Research · Materials AI & Energy

Research in materials AI & solid-state batteries

I work at the intersection of atomistic simulations, data-driven models and inverse design, with a focus on solid electrolytes for all-solid-state batteries and related energy materials.

Current position
Doctoral researcher, DTU Energy
Deep generative models for solid electrolytes
Research themes
Inverse design · Generative modelling · Fast-ion conductors
Collaborations
DTU Energy · University of Queensland · Industry partners
PhD project

Deep generative models for inverse design of solid electrolytes

The long-term goal is to accelerate the discovery of stable, high-conductivity solid electrolytes that can enable safer and more efficient all-solid-state batteries.

1

Motivation

The transition to green energy requires safe, scalable and affordable energy storage. Solid-state batteries promise higher energy densities and improved safety compared to conventional liquid-electrolyte cells.

Discovering suitable solid electrolytes is challenging because of the vast chemical and structural design space and the demanding stability and conductivity requirements.

2

Approach

I develop periodic deep generative models that can propose candidate crystal structures conditioned on target properties such as thermodynamic stability and ionic conductivity.

These models are integrated with high-throughput first-principles calculations and workflows for screening and refinement.

3

Objectives

The overarching goals of the project include:

  • Design of solid electrolytes with high Li-ion conductivity.
  • Development of generative models tailored to periodic materials.
  • Understanding ionic transport mechanisms via atomistic simulations and model analysis.
Previous & parallel work

Broader research experience

Before focusing on solid-state batteries, I worked on atomistic modelling of solid–liquid interfaces, electronic properties of topological materials and high-throughput discovery of functional materials.

Q

Qpi Volta Technologies

At Qpi Volta I contributed to projects on high-throughput discovery of solid electrolytes for Na-ion batteries, machine-learning interatomic potentials for interfaces, and environmentally friendly materials for diverse applications.

This work connected industrial needs in energy materials with state-of-the-art simulation and data-driven methods.

J

Jawaharlal Nehru Centre for Advanced Scientific Research

At JNCASR I worked on atomistic modelling of solid–liquid interfaces, studying the dissolution of platinum in water using first-principles simulations, in collaboration with researchers at Lawrence Livermore National Laboratory.

The project combined surface science, electrochemistry and ab-initio modelling.

I

Indian Institute of Technology (BHU)

During my Master’s at IIT-BHU I studied electronic properties of topological insulators and Weyl semimetals using first-principles calculations, with a broader background in condensed matter physics and quantum information.

This early work shaped my interest in materials informatics and quantum-mechanical modelling.

Publications & output

Papers, talks & open resources

A full, always-up-to-date list of publications and research outputs is maintained in institutional databases and academic profiles.

For the complete publication list, please see my DTU profile.

The DTU Research Database entry aggregates peer-reviewed articles, conference contributions and related outputs linked to my affiliations.

Additional resources, preprints and code may also appear on GitHub and other platforms linked from the homepage.
DTU publication profile
Preprints · Talks · Code