PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

Researchers at PNNL studied the effects of high temperatures and ionizing radiation on tungsten heavy alloys.

Researchers can now quantify uncertainty in trained AI models aimed at solving difficult chemistry, biology and materials science problems.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Scientists are exploring how web search engine technology might also keep the lights on, the water running and the trains moving.

PNNL researchers co-organized a workshop on fusion commercialization with partners from industry and academia

A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.

PNNL researchers will pursue both fundamental and applied projects with this support from the Department of Energy

Combining cold spray deposition and friction stir processing for a more efficient route to oxide dispersion strengthened steel.

PNNL researchers studied the microstructure of lithium silicates under emulated fusion conditions.

The Department of Energy’s Vehicle Technologies Office recognized Livewire’s outstanding teamwork and technical expertise.

Researchers studied the boundary precipitation of tungsten heavy alloys in an extended high temperature irradiation environment

The Department of Energy Office of Nuclear Energy acting assistant secretary makes his first visit to a national laboratory in his new role, touring PNNL's Radiochemical Processing Laboratory.

PNNL research exploring tungsten heavy alloys for use in advanced nuclear fusion reactors makes Scientific Reports Top 100 Collection.

Visual Sample Plan, a free software tool developed at PNNL that boosts statistics-based planning, has been recognized with a 2024 Federal Laboratory Consortium Award.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

Tumeo will lead the ChemComp project, which was awarded for Exploratory Research in Extreme Scale Science

PNNL’s software tool brings together artificial intelligence and satellite imagery to help responders assess damage and take action.

Stinis will serve as a principal investigator on two of the four projects selected for funding by the Advanced Scientific Computing Research program.