4 papers
Computed materials proposals depart from the structural memory of experimental discovery
Dan Nguyen, Karen Cao, Brian Chu +3
Generative AI and high-throughput DFT pipelines propose millions of inorganic crystal structures, but lack a calibrated reference frame against experimentally realized chemistry. H…
Accelerating Quantum Materials Characterization: Hybrid Active Learning for Autonomous Spin Wave Spectroscopy
William Ratcliff
Autonomous neutron spectroscopy must solve three distinct tasks: detection (where is the signal?), inference (which Hamiltonian governs it?), and refinement (what are the parameter…
Attention Is Not All You Need for Diffraction
Elizabeth J. Baggett, Edward G. Friedman, Abhishek Shetty +5
Determining crystal symmetry from powder X-ray diffraction is a central problem in materials characterization, yet multiple space groups can produce indistinguishable patterns, mak…
Data Science Education in Undergraduate Physics: Lessons Learned from a Community of Practice
Karan Shah, Julie Butler, Alexis Knaub +3
It is becoming increasingly important that physics educators equip their students with the skills to work with data effectively. However, many educators may lack the necessary trai…