Bakhtiyor Rasulev, Ph.D.

2014-2016 Center for Computationally Assisted Science and Technology North Dakota State University, Fargo, ND, United States 
 2017- Coatings and Polymeric Materials North Dakota State University, Fargo, ND, United States 
computational chemistry, QSAR, machine learning, nanotoxicology, cheminformatics
"Bakhtiyor Rasulev"

Dr. Bakhtiyor Rasulev is an Assistant Professor at Department of Coatings and Polymeric Materials (North Dakota State University, Fargo, ND USA). Previously he was working at Interdisciplinary Center for Nanotoxicity (Jackson State University, Jackson, MS USA), directed by Prof. Jerzy Leszczynski. Dr. Rasulev received his PhD degree in Chemistry in 2002.
Dr. Rasulev’s research covers a range of topics in structure-activity relationship studies dealing with biological activity prediction, physico-chemical and toxicity of various organic compounds, polymers and nanomaterials, including metal oxide nanoparticles and carbon nanomaterials. Dr. Rasulev is an Editor-in-Chief of the IJANR and a permanent reviewer for more than 25 scientific journals that cover chemical, biological, polymer and nanoscience topics.

Mean distance: 106866


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Jerzy Leszczynski post-doc 2003-2007 Jackson State University, MS (Chemistry Tree)
Jerzy Leszczynski research scientist 2007-2013 Jackson State University, MS (Chemistry Tree)


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Jerzy Leszczynski collaborator 2004- Jackson State University, MS (Chemistry Tree)
Tomasz Puzyn collaborator 2008- University of Gdańsk
Natalia Sizochenko collaborator 2013- Univ. Montana
Philip Boudjouk collaborator 2014- North Dakota State University (Chemistry Tree)
Dmitri S. Kilin collaborator 2014- North Dakota State University (Chemistry Tree)
Lyudvig Petrosyan collaborator 2014- Jackson State University, MS
Svetlana V. Kilina collaborator 2015- North Dakota State University (Chemistry Tree)
Andriy Voronov collaborator 2016- North Dakota State University (Chemistry Tree)
Wenfang Sun collaborator 2017- North Dakota State University (Chemistry Tree)
Dali Sun collaborator 2018- North Dakota State University
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Erickson M, Han Y, Rasulev B, et al. (2022) Molecular Dynamics Study of the Photodegradation of Polymeric Chains. The Journal of Physical Chemistry Letters. 4374-4380
Varghese P J G, David DA, Karuth A, et al. (2022) Experimental and Simulation Studies on Nonwoven Polypropylene-Nitrile Rubber Blend: Recycling of Medical Face Masks to an Engineering Product. Acs Omega. 7: 4791-4803
Patnode K, Rasulev B, Voronov A. (2022) Synergistic Behavior of Plant Proteins and Biobased Latexes in Bioplastic Food Packaging Materials: Experimental and Machine Learning Study. Acs Applied Materials & Interfaces. 14: 8384-8393
Han Y, Iduoku K, Grant G, et al. (2021) Hot Carrier Dynamics at Ligated Silicon(111) Surfaces: A Computational Study. The Journal of Physical Chemistry Letters. 7504-7511
Serdiuk V, Shogren KL, Kovalenko T, et al. (2020) Detection of macromolecular inversion-induced structural changes in osteosarcoma cells by FTIR microspectroscopy. Analytical and Bioanalytical Chemistry
Erickson ME, Ngongang M, Rasulev B. (2020) A Refractive Index Study of a Diverse Set of Polymeric Materials by QSPR with Quantum-Chemical and Additive Descriptors. Molecules (Basel, Switzerland). 25
Fjodorova N, Novič M, Venko K, et al. (2020) A Comprehensive Cheminformatics Analysis of Structural Features Affecting the Binding Activity of Fullerene Derivatives. Nanomaterials (Basel, Switzerland). 10
Sizochenko N, Syzochenko M, Fjodorova N, et al. (2019) Evaluating genotoxicity of metal oxide nanoparticles: Application of advanced supervised and unsupervised machine learning techniques. Ecotoxicology and Environmental Safety. 185: 109733
Mikolajczyk A, Sizochenko N, Mulkiewicz E, et al. (2019) A chemoinformatics approach for the characterization of hybrid nanomaterials: safer and efficient design perspective. Nanoscale. 11: 11808-11818
Petrosyan LS, Sizochenko N, Leszczynski J, et al. (2019) Modeling of Glass Transition Temperatures for Polymeric Coating Materials: Application of QSPR Mixture-based Approach. Molecular Informatics
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