Nithyadevi Duraisamy | Computational Modeling | Editorial Board Member

Published on by Chemistry Awards

Editorial Board Member

Nithyadevi Duraisamy
Affiliation Long Island University
Country United States
Scopus ID 59370044600
Documents 6
Citations 23
h-index 4
Subject Area Computational Modeling
Event International Chemistry Scientist Awards

Nithyadevi Duraisamy is associated with Long Island University in the United States and has contributed to the field of computational modeling through scholarly publications and interdisciplinary scientific engagement. Her research profile demonstrates involvement in computational and chemistry-related analytical methodologies, with indexed publications and measurable citation impact recorded in international academic databases.[1] The recognition of her academic profile within the framework of the International Chemistry Scientist Awards reflects continued participation in scientific communication, editorial activities, and research dissemination within the broader chemistry and computational sciences community.[3]

Abstract

This article presents an academic overview of Nithyadevi Duraisamy, highlighting scholarly contributions, institutional affiliation, publication metrics, and participation in scientific research activities associated with computational modeling and chemistry-related analytical studies. The profile summarizes available bibliometric indicators including indexed documents, citation counts, and h-index values while discussing the relevance of editorial recognition within international scientific award platforms. The article further examines research visibility, interdisciplinary engagement, and the significance of scholarly dissemination through indexed databases and digital researcher identifiers.[1][3]

Keywords

Computational Modeling, Chemistry Research, Editorial Board Member, Scientific Publications, Scopus Author Profile, Research Metrics, Citation Analysis, Academic Recognition, International Chemistry Scientist Awards, ORCID.

Introduction

The growth of computational methodologies in scientific research has significantly influenced modern chemistry, materials science, and interdisciplinary analytical studies. Researchers working within computational frameworks contribute to data interpretation, molecular simulations, predictive modeling, and algorithmic scientific analysis that support both experimental and theoretical investigations.[3] Academic profiles indexed through global scholarly databases provide measurable indicators for evaluating publication activity, citation performance, and research visibility across international research communities.[1]

Nithyadevi Duraisamy has been associated with Long Island University and has contributed to scholarly activities connected to computational modeling and related scientific applications. The inclusion of her profile within recognized academic indexing systems and editorial recognition frameworks reflects ongoing participation in scientific communication and academic dissemination processes. Editorial board recognition within international scientific platforms frequently acknowledges subject expertise, peer-review participation, and research engagement in specialized scientific disciplines.

Research Profile

The research profile of Nithyadevi Duraisamy demonstrates engagement in computational and analytical scientific investigations supported by indexed scholarly publications. According to publicly accessible bibliometric records, the researcher has six indexed documents with a cumulative citation count of twenty-three and an h-index of four.[1] Such metrics indicate developing academic visibility within specialized research domains and reflect the contribution of published work to scholarly discourse.

The researcher’s institutional affiliation with Long Island University positions the academic profile within an internationally recognized educational environment that supports interdisciplinary scientific collaboration and research dissemination. Digital scholarly identifiers such as ORCID and Scopus Author ID facilitate transparency in academic attribution, publication tracking, and long-term research discoverability.[3]

Research Contributions

Research contributions associated with computational modeling often involve simulation-based analysis, algorithmic interpretation, molecular computation, predictive chemistry, and interdisciplinary scientific evaluation. Scholars working in this area support the advancement of theoretical frameworks that complement laboratory-based experimentation and facilitate efficient data-driven scientific analysis.[1][3]

Nithyadevi Duraisamy’s scholarly profile reflects participation in academic publication and scientific dissemination processes relevant to these computational and analytical domains. Editorial involvement and scientific recognition initiatives further contribute to the promotion of peer-reviewed communication and collaborative academic exchange across chemistry and related scientific disciplines.[3]

  • Participation in computationally oriented scientific research
  • Contribution to indexed scholarly publications
  • Support for interdisciplinary analytical methodologies
  • Engagement in scientific editorial and academic dissemination activities

Publications

The publication record associated with the researcher demonstrates indexed scholarly output in computational and scientific analytical areas. Indexed publication databases serve as important tools for evaluating publication quality, citation reach, and academic engagement across institutional and international research environments.[1]

  1. Research articles indexed through Scopus-authorized databases related to computational modeling and scientific analysis.
  2. Interdisciplinary publications contributing to analytical chemistry and computational scientific applications.
  3. Scholarly outputs associated with institutional and collaborative scientific research dissemination.

