Dilshod D Nematov

Dr. Dilshod NEMATOV (PhD), is currently working as the Head of the Quantum Electronics Laboratory at the S. Umarov Physical-Technical Institute of the National Academy of Sciences of Tajikistan. He graduated from the Physics Department of the Tajik National University and worked as a Senior Lecturer at the Physics Department of the Tajik Technical University from 2017 to 2021. From 2021 to 2023, he worked as a Senior Researcher at the Center for the Study and Use of Renewable Energy Sources of the National Academy of Sciences of Tajikistan. He received his PhD in Materials Science from the Tajik Technical University. He has made several short-term and long-term research visits and scientific internships in advanced laboratories in Japan, Portugal, Spain, Germany, Ukraine, Kazakhstan and other countries, in order to improve his professional classification and master the skills of synthesis and experimental analysis of advanced materials. In doing so, he has established an excellent international scientific network. He started his scientific career with molecular dynamics studies of protein-surface interactions, but in recent years he has expanded his research to the application of Machine Learning (ML) and quantum chemistry techniques to the analysis of functional materials for photovoltaic and LED applications.

His current research interests focus on the synthesis, characterization and optimization of new efficient materials for photovoltaic devices, as well as their application in energy and environmental applications.

In addition to his knowledge of advanced experimental techniques, Dr. Dilshod Nematov is an expert in first-principles calculations (DFT modeling) and the application of Artificial Intelligence (AI) to the analysis of solid-state materials. In recent years, his group has begun to apply combined DFT/AI approaches to effectively predict the properties of materials before they are synthesized. For outstanding research work, he was awarded the Dushanbe Mayor's Prize in Natural and Technical Sciences in 2023, and at the end of 2023, he was awarded the Order of the Best Young Scientist of the CIS Countries. He is the author of more than 80 scientific articles in peer-reviewed scientific journals, a series of patents, and the author of one textbook for university lecture courses on general physics.

He began his scientific career with the molecular dynamics study of protein-surface interaction processes (DNA/RNA with biocompatible oxide surfaces), but in recent years he has expanded the range of his scientific research to the use of Machine Learning (ML) technology and quantum chemistry methods for the analysis of functional materials for photovoltaic technology and LED devices. At the very beginning of my research, I began to study the processes of interaction of biological objects with nanoscale materials, including modeling the molecular orientation and conformational behavior of DNA / RNA on biocompatible dielectric oxide surfaces as memory arrays for future DNA computers. At the same time, he has been actively collaborating with leading experts from developed countries around the world, including Japan, Spain, Portugal, Germany, Sweden, Egypt and other countries. In recent years, together with scientists from leading universities in Japan, China, Serbia, Romania and Estonia, we have been intensively studying the synthesis and development of new perovskite materials for solar cells and LED technology. The objects of our current research are solid-state synthesis and sol-gel fabrication of new rare-earth-free phosphorus materials for white LEDs. Our current research strategy is to conduct a series of density functional theory (DFT) calculations and preliminary predictive studies using machine learning (ML) methods, including other artificial intelligence (AI) models, based on the analysis of large data sets to effectively select the optimal candidates among a huge number of rare-earth-free phosphors from the class of silicates, garnets, perovskite oxides, aluminates, phosphates, vanadates, titanates and other revolutionary phosphors based on other matrix lattices. Synthesis and development of new materials are based on AI/DFT predictions with the aim of reducing negative side effects and improving the efficiency of LEDs.