Research

Our research group focuses on Computational Thermodynamics and its applications in materials and metallurgical engineering, a vital component of Integrated Computational Materials Engineering (ICME). We aim to develop accurate Gibbs energy models for solid crystalline metal phases, with particular emphasis on modeling short-range ordering (SRO) effects, using advanced methods like the Cluster Variation Method (CVM). This work is crucial for designing advanced materials such as high-entropy alloys, Ti-based composites for defense, bioimplants, and energy storage systems. Our research combines experimental techniques (e.g., drop calorimetry, DSC) with first-principles calculations (e.g., DFT) to acquire thermochemical data, and we develop CE-CVM-based algorithms to predict phase diagrams and optimize material properties. We also contribute to CALPHAD and CE-CVM database development, supporting the design and processing of novel materials.

More specifically, we are interested in:

• Titanium-based systems
• Binary, ternary, and multicomponent transition metal systems
• Compositionally complex alloys (CCA and HEA)

1. Development of Functionally Graded Armor Composites (FGACs) Materials (2019-2022). Funded by DRDO under the ARMREB Grant-in-Aid Scheme.
2. Role of Short Range Ordering in designing High Entropy Alloys (2019-2022). Funded by SERB under Core Research Grant.
3. Development of low-cost β-Ti alloy for biomedical applications (2020-2023). Co-PI. Funded by SERB under Core Research Grant.
4. Phase-diagrams and thermodynamic investigations of Ti-Hf-Zr system using Cluster Variation Method (CVM) (2018-2020). Funded by IIT (BHU).
5. Free energy minimization in binary alloys via genetic algorithms (2012). Funded by UGC XI-Plan Research Grant for New Faculty.
6. Development of e-content on ancient Indian metallurgy and modern process metallurgy (2011-12). Funded by NMEICT, New Delhi.