A5031054645- Machine Learning in Materials Science
- Magnetic and transport properties of perovskites and related materials
- 2D Materials and Applications
- Electronic and Structural Properties of Oxides
- Magnetic properties of thin films
- Advanced Condensed Matter Physics
- Recycling and Waste Management Techniques
- Integrated Circuits and Semiconductor Failure Analysis
- Iron-based superconductors research
- Advanced Semiconductor Detectors and Materials
- Semiconductor Quantum Structures and Devices
- Multiferroics and related materials
- Advanced Memory and Neural Computing
- Extraction and Separation Processes
- Topological Materials and Phenomena
- Advancements in Battery Materials
Carnegie Mellon University
2024-2025
Tsinghua University
2023-2024
Majorana zero modes are predicted to emerge in semiconductor/superconductor interfaces, such as InAs/Al. could be utilized for fault tolerant topological qubits. However, their realization is hindered by materials challenges. The coupling between the superconductor and semiconductor may too strong emerge, due effective doping of metallic contact. This mediated adding a tunnel barrier controlled thickness. We use density functional theory (DFT) with Hubbard U corrections, whose values...
Abstract The profound impact of excited magnetic states on the intricate interplay between electron and lattice behaviors in materials is a topic great interest. Unfortunately, despite significant strides that have been made first-principles methods, accurately tracking these phenomena remains challenging elusive task. crux challenge lies before us centered task characterizing configuration an state, utilizing first-principle approach firmly rooted ground state system. We propose versatile...
Atomistic simulations hold significant value in clarifying crucial phenomena such as phase transitions and energy transport materials science. Their success stems from the presence of potential functions capable accurately depicting relationship between system lattice changes. In magnetic materials, two atomic scale degrees freedom come into play: spin. However, tracing simultaneous evolution both spin at an is a substantial challenge. This largely due to complexity involved interaction...
Atomistic simulations hold significant value in clarifying crucial phenomena such as phase transitions and energy transport materials science. Their success stems from the presence of potential functions capable accurately depicting relationship between system lattice changes. In magnetic materials, two atomic scale degrees freedom come into play: spin. However, tracing simultaneous evolution both spin at an is a substantial challenge. This largely due to complexity involved interaction...
Majorana zero modes are predicted to emerge in superconductor/semiconductor interfaces, such as Al/InAs. could be utilized for fault tolerant topological qubits. However, their realization is hindered by materials challenges. The coupling between the superconductor and semiconductor may too strong emerge, due effective doping of metallic contact. This mediated adding a tunnel barrier controlled thickness. We use density functional theory (DFT) with Hubbard U corrections, whose values...
Spin fluctuations have a substantial influence on the electron and lattice behaviors in magnetic materials, which, however, is difficult to be tracked properly by prevalent first-principles methods. We propose versatile self-adaptive spin-constrained density functional theory formalism. Applying it simulation of itinerant ferromagnetic Fe, we present potential energy surface comprising longitudinal transverse variations magnetization. Moreover, this method enables us identify delicate...
Magnetic axis rotation (MAR) in ferromagnetic (FM) layers is crucial for strain-mediated converse magnetoelectric coupling. Employing the density functional theory (DFT), we computationally study magnetic anisotropy of selected deformed FM materials such as body-centered iron. The results show that short more energy-favorable at high in-plane strain difference than previously predicted phenomenologically. This anomalous trend and complex energy behaviors different conditions explain why...