Dr. Ahmad Ranjbar | Density Functional Theory | Best Researcher Award
University of Paderborn | Germany
AUTHOR PROFILE
EARLY ACADEMIC PURSUITS
Dr. Ahmad Ranjbar's academic journey began with a Bachelor's degree in Physics from Ferdowsi University of Mashhad, where he graduated with distinction. He then pursued a Master's degree in Condensed Matter Physics at Sharif University of Technology, focusing on first-principles calculations of many-body states for single nitrogen-vacancy defects in diamond. His PhD in Materials Science & Engineering from Tohoku University further honed his expertise, with a thesis on hydrogen adsorption on carbon-based materials, specifically applied to magnetism and energy storage.
PROFESSIONAL ENDEAVORS
Dr. Ranjbar has held several prestigious positions throughout his career. He is currently a Guest Scientist at the University of Paderborn, Germany, where he implements hybrid machine learning models and discovers novel materials. His previous roles include being a Research Scientist at Technische Universität Dresden and a Project Engineer at Steinbeis-Forschungszentrum quantUP, where he focused on computational investigations of gas sensors and numerical modeling of sputter deposition processes. His extensive experience also includes a Senior Research Scientist role at the University of Paderborn and a Postdoctoral Researcher position at RIKEN Center for Computational Science, where he conducted in-depth first-principles DFT investigations.
CONTRIBUTIONS AND RESEARCH FOCUS
Dr. Ranjbar’s research is centered on Density Functional Theory (DFT) and its applications in materials science. His work includes developing functional materials for energy harvesting, storage, and photocatalysis. He has conducted pioneering research on MAX phases and 2D MXenes, exploring their electronic, magnetic, and quantum transport characteristics. His contributions also extend to the study of topological insulators, magnetic topological insulators, and gas sensors, where he has applied high-throughput computational screening and hybrid machine learning models.
IMPACT AND INFLUENCE
Dr. Ranjbar's work in Density Functional Theory and computational materials science has significantly influenced the field. His research on the catalytic activity of various phases of NiS2, the discovery of topological insulator materials, and the development of photocatalysts have been widely recognized. His ability to integrate machine learning with traditional computational methods has advanced the understanding and prediction of material properties, impacting both academic research and practical applications in energy and sensor technologies.
ACADEMIC CITES
Throughout his career, Dr. Ranjbar has authored numerous publications in high-impact journals. His expertise in Density Functional Theory and materials science has led to significant citations, highlighting the importance and relevance of his work. His research on 2D MXenes, photocatalytic materials, and gas sensors has been extensively cited, reflecting his contributions to advancing computational techniques and material innovations.
LEGACY AND FUTURE CONTRIBUTIONS
Dr. Ahmad Ranjbar's legacy is built upon his groundbreaking research in computational materials science and Density Functional Theory. His innovative approaches to integrating machine learning with first-principles modeling techniques have set new standards in the field. As he continues his work, Dr. Ranjbar is expected to make further advancements in the development of new materials for energy applications and sensor technologies. His commitment to education and collaboration ensures that his contributions will continue to influence future generations of scientists.
DENSITY FUNCTIONAL THEORY
Central to Dr. Ranjbar’s work is Density Functional Theory, a powerful computational method used to investigate the electronic structure of materials. His proficiency in DFT has enabled significant discoveries in various domains, including topological materials, MXenes, and gas sensors. Dr. Ranjbar’s expertise in DFT not only contributes to the theoretical understanding of material properties but also drives practical innovations in material design and application, underscoring the critical role of this theory in modern materials science.
NOTABLE PUBLICATION
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Citation: 01 Year: 2023
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Citation: 01 Year: 2022
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Citation: 03 Year: 2022
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Citation: 03 Year: 2022
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Citation: 24 Year: 2020