Hydrogen bonding and proton transfer control the identity and reactivity of molecules in highly concentrated and alkaline aluminate solutions.

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

Researchers identified a new intermediate phase that forms during the crystallization of hydrated aluminum-containing salts.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

The amount of radiation in a system influences how fast aggregated boehmite particles dissolve.

Simulations show that pH influences boehmite nanoparticle structure and sorption ability.

Developing a new understanding of the structure of natrophosphate, a complex mineral found in radioactive tank waste at the Hanford Site, by integrating experimental techniques.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

The size and concentration of ions influences the aggregation behavior of solutions of boehmite.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

Performing a network analysis of forces between particles reveals new insight into shear induced thinning and thickening in non-Newtonian fluids.

IDREAM researchers show that high concentrations of sodium hydroxide significantly impact the molecular and macroscale properties of sodium nitrite solutions.

Researchers in the IDREAM Energy Frontier Research Center unearth new defects during gibbsite crystallization using a multi-instrument approach.

Newly determined energy transfer mechanisms help identify how water releases from and damages irradiated interfaces.

Developing an understanding of how water breaks apart after radiation exposure.

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

Pacific Northwest National Laboratory researchers developed a patented, nearly non-destructive approach, known as liquid secondary ion mass spectrometry, to analyze nuclear samples.

PNNL paper in Nuclear Technology journal unveils modeling possibilities for TRISO used fuel, implications for reactor planning, and resulting carbon-free nuclear energy.