Soungmin Bae

collaborators

3 papers

cond-mat.mtrl-sci2025

Machine Learning Prediction of Charged Defect Formation Energies from Crystal Structures

Shin Kiyohara, Chisa Shibui, Soungmin Bae +1

Recent advances in materials informatics have expanded the number of synthesizable materials. However, screening promising candidates, such as semiconductors, based on defect prope…

cond-mat.mes-hall2024

Exploring Intrinsic and Extrinsic $p$ -type Dopability of Atomically Thin $β$ -TeO $_{2}$ from First Principles

Rafael Costa-Amaral, Soungmin Bae, Vu Thi Ngoc Huyen +1

Two-dimensional (2D) $β$ -TeO $_{2}$ has gained attention as a promising material for optoelectronic and power device applications, thanks to its transparency and high hole mobility. H…

cond-mat.mtrl-sci2024

Native defects and $p$ -type dopability in transparent $β$ -TeO $_{2}$ : A first-principles study

Vu Thi Ngoc Huyen, Soungmin Bae, Rafael Costa-Amaral +1

Although $β$ -TeO $_{2}$ is a promising $p$ -type transparent conducting oxide (TCO) due to the large optical gap ( $\sim$ 3.7 eV) and a light effective hole mass, its hole dopability st…

Machine Learning Prediction of Charged Defect Formation Energies from Crystal Structures

Exploring Intrinsic and Extrinsic p-type Dopability of Atomically Thin β-TeO2​ from First Principles

Native defects and p-type dopability in transparent β-TeO2​: A first-principles study

Exploring Intrinsic and Extrinsic $p$ -type Dopability of Atomically Thin $β$ -TeO $_{2}$ from First Principles

Native defects and $p$ -type dopability in transparent $β$ -TeO $_{2}$ : A first-principles study