Uploaded December 2021 | Updated September 2026, 1 week ago
LLNL’s Data Science Institute (DSI) was established in 2018 to enable excellence in data science research and applications across the Lab’s core missions. Computational chemist Rebecca Lindsey, PhD, explains how machine learning and data science techniques are used to develop diagnostic tools for stockpile stewardship, such as models that predict detonator performance. Lindsey also describes how atomistic simulations improve researchers’ understanding of the microscopic phenomena that govern the chemistry in materials under extreme conditions. For example, machine learning interatomic models have recovered structure, dynamics, and other characteristics with quantum accuracy and computational efficiency, enabling researchers to work in previously inaccessible problem spaces.
Learn more about the Data Science Institute at data-science.llnl.gov
💻 LLNL News: llnl.gov/news
📲 Instagram: instagram.com/livermore_lab
🤳 Facebook: facebook.com/livermore.lab
🐤 Twitter: twitter.com/Livermore_Lab
🔔 Subscribe: youtube.com/c/LivermoreLab
About LLNL: Lawrence Livermore National Laboratory has a mission of strengthening the United States’ security through development and application of world-class science and technology to: 1) enhance the nation’s defense, 2) reduce the global threat from terrorism and weapons of mass destruction, and 3) respond with vision, quality, integrity and technical excellence to scientific issues of national importance. Learn more about LLNL: llnl.gov/.
LLNL-VIDEO-829655
#DataScience #LLNL #MaterialsBehavior
LLNL’s Data Science Institute (DSI) was established in 2018 to enable excellence in data science research and applications across the Lab’s core missions. Computational chemist Rebecca Lindsey, PhD, explains how machine learning and data science techniques are used to develop diagnostic tools for stockpile stewardship, such as models that predict detonator performance. Lindsey also describes how atomistic simulations improve researchers’ understanding of the microscopic phenomena that govern the chemistry in materials under extreme conditions. For example, machine learning interatomic models have recovered structure, dynamics, and other characteristics with quantum accuracy and computational efficiency, enabling researchers to work in previously inaccessible problem spaces.
Learn more about the Data Science Institute at data-science.llnl.gov
💻 LLNL News: llnl.gov/news
📲 Instagram: instagram.com/livermore_lab
🤳 Facebook: facebook.com/livermore.lab
🐤 Twitter: twitter.com/Livermore_Lab
🔔 Subscribe: youtube.com/c/LivermoreLab
About LLNL: Lawrence Livermore National Laboratory has a mission of strengthening the United States’ security through development and application of world-class science and technology to: 1) enhance the nation’s defense, 2) reduce the global threat from terrorism and weapons of mass destruction, and 3) respond with vision, quality, integrity and technical excellence to scientific issues of national importance. Learn more about LLNL: llnl.gov/.
LLNL-VIDEO-829655
#DataScience #LLNL #MaterialsBehavior
