Under the three-year DeNOVO project, LLNL and other institutions will apply high-performance computing and AI to push the boundaries of antibody design.
Science and Technology Highlights
In a study published in PNAS Nexus, LLNL researchers described how a new deep learning model is capable of predicting toxic plume behavior in just a few minutes.
LLNL is partnering with Cornell University to build the Autonomous Alloy Prediction and EXperimentation (APEX) platform for 3D printing, grinding, polishing and characterizing alloy samples.
LLNL scientists and Purdue University collaborators develop and demonstrate a high-throughput, automated mass spectrometry platform.
LLNL and the Extreme Light Infrastructure (ELI) European Research Infrastructure Consortium (ERIC) have signed a new Memorandum of Understanding that builds on their existing strategic collaboration for scientific research and laser innovation.
In a recent study, published in Nature, an international team including LLNL researchers experimentally measured the structure of liquid carbon for the first time.
A new cancer drug candidate developed by LLNL and collaborators demonstrates the ability to block tumor growth without triggering a common and debilitating side effect.
LLNL and collaborators have succeeded in describing warm dense matter much more accurately than before using a new computational method.
In a new study LLNL researchers and collaborators triggered a slow decomposition of a high explosive and measured the effects on the molecules within it.
LLNL researchers develop a novel 3D printing technique that uses light to build complex structures, expanding possibilities in multi-material additive manufacturing.