale Modeling of Mechanical Properties in Graphene/Borophene Heterostructures Empowered by Machine‐Learning Interatomic Potentials
Bohayra Mortazavi, Mohammad Silani, Evgeny V. Podryabinkin, et al.
Advanced Materials (2021) Vol. 33, Iss. 35
Open Access | Times Cited: 264
Graphene-enabled wearable sensors for healthcare monitoring
Huiqing Zhang, Rongyan He, Yan Niu, et al.
Biosensors and Bioelectronics (2021) Vol. 197, pp. 113777-113777
Closed Access | Times Cited: 122
Intelligent on-demand design of phononic metamaterials
Yabin Jin, Liangshu He, Zhihui Wen, et al.
Nanophotonics (2022) Vol. 11, Iss. 3, pp. 439-460
Open Access | Times Cited: 103
A State-of-the-Art Review on Machine Learning-Based Multiscale Modeling, Simulation, Homogenization and Design of Materials
Dana Bishara, Yuxi Xie, Wing Kam Liu, et al.
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 1, pp. 191-222
Closed Access | Times Cited: 91
Atomistic modeling of the mechanical properties: the rise of machine learning interatomic potentials
Bohayra Mortazavi, Xiaoying Zhuang, Timon Rabczuk, et al.
Materials Horizons (2023) Vol. 10, Iss. 6, pp. 1956-1968
Open Access | Times Cited: 61
Predicting lattice thermal conductivity via machine learning: a mini review
Yufeng Luo, Mengke Li, Hongmei Yuan, et al.
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 51
Recent Advances in Machine Learning‐Assisted Multiscale Design of Energy Materials
Bohayra Mortazavi
Advanced Energy Materials (2024)
Open Access | Times Cited: 16
Efficient Artificial neural networks based on a hybrid metaheuristic optimization algorithm for damage detection in laminated composite structures
H. Tran-Ngoc, Samir Khatir, H. Ho-Khac, et al.
Composite Structures (2020) Vol. 262, pp. 113339-113339
Closed Access | Times Cited: 116
Machine learning on neutron and x-ray scattering and spectroscopies
Zhantao Chen, Nina Andrejevic, Nathan C. Drucker, et al.
Chemical Physics Reviews (2021) Vol. 2, Iss. 3
Open Access | Times Cited: 79
Deep dive into machine learning density functional theory for materials science and chemistry
Lenz Fiedler, Karan Shah, Michael Bußmann, et al.
Physical Review Materials (2022) Vol. 6, Iss. 4
Open Access | Times Cited: 65
Recent developments in the application of machine-learning towards accelerated predictive multiscale design and additive manufacturing
Sandeep Suresh Babu, Abdel‐Hamid I. Mourad, Khalifa H. Harib, et al.
Virtual and Physical Prototyping (2022) Vol. 18, Iss. 1
Open Access | Times Cited: 47
Contemporary Quantum Computing Use Cases: Taxonomy, Review and Challenges
Jaiteg Singh, Kamalpreet Singh Bhangu
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 1, pp. 615-638
Closed Access | Times Cited: 42
Functionalized graphene origami metamaterials with tunable thermal conductivity
Jun Cai, Ehsan Estakhrianhaghighi, Abdolhamid Akbarzadeh
Carbon (2022) Vol. 191, pp. 610-624
Closed Access | Times Cited: 41
Current Trends in Fluid Research in the Era of Artificial Intelligence: A Review
Filippos Sofos, Christos Stavrogiannis, Kalliopi K. Exarchou-Kouveli, et al.
Fluids (2022) Vol. 7, Iss. 3, pp. 116-116
Open Access | Times Cited: 38
Mechanical, Electronic, and Optical Properties of 8-16-4 Graphyne: A 2D Carbon Allotrope with Dirac Cones
Raphael M. Tromer, Marcelo Lopes Pereira, K. A. L. Lima, et al.
The Journal of Physical Chemistry C (2023) Vol. 127, Iss. 25, pp. 12226-12234
Open Access | Times Cited: 36
Structural, electronic, thermal and mechanical properties of C60-based fullerene two-dimensional networks explored by first-principles and machine learning
Bohayra Mortazavi
Carbon (2023) Vol. 213, pp. 118293-118293
Open Access | Times Cited: 34
Unraveling Thermal Transport Correlated with Atomistic Structures in Amorphous Gallium Oxide via Machine Learning Combined with Experiments
Yuanbin Liu, Huili Liang, Lei Yang, et al.
Advanced Materials (2023) Vol. 35, Iss. 24
Open Access | Times Cited: 32
Accelerating the prediction of stable materials with machine learning
Sean D. Griesemer, Yi Xia, Chris Wolverton
Nature Computational Science (2023) Vol. 3, Iss. 11, pp. 934-945
Closed Access | Times Cited: 30
Electronic transport in copper–graphene composites
Kashi N. Subedi, K. Nepal, C. Ugwumadu, et al.
Applied Physics Letters (2023) Vol. 122, Iss. 3
Open Access | Times Cited: 24
The rise of borophene
Prashant Kumar, Gurwinder Singh, Rohan Bahadur, et al.
Progress in Materials Science (2024) Vol. 146, pp. 101331-101331
Open Access | Times Cited: 15
Insight into Interfacial Heat Transfer of β-Ga2O3/Diamond Heterostructures via the Machine Learning Potential
Zhanpeng Sun, Dongliang Zhang, Zijun Qi, et al.
ACS Applied Materials & Interfaces (2024) Vol. 16, Iss. 24, pp. 31666-31676
Closed Access | Times Cited: 8
Heat transport exploration through the GaN/diamond interfaces using machine learning potential
Zhanpeng Sun, Yunfei Song, Zijun Qi, et al.
International Journal of Heat and Mass Transfer (2025) Vol. 241, pp. 126724-126724
Closed Access | Times Cited: 1
Two-dimensional carbon nitride C6N nanosheet with egg-comb-like structure and electronic properties of a semimetal
A. Bafekry, Masoud Shahrokhi, Aamir Shafique, et al.
Nanotechnology (2020) Vol. 32, Iss. 21, pp. 215702-215702
Closed Access | Times Cited: 60
Recent advances in lattice thermal conductivity calculation using machine-learning interatomic potentials
Saeed Arabha, Zahra Shokri Aghbolagh, Khashayar Ghorbani, et al.
Journal of Applied Physics (2021) Vol. 130, Iss. 21
Open Access | Times Cited: 42
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