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…
A comparative first-principles investigation of bilayer NbOX2 (X=Cl, Br, I) for Photocatalytic water splitting applications
Laku Dorjee Tamang, Shivraj Gurung, Bhanu Chettri +6
Motivated by our previous work on bulk NbOX2 , where we have reported its high 1dielectric polarisation and finite piezoelectric response, this work extends to its 2D homo bilayer…
Tuning the optoelectronic and magnetic properties of Penta-PtN2 nanoribbons via edge engineering and defects
Le Thi Thuy My, Pham Thi Bich Thao, Nguyen Hai Dang +1
In this study, we investigate aspects including the structural, electronic, optical, and magnetic properties of the PtN$\_\{2\}$ nanoribbons.
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…