Band gap engineering of cadmium selenide nanocrystals using 120 MeV Ag7+ swift heavy ions, alongside theoretical evidence through PBE+U analysis

Nath, Debojyoti; Singh, Fouran; Das, Ratan

doi:10.1016/j.jallcom.2020.155535

Cited by 5 publications

(1 citation statement)

References 40 publications

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“…In recent years, some domestic and foreign researchers have successfully predicted the band gap of various materials using mathematical algorithms. [7]…”

Section: Band Gapmentioning

confidence: 99%

Progress in the Application of Mathematical Algorithms in Materials Science

2023

jmpd

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As materials are the direct drive for scientific development and social progress, the research on their structure and properties has always been a research hotspot in materials science. At present, the discovery of new materials is mainly carried out by the researcher's intuitive judgment of materials and a large number of "trial and error" experiments, which is inefficient and difficult to effectively discover a large number of possible new material combinations. Materials science has long relied on two major means of experiment and calculation. The machine learning-based mathematical algorithms offers a new research method. This article systematically expounds the common mathematical algorithms and the basic processes of their calculation methods, details the application of mathematical algorithms in material performance prediction and new material design, and gives a summarization and outlook of the challenges and application prospects concerning their application in materials science.

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“…In recent years, some domestic and foreign researchers have successfully predicted the band gap of various materials using mathematical algorithms. [7]…”

Section: Band Gapmentioning

confidence: 99%