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Understanding how methanogenic bacteria can “bio-mine” minerals advances biotechnology and helps scientists understand the Earth’s geological history.
Powerful statistical tools, simulations, and supercomputers explore a billion different nuclear forces and predict properties of the very-heavy lead-208 nucleus.
In conflict with a long-held explanation of cadmium isotope motion, a new experiment found that cadmium-106 may rotate instead of vibrate.
Interfaces made by stacking certain complex oxide materials can tune the quantum interactions between electrons, yielding exotic spin textures.
Researchers detect an exotic electron phase called Wigner crystal in tungsten diselenide/tungsten disulfide moiré superlattices.
Patterned arrays of nanomagnets produce X-ray beams with a switchable rotating wavefront twist.
Nuclear physicists test whether next generation artificial intelligence and machine learning tools can process experimental data in real time.
New results could significantly improve resonance ionization mass spectrometry ultra-trace analysis of plutonium isotopes.
Particles choose partners for short-range correlations differently when farther apart in light nuclei versus when packed closer together in heavy nuclei.
As machine learning tools gain momentum, a review of machine learning projects reveals these tools are already in use throughout nuclear physics.
The results of parity-violating electron scattering experiments PREX and CREX suggest a disagreement with global nuclear models.
Roughening of fusion reactor wall surfaces over time may significantly reduce erosion rate predictions
