4 papers · 1 filter
Machine Learning for Predicting Magnetization from X-ray Diffraction of Iron Oxide Nanoparticles Using Simple Physics-Based Data Generation
Frank M. Abel, Paige Burke, Daniel Wines +3
Automation and high-throughput characterization and synthesis for material development are becoming increasingly common; these approaches require machine learning (ML) tools to ass…
Toward improved property prediction of 2D materials using many-body quantum Monte Carlo methods
Daniel Wines, Jeonghwan Ahn, Anouar Benali +10
The field of two-dimensional (2D) materials has grown dramatically in the last two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic…
Probing Magnetic Properties of RuO Heterostructures Through the Ferromagnetic Layer
Frank M. Abel, Subhash Bhatt, Shelby S. Fields +20
RuO has been proposed as the prototypical altermagnetic material. However, several reports have recently questioned its intrinsic magnetic ordering, leading to conflicting fi…
Quantum Monte Carlo and density functional theory study of strain and magnetism in 2D 1T-VSe with charge density wave states
Daniel Wines, Akram Ibrahim, Nishwanth Gudibandla +18
Two-dimensional (2D) 1T-VSe has prompted significant interest due to the discrepancies regarding alleged ferromagnetism (FM) at room temperature, charge density wave (CDW) stat…