Prof. Banjo Semire | Computational Chemistry | Distinguished Scientist Award

Dr. Zahra Mongashti | Computational Chemistry | Research Excellence Award

Dr. Zahra Mongashti | Computational Chemistry | Research Excellence Award

Master | Yasuj University | Iran

Dr. Zahra Mongashti is a physical chemistry researcher with expertise in computational and theoretical chemistry, focusing on electrochemistry, thermodynamic parameters, density function analysis, deformation density, and molecular confinement. Their work explores host–guest interactions, charge transfer processes, molecular encapsulation, and adsorption phenomena, employing advanced computational tools such as Gaussian, GaussView, AIM2000, Densitizer, and Origin. Notable studies include analyses of chlorinated hydrocarbons within C60 fullerene, lithium–oxygen interactions, halozhenal quinone thermodynamics, and methane–C60 interactions. They have published multiple theoretical studies, contributing to SCOPUS with 2 documents,  reflecting emerging yet impactful research in molecular modeling.

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Featured Publications

Dr. Faranak Hatami | Computational Chemistry | Best Researcher Award

Dr. Faranak Hatami | Computational Chemistry | Best Researcher Award

Dr. Faranak Hatami , Computational Chemistry , PhD at University of massachuessetes Lowell, United States

Faranak Hatami (Fara) is a dedicated physicist and researcher specializing in molecular dynamics simulations, machine learning, and nuclear materials science. Currently pursuing her Ph.D. in Physics at the University of Massachusetts Lowell, she focuses on transport property analysis and multi-objective optimization for molecular systems like Tri-Butyl-Phosphate (TBP). Faranak holds two master’s degrees—one in Physics from UMASS Lowell, where she explored force fields for TBP, and another in Nuclear Engineering from Shahid Beheshti University, where she investigated radiation damage in metals. With a robust background in computational physics, AI, and advanced simulation tools, she has authored multiple publications across nuclear materials and computational chemistry. Her teaching experience spans both the U.S. and Iran, reflecting her passion for education. Beyond academia, she completed a research internship at the University of Montreal. Faranak’s work bridges fundamental physics and practical applications, contributing innovative insights to the fields of material science and chemical engineering.

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Google Scholar 

Summary of Suitability for Award:

Faranak Hatami is a highly suitable candidate for a “Best Researcher Award”. She demonstrates exceptional multidisciplinary expertise spanning physics, molecular dynamics, machine learning, and nuclear materials science. Her Ph.D. work at UMASS Lowell innovatively combines atomic-scale simulations with AI to optimize force field parameters for Tri-Butyl-Phosphate, addressing both fundamental science and practical applications.  She has authored several impactful publications in reputable journals and preprints, covering diverse topics from radiation damage in metals to machine learning models predicting thermodynamic properties. Her research portfolio includes complex computational modeling, multi-objective optimization, and advanced materials analysis. Additionally, Faranak’s teaching record and successful research internship in Canada reflect her commitment to knowledge dissemination and international collaboration. Her ability to merge computational physics with machine learning showcases originality and forward-thinking, key attributes for top research honors. Faranak Hatami embodies the qualities of a best researcher: scientific rigor, innovative thinking, multidisciplinary skillset, and impactful publications. Her contributions significantly advance computational methods in physical sciences and engineering, making her a strong and deserving candidate for a “Best Researcher Award”.

🎓Education:

 Faranak Hatami is completing her Ph.D. in Physics at the University of Massachusetts Lowell (2021–2025), with her thesis focused on transport property analysis and optimization of force field parameters for Tri-Butyl-Phosphate (TBP), combining atomic-scale simulations with machine learning. Prior to this, she earned her M.Sc. in Physics from the same university in 2023, where she conducted a comparative study of force fields for liquid TBP using molecular dynamics. Earlier, she obtained her M.Sc. in Nuclear Engineering from Shahid Beheshti University in Iran (2016), where she examined radiation damage effects on zirconium and iron grain boundaries through simulations. Her academic journey began with a B.S. in Electrical Engineering from Kurdistan University in 2013. Throughout her studies, Faranak has integrated advanced computational methods, AI, and experimental data analysis, building a multidisciplinary foundation that connects physics, materials science, and engineering disciplines.

