New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.

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

PNNL’s Ján Drgoňa and Draguna Vrabie are part of an international team that authored a most-cited paper on Model Predictive Control, an approach for improving operations, energy efficiency, and comfort in buildings.

Research organizations work toward compelling market-ready solutions for building operations.

We are pleased to welcome 20 new joint appointees to PNNL.

Teams at PNNL welcomed their first two interns this summer from the competition-based program.

PNNL’s Reid Hart and Bing Liu have earned individual Champions of Energy Efficiency in Buildings awards from the American Council for an Energy-Efficient Economy.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

Srinivas Katipamula and Ron Underhill were invited to share their expertise in energy efficient building operations.

PNNL scientists have developed a new mass spectrometry method for in-depth analysis of proteins in individual cells.

Data from increasingly complex mass spectrometry instruments met with adaptable data analysis solution.

PNNL lighting research scientist Kate Hickcox will contribute her expertise to help guide industry lighting standards.

Four research staff from PNNL are part of an international team that earned top honors for a journal paper focused on a new algorithm-evaluation approach for buildings.

The scientist behind the online cartoon RedPen/BlackPen explains how humor can build bridges between scientists and the public.

PNNL scientists are protecting first responders and others by expanding what’s known about fentanyl, the driver of the opioid epidemic.

Researchers characterize protein signatures that indicate Acute Kidney Injury in COVID-19 patients.

Simulations reveal advantages of using new model vs. allometric scaling for risk assessment.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Scientists have devised a way to engineer yeast to produce sustainable, eco-friendly commodity chemicals using computing power as a guide.

The nested nanoPOTS chip is the next generation of technology developed at PNNL to prepare single cells for proteomics.