Researchers designed a new, highly efficient, stable redox-active material from neutral red dye that can efficiently capture CO2 from air.

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.

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

Biochemical preservation and mineral association retain carbon in grassland soils, resulting in consistent molecular composition across ecosystems.

Across the United States, water moving between the river and riverbed sediments does not overcome localized processes that govern organic matter chemistry.

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

A novel combination of temperature and four-dimensional geophysical sensors revealed otherwise unseeable hydrologic dynamics below riverbed sediments.

The size of the alkali metal within the material influences the crystallization pathway.

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.

New data analysis approach gives researchers deeper understanding of microbial ecology and evolution.

Surface characterization allows researchers to explore the compatibility between different solvent-membrane combinations.

Improving predictability of water quality and nutrient cycling in large river systems.

Developing conceptual models for microbial-environmental–ecosystem interactions is key to enhancing the ability of models to predict future ecosystem function.

Research from the PNNL-led WHONDRS consortium reveals chemistry and spatial gradients of metabolomes from river water and sediments around the globe.

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

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

Researchers used deep learning methods to estimate the subsurface permeability of a watershed from stream discharge measurements.

A code comparison study demonstrates a leap in the accuracy and reliability of modeling gas hydrate for the discovery and production of natural gas.

Controlled synthesis and processing allow researchers to test how ions move through energy-relevant materials.

Geophysical modeling and inversion software meets DOE and nuclear industry standards for use in decision-making for radiologically contaminated sites.