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Improvement of new electronic materials using computer modeling.

Title: Improvement of new electronic materials using computer modeling.
Alternate Title: Удосконалення нових електронних матеріалів за допомогою комп’ютерного моделювання. (Ukrainian)
Authors: Bondaruk, Y. V.; Kavetskyy, T. S.; Vinkovskaya, A. O.; Kushniyazova, M.; Dyachok, D. O.; Pankiv, L. I.; Klepach, H. M.; Mushynska, O. R.; Zubrytska, O. V.; Matskiv, O. I.; Pavlovskyy, Y. V.; Voloshanska, S. Y.; Monastyrska, S. S.; Bodnar, L. V.; Kiv, A. E.
Source: Semiconductor Physics, Quantum Electronics & Optoelectronics; 2023, Vol. 26 Issue 4, p470-474, 5p
Subject Terms: ELECTRONIC materials; COMPUTER simulation; POROUS materials; FAST ions; ELECTRONIC equipment; NANOPORES
Abstract: Porous materials occupy an important place among the materials of electronic equipment. Nanopores, which are obtained by ion irradiation of materials, have a complex internal structure that depends on the interaction of fast ions with the substance. Obtaining such structures is important, in particular, in the manufacture of biosensor devices based on them. The most effective methods of studying their properties are computer simulations. However, effective computer models of track structures, necessary for the development and improvement of modern biosensors, are not being created actively enough. The approach proposed here involves a detailed study of the interaction of ion flows with the inner surface of the nanotrack. This approach takes into account the structural features of the inner surface of the track as well as the role of adsorption and scattering centers and other local centers. In the existing approaches, the processes mentioned above are mainly described phenomenologically, which does not indicate the ways of modifying the characteristics of the material that is necessary for the device improvement. [ABSTRACT FROM AUTHOR]
: Copyright of Semiconductor Physics, Quantum Electronics & Optoelectronics is the property of V. Lashkaryov Institute of Semiconductor Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index