Center for Computer Modeling of Inorganic and Composite Nanoscale Materials
Publications
104
Citations
4 186
h-index
21
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The Center's staff is engaged in solving fundamental problems at the intersection of physics, chemistry and biology. The main profile of the Center is the use of modern computational methods of computer materials science, such as quantum chemical methods, evolutionary algorithms, machine learning and artificial intelligence methods to solve tasks. The group's research is supported by several grants from the Russian Science Foundation (RNF), an international grant from the Russian Foundation for Basic Research (RFBR) and a grant from the President of the Russian Federation for state support of young Russian scientists and state support from leading scientific schools of the Russian Federation.
- DFT calculations
- Molecular dynamics and quantum chemical calculations
- The evolutionary search for materials
- Machine learning
Zakhar Popov
Leading researcher
Anastasia Korovina
Junior researcher
Adilet Toksumakov
PhD student
Albert Shipaktsyan
Student
Denis Ivanov
Student
Research directions
Low density nanomaterials for various applications
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Research of nanoporous materials based on light elements, as well as new Mo-S phases for use as filter elements, chemically active surfaces for hydrogen production and storage, lithium-ion battery elements
Investigations of the propagation of an electronic wave packet in low-dimensional nanomaterials
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Development and writing of algorithms based on the strong coupling method for the study of electronic transport in low-dimensional nanomaterials.
Investigation of implantation processes of low-dimensional nanomaterials
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Modeling of the processes of implantation of CNTs, fullerenes, atomic groups and ions into the surface of low-dimensional nanomaterials. Search for possible methods for obtaining new porous nanostructures and quantum dots using implantation.
New 0D/2D heterostructures for photonics, sensors and catalysis
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Two-dimensional nanomaterials represent a promising platform for creating materials with the potential for use in a wide range of applications: optics, sensors, catalysis. An obstacle to the widespread use of newly synthesized two-dimensional nanomaterials of various chemical compositions is their low stability in the environment under normal conditions. An alternative to the search for new low-dimensional structures can be the functionalization of known structures of metal dichalcogenides (DPM) and two-dimensional forms of carbon, such as graphene and its derivatives (graphene oxide (OH), reduced graphene oxide) in order to give them the desired properties. Thus, it is possible not only to increase their stability in the environment, but also to significantly improve their characteristics. The project is aimed at finding new scalable approaches for the functionalization of the surface of two-dimensional nanomaterials with organic molecules to detect promising coatings not only to protect materials from degradation under the influence of environmental conditions, but also to endow this material and the entire resulting new heterostructure with a unique set of necessary properties for potential application in industry.
Search and research of new two-dimensional materials for use as biochemical sensors
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The focus of scientific interests in the field of low-dimensional nanostructures is increasingly shifting towards those two-dimensional materials, the synthesis of which is possible only in laboratory conditions. This is due to the fact that most two-dimensional materials, which can be obtained from crystalline materials of natural origin having a layered structure (graphene, transition metal dichalcogenides, etc.) have already been subjected to comprehensive research. Theoretical approaches to the prediction and research of new materials can significantly reduce the time spent on experimental synthesis and research of materials promising for use in electronics, catalysis and sensors. The search for new low-dimensional materials with a high specific surface area and high sensitivity for sensors is an extremely difficult task from an experimental point of view. To speed up the process of searching for new materials in this project, it is proposed to use methods of theoretical materials science.
Development of analytical models and algorithms based on neural networks to effectively describe the relationship between structure and properties
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Investigation of the influence of external disturbances, such as mechanical deformations, electric field on the physico-chemical properties of low-dimensional nanomaterials. The study and description of the patterns between atomic structure and properties. Creation of an analytical model for calculating polarization and piezoelectric coefficients in two-dimensional materials. Training a neural network-based model to describe the relationship between structure and piezoelectric properties.
Design of low-dimensional nanomaterials for artificial photosynthesis
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Artificial photosynthesis is a chemical process that biomimicrates the natural process of photosynthesis to convert sunlight, water, and carbon dioxide into carbohydrates and oxygen. The term artificial photosynthesis is commonly used to refer to any scheme for capturing and storing the energy of sunlight in chemical bonds of fuel (solar fuel). The proposed research is aimed at finding new materials for the implementation of photocatalytic splitting of water with the formation of hydrogen and oxygen
Publications and patents
Леонид Александрович Чернозатонский, Виктор Александрович Демин, Дмитрий Геннадьевич Квашнин
RU2772338,
2022
2023
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2024
| Суханова Екатерина Владимировна
2021
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2024
| Квашнин Дмитрий Геннадьевич
2021
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2024
| Попов Захар Иванович
Lab address
Москва, ул.Косыгина 4, ризалит 3, комн. 334, 329, 164
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