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Papers matching “interatomic potentials” 69

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Supporting data for "The Elusive Nature of Aromatic Carbocation Intermediates in Confined Catalytic Environments"
2026 Zenodo (CERN European Organization for Nuclear Research) dataset Chemistry Organic and Inorganic Chemical Reactions Open access

Chintu Das, Princy Jarngal, Fabian Berger, Abhishek Khetan, GiovanniMaria Piccini

0

citations
The Elusive Nature of Aromatic Carbocation Intermediates in Confined Catalytic Environments
2026 Research Square preprint Chemistry Zeolite Catalysis and Synthesis Open access

GiovanniMaria Piccini, Chintu Das, Princy Jarngal, Fabian Berger, Abhishek Khetan

0

citations
ChemRefine: An open-source automated and interoperable platform for machine learning and quantum chemistry simulations
2025 ChemRxiv preprint Materials Science Machine Learning in Materials Science Open access

Ignacio Migliaro, Alistair J. Sterling

0

citations
To Be or Not to Be: The Elusive Nature of Wheland-type Intermediates in Zeolite-Catalyzed Aromatic Alkylation Revealed by CCSD(T)-quality Metadynamics
2026 ChemRxiv preprint Chemistry Zeolite Catalysis and Synthesis Open access

Chintu Das, Princy Jarngal, Fabian Berger, GiovanniMaria Piccini

0

citations
A first-principles and machine learning combined method to investigate the interfacial friction between corrugated graphene
2021 Modelling and Simulation in Materials Science and Engineering article Materials Science Machine Learning in Materials Science

Zugang Liu, Xinpeng Zhao, Heyuan Wang, Yuan Ma, Lei Gao, Haiyou Huang, +3 more

9

citations
Datasets for manuscript "Exploring Chemistry and Catalysis by Biasing Skewed Distributions via Deep Learning"
2025 Zenodo (CERN European Organization for Nuclear Research) dataset Materials Science Machine Learning in Materials Science Open access

Zhikun Zhang

1

citations
Datasets for manuscript "Exploring Chemistry and Catalysis by Biasing Skewed Distributions via Deep Learning"
2025 Zenodo (CERN European Organization for Nuclear Research) dataset Materials Science Machine Learning in Materials Science Open access

Zhikun Zhang

1

citations
Advancing density functional tight-binding method for large organic molecules through equivariant neural networks
2026 Physical Chemistry Chemical Physics article Physics and Astronomy Advanced Chemical Physics Studies Open access

Leonardo Rafael Medrano Sandonas, Mirela Puleva, Zekiye Erarslan, Ricardo Parra Payano, Martin Stöhr, Gianaurelio Cuniberti, +1 more

8

citations
In silico design and prediction of metastable quaternary phases in Cu–Ni–Si–Cr alloys
2024 APL Machine Learning article Materials Science Machine Learning in Materials Science Open access

Ángel Díaz Carral, Simon Gravelle, Maria Fyta

3

citations
Simulating H$$^+$$, O$$^{2-}$$ and Sr$$^{2+}$$ transport in SrTiO$$_3$$ with a machine-learning potential
2025 Journal of Materials Science Materials in Energy article Materials Science Machine Learning in Materials Science Open access

Caitlin Perkampus, Stefan N. Adams, Roger A. De Souza

1

citations
In silico design and prediction of metastable quaternary phases in Cu-Ni-Si-Cr alloys
2024 arXiv (Cornell University) preprint Materials Science Machine Learning in Materials Science Open access

Ángel Díaz Carral, Simon Gravelle, Maria Fyta

0

citations
Graphene at Liquid Copper Catalysts: Atomic‐Scale Agreement of Experimental and First‐Principles Adsorption Height
2022 Advanced Science article Materials Science Graphene research and applications Open access

Hao Gao, Valentina Belova, Francesco La Porta, Juan Santiago Cingolani, Mie Andersen, Mehdi Saedi, +6 more

23

citations
Graphene at Liquid Copper Catalysts: Atomic-Scale Agreement of Experimental and First-Principles Adsorption Height
2022 ChemRxiv preprint Materials Science Graphene research and applications Open access