🏢Work Experience:

Faranak Hatami brings diverse experience across research, teaching, and technical projects. At UMASS Lowell, she serves as a Teaching Assistant in Physics while pursuing her Ph.D., guiding students through complex concepts. Previously, she lectured on Computational Methods and Statistical Methods and Physics courses at Shahid Beheshti University between 2014 and 2018. Her research career includes an internship at the University of Montreal (2019–2021), exploring hydrogen’s effects on iron grain boundaries using the kinetic activation relaxation technique (k-ART). Faranak has led significant academic projects spanning molecular dynamics simulations, multi-objective optimization, and machine learning applications in material science. She has deep expertise in computational tools such as LAMMPS, MCNP, VASP, and Python-based AI frameworks. Her work reflects a unique blend of fundamental physics research, practical problem-solving, and advanced data analysis, contributing to fields like chemical engineering, nuclear materials, and computational modeling.

🏅Awards: 

 Faranak Hatami has built an impressive research portfolio during her academic career, reflected in multiple publications and conference presentations. While specific named awards were not explicitly listed in her profile, her contributions have earned her recognition through invited presentations such as at the AIChE Annual Meeting, showcasing her expertise in molecular dynamics simulations and force field optimization. Completing dual M.Sc. degrees in Physics and Nuclear Engineering highlights her dedication and academic excellence. Her selection as a research intern at the University of Montreal, working on advanced computational studies in materials science, further underscores her capability and esteem in her field. Through her multidisciplinary approach integrating AI, molecular modeling, and nuclear materials science, she stands out as a rising scholar contributing valuable insights to computational physics and chemical engineering. As she advances her Ph.D., she is poised for further accolades in research innovation and scientific community engagement.

🔬Research Focus:

 Faranak Hatami focuses her research on the intersection of molecular dynamics simulations, machine learning, and materials science. Her Ph.D. work centers on analyzing transport properties and optimizing force field parameters for Tri-Butyl-Phosphate (TBP) using multi-objective optimization algorithms like NSGA-II/III. She applies molecular dynamics to predict critical thermodynamic and transport properties, integrating neural networks for parameter tuning. Additionally, she explores AI-based classification of microscopy and atomic-scale images, blending physics with cutting-edge data science. Faranak’s earlier research in nuclear engineering examined radiation damage in metals such as zirconium and nickel, utilizing techniques like climbing image nudged elastic band (CI-NEB) for defect analysis. She’s also investigated hydration free energies, grain boundary behaviors, and primary knock-on atom (PKA) spectra in irradiated materials. Her work bridges computational physics with practical engineering challenges, advancing predictive models and simulation methods to better understand complex molecular and material systems.

Publication Top Notes:

Comparative Analysis of Machine Learning Models for Predicting Viscosity in Tri-n-Butyl Phosphate Mixtures Using Experimental Data

Citations: 6

Quantification of Methane Hydration Energy Through Free Energy Perturbation Method

Comparison of Different Machine Learning Approaches to Predict Viscosity of Tri-n-Butyl Phosphate Mixtures Using Experimental Data

Citations: 3

Properties of Tri-Butyl-Phosphate from Polarizable Force Field MD Simulations

Citations: 1

A Revision of Classical Force Fields for Tri-N-Butyl Phosphate Molecular Dynamics Simulations

Interaction of primary cascades with different atomic grain boundaries in α-Zr: An atomic scale study

Citations: 34

An energetic and kinetic investigation of the role of different atomic grain boundaries in healing radiation damage in nickel

Citations: 31

Mrs. Ralitsa Uzunova | Physical Chemistry | Best Researcher Award

Mrs. Ralitsa Uzunova | Physical Chemistry | Best Researcher Award

Mrs. Ralitsa Uzunova | Physical Chemistry | PhD student/ Researcher at Department of Chemical and Pharmaceutical Engineering, sofia university, Bulgaria

Ralitsa Ivanova Uzunova is a dedicated Ph.D. student and researcher in the Department of Chemical and Pharmaceutical Engineering at Sofia University “St. Kliment Ohridski.” With a strong background in chemistry, she holds a Bachelor’s degree in “Chemistry” and a Master’s in “Medicinal Chemistry.” Over the past seven years, she has actively contributed to various research projects, particularly in surfactant solutions, interfacial tension, and adsorption studies. She has participated in 13 national and international conferences, delivering nine oral presentations, including at the prestigious 37th European Colloid and Interface Society Conference and the 19th European Student Colloid Conference. Her collaborations extend to industry giants like Unilever and S.C. Johnson, as well as the National Science Fund of Bulgaria. Ralitsa’s work focuses on understanding volatile molecules’ adsorption-desorption mechanisms, which are crucial in cosmetics, household products, and pharmaceuticals. Her dedication to research has led to two indexed journal publications, benefiting the broader scientific community.

