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Combining synthesis, characterization, and theory confirmed the exotic properties and structure of a new intrinsic ferromagnetic topological material.
Scientists develop a new learning method that incorporates quantum chemistry descriptions with conventional machine learning to predict the properties of biochemical molecules.
Neutrons reveal remarkable atomic behavior in thermoelectric materials for more efficient conversion of heat into electricity.
The results may offer insight into the quark-gluon plasma—the hot mix of fundamental nuclear-matter building blocks that filled the early universe.
Studies of the nanostructure of a chiral magnet provides insights on controlling magnetic properties for applications in computers and other electronics.
New optics-on-a-chip device paves the way to helping characterize fast chemical, material, and biological processes.
Neutron scattering monitors structures during post-production heat treatment to validate production models.
Neural networks determine the amplitude and phase of X-ray pulses, enabling new, high-resolution quantum studies.
Using two methods is better than one when it comes to observing how solar cells form and improving cell properties.
Scientists capture the short-lived hydroxyl-hydronium pair and the induced dynamic response in ionized liquid water in unprecedented detail.
Photon-deuteron collisions offer insight into the gluons that bind the building blocks of matter—and what it takes to break protons and neutrons apart.
Discovery of a short-lived state could lead to faster and more energy-efficient computing devices.
