PNNL researchers comment on the “Adversarial Machine Learning” white paper from the National Institute of Standards and Technology.

Hi-C metagenomics-informed phage-host infection networks detected in soil pre- and post-drying.

Scientists at PNNL have published a new article that focuses on understanding the composition, dynamics, and deployment of beneficial soil microbiomes to get the most out of soil.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere. Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere.

Researchers from PNNL, CSET, and Google DeepMind delved into the potential risks of artificial intelligence in a roundtable discussion.

Pasco School District teachers join PNNL for an immersive teaching experience.

Scientists can now generate a protein database directly from proteomics data gathered from a specific soil sample using a digital tool and deep learning computer model called Kaiko.

The Human Factors Symposium took place at Discovery Hall at PNNL in May 2023. Fifty-seven attendees participated in the three-day event representing 15 different institutions.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

Computational chemistry libraries from NWChem, NWChemEX, SPEC, and more are now available on Azure Quantum Elements.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

PNNL and The University of Texas at El Paso expand their premier partnership to include the Cyber Halo Innovation Research Program.

The popular approach of organizing soil bacteria into fast- or slow-growing groups is problematic because most bacteria grow at comparable rates in soil.

Metabolomics analysis revealed differences in metabolome profiles for two distinct modes of fungal wood decay.

Under Secretary for Science and Innovation at the Department of Energy Geri Richmond visited PNNL.

Advances in understanding the nature of the chemical bond are featured in this special issue of The Journal of Chemical Physics.

Variations in burn severity are a key control on the chemical constituents of dissolved organic matter delivered to streams within a single burn perimeter.

Deep learning helps make predictions on the effects of the El Niño-Southern Oscillation on river flows more accurate.