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.
Roughening of fusion reactor wall surfaces over time may significantly reduce erosion rate predictions
Researchers use CRISPR to engineer a bacteriophage to deliver DNA into targeted members of microbial communities for precise genome editing.
Scientists analyzed detonation formation in hydrogen/methane air mixtures, quantifying the effect of non-thermal reactions on the mechanism of detonation.
A novel experiment sheds new light on a possible mechanism that may seed magnetic fields for the galactic dynamo.
New improvements to an open-source platform streamline enzyme engineering.
Even microbes that can’t break down a plentiful food source can still be successful by interacting with fellow community members.
New measurements show the proton’s electromagnetic structure deviates from theoretical predictions.
AI reveals relationships between weather systems and cloud physics.
