Global climate change is often at the forefront of national and international discussions and controversies, yet many details of the specific contributing factors are poorly understood.
Through her role in the Department of Energy’s Advanced Scientific Computing Research-supported ExaLearn project, Jenna Pope is developing deep learning approaches for finding optimal water cluster structures for a variety of applications.
PNNL scientists Richard (Dick) Smith and Ljiljana (Lili) Paša-Tolić are recognized by The Analytical Scientist in its 2019 Power List as two of 2019’s top 100 minds in analytical science.
In the third year of the DISCOVR Consortium project, the consortium team has identified an algal strain that progressed successfully through multiple evaluation phases.
Two forms of magnesium material were processed into tubing using PNNL’s Shear Assisted Processing and Extrusion™ technology. Both materials were found to have quite similar and improved properties—even though they began vastly different.
Quin Miller is a geochemistry postdoctoral research associate who was recently recognized for “exceptional contributions” to PNNL. The nomination criteria included productivity, innovation, dedication, hard work, and strong sponsor impact.
Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.
B3? E4? Remember the board game Battleship? One player suggests a set of coordinates to another, hoping to find the elusive location of an unseen vessel.That is a good place to start in assessing the search for dark matter.
