Tracking down nefarious users is just one example of work at PNNL’s Center for Advanced Technology Evaluation, a computing proving ground supported by DOE’s Advanced Scientific Computing Research program.

Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.

Geophysical modeling and inversion software meets DOE and nuclear industry standards for use in decision-making for radiologically contaminated sites.

PNNL researchers used machine learning to develop a tool for a nonprofit to identify orthopedic implants in X-ray images to improve surgical speed and accuracy.

PNNL recognizes researchers during National Postdoc Appreciation Week.

The PNNL-developed VOLTTRON™ software platform’s advancement has benefited from a community-driven approach. The technology has been used in buildings nationwide, including most recently on a university campus.

PNNL Lab fellow and Earth scientist Nik Qafoku earns highest recognition from the Soil Science Society of America.

PNNL scientists have created a tool called WatchOwl to collect more than 4 million tweets per day related to the COVID-19 pandemic. The tool analyzes tweets related to interventions like social distancing and movement restrictions.

Five papers co-written by 23 PNNL researchers were named Superior Paper Award Winners by the Waste Management Symposia.

Embedding the known physics of the system to be controlled in the AI model of the system is data efficient and provides safety guarantees.

To study the impact of accelerated dryland expansion and degradation on global dryland gross primary production (GPP,) PNNL and Washington State University researchers assessed GPP data from 2000-2014 and the CMIP5 aridity index (AI).

Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.

A 2011 earthquake and tsunami in Japan that knocked out a nuclear power plant helped inspire PNNL computational scientists looking for clues of future nuclear reactor mishaps by tracking radioactive iodine.

Ang Li and Antonino Tumeo will present hardware to balance machine learning workloads at a top computer architecture conference.

Environmental engineer Mike Truex presented an Environmental Protection Agency webinar about how conceptual site models must change as new data is acquired for remedy optimization.

PNNL research scientists Jay Grate and Matthew O'Hara co-authored a chapter in the fourth edition of the Handbook of Radioactivity Analysis. 

PNNL quantum algorithm theorist and developer Nathan Wiebe is applying ideas from data science and gaming hacks to quantum computing

PNNL has patented an instant, accurate and portable way to detect minuscule amounts of troublesome toxic PFAS chemicals in water samples.

At PNNL, subsurface science inhabits two separate but interlocking worlds. One looks at basic science, the other at applied science and engineering. Both are funded by the U.S. Department of Energy (DOE).

Artificial intelligence helps researchers identify metabolites, the small molecules that underlie life.