Dr. Pooja Sharma | Computational Chemistry | Research Excellence Award

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Dr. Pooja Sharma | Computational Chemistry | Research Excellence Award

Assistant Professor | Chandigarh University | India

Dr. Pooja Sharma is a dedicated researcher whose work in Computational Chemistry consistently advances the understanding of material behaviour for sustainable energy technologies. Her contributions in Computational Chemistry focus on theoretical investigations of perovskite materials, optoelectronic properties, and structural modelling for improved solar-energy systems. Through extensive publications in high-quality journals, she demonstrates strong proficiency in Computational Chemistry, integrating density functional theory, conceptual modelling, and simulation-driven interpretation of electronic structures. Her expertise in Computational Chemistry has supported multidisciplinary collaborations with research groups working on photovoltaics, molecular modelling, and material innovation. She applies Computational Chemistry to explore environmentally relevant materials, contributing to societal progress by enabling cleaner and more efficient technologies. Her sustained involvement in collaborative projects and workshops highlights her commitment to advancing Computational Chemistry as a tool for scientific development, while her academic contributions reflect a deep understanding of the broader impact of material research. As a leading voice in Computational Chemistry, she continues to enhance knowledge exchange across academia, fostering innovation in sustainable energy applications. Her research orientation, grounded in Computational Chemistry, reinforces her role as a scholar with meaningful influence. Google Scholar Profile Of Citations 104, h-index 5, i10-index 4.

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Featured Publications

Mehabaw Fikrie Yehuala |  Computaional Physics | Best Researcher Award

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Mr. Mehabaw Fikrie Yehuala |  Computaional Physics | Best Researcher Award

Chief Academic Technical Assistant | University of Gondar | Ethiopia

Mr. Mehabaw Fikrie Yehuala is an emerging researcher and academic professional specializing in Computational Physics, with an active role as Chief Academic Technical Assistant at the University of Gondar. His career reflects a deep commitment to advancing Computational Physics through theoretical modeling, simulation techniques, and practical implementation in modern physical systems. His research expertise centers on Computational Physics applications in material dynamics, phase separation, and simulation-based investigations, particularly focusing on systems involving complex mixtures and energy interactions. Through his scholarly journey, Mr. Mehabaw has demonstrated a rigorous approach to Computational Physics, integrating programming proficiency in Python, Fortran, and LaTeX with analytical frameworks to model and interpret physical phenomena. His publication in Separation Science and Technology stands as a key contribution to the scientific community, highlighting the relevance of Computational Physics in studying the phase separation of oil–water mixtures using Monte Carlo simulation methods. His collaborative research embodies an interdisciplinary essence, bridging experimental insights with the predictive strength of Computational Physics. Mr. Mehabaw’s professional engagement extends beyond research into educational innovation, where he has contributed significantly to the development of physics laboratory manuals and academic resource materials, further strengthening the pedagogical aspects of Computational Physics education. His recognition for academic excellence and active participation in institutional development underscores his leadership and dedication to the advancement of scientific knowledge. As an analytical thinker and a collaborative scientist, Mr. Mehabaw continues to explore new dimensions in Computational Physics, contributing to both academic and societal progress. His vision emphasizes fostering research-driven learning environments and leveraging Computational Physics methodologies to address real-world scientific and industrial challenges, marking him as a promising contributor to the global physics and research community.

Profile: ORCID

Featured Publication

1. Fikrie, M., Birhanu, T., Bassie, Y., Abebe, Y., & Temare, Y. (2025). Investigation of phase separation of mixture of oil and water in Monte Carlo simulation. Separation Science and Technology.

Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

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Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

Professor | Xi'an Jiaotong University | China

Prof. Dr. Jinju Sun is a distinguished scholar in the School of Energy and Power Engineering at Xi’an Jiaotong University, renowned for her pioneering contributions to fluid mechanics, turbomachinery, and multiphase flow systems through advanced Computational Methods. Her educational journey spans cryogenic engineering to a PhD in turbomachinery and engineering mechanics, which laid the foundation for her expertise in Computational Methods applied to turbomachinery optimization, Lattice Boltzmann modeling, and Vortex Method simulations. Throughout her professional career, she has served as a researcher, lecturer, and professor, advancing research through numerous national and international collaborations emphasizing Computational Methods in fluid dynamics and green energy system design. She has received prestigious honors, including the Donald Julius Groen Prize and the Arthur Charles Main Award from the Institution of Mechanical Engineers (UK), in recognition of her outstanding achievements utilizing Computational Methods for energy system modeling and flow optimization. Her research interests include cryogenic liquid turbines, compressor instabilities, and innovative Computational Methods for fluid-structure interaction and multiphase flow behavior. She has authored numerous high-impact publications and holds multiple international patents that demonstrate her excellence in Computational Methods-based innovation. Prof. Dr. Jinju Sun’s research skills encompass CFD modeling, LBM, topology optimization, and Computational Methods-driven analysis for turbomachinery and green energy systems. In conclusion, her dedication to advancing Computational Methods in engineering has positioned her as a global leader driving innovation, sustainability, and scientific excellence in modern energy and power engineering.

