Mathematical Modeling of Properties and Structures of Crystals: From Quantum Approach to Machine Learning DOI Creative Commons
Grzegorz Matyszczak,

Christopher Jasiak,

Gabriela Rusinkiewicz

и другие.

Crystals, Год журнала: 2025, Номер 15(1), С. 61 - 61

Опубликована: Янв. 9, 2025

The crystalline state of matter serves as a reference point in the context studies properties variety chemical compounds. This is due to fact that prepared solids practically useful materials (inorganic or organic) may be utilized for thorough characterization important such (among others) energy bandgap, light absorption, thermal and electric conductivity, magnetic properties. For reason it develop mathematical descriptions (models) structures crystals. They used interpretation experimental data and, well, predictions novel, unknown compounds (i.e., design novel practical applications photovoltaics, catalysis, electronic devices, etc.). aim this article review most models crystal vary, among others, from quantum (e.g., density functional theory, DFT), through discrete mathematics cellular automata, CA), machine learning artificial neural networks, ANNs).

Язык: Английский

Beyond elemental intrinsic characteristics: ΔHmixBF-driven solid solution phase structure modeling in HEAs DOI
Kexin Yin,

Yijiala Yiliti,

Songtao Li

и другие.

Intermetallics, Год журнала: 2025, Номер 184, С. 108838 - 108838

Опубликована: Май 24, 2025

Язык: Английский

Процитировано

0

Mathematical Modeling of Properties and Structures of Crystals: From Quantum Approach to Machine Learning DOI Creative Commons
Grzegorz Matyszczak,

Christopher Jasiak,

Gabriela Rusinkiewicz

и другие.

Crystals, Год журнала: 2025, Номер 15(1), С. 61 - 61

Опубликована: Янв. 9, 2025

The crystalline state of matter serves as a reference point in the context studies properties variety chemical compounds. This is due to fact that prepared solids practically useful materials (inorganic or organic) may be utilized for thorough characterization important such (among others) energy bandgap, light absorption, thermal and electric conductivity, magnetic properties. For reason it develop mathematical descriptions (models) structures crystals. They used interpretation experimental data and, well, predictions novel, unknown compounds (i.e., design novel practical applications photovoltaics, catalysis, electronic devices, etc.). aim this article review most models crystal vary, among others, from quantum (e.g., density functional theory, DFT), through discrete mathematics cellular automata, CA), machine learning artificial neural networks, ANNs).

Язык: Английский

Процитировано

0