AI in Superconductivity and Magnetism
Design and optimization of superconducting materials
Prediction of magnetic properties and new phases
AI-assisted study of superconducting and magnetic mechanisms
Machine learning applications in magnetic quantum materials
Intelligent experimental data processing and analysis
Smart control for superconducting devices
AI in Low-dimensional and Topological Physics
Identification and classification of topological materials
Electronic state analysis in low-dimensional systems
Topological quantum computing and information processing
Dynamics simulations of low-dimensional heterostructures
Detection of topological phases and experimental data analysis
AI in Non-equilibrium and Statistical Physics
Simulations of non-equilibrium dynamics and phase transitions
Modeling of many-body system dynamics
Analysis of thermal transport and energy conversion
Theoretical modeling of non-equilibrium systems
Deep learning in complex dissipative systems
Integration of intelligent simulations with experimental data
Intelligent Methods in Computational and Materials Physics
AI-assisted electronic structure calculations
Multiscale materials simulations with machine learning
High-throughput materials screening and design
Analysis of defects and interfaces in electronic structures
Machine-learned potentials and accelerated simulations
AI research in energy materials