Hao Gao, Valentina Belova, Francesco La Porta, Santiago Cingolani, Mie Andersen, Mehdi Saedi, +6 more

3

citations
Operando Characterization and Molecular Simulations Reveal the Growth Kinetics of Graphene on Liquid Copper During Chemical Vapor Deposition
2024 ACS Nano article Materials Science Graphene research and applications Open access

Valentina Rein, Hao Gao, Hendrik H. Heenen, Wissal Sghaier, Anastasios C. Manikas, Christos Tsakonas, +8 more

15

citations
Multimap targeted free energy estimation
2023 Zenodo (CERN European Organization for Nuclear Research) article Chemistry Advanced Physical and Chemical Molecular Interactions Open access

Andrea Rizzi, Paolo Carloni, Michele Parrinello

6

citations
SPARC: A Computational Framework for Prediction of Infrared Spectra for Zeolitic Catalyst Systems via Machine Learning of Born Effective Charges and Atomic Velocities
2026 ChemRxiv preprint Materials Science Machine Learning in Materials Science Open access

Hairong Cheng, Huarong Lei, Princy Jarngal, Peirong Chen, Abhishek Khetan

0

citations
Atomate2: modular workflows for materials science
2025 Digital Discovery article Materials Science Machine Learning in Materials Science Open access

Alex M. Ganose, Hrushikesh P. Sahasrabuddhe, Mark Asta, Tathagata Biswas, Alexander Bonkowski, Joana Bustamante, +48 more

72

citations
Atomate2: Modular workflows for materials science
2025 ChemRxiv preprint Materials Science Machine Learning in Materials Science Open access

Alex M. Ganose, Hrushikesh P. Sahasrabuddhe, Mark Asta, Tathagata Biswas, Alexander Bonkowski, Joana Bustamante, +46 more

8

citations
Supported Catalytically Active Liquid Metal Solutions (SCALMS) for Propane Dehydrogenation–Intermetallic Phases and Liquid Alloys Studied by Pair Distribution Function Analysis and Density Functional Theory
2025 Advanced Science article Chemical Engineering Catalysis and Oxidation Reactions Open access

Felix Egger, Andreas Mölkner, Julien Steffen, Nicola Taccardi, Narayanan Raman, Mirijam Zobel, +3 more

8

citations
Electrolyte engineering for lithium-ion batteries: Mechanistic insights into the development of electrolyte from atomic-scale simulation
2025 Energy storage materials article Engineering Advanced Battery Materials and Technologies

Hongjun Chang, Hyunsang Joo, Byung Gon Kim, Egbert Figgemeier, Janghyuk Moon

3

citations
Atomic-scale insights into interfacial thermal transport in AlN/Al₂O₃ Heterostructures via deep potential molecular dynamics
2026 Surfaces and Interfaces article Materials Science Thermal properties of materials

Jiading Bao, Haiyu Wang, Zhuoshi Liu, Zhonghao Zheng, Heping Cui, Xianping Chen, +1 more

1

citations
A machine learning model for nuclear Hessians based on GFN2-xTB-derived atomistic features
2026 ChemRxiv preprint Materials Science Machine Learning in Materials Science Open access

Gereon Feldmann, Pit Steinbach, Christoph Bannwarth

1

citations
Refinement results for analytic non-spherical scattering factor calculation by direct partitioning of tailor-made wavefunctions using density fitting
2026 Zenodo (CERN European Organization for Nuclear Research) dataset Chemistry Crystal structures of chemical compounds Open access

Florian Kleemiss, Lukas Manuel Seifert

0

citations
A machine learning model for nuclear Hessians based on GFN2-xTB-derived atomistic features
2025 Zenodo (CERN European Organization for Nuclear Research) preprint Materials Science Machine Learning in Materials Science Open access

Gereon Feldmann, Pit Steinbach, Christoph Bannwarth

0

citations
Stability of Binary Precipitates in Cu-Ni-Si-Cr Alloys Investigated Through Active Learning
2023 SSRN Electronic Journal preprint Materials Science Machine Learning in Materials Science Open access

Ángel Díaz Carral, Xiang Xu, Simon Gravelle, Azade YazdanYar, Siegfried Schmauder, Maria Fyta

0

citations