A review article examines a decade of work on the atom-scale process of turning carbon dioxide into stable minerals.

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.

A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management.

SEA-CROGS is one of four Mathematical Multifaceted Integrated Capability Centers selected for support by the Department of Energy.

New research makes molecular-level calculations of water faster and easier.

Updated flexible software generates and optimizes monitoring programs for detecting potential leaks from geological carbon storage with an enhanced user experience.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

A new perspective article discusses how integrating carbon dioxide capture and conversion in solvents can lead to cheaper and more efficient carbon management systems.

Providing a perspective on the importance of integrating experimental work with theory and simulations when designing new carbon capture solvents.

Researchers use machine learning to speed up the analysis of aerosol datasets from mass spectrometry.

PNNL scientists have developed a new mass spectrometry method for in-depth analysis of proteins in individual cells.

Data from increasingly complex mass spectrometry instruments met with adaptable data analysis solution.

Proteomics revealed molecular mechanisms by which the drug Verapamil could prolong beta cell function in early-onset type 1 diabetes patients.

Study highlights microbiome’s role in regulating xenobiotic metabolism.

Development of a one-meter path length miniature ion mobility spectrometer based on multilevel structures for lossless ion manipulations.

Researchers characterize protein signatures that indicate Acute Kidney Injury in COVID-19 patients.

Soil moisture influences both the activity of soil DNA viruses, as well as the composition and abundance of RNA viruses.

Knowing which bacteria in a community are involved with carbon cycling could help scientists predict how microbial carbon storage and release could influence future climate dynamics.

Hypergraphs can more faithfully identify important genes in complex immune responses.

New quantum chemistry pipeline can help predict the effects of bioengineering.