Professional Profile :         

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Summary of Suitability for Award:

Ralitsa Ivanova Uzunova is an emerging researcher in the field of Chemical and Pharmaceutical Engineering, specializing in surface chemistry, interfacial tension, and adsorption phenomena. With a strong academic background (Bachelor’s in Chemistry and Master’s in Medicinal Chemistry), she has gained seven years of research experience at Sofia University “St. Kliment Ohridski.” Her participation in eight research projects, two indexed journal publications, and four industry collaborations with Unilever, S. C. Johnson, and others demonstrate her contribution to applied research. Additionally, her active engagement in national and international conferences (including the 37th European Colloid and Interface Society Conference) highlights her role in scientific dissemination. Her work on volatile molecules used in cosmetics and household formulations has both theoretical significance and industrial application, aligning well with the criteria for excellence in research. Ralitsa Ivanova Uzunova is a deserving candidate for the “Best Researcher Award”, given her multifaceted contributions to chemical engineering research, industrial collaborations, and scientific impact. Her interdisciplinary expertise in cosmetics, pharmaceuticals, and surface chemistry showcases her ability to bridge academia and industry, making her an ideal contender for this prestigious recognition.

🎓Education:

Ralitsa Ivanova Uzunova pursued her higher education in chemistry with a keen interest in interdisciplinary applications. She obtained her Bachelor’s degree in Chemistry from Sofia University “St. Kliment Ohridski,” where she built a strong foundation in chemical principles and analytical techniques. Following her undergraduate studies, she completed a Master’s degree in Medicinal Chemistry, focusing on bioactive compounds and their applications in pharmaceuticals and healthcare. Currently, she is pursuing a Ph.D. in Chemical and Pharmaceutical Engineering, specializing in surfactant solutions, interfacial tension, and adsorption phenomena. Throughout her academic journey, she has been actively engaged in research and has collaborated with industrial partners on multiple projects. Her educational background has equipped her with expertise in static and dynamic interfacial tension, cleaning mechanisms, and volatile molecule adsorption-desorption processes. Ralitsa continues to expand her knowledge through research collaborations, conference presentations, and scientific publications.

🏢Work Experience:

Ralitsa Ivanova Uzunova has amassed seven years of experience in research and academia while working in the Department of Chemical and Pharmaceutical Engineering at Sofia University. Her expertise spans static and dynamic interfacial tension, surfactant solutions, and oil drop attachment/detachment studies. She has contributed to eight research projects, collaborating with industry leaders such as Unilever, S. C. Johnson, and the National Science Fund of Bulgaria. Additionally, she has been involved in four consultancy/industry projects, applying her knowledge to real-world challenges in cosmetics and household chemistry. Ralitsa has actively participated in 13 national and international conferences, delivering nine oral presentations, including at prestigious European colloid conferences. Her research has resulted in two indexed journal publications, contributing valuable insights into volatile molecule interactions. Her work is instrumental in developing formulations for personal care and industrial applications, bridging the gap between scientific research and industrial needs.

🏅Awards: 

Ralitsa Ivanova Uzunova has been recognized for her exceptional contributions to the field of chemical and pharmaceutical engineering. She has received multiple accolades for her oral presentations at international conferences, particularly at the 37th European Colloid and Interface Society Conference and the 19th European Student Colloid Conference, where her work on interfacial tension and surfactant solutions was highly appreciated. As a member of the Bulgarian Association of Cosmetologists, she has contributed significantly to research in cosmetics and household chemistry. Her research collaborations with Unilever and S. C. Johnson have also been acknowledged for their impact on industrial formulations. Additionally, her involvement in National Science Fund of Bulgaria projects has played a crucial role in advancing knowledge in volatile molecule adsorption-desorption mechanisms. Ralitsa is currently nominated for the Best Researcher Award, recognizing her dedication to scientific excellence and innovation in colloid and interface science.

🔬Research Focus:

Ralitsa Ivanova Uzunova’s research focuses on static and dynamic interfacial tension, surfactant solutions, and volatile molecule interactions. Her work explores the bulk properties and adsorption behaviors of surfactants, which are crucial in cleaning, cosmetics, and pharmaceutical applications. She investigates the attachment/detachment of oil drops, enhancing formulations for detergents, skincare, and industrial surfactants. A significant part of her research delves into volatile molecule adsorption and desorption at interfaces, examining compounds like menthol, geraniol, linalool, benzyl acetate, and citronellol, widely used in personal care products and medicine. Her studies provide critical insights into optimizing formulations for enhanced stability, efficiency, and sustainability. Through collaborations with Unilever, S. C. Johnson, and the National Science Fund of Bulgaria, she applies her findings to industrial applications. Her work contributes to improving product performance, environmental sustainability, and the development of novel surfactant-based systems, making significant advancements in colloid and interface science.

