Atomic Fortune-Telling: Forecasting the Evolution of Chemical Reactions
Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.
Horawalavithana Selected as Editor of Two Journals
PNNL’s Sameera Horawalavithana joins the journals IEEE Transactions on Artificial Intelligence and Humanities and Social Sciences Communications.
Xantheas Honored with Gauss Professorship
Xantheas was one of four professors in 2021/2022 to be selected by the Göttingen Academy of Sciences and Humanities for this award.
Predicting Catalyst Degradation with Machine Learning
Robert Rallo from Pacific Northwest National Laboratory will direct a machine learning thrust for a new Department of Energy-funded project led by SLAC National Accelerator Laboratory.
Developing Data Science Approaches for Nanoparticle Synthesis
Machine learning methods and data science can uncover hidden patterns in nanoparticle synthesis conditions and property outcomes.
Water Research Earns INCITE Supercomputer Access
The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.
Physicist Malachi Schram Co-Edits ‘AI for Nuclear Physics’ Report
The workshop brought together 184 scientists to explore research opportunities for nuclear physics in artificial intelligence.
Decoding Protein Interactions with Domain-Aware Machine Learning
Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.
PNNL Joins Science Leaders on National Stage in Seattle
PNNL researchers and professional staff led discussions ranging from biothreats and climate change to science careers at the 2020 annual meeting of the American Association for the Advancement of Science, held this year in Seattle.