5 papers
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…
Towards Long-Horizon Vision-Language Navigation: Platform, Benchmark and Method
Xinshuai Song, Weixing Chen, Yang Liu +3
Existing Vision-Language Navigation (VLN) methods primarily focus on single-stage navigation, limiting their effectiveness in multi-stage and long-horizon tasks within complex and…
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…