Mozhgan Sepahvandian | Computational Chemistry | Best Researcher Award

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Dr. Mozhgan Sepahvandian | Computational Chemistry | Best Researcher Award

Iranian | Iran

Dr. Mozhgan Sepahvandian is a dedicated researcher in inorganic chemistry, contributing to the advancement of materials science through innovative approaches in synthesis, characterization, and application-driven design of inorganic compounds. Her scientific focus spans functional materials, catalytic systems, coordination chemistry, and metal-based structures with potential relevance across energy, environmental, and biomedical domains. She has completed numerous research projects demonstrating strong analytical insight, experimental precision, and a commitment to solving complex chemical challenges. Her publication record includes contributions to peer-reviewed journals indexed in leading scientific databases, reflecting the relevance and impact of her findings within the research community. With active involvement in multiple collaborative scientific initiatives, Dr. Sepahvandian integrates interdisciplinary perspectives into her work, enhancing the applicability of her research outcomes. She has contributed to scientific knowledge through studies exploring structural behavior, reactivity patterns, and advanced material performance, supporting the development of sustainable and efficient chemical solutions. Her engagement in scholarly activities includes reviewing literature, participating in knowledge-exchange platforms, and interacting with researchers across diverse domains. She maintains a strong interest in exploring new inorganic frameworks, optimizing synthesis pathways, and extending the utility of inorganic materials toward emerging technological needs. Her research contributions reflect a clear commitment to scientific excellence, innovation, and the continuous expansion of chemical knowledge, positioning her as a promising and impactful scientist in her field.

Profile: Orcid

Featured Publications

Sepahvandian, M., & Zabardasti, A. (2025). Computational study of dacarbazine–amino acid interactions. Journal of Biomolecular Structure and Dynamics.

Sepahvandian, M., & Zabardasti, A. (2025). Exploring limonene adsorption on magnesium and selenium doped AlP nanosheets: A DFT study. Computational Condensed Matter, 33, e01094.

Sepahvandian, M., Abd Al-Aama, Z. M., Al-Masoudi, H. Q., & Zabardasti, A. (2025). Theoretical investigation of optical properties of adducts of Aun and Cun (n = 1–3) with free base porphyrins. Bulletin of the Chemical Society of Ethiopia, 39(9).

Jaber Jahanbin Sardroodi | Computational Chemistry | Best Researcher Award

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Prof. Dr. Jaber Jahanbin Sardroodi | Computational Chemistry | Best Researcher Award

Azarbaijan Shahid Madani University | Iran

Prof. Dr. Jaber Jahanbin Sardroodi is a distinguished scholar in theoretical and computational physical chemistry, serving as Professor of Physical Chemistry at Azarbaijan Shahid Madani University. His research spans a wide range of topics, integrating molecular simulation, thermodynamics, and quantum chemistry to address complex chemical and biological systems. He leads the Molecular Simulation Lab and the Molecular Science and Engineering Research Group, where his work focuses on molecular dynamics simulations, free energy calculations, solvation processes, and drug–protein interactions. Prof. Sardroodi’s studies also explore deep eutectic solvents, nanomaterials, and molecular mechanisms of pharmaceutical interactions in aqueous and membrane environments. In addition, his research extends to quantum mechanics of many-body systems, density functional theory (DFT), quantum thermodynamics, and open quantum systems, contributing to the understanding of quantum information and thermal engines. His group employs advanced computational tools, including Python, Fortran, and C++, and increasingly integrates artificial intelligence and deep learning techniques into physical chemistry problem-solving. Prof. Sardroodi has authored numerous peer-reviewed publications in high-impact journals such as Scientific Reports, Chemical Engineering Science, and Journal of Molecular Modeling. His research contributes significantly to the advancement of molecular modeling, smart drug delivery systems, and energy materials, reflecting a blend of rigorous theoretical insight and computational innovation in modern chemical science.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Barani Pour, S., Jabbarvand Behrooz, N., Jahanbin Sardroodi, J., & Avestan, M. S. (2025). Potential use of deep eutectic solvents based on sugar as green separation media for the acidic gases capture process from the gas mixtures: Molecular dynamics simulation and COSMO-RS insights. Journal of Molecular Modeling.

