Machine learning methods and data science can uncover hidden patterns in nanoparticle synthesis conditions and property outcomes.

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

COVID-19 had multiple impacts on the electric sector and the nature of those impacts varied on the scale analyzed.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

PNNL researchers have developed a new class of chemistry focused on carbon capture technology and made incremental strides in driving down costs.

Researchers developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

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.

Pacific Northwest marsh carbon stocks are twice the global average. Long-term sea-level rise impacts will likely decrease ecosystem carbon stocks.