PNNL researchers have published their paper “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data” in the Journal of Proteome Research.

Under an optical field, nanoparticle attachment in a model system heavily depends on surface roughness.

Directionally biased electrostatic interactions are the key to significantly tuning the reduction potential of iron/sulfur clusters.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

Jingshan Du, a postdoctoral scientist at PNNL whose research focuses on crystallization pathways of water and other materials, was named a 2025 CAS Future Leader.

Formal mathematics both reveals what’s inside the black box of AI algorithms and pushes the boundary of what’s possible within math as a discipline.

Machine learning and autonomous experimentation are poised to revolutionize how scientists grow very thin films on surfaces, important for technologies like microelectronics and quantum computing.

Chromium cations better adapt to changes in oxygen stoichiometry than iron cations.

A new generation of microelectronics research begins at PNNL.

Using interfacial charge transfer to control cation charges in oxide superlattices offers insights for designing functional heterostructures.

Calcium carbonate mineralization occurs through a multi-step process that begins with a dense liquid phase.

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

Postdoctoral scientist Jingshan Du received the Nanoscale Science and Technology Division Early Career Award from AVS.

Graduate student Ying Xia has been selected as a Graduate Student Award Finalist for the 2024 Materials Research Society Fall Meeting.

Controlling the nanostructure of silk fibroin—a protein found in silk—is a key step toward designing and fabricating electronics that leverage the material’s promising mechanical, optical and biocompatible properties.

A newly funded project will develop the fundamental understanding of phenomena that underpin material properties important for quantum applications.

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

A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.

Samrat (Sam) Chatterjee, a PNNL chief data scientist and team leader with the Data Sciences and Machine Intelligence group, was co-author of a CSET workshop report on agentic artificial intellilligence

PNNL computational and data scientist Mark Maupin was the team lead for a paper published in the journal Molecules.