Research
Experimental Inorganic and Solid-State Chemistry
Synthesis of Rare-earth containing chalcogenides, oxychalcogenides, and Intermetallics through high-temperature solid-state synthesis or ceramic method.
Structure determination through X-ray crystallography using single crystal and/or powder X-ray diffraction.
Measuring physical properties such as optical band gaps using UV-Vis-NIR spectrometer, and magnetic and resistivity using PPMS.
Explore the potential applications of discovered materials, such as electrocatalysis (HER, OER), and thermoelectrics in collaboration with multidisciplinary teams.
Machine Learning to Accelerate Materials Discovery
Assessing the potential of materials already available in the literature for solid oxide fuel cells and laser applications.
Compiling a library of compounds through a literature survey to train the machine-learning models.
Identify new candidates through classifier models and predict their properties through regression models.
As humans can not understand complex black box models, I use SISSO to get 1 - 2 dimensional interpretable models.
Verifying the predictions experimentally.
DFT Calculations to Unravel the Electronic Structure of Materials
Perform the first principle quantum calculations to evaluate the electronic structure of materials and understand their behavior, such as metallic, semiconducting, or insulating.
Routine calculations involve band structure to know the type of band gap (direct or indirect) and density of states (DOS).
Infer the chemical bonding through Crystal Orbital Hamilton Populations (COHP) and visualize by Electron Localization Functions (ELFs).
Quantify the ionic and covalent character through Crystal Orbital Bond Index calculations (COBI).
Frequent use of VASP and occasional use of LMTO, Quantum Espresso, and AkaiKKR.
My primary research focuses on experimental Inorganic and Solid-State Chemistry, integrating advanced machine learning algorithms and first-principle quantum calculations.
1. Oxychalcogenides: Investigating materials with insulating and semiconducting blocks in their crystal structure, allowing precise tuning of band gaps for electrocatalytic applications (HER and OER) and thermoelectrics. [Link1] [Link2]
2. Chalcogenides: Exploring materials for semiconducting applications, including their use in photovoltaic cells and catalysis. [Link1] [Link2] [Link3] [Link4]
3. Intermetallics: Studying materials for their magnetic and resistivity properties. [Link1] [Link2] [Link3]
4. Coloured Intermetallics: Investigating materials with intriguing colors, potentially applicable in jewelry and battery technologies. [Link1] [Link2]
I grow single crystals of these materials through high-temperature standard solid-state synthesis and employ Bruker's Platform, D8 Venture single-crystal X-ray diffractometer for crystallographic analysis. Phase purity of powder samples is confirmed using Bruker D8 advance powder X-ray diffractometer, and the quality and composition of single crystals are assessed through Jeol scanning electron microscope, Zeiss Sigma 300 VP-FESEM, and EDX analysis. Diffuse reflectance measurements are conducted to determine optical band gaps.
Following the experimental discovery of materials, I delve into understanding their electronic properties, including band structure and Density of States. Chemical bonding is explored to quantify ionicity and covalency in constructing these materials.
Recently, I've incorporated machine learning algorithms to expedite material discovery. Employing ML, I classify and predict new materials such as Perovskites, Spinels, and non-centrosymmetric compounds for applications in solid oxide fuel cells, catalysts, lasers, and solar cells.
Predictions of materials and related properties from ML results are only helpful when they can be realized experimentally. Thus, after predictions, I verify them experimentally on a laboratory scale.