Hydrogen bonding and proton transfer control the identity and reactivity of molecules in highly concentrated and alkaline aluminate solutions.

Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.

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.

A team from the Environmental Molecular Sciences Laboratory published research, demonstrating that the soil microbes were directly involved in the stabilization of soil organic carbon and mineral weathering.

Advanced proteomic analysis tools dig deep into human blood plasma to understand the molecular nature of advanced alcoholic disease.

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.

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

Findings show method to better prepare human lung tissue for study; it represents the latest mass spectrometry-based omics advances.

STEM Education programs at DOE and national labs offer environmental management internships; applications are due soon for summer 2023.

The Joint Appointment program at PNNL is one of the most diverse among other U.S. national laboratories, involving nearly 60 universities and research institutions in the United States and abroad.

Researchers identified a new intermediate phase that forms during the crystallization of hydrated aluminum-containing salts.

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.

Data-driven experiments can help determine best practices for Random Forest machine learning to predict water quality, particularly nitrate levels.

Silicone wristbands could be more convenient option for collecting exposure data.

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

PNNL gathered researchers from eight national laboratories plus the U.S. Department of Energy (DOE) to share ideas and build synergy at the Energy Equity and Environmental Justice Summit.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

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

The amount of radiation in a system influences how fast aggregated boehmite particles dissolve.

PNNL research, featured on the cover of two science journals, describes advancements in using Raman spectrometry for Hanford Site nuclear waste remediation.