Associate Professor
Amrita Bhattacharya
Email: b_amrita[at]iitb[dot]ac[dot]in
Phone: (+91) (022) 2576 7620
Education:
- BSc Phy. Burdwan University, 2004
- MSc Phy., Burdwan University, 2006
- PhD Matls. Sci., Indian Asso. for the Cultivation of Sci., 2012
Prof. Amrita Bhattacharya has interest in the various topics of materials science related to condensed matter physics. Over the last five years, she has taught the following courses in the department; Undergraduate courses: MM318, Electronic properties of materials Postgraduate courses: MM747, First principles approach to materials science
Prof. Amrita Bhattacharya leads the Ab initio Computational Materials Simulation laboratory in the MEMS department. Her works involve understanding and predicting the microscopic phenomena behind the electronic, magnetic, and transport properties of emerging materials using the stateoftheart quantum mechanical density functional theory based methods. In addition, she has also set up an experimental laboratory for the solidstate synthesis of alloys and for the analysis of their electronic transport properties. She also has an interest in data driven machine learning based methods.
- Computational Materials Science,
- Density functional theory based methods,
- Electronic structure theory,
- Charge and heat transport,
- Machine learning
Unravelling the charge and heat transport in thermo- electric materials through theory and experiments ;
- Strain driven anomalous anisotropic enhancement in the thermoelectric performance of monolayer MoS2, S Chaudhuri, A Bhattacharya*, AK Das, GP Das, BN Dev Applied Surface Science 626, 157139 (2023).
- Self-Doping for Synergistically Tuning the Electronic and Thermal Transport Coefficients in nType Half-Heuslers, P R Raghuvanshi, D Bhattacharjee, A Bhattacharya*, ACS Applied Materials & Interfaces 13 (46), 55060 (2021)
- A high throughput search for efficient thermoelectric halfHeusler compounds, P R Raghuvanshi, S Mondal, A Bhattacharya Journal of Materials Chemistry A 8, 25187 (2020)
Exploring the physics of correlated magnetic oxides and other magnetic metallic phases.
- First-principles investigation of the structure, stability, and magnetic properties of the Heusler alloy J Jami, R Pathak, N Venkataramani, KG Suresh, Amrita Bhattacharya*, Physical Review B 108 (5), 054431 (2023)
- A strategic high throughput search for identifying stable Li based half-Heusler alloys for spintronics applications, R Pathak, PR Raghuvanshi, A Bhattacharya*, Journal of Magnetism and Magnetic Materials 553, 169244 (2022).
High throughput calculations and machine learning the physical properties of materials
- Machine learning the vibrational free energy of perovskites, K Kundavu, S Mondal, A Bhattacharya, Materials Advances (2023).
- Thorough Descriptor Search to Machine Learn the Lattice Thermal Conductivity of Half-Heusler Compounds, D Bhattacharjee, K Kundavu, D Saraswat, PR Raghuvanshi, Amrita Bhattacharya*, ACS Applied Energy Materials 5 (7), 8913 (2022).