A decade after working as a post-bachelor’s researcher at PNNL, chemist Quin Miller is helping develop the workforce for the critical minerals-focused mines of the future.
Predicting how organisms’ characteristics respond to not only their genes, but also their environments (a nascent field called predictive phenomics), is extraordinarily challenging. Researchers at PNNL are using AI to tackle that challenge.
A breakthrough at PNNL could free friction stir from current constraints—and open the door for increased use of the advanced manufacturing technique on commercial assembly lines.
PNNL researchers have found yet another way to turn trash into treasure: using algal biochar, a waste production from hydrothermal liquefaction, as a supplementary material for cement.
The first direct molecular-scale evidence of the temperature-driven transformation of the coordination environment of ytterbium at geologically relevant conditions.
PNNL researchers continue to deliver high-quality, high-impact research on radioactive waste and nuclear materials management, earning “Papers of Note” and “Superior Paper” awards.
By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.
Led by interns from multiple DOE programs, a newly expanded dataset allows researchers to use easy-to-obtain measurements to determine the elemental composition of a promising carbon storage mineral.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
