Now, anyone can easily explore and access data from a nationwide map of data centers, the infrastructure that powers them, and projections of future data center locations.

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

The Genesis Mission will mobilize the Department of Energy’s 17 National Laboratories, industry, and academia to build an integrated discovery platform.

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

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

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

Researchers have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

PNNL STEM Ambassadors engage students about salmon migration, hydropower, cybersecurity, water quality, and more at the annual Salmon Summit.

A new study led by PNNL researcher TC Chakraborty provides some answers about how irrigated agricultural land near cities affects urban heat stress.

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

A new generation of microelectronics research begins at PNNL.

New datasets delineating global urban land support scientific research, application, and policy, but they can produce different results when applied to the same problem making it difficult for researchers to decide which to use.

Knowing future snow levels is key for managing the recovery of endangered bighorn sheep. PNNL scientists help to forecast how the sheep could fare.

A new study reveals just how costly Earth's tipping points can be.

The demand for energy is growing—and so is the technology supporting it. However, future development of power generation technologies could be affected by a key factor: material supply.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

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

Mengqi Zhao and Chris Vernon were selected to serve in editorial roles at JOSS for Earth science and data science, respectively.

Researchers discussed this topic at the 2024 Analog Computing for Science Workshop co-led by Antonino Tumeo.

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.