Theoretical Materials Science

Chowdhury Research Institute for Theoretical Materials Science

Pioneering high-quality research in applied quantum mechanics and condensed matter physics. Supporting doctoral, master's, and undergraduate theses, journal publications, conferences, and research projects.

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Advancing Materials Science
Through Theory & Computation

CRITMS is dedicated to pushing the boundaries of theoretical and computational materials science, bridging fundamental physics with real-world applications.

Quantum Mechanics

Applying first-principles quantum mechanical methods to understand and predict material properties at the atomic scale.

Computational Modeling

Leveraging high-performance computing and machine learning for accelerated materials discovery and screening.

Applied Research

Translating theoretical insights into practical solutions for energy, catalysis, electronics, and environmental challenges.

Academic Support

Providing mentorship and resources for doctoral, master's, and undergraduate theses, publications, and research projects.

Our Research Domains

Six interconnected domains spanning the frontiers of theoretical materials science.

Our Methodological Toolkit

State-of-the-art computational and theoretical approaches driving our research.

01

Density Functional Theory

First-principles electronic structure calculations for predicting material properties with quantum mechanical accuracy.

DFT Electronic Structure
02

Many-Body Methods

Advanced electronic structure techniques including GW, Bethe-Salpeter equation, and coupled-cluster approaches.

GW BSE
03

Quantum Chemistry

High-level ab initio and post-Hartree-Fock methods for precise molecular and materials characterization.

Ab Initio CCSD(T)
04

Molecular Dynamics

Classical and ab initio molecular dynamics simulations for studying atomic-scale dynamics and thermodynamics.

AIMD Thermodynamics
05

High-Throughput Screening

Automated computational pipelines for rapid discovery and evaluation of novel material candidates.

Automation Screening
06

Machine Learning

AI-driven materials discovery using neural networks, Gaussian processes, and graph-based models.

Neural Networks GP
07

Materials Informatics

Data-driven approaches combining databases, statistical analysis, and visualization for materials insights.

Big Data Statistics
08

Multiscale Modeling

Bridging atomistic to continuum scales for comprehensive understanding of material behavior and properties.

Multiscale Bridging

Leadership

Guided by experienced researchers and visionaries in theoretical materials science.

Scientific Director

Dr. Salena Akther

Overseeing scientific operations and research quality across all domains.

Chief Scientific Advisor

Prof. Dr. Golam Hafez

Providing strategic scientific guidance and mentorship to the research team.

Recent Research Output

Peer-reviewed contributions advancing the field of theoretical materials science.

2026

High-Throughput Screening of Two-Dimensional Materials for Quantum Computing Applications

S. M. Chowdhury, et al.

npj Computational Materials

2026

Machine Learning-Driven Discovery of Novel Metal–Organic Frameworks for Hydrogen Storage

S. Akther, S. M. Chowdhury, G. Hafez

Journal of Materials Chemistry A

2025

Electronic Structure and Catalytic Activity of Single-Atom Catalysts on 2D Substrates: A DFT Study

G. Hafez, S. M. Chowdhury

ACS Catalysis

2025

Topological Phase Transitions in Magnetic Heterostructures: A Multiscale Modeling Approach

S. M. Chowdhury, S. Akther

Physical Review Materials

Get in Touch

Interested in collaborating, pursuing research, or learning more about CRITMS? Reach out to us.

Address

Chowdhury Research Institute for Theoretical Materials Science