Profile: ORCID

Featured Publications

1. Qu, Y., Sun, J., Song, P., & Wang, J. (2025). Enhancing efficiency and economic viability in Rectisol system with cryogenic liquid expander. Asia-Pacific Journal of Chemical Engineering.

2. Ge, Y., Peng, J., Chen, F., Liu, L., Zhang, W., Liu, W., & Sun, J. (2023). Performance analysis of a novel small-scale radial turbine with adjustable nozzle for ocean thermal energy conversion. AIP Advances.

3. Fu, X., & Sun, J. (2023). Three-dimensional color-gradient lattice Boltzmann model for simulating droplet ringlike migration under an omnidirectional thermal gradient. International Journal of Thermal Sciences.

4. Song, P., Sun, J., Wang, S., & Wang, X. (2022). Multipoint design optimization of a radial-outflow turbine for Kalina cycle system considering flexible operating conditions and variable ammonia-water mass fraction. Energies.

5. Song, P., Wang, S., & Sun, J. (2022). Numerical investigation and performance enhancement by means of geometric sensitivity analysis and parametric tuning of a radial-outflow high-pressure oil–gas turbine. Energies.

Sathya Arumugam Thirumalai | Computational Methods | Young Scientist Award

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Mr. Sathya Arumugam Thirumalai | Computational Methods | Young Scientist Award

Mr. Sathya Arumugam Thirumalai | Indian Institute of Technology Roorkee | India

Mr. Sathya Arumugam Thirumalai is a highly motivated researcher whose work integrates Computational Methods with experimental nanomaterial science, emphasizing sustainability, environmental protection, and advanced detection technologies. His academic journey, from IIT Roorkee to TU Dresden, reflects an enduring commitment to merging experimental nanotechnology with Computational Methods for the synthesis and characterization of perovskite, MXene, and 2D materials. Mr. Sathya’s professional experience spans renowned institutions like IISc Bengaluru, BARC Mumbai, and IIT Roorkee, where he utilized Computational Methods in density functional theory (DFT) simulations, material modeling, and radiation detector design. His research, grounded in Computational Methods, has contributed to multiple journal publications addressing gas sensing, field emission, and radiation detection. He applies Computational Methods to optimize nanomaterial performance, enhance photonic properties, and improve the efficiency of radiation detectors. Recognized with several awards and fellowships, including the National Talent Search Fellowship and the Saxon Student Mobility Grant, he has demonstrated excellence in both theoretical and practical domains. His technical mastery extends to Python, MATLAB, COMSOL, and VASP, emphasizing his strength in applying Computational Methods across interdisciplinary fields. Mr. Sathya’s skill in Computational Methods enables him to bridge theoretical simulations with experimental validation, ensuring scientific precision and innovation. His collaborative engagements with global research groups highlight his leadership and cross-disciplinary adaptability. In conclusion, Mr. Sathya exemplifies how Computational Methods can revolutionize material science, fostering technological advancements that align with sustainability and human welfare.

Profiles: Google Scholar | ORCID

Featured Publications

1. Sathya, A. T., Jethawa, U., Sarkar, S. G., & Chakraborty, B. (2025). Pd-decorated MoSi₂N₄ monolayer: Enhanced nitrobenzene sensing through DFT perspective. Journal of Molecular Liquids, 427, 127310.

2. Sathya, A. T., Kandasamy, M., & Chakraborty, B. (2024). Strain induced nitrobenzene sensing performance of MoSi₂N₄ monolayer: Investigation from density functional theory. Surfaces and Interfaces, 55, 105386.

3. Sanyal, G., Vaidyanathan, A., Sathya, A. T., & Chakraborty, B. (2025). Efficient catechol sensing in newly synthesized 2D material Ti₂B MBene: Insights from density functional theory simulations. Langmuir, 41(33), 22525–22534.

4. Sathya, A. T., Sarkar, S. G., Bakhtsingh, R. I., & Mondal, J. (2024). Suppression of shielding effect of large area field emitter cathode in radio frequency gun environment. Physica Scripta, 99(12), 125301.