Publication Top Notes:

“Quantitative characterization of the mass transfer of volatile amphiphiles between vapor and aqueous phases: Experiment vs theory”

“Kinetics of transfer of volatile amphiphiles (fragrances) from vapors to aqueous drops and vice versa: Interplay of diffusion and barrier mechanisms”

Dr. Jean Moto Ongagna | Theoretical Chemistry | Catalysis Award

Dr. Jean Moto Ongagna | Theoretical Chemistry | Catalysis Award

Dr. Jean Moto Ongagna | Theoretical Chemistry | Lecturer – University of Douala-Cameroon , Cameroon

Dr. Jean Moto Ongagna is a Cameroonian researcher specializing in Theoretical chemistry and Computational Chemistry . He obtained his Ph.D. from the University of Douala in 2021. His expertise spans Density Functional Theory (DFT), Pharmacokinetics (ADMET), Molecular Docking, Molecular Dynamics (MD), and ab initio Molecular Dynamics (ADMP). Dr. Ongagna has contributed significantly to computational chemistry, particularly in studying metal complexes, chemical bonding, and reaction mechanisms. He has participated in prestigious international conferences and workshops, presenting groundbreaking research on chemical bonding interactions. With numerous publications in high-impact journals such as RSC Advances and the International Journal of Quantum Chemistry, his work advances the understanding of transition metal complexes and their applications. He actively collaborates with researchers worldwide and is dedicated to developing computational tools for chemical and biological systems.

Professional Profile : 

Orcid  

Summary of Suitability for Award:

Dr. Jean Moto Ongagna is an outstanding candidate for the “Catalysis Awards”, given his significant contributions to computational catalysis and theoretical chemistry. His research extensively applies Density Functional Theory (DFT), Quantum Chemical Calculations, and Molecular Dynamics (MD) to investigate transition metal complexes, non-standard chemical bonding, and catalytic reaction mechanisms. His studies provide deep insights into metal-ligand interactions, catalytic efficiency, and reaction pathways, which are fundamental for designing novel catalytic systems. Dr. Jean Moto Ongagna’s research in computational catalysis, transition metal chemistry, and theoretical modeling aligns perfectly with the objectives of the “Catalysis Awards”. His work advances the understanding of catalyst behavior, reaction mechanisms, and molecular interactions, making a substantial impact on modern catalysis research. His ability to integrate quantum chemistry tools with catalytic design positions him as a highly suitable candidate for this prestigious recognition.

🎓Education:

Dr. Jean Moto Ongagna pursued his higher education at the University of Douala, Cameroon. He earned a Ph.D. in Theoretical and Computational Chemistry (2021), focusing on Density Functional Theory (DFT) and molecular simulations. In 2016, he completed his Master’s degree in the same field, where he explored the computational analysis of metal-ligand interactions. His Bachelor’s degree in Physical Chemistry (2013) laid the foundation for his research on quantum chemistry and molecular modeling. Before university, he completed his GCE Advanced Level (Baccalauréat D) in 2008 at Laic Private College “La Liberté” in Douala. His education equipped him with expertise in quantum chemistry, molecular docking, and theoretical modeling, enabling him to contribute to cutting-edge research. Throughout his academic journey, he attended specialized workshops and conferences to enhance his skills in computational chemistry, continuously refining his expertise in quantum simulations and advanced chemical theories.

🏢Work Experience:

Dr. Jean Moto Ongagna has extensive experience in Theoretical chemistry and Computational Chemistry, with expertise in Density Functional Theory (DFT), Molecular Docking, Pharmacokinetics (ADMET), and ab initio Molecular Dynamics (ADMP). He has actively participated in international conferences, presenting research on transition metal complexes, chemical bonding, and molecular interactions. He has contributed to significant projects involving the computational study of catalysts, biomolecular interactions, and pharmaceutical compounds. Dr. Ongagna has also collaborated with renowned institutions and researchers worldwide, publishing extensively in high-impact journals. His research experience includes developing and applying quantum chemical tools for investigating metal-ligand interactions and reaction mechanisms. He has been involved in multiple computational chemistry workshops, enhancing his knowledge of secondary metabolite discovery, quantum topology, and electronic structure theory. His contributions have led to a deeper understanding of non-standard chemical bonding and have implications for catalysis, drug design, and materials science.

