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.

The diversity and function of organic matter in rivers at a large scale are influenced by factors, such as the types of vegetation covering the land, the energy characteristics, and the breakdown potential of the molecules.

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

Recovery Simulator and Analysis tool further strengthens PNNL’s short-term resilience planning efforts for Puerto Rico.

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.

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.

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.

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

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 new microbial community model reveals previous exposure to hydrologic variation influences a species’ specialized biogeochemical functions.

Detailed characterization of molecules in, under, and along the Columbia River reveal potential mechanisms for biogeochemical cycling.

Integrating hydrogeology and biogeochemistry are required to model the dynamics of geochemical processes occurring in river corridor zones where groundwater and surface water mix.

Theoretical analysis reveals flow variations that happen over longer time periods affect a plume’s spread and center of mass.

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

Principles derived from coastal wetlands to describe wetland channel cross-sections were applicable to the Columbia River estuary, but not the tidal river.