🔬Research
1. Development of Ab-initio Model for Phase Diagram of Binary Alloy.
- Melting Curve Calculation up to high pressure is crucial to predict the materials that sustain extreme conditions, including nuclear fusion reactors (as wall materials), the aerospace industry, military projects, and so on.
- Melting curves up to higher pressures are necessary for understanding the structure of planets and the behavior of their cores.
- Fundamental to predict the phases of material under high temperatures and pressure in material sciences.
- Alloys exhibiting high melting points and mechanical strength (hardness) with low thermal expansion coefficients are highly desirable for several applications including the aerospace industry, military projects, and nuclear fusion reactors (as wall materials).
- Introducing impurities on pristine metals at different concentration levels and doping regimes to predict the stable alloys and study their structural, electronic, magnetic, and thermo-mechanical properties under different pressure conditions utilizing the first principle density functional theory (DFT) calculations and molecular dynamic simulation. Further, electronic structure and statistical mechanics techniques in adjunct to a complementary approach can be employed to predict the accurate phase diagram for the alloys and compare the results with pristine bulk metals.
- Introducing impurities leads to changes in the material's electronic structure and chemical potential, resulting in improved physio-chemical properties. These alloy enhancements are critically important for a vast array of applications.
- We will use first-principle calculations coupled with recent Machine Learning Techniques to predict the melting properties of metals and alloys.
2. Premelting Effect in the Mechanical Properties Materials.
- The melting behaviour of materials is affected by the inclusion of impurities. Using ab-intio molecular dynamics and electronic structural calculation we compute the phase diagram up to high pressure.
4. Low dimensional (0 D, 1D and 2D) material properties
- Quantum transport (DFT + NEGF)
- Thermodynamics
- Nanomechanics
- Optoelectronics
- Magnetism
- Influence of doping, strain, electric field, and chemical passivation.
5. Predict Novel multi-functional 2D materials.
- Predict and design new 2D material using structural prediction techniques and Machine Learning.
- Test their stability and formation (AIMD+DFT)
- Compute various properties
6. 3D materials and their facet-dependent properties.
- Bulk to slab cleaving and modeling.
- Doping effects.
7. Predict Novel Electrides.
- DFT and AIMD to explore novel elelctrides (0D to 3D)
8. 3D materials and their facet-dependent properties
- Bulk to slab cleaving and modeling.
- Doping effects.