Global exercise advances nuclear forensic science and investigative capabilities.

Using multiple specialized techniques, IDREAM researchers gained a better understanding of how trace impurities within gibbsite affect the hydrogen yield.

Five PNNL innovations earned 2026 R&D 100 Awards for advances in biotechnology, manufacturing, critical minerals, and nuclear security.

A new report highlights a public workshop hosted by the National Academies Forum on Microbial Threats and features PNNL's Lauren Charles and the AI-Driven One Health Security program.

A research team from Pacific Northwest National Laboratory used machine reasoning to schedule scientific workflows while guaranteeing quality of service (QoS).

Integrating new functions into a genome-scale model enabled researchers to simulate and experimentally validate viral hijacking pathways.

Nanosize platelets of an aluminum material slide and join in a staggered orientation to form larger crystals.

The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.

IDREAM researchers uncovered how dimeric complexes control how aluminum hydroxide minerals dissolve.

A study by researchers at PNNL assessed the feasibility of using strontium isotope ratios and an existing machine learning–based model to predict and verify a product’s source—in this case, honey.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

Trace amounts of iron and chromium can incorporate into gibbsite, affecting how the mineral dissolves.

Increasing concentrations of ions slows the rate of particle aggregation in boehmite suspensions.

New IDREAM research explores the effects of electrolyte species on boehmite nanoparticle aggregation in legacy wastes.

Hydrogen atoms released and trapped in irradiated gibbsite are destabilized by synthetic-precursor residuals.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

In the latest issue of the Domestic Preparedness Journal, Ashley Bradley and Kristin Omberg share how new research is shedding light on the scientific and technological challenges with detecting fentanyl.

When exposed to a sufficiently high dose of ionizing radiation, gibbsite and boehmite are less susceptible to dehydration-induced breakdown.

A new approach validates quantum algorithms for low-energy nuclear physics applications

PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence