PermitAI’s newly released dataset, NEPATEC 2.0, captures and curates environmental review data for faster, better federal permitting.

Micron and PNNL co-design the Crete computer system, delivering a new memory architecture for data-intensive scientific computing and AI applications.

Scientists have tapped AI and powerful computing to speed up how quickly officials are able to learn important details about nuclear events.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.

Chemist Wendy Shaw, a nationally recognized scientific leader, has been chosen to serve as the associate laboratory director for PNNL's Physical and Computational Sciences Directorate.

Researchers can now quantify uncertainty in trained AI models aimed at solving difficult chemistry, biology and materials science problems.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Scientists are exploring how web search engine technology might also keep the lights on, the water running and the trains moving.

Mini flow cell battery provides the first step toward an AI-driven, robotic energy storage discovery laboratory.

A new generation of microelectronics research begins at PNNL.

Federal environmental permitting process to be fast-tracked with AI-powered tools and cloud-supported data analysis.

Computing and artificial intelligence aid scientists who seek to understand function-driven design and control of biological systems.

The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.

This work shows that linear pattern scaling is an effective means of obtaining global-to-local relationships for CMIP6 models, as it has been in past model eras.

A cross-institutional team of scientists developed PeakQC, a new software tool for automated quality control of mass spectrometry data.

Cloud and its radiative effect are among the determining processes for the energy balance of the global climate; they are also the most challenging processes for the climate models to simulate.

Three PNNL technologies have been named 2024 R&D 100 Award winners.

Researchers will explore climate, pathogens and energy-efficient microelectronics using 3 million node hours on the nation’s supercomputers.

At a one-day summit on PNNL’s Richland campus, scientists and engineers gather to hear from leaders and learn to lead others.