PNNL’s Climate Network with MSIs and HBCUs aims to bring opportunities to diverse populations.

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

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

This study demonstrated that a large-scale flooding experiment in coastal Maryland, USA, aiming to understand how freshwater and saltwater floods may alter soil biogeochemical cycles and vegetation in a deciduous coastal forest.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches.

Microbes that were previously frozen in soils are becoming more active. This study demonstrates the diverse RNA viral communities found in thawed permafrost.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

Organismal contribution and community interaction drive soil organic matter breakdown by microbes.

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.

Proteins from “auxiliary” genes in soil viruses play a role in the carbon cycle and climate, scientists have found.

A new study shows how organic molecules respond to global change varies according to functional traits and ecological processes.

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

Soil transplant experiment gives new insights into coastal forest resilience, rising seas, and increasing storms.

ICON science is a Department of Energy-developed framework to enhance scientific outcomes via more intentional design of research efforts across all domains of science.

A novel ecological measurement uncovered interactions between river corridor organic matter assemblages and microbial communities, highlighting potentially important microbial taxa and molecular formula types.