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Albert P. Bartók on Muck Rack

Albert P. Bartók

As seen in: ACS Publications, Science Magazine, Physical Review B
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Articles

Experiment-Driven Atomistic Materials Modeling: A Case Study Combining X-Ray Photoelectron Spectroscopy and Machine Learning Potentials to Infer the Structure of Oxygen-Rich Amorphous Carbon

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By Tigany Zarrouk, Rina Ibragimova, Albert P. Bartók, Miguel A. Caro
| ACS Publications
One of the objectives of computational materials modeling is to infer the atomistic structure of matter, both for the purpose of satisfying our curiosity about what matter “looks like” at the atomic scale, and to obtain structure–property relations which might help in the design of useful materials and molecules.
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Experiment-Driven Atomistic Materials Modeling: A Case Study Combining X-Ray Photoelectron Spectroscopy and Machine Learning Potentials to Infer the Structure of Oxygen-Rich Amorphous Carbon

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By Tigany Zarrouk, Rina Ibragimova, Albert P. Bartók, Miguel A. Caro
| dx.doi.org
One of the objectives of computational materials modeling is to infer the atomistic structure of matter, both for the purpose of satisfying our curiosity about what matter “looks like” at the atomic scale, and to obtain structure–property relations which might help in the design of useful materials and molecules.
Open in Who Shared Issue with article?

Incompleteness of Atomic Structure Representations

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By Sergey Pozdnyakov, Albert P. Bartók, Christoph Ortner, Michael J. Willatt
| Physical Review B
Abstract Many-body descriptors are widely used to represent atomic environments in the construction of machine-learned interatomic potentials and more broadly for fitting, classification, and embedding tasks on atomic structures. There is a widespread belief in the community that three-body correlations are likely to provide an overcomplete description of the environment of an atom.
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