Jahanbakhsh-Bonab, P., Pazuki, G., Jahanbin Sardroodi, J., & Dehnavi, S. M. (2023). Assessment of the properties of natural-based chiral deep eutectic solvents for chiral drug separation: Insights from molecular dynamics simulation. Physical Chemistry Chemical Physics.

Barani Pour, S., Jahanbin Sardroodi, J., Ebrahimzadeh, A. R., & Pazuki, G. (2023). Investigation of the effect of water addition on intermolecular interactions of fatty acids-based deep eutectic solvents by molecular dynamics simulations. Scientific Reports.

Heidari, S., Esrafili, M. D., & Jahanbin Sardroodi, J. (2023). Li, Na and K storage capacity of a novel 2D graphitic carbon-nitride membrane, C₉N₄: A computational approach. Chemical Physics Letters.

Mousavian, P., Esrafili, M. D., & Jahanbin Sardroodi, J. (2023). Outstanding performance of transition-metal decorated BC₃ nanotubes for high capacity CH₄ storage. Applied Surface Science.

Angelina Makaye | Computational Chemistry | Best Researcher Award

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Ms. Angelina Makaye | Computational Chemistry | Best Researcher Award

University of Dodoma | Tanzania

Ms. Angelina Isaack Makaye is an Assistant Lecturer in the Department of Chemistry at the University of Dodoma and an emerging scholar in computational chemistry with a focus on molecular modeling and environmental chemical sciences. Her research integrates computational methods such as molecular docking, molecular dynamics simulations, and free energy calculations to explore biomolecular interactions of natural products and pharmaceutical pollutants. She is currently pursuing a Ph.D. in Computational Chemistry, investigating the molecular mechanisms governing solvent effects on the conformational stability and binding kinetics of indole alkaloids as potential anti-mosquito agents. Her work aims to advance sustainable, data-driven approaches to drug discovery and environmental contaminant management, with particular relevance to the challenges faced by developing countries. Dr. Makaye’s publications address key topics in computational biology, pharmacology, and environmental research, contributing to understanding the behavior of pharmaceutical contaminants and the molecular basis of bioactive natural products. She possesses strong technical expertise in software tools such as GROMACS, AutoDock Vina, CHARMM, and visualization platforms like PyMOL and Chimera, complemented by programming and data analysis skills in Python and R. Her research excellence has been recognized through academic honors and invitations to international research collaborations. Dr. Makaye is an active member of professional networks including the Chemical Society of Tanzania, the African Computational Chemistry Network, and the Open Science Grid community, reflecting her commitment to advancing open and collaborative science in the field of computational chemistry.

Profile: Google Scholar

Featured Publications

Makaye, A., Ripanda, A. S., & Miraji, H. (2022). Transport behavior and risk evaluation of pharmaceutical contaminants from Swaswa Wastewater Stabilization Ponds. Journal of Biodiversity and Environmental Sciences, 20(2), 30–41.

Mkoma, S. L., Makaye, A. I., & Ndunguru, P. A. (2013). Students’ knowledge on particulate nature of matter in Chemistry. Tanzania Journal of Natural and Applied Sciences (TaJONAS), 4(2), 648–655.

Makaye, A. I., Paul, L., Vuai, S. A. H., & Shadrack, D. M. (2025). In silico ligand self-assembly drives binding recognition of natural products into Anopheles gambiae cytosolic sulfotransferases (AgSULT-001425) protein. In Silico Pharmacology, 13(3), 138.

Obakiro, S. B., Kiyimba, K., Gavamukulya, Y., Maseruka, R., Nabitandikwa, C., … Makaye, A. I. (2025). Deciphering the molecular mechanism of aloe-emodin in managing type II diabetes mellitus using network pharmacology, molecular docking, and molecular dynamics simulation. In Silico Pharmacology, 13(1), 45.

Makaye, A. I. (2018). Levels of selected heavy metals in paints from selected industries in Dar es Salaam