GW

5 items, newest first.

Now
Project
Persistent photoconductivity in hBN
Defect discovery and photoinduced doping in hexagonal boron nitride, aimed at deep-UV optoelectronics.
Physics AI/ML hBN 2D materials Point defects Persistent photoconductivity DFT GW BSE ML interatomic potentials Molecular dynamics
2025
Publication
Machine Learning-Driven First-Principles Modeling of Far-Infrared Materials
Ritwik Das. PhD thesis, Université Paris-Saclay, C2N (CNRS). NNT 2025UPAST100
Physics AI/ML Bayesian optimization Gaussian processes Machine learning DFT+U Hybrid functionals GW InSb InAsSb alloys Heterointerfaces Band alignment Virtual crystal approximation Alloys Infrared materials Semiconductors
PhD, completed 2025
Project
Machine-learning-driven modeling of far-infrared semiconductors
InSb, InAs, InAsSb alloys and CdTe/InSb heterointerfaces from first principles.
Physics Electronics Semiconductors Infrared materials InSb InAsSb alloys Heterointerfaces Alloys DFT DFT+U Hybrid functionals GW DFPT Band alignment Bayesian optimization Machine learning
2025
Publication
Structural, Electronic Properties and Band Gap Bowing Parameters of CuPt-Ordered InAsxSb1−x Alloys: First-Principles Insights from HSE, G0W0, mBJ, and DFT+U
R. Das, A.-S. Grimault-Jacquin, F. Aniel. Submitted to Physical Review Materials
Physics Electronics InAsSb alloys Alloys Semiconductors Infrared materials Hybrid functionals GW DFT+U
2025
Publication
High-fidelity electronic structure and properties of InSb: G0W0 and Bayesian-optimized hybrid functionals and DFT + U approaches
Ritwik Das, Anne-Sophie Grimault-Jacquin, Frédéric Aniel. Physical Review B 112, 075136
Physics AI/ML InSb Semiconductors Infrared materials GW Hybrid functionals DFT+U Bayesian optimization Machine learning