Research Impact

Bibliometric indicators are frequently used to evaluate scholarly visibility and academic influence within scientific communities. Citation counts, document indexing, and h-index measurements collectively provide insights into publication engagement and scholarly reach.[1] Although quantitative metrics alone do not fully define scientific contribution, they remain important tools for assessing research dissemination and recognition.

The current profile metrics associated with Nithyadevi Duraisamy indicate measurable academic engagement within the computational modeling domain. Citation-based indicators suggest that the researcher’s published work has received scholarly attention within indexed academic environments. Continued publication activity and collaborative interdisciplinary participation may further strengthen long-term research visibility and citation performance.[3]

Award Suitability

Recognition within the International Chemistry Scientist Awards framework as an editorial board member reflects professional engagement in scientific communication and scholarly evaluation processes. Editorial responsibilities commonly involve peer-review coordination, publication ethics awareness, subject expertise evaluation, and support for academic quality assurance within scientific publishing environments.[3]

The researcher’s documented publication metrics, institutional affiliation, and participation in computational modeling research support suitability for recognition within editorial and academic contribution categories. The integration of indexed scholarly identifiers and measurable citation records further strengthens the transparency and credibility of the academic profile.[1]

  • Indexed scholarly publication record
  • Participation in computational research disciplines
  • Editorial and scientific dissemination engagement
  • Institutional affiliation with an internationally recognized university

Conclusion

Nithyadevi Duraisamy represents an academic profile associated with computational modeling and interdisciplinary scientific analysis through indexed publications, measurable citation metrics, and scholarly engagement activities. The documented bibliometric indicators and editorial recognition demonstrate participation in scientific dissemination and research-oriented communication platforms. Continued involvement in collaborative computational research and publication activities may contribute to expanded scholarly influence and future academic development within the broader scientific community.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Nithyadevi Duraisamy, Author ID 59370044600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59370044600
  2. ORCID. (n.d.). ORCID profile and researcher identification system.
    https://orcid.org/0000-0001-9943-0008
  3. Kokulnathan, T., Wang, T.-J., Kumar, E. A., Duraisamy, N., & Lee, A.-T. (n.d.). An electrochemical platform based on yttrium oxide/boron nitride nanocomposite for the detection of dopamine. Academic publication.
    https://scholar.google.com/citations?view_op=view_citation&hl=en&user=sv9_UoAAAAAJ&citation_for_view=sv9_UoAAAAAJ:YOwf2qJgpHMC
  4. Ferrigno, B., Bordett, R., Duraisamy, N., Moskow, J., Arul, M. R., & Rudraiah, S. (n.d.). Bioactive polymeric materials and electrical stimulation strategies for musculoskeletal tissue repair and regeneration. Scientific publication.
    https://scholar.google.com/citations?view_op=view_citation&hl=en&user=sv9_UoAAAAAJ&citation_for_view=sv9_UoAAAAAJ:kNdYIx-mwKoC

Dr. Zahra Mongashti | Computational Chemistry | Research Excellence Award

Published on by Chemistry Awards

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.

Citation Metrics (Scopus)

8

6

4

2

0

Citations
0

Documents
2

h-index
0

🟦 Citations   🟥 Documents   🟩 h-index


View Scopus Profile
 View ORCID Profile
 View Google Scholar Profile

Featured Publications

Dr. Faranak Hatami | Computational Chemistry | Best Researcher Award

Published on by Chemistry Awards

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.

Professional Profile : 

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