Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging

Abstract Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with strong correlations, either in electronic behavior or c...

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Autores principales:	Lukas Vlcek, Shize Yang, Yongji Gong, Pulickel Ajayan, Wu Zhou, Matthew F. Chisholm, Maxim Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/c867ca002f1b4ac285df393ed32a5cff
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spelling	oai:doaj.org-article:c867ca002f1b4ac285df393ed32a5cff2021-12-02T16:35:54ZThermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging10.1038/s41524-021-00507-72057-3960https://doaj.org/article/c867ca002f1b4ac285df393ed32a5cff2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41524-021-00507-7https://doaj.org/toc/2057-3960Abstract Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with strong correlations, either in electronic behavior or chemical segregation. In these cases, the details of atomic arrangements are generally not explored and analyzed. The knowledge of the generative physics and chemistry of the material can obviate this problem, since defect configuration libraries as stochastic representation of atomic level structures can be generated, or parameters of mesoscopic thermodynamic models can be derived. To obtain such information for improved predictions, we use data from atomically resolved microscopic images that visualize complex structural correlations within the system and translate them into statistical mechanical models of structure formation. Given the significant uncertainties about the microscopic aspects of the material’s processing history along with the limited number of available images, we combine model optimization techniques with the principles of statistical hypothesis testing. We demonstrate the approach on data from a series of atomically-resolved scanning transmission electron microscopy images of Mo x Re1- x S2 at varying ratios of Mo/Re stoichiometries, for which we propose an effective interaction model that is then used to generate atomic configurations and make testable predictions at a range of concentrations and formation temperatures.Lukas VlcekShize YangYongji GongPulickel AjayanWu ZhouMatthew F. ChisholmMaxim ZiatdinovRama K. VasudevanSergei V. KalininNature PortfolioarticleMaterials of engineering and construction. Mechanics of materialsTA401-492Computer softwareQA76.75-76.765ENnpj Computational Materials, Vol 7, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
spellingShingle	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765 Lukas Vlcek Shize Yang Yongji Gong Pulickel Ajayan Wu Zhou Matthew F. Chisholm Maxim Ziatdinov Rama K. Vasudevan Sergei V. Kalinin Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging
description	Abstract Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with strong correlations, either in electronic behavior or chemical segregation. In these cases, the details of atomic arrangements are generally not explored and analyzed. The knowledge of the generative physics and chemistry of the material can obviate this problem, since defect configuration libraries as stochastic representation of atomic level structures can be generated, or parameters of mesoscopic thermodynamic models can be derived. To obtain such information for improved predictions, we use data from atomically resolved microscopic images that visualize complex structural correlations within the system and translate them into statistical mechanical models of structure formation. Given the significant uncertainties about the microscopic aspects of the material’s processing history along with the limited number of available images, we combine model optimization techniques with the principles of statistical hypothesis testing. We demonstrate the approach on data from a series of atomically-resolved scanning transmission electron microscopy images of Mo x Re1- x S2 at varying ratios of Mo/Re stoichiometries, for which we propose an effective interaction model that is then used to generate atomic configurations and make testable predictions at a range of concentrations and formation temperatures.
format	article
author	Lukas Vlcek Shize Yang Yongji Gong Pulickel Ajayan Wu Zhou Matthew F. Chisholm Maxim Ziatdinov Rama K. Vasudevan Sergei V. Kalinin
author_facet	Lukas Vlcek Shize Yang Yongji Gong Pulickel Ajayan Wu Zhou Matthew F. Chisholm Maxim Ziatdinov Rama K. Vasudevan Sergei V. Kalinin
author_sort	Lukas Vlcek
title	Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging
title_short	Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging
title_full	Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging
title_fullStr	Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging
title_full_unstemmed	Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging
title_sort	thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/c867ca002f1b4ac285df393ed32a5cff
work_keys_str_mv	AT lukasvlcek thermodynamicsoforderandrandomnessindopantdistributionsinferredfromatomicallyresolvedimaging AT shizeyang thermodynamicsoforderandrandomnessindopantdistributionsinferredfromatomicallyresolvedimaging AT yongjigong thermodynamicsoforderandrandomnessindopantdistributionsinferredfromatomicallyresolvedimaging AT pulickelajayan thermodynamicsoforderandrandomnessindopantdistributionsinferredfromatomicallyresolvedimaging AT wuzhou thermodynamicsoforderandrandomnessindopantdistributionsinferredfromatomicallyresolvedimaging AT matthewfchisholm thermodynamicsoforderandrandomnessindopantdistributionsinferredfromatomicallyresolvedimaging AT maximziatdinov thermodynamicsoforderandrandomnessindopantdistributionsinferredfromatomicallyresolvedimaging AT ramakvasudevan thermodynamicsoforderandrandomnessindopantdistributionsinferredfromatomicallyresolvedimaging AT sergeivkalinin thermodynamicsoforderandrandomnessindopantdistributionsinferredfromatomicallyresolvedimaging
_version_	1718383718174818304

Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging

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