🏅Awards: 

Dr. Jean Moto Ongagna has received multiple recognitions for his contributions to Theoretical and Computational Chemistry. He has been invited as a speaker at international conferences, including the 4th Commonwealth Chemistry Posters (2023) and the Virtual Conference on Chemistry and Its Applications (2021, 2022). His research on transition metal complexes and quantum chemistry has been published in high-impact journals such as RSC Advances and the International Journal of Quantum Chemistry. He has received accolades for his computational investigations on catalytic and biomolecular systems, contributing to the advancement of quantum chemical methodologies. His participation in scientific workshops at the University of Buea (Cameroon) and Technische Universität Dresden (Germany) further highlights his academic excellence. His continuous engagement in international scientific discussions and collaborations has strengthened his reputation as a leading researcher in quantum chemistry and molecular modeling.

🔬Research Focus:

Dr. Jean Moto Ongagna’s research focuses on Theoretical and Computational Chemistry, particularly Density Functional Theory (DFT), Quantum Chemical Calculations, Molecular Docking, Pharmacokinetics (ADMET), and Molecular Dynamics (MD). He specializes in studying transition metal complexes, non-standard chemical bonds, and catalytic reactions. His work involves topological analysis of chemical interactions using advanced computational techniques such as Quantum Theory of Atoms in Molecules (QTAIM), Energy Decomposition Analysis (EDA), and Natural Bond Orbital (NBO) analysis. He has made significant contributions to understanding palladium complexes, Diels–Alder reactions, and bioactive compounds. His research extends to computational drug discovery, antimicrobial compounds, and bioinorganic chemistry, aiming to bridge the gap between theoretical modeling and experimental applications. By integrating quantum chemical methods with molecular simulations, his studies provide valuable insights into reaction mechanisms, electronic structures, and potential applications in pharmaceuticals, catalysis, and material science.

Publication Top Notes:

Deciphering the Influence of Alkylene Bridged and Chelating Mode on Pd—C and Pd—X (X = Cl, Br, and I) Bonding Interaction Within Bis‐(NHC)‐Palladium Complexes Using Quantum Chemistry Tools

Authors: Gaël Mouzong D’Ambassa, Jean Moto Ongagna, Adjieufack Abel Idrice, Désiré Bikele Mama

Year: 2024

Computational Exploration of the Impact of Low‐Spin and High‐Spin Ground State on the Chelating Ability of Dimethylglyoxime Ligand on Dihalo Transition Metal: A QTAIM, EDA, and CDA Analysis

Authors: Daniel Lissouck, Suzane Leonie Djendo Mazia, Gaël Mouzong D’Ambassa, Jean Moto Ongagna

Year: 2024

Deciphering the Influence of PdII and PdIV Oxidation States on Non-Standard Chemical Bonds Within Bis(N-Heterocyclic Carbene) Complexes: Insights from DFT

Authors: Gaël Mouzong D’Ambassa, Jean Moto Ongagna, Adjieufack Abel Idrice, Désiré Bikele Mama

Year: 2024

Exploring the Mechanism of the Intramolecular Diels–Alder Reaction of (2E,4Z,6Z)-2(allyloxy)cycloocta-2,4,6-trien-1-one Using Bonding Evolution Theory

Authors: Jean Moto Ongagna, Gaël Mouzong D’Ambassa

Year: 2023

In Vitro and In Silico Studies of Antibacterial Activities of Secofriedelane Derivatives from Senna alata (L) Roxb

Authors: Jean Moto Ongagna, Gaël Mouzong D’Ambassa

Year: 2023

How a Chromium Tricarbonyl Complex Catalyzes the [3 + 2] Cycloaddition Reaction of N-Substituted Phenylnitrones with Styrene: A Molecular Electron Density Theory Analysis

Authors: Jean Moto Ongagna, Gaël Mouzong D’Ambassa

Year: 2023

Insight into the Antioxidant and Antiradical Properties of Colorotane Sesquiterpenes Extracted from Warburgia ugandensis: Theoretical Evaluation

Authors: Jean Moto Ongagna, Gaël Mouzong D’Ambassa

Year: 2021

Topological Unraveling of the [3+2] Cycloaddition (32CA) Reaction Between N-Methylphenylnitrone and Styrene Catalyzed by the Chromium Tricarbonyl Complex Using Electron Localization Function and Catastrophe Theory

Authors: Jean Moto Ongagna, Gaël Mouzong D’Ambassa

Year: 2021

B3LYP, M06 and B3PW91 DFT Assignment of nd8 Metal-Bis-(N-Heterocyclic Carbene) Complexes

Authors: Jean Moto Ongagna, Gaël Mouzong D’Ambassa

Year: 2020