Researchers have developed a new artificial intelligence (AI)-powered approach to analyzing X-ray diffraction (XRD) data. The X-ray Crystallography companion Agent (XCA) approach assembles a group of AIs that debate each other while analyzing live streaming X-ray data. Once the AIs cast their final votes, the XCA approach uses the vote tally to interpret what the most likely atomic structure is and to suggest how confident the researchers should be of the AI analysis. The AI analysis matches human effectiveness but takes just seconds.
- Nature Computational Science
Drizzle is an important factor in how clouds form and change and how water moves around the Earth. This is an extremely complex process, so scientists simplify it for climate models using parameterization. However, many models do not model drizzle formation with sufficient accuracy. This research used data collected in the field along with machine learning to create new methods to estimate drizzle formation. The results also reveal the importance of drizzle drop number concentration in drizzle formation.
- Geophysical Research Letters
Scientists from Oak Ridge National Laboratory (ORNL) developed a new computational technique that improves the effective resolution of neutron instruments by 500 percent. The solution comes at virtually no cost since it requires no additional hardware and uses open source software.
- Review of Scientific Instruments
Industry produces acetone and isopropanol using processes that release carbon dioxide and other greenhouse gases. Researchers have now developed a new fermentation process that efficiently converts waste carbon oxide gases into acetone and isopropanol. This use of engineered bacteria advances progress on “carbon-negative” biomanufacturing for more sustainable industrial production and reduced greenhouse gas emissions.
- Nature Biotechnology
Quantum computers are prone to errors that limit their usefulness in scientific research. While error correction would be the ideal solution, it is not yet feasible due to the number of qubits needed. New research shows the value of an error mitigation approach called noise estimation circuits for improving the reliability of quantum computer simulations.
- Physical Review Letters
Scientists have developed a new theoretical model for preparing particle accelerator structures made of niobium metal. The model predicts how oxygen in the thin oxide layer on the surface of the niobium metal moves deeper into the metal during heat treatment. Tests indicate that the treatment should improve accelerator structure performance and make accelerators easier to build.
- Applied Physics Letters
Scientists have developed a groundbreaking AI-based algorithm for modeling the properties of materials at the atomic and molecular scale. It should greatly speed up materials discovery.
- Nature Communications