Projects |

First-Principles Thermal Transport

Wed, 12 Jul 2023 00:00:00 +0000

Overview

Heat conduction at the nanoscale is governed by phonons, and predicting it from first principles remains computationally demanding. This project develops and applies state-of-the-art methods to overcome these bottlenecks.

Key Contributions

Symmetry-adapted approach: Exploiting the line group symmetry of quasi-1D systems (carbon nanotubes, nanowires) to dramatically reduce the computational cost of thermal conductivity calculations via the Green-Kubo formalism.
ML-accelerated MD: Benchmarking and applying machine-learned interatomic potentials (MLIPs) to enable long-timescale molecular dynamics for accurate thermal conductivity prediction.
Defect effects: Systematic study of how intrinsic defects alter heat transport in 1D nanomaterials, bridging theory and experimental observations.

Ab-initio heat transport in defect-laden quasi-1D systems — npj Computational Materials (2026)
Accelerating first-principles MD thermal conductivity calculations — J. Chem. Theory Comput. (2025)
Accelerating Green-Kubo heat transport for quasi-1D systems using ML force fields — PSI-K 2025

PULGON Project

Wed, 12 Jul 2023 00:00:00 +0000

Symmetry-Based Materials Design

Tue, 01 Sep 2020 00:00:00 +0000

Overview

Identifying the stable atomic configurations of multi-component materials is a combinatorial challenge. This project addresses it by leveraging crystal symmetry to dramatically reduce the configuration space.

Key Contributions

Alloy ground states: Developed a symmetry-based classification scheme to efficiently determine the ground-state configurations of binary and ternary alloys, enabling high-throughput DFT screening.
Mixed-anion perovskites: Extended the symmetry approach to mixed-anion perovskite materials (e.g., halide–oxide–nitride combinations), accelerating the search for thermodynamically stable functional materials.
Topological materials: First-principles study of electronic structure and defect properties in topological magnetic materials (MnSb₂Te₄), relevant to quantum computing applications.

Determining ground states of alloys by a symmetry-based classification — Phys. Rev. Materials (2022)
Accelerating the identification of stable configurations in mixed-anion perovskite materials — Comput. Mater. Sci. (2025)
High Concentration Intrinsic Defects in MnSb₂Te₄ — Materials (2023)

Projects |

First-Principles Thermal Transport

Overview

Key Contributions

Related Publications

PULGON Project

Symmetry-Based Materials Design

Overview

Key Contributions

Related Publications