4 papers
A DFT and Machine Learning-Assisted Study on the Lattice Thermal Conductivity of LiCdSb for Thermoelectric Applications
R. Zosiamliana, Lalhriat Zuala, N. T. Tien +3
By using first-principles density functional theory (DFT) and the Boltzmann transport equation, we have calculated the corresponding electronic and thermoelectric properties of LiC…
Efficient molecular dynamics simulation of 2D penta-silicene materials using machine learning potentials
Le Huu Nghia, Pham Thi Bich Thao, Truong Do Anh Kha +2
Machine Learning Interatomic Potentials (MLIPs) are a modern computational method that allows achieving near-quantum mechanical accuracy (DFT) while still describing large-scale sy…
Symmetry-Driven Valleytronics in Single-Layer Tin Chalcogenides
Vo Khuong Dien, Pham Thi Bich Thao, Nguyen Thi Han +1
The concept of valleytronics has recently gained considerable research attention due to its intriguing physical phenomena and practical applications in optoelectronics and quantum…
Unlocking the Potential of GeS Monolayer: Strain-Enabled Control of Electronic Transports and Exciton Radiative Lifetimes
Vo Khuong Dien, Pham Thi Bich Thao, Nguyen Thi Han +4
Monolayer germanium sulfide is gaining significant attention for its exceptional anisotropic electronic conductance, notable excitonic effects, and wide range of potential applicat…