This PNNL-developed separation system quickly and successfully separates larger particles from smaller ones at various scales, in different solid-liquid mixtures and at different flow rates.
Lighting control data are critical for optimizing the design and operation of future lighting systems for the benefit of occupants and energy efficiency.
A research project that brings together mathematicians and atmospheric scientists has developed into a deep collaboration for improving atmospheric models.
With quantum chemistry, researchers led by PNNL computational scientist Simone Raugei are discovering how enzymes such as nitrogenase serve as natural catalysts that efficiently break apart molecular bonds to control energy and matter.
PNNL highlights four researchers whose joint appointments are creating new and diverse opportunities for expanding knowledge and scientific impact across institutions.
On the looming 10th anniversary of the Fukushima disaster at the Daiichi Power Station in Japan, PNNL looks back at the science and solidarity it has shared with Fukushima and its nuclear cleanup effort.
As COVID-19 was limiting in-person contact, halting travel, and creating additional barriers, researchers at PNNL were working to find solutions on how they could still get work done while establishing new safety protocols.
PNNL researchers have shown an improved binarized neural network can deliver a low-cost and low-energy computation to help the performance of smart devices and the power grid.
