Department of Physics

Permanent URI for this communityhttps://ir.nbu.ac.in/handle/123456789/4173

Physics is one of those departments with which North Bengal University started its journey in the year 1962. At present there are nine faculty members and ten non-teaching employees in the department. The department has active research groups in the field of (a) Liquid Crystal, (b) Relativity, Cosmology, and Astrophysics, (c) High-energy Heavy-ion Interaction and Cosmic-ray Physics, and (d) Solid-state devices. Several research projects sponsored by the DST, DAE, UGC, and Tea Research Board are running in the department. In the year 2003 the department received a financial support under the FIST programme from the DST, Govt. of India. The department offers both M.Sc. and Ph.D. courses. A semester system is followed in the M.Sc. level, with three different areas of specialization namely, Condensed Matter Physics, Electronics and Nuclear and Particle Physics, out of which a student can choose one. The annual intake capacity in M.Sc. is 40 students. In the Ph.D. programme of the department right now 25 research students are enrolled under the supervision of different faculty members. Almost all faculty members are involved in intra and inter-university national and international collaborations of scientific research. The department houses one IUCAA Resource Centre, a Data Centre for Observational Astronomy, six teaching laboratories, several research laboratories and one departmental library. From time to time the department organizes Seminars, Symposia, Conferences, Schools, Refresher Courses, and Outreach Programs.

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Author: search.filters.author.Debnath, PratikSubject: search.filters.subject.Physics

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    Design and Development of Mixed Perovskite Solar Cells with High Efficiency and Stability through DFT and AI-Based Design Approaches
    (University of North Bengal, 2025-03) Chatterjee, Suman; Subba, Subham; Talukdar, Avijit; Debnath, Pratik; Sarkar, Joy
    Compared to different solar technologies, Perovskite-based solar cells are preferred by many for their high PCE and cost-effectiveness. Still, building a market-ready solution requires handling various important issues related to stability, how the device is designed, and efficiency. The study presents comprehensive approaches involving Density Functional Theory (DFT), device modeling, and Machine Learning (ML) to improve and evaluate mixed perovskite materials. DFT was utilized to study the electronic structure, energy gap, and defect properties of perovskites. By using SCAPS-1D simulations, different optimization factors were studied. Furthermore, different ML algorithms were trained to find key device properties. The training involved both experiments and simulations to learn from the data and predict how each material would work, allowing for fast screening of various perovskite compositions. Because of this framework, researchers can identify new, efficient materials and learn more about how different compositions affect solar cell performance. This strategy uses DFT modeling, numerical simulation, and data analysis together to improve the speed of developing better perovskite solar cells.