PNNL-developed catalytic process and catalyst to upgrade ethanol to sustainable aviation fuel wins American Chemical Society award.

Newly developed models can help rapidly optimize systems to meet the need for rapidly deployable commercial carbon capture.

Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.

A new system can convert common plastics into valuable fuel molecules.

A new method to convert waste plastic to fuel and raw materials promises to help close the carbon cycle at mild temperature and with high yield.

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.

Within zeolite pores, rates of alcohol dehydration increase with ionic strength until reaching a maximum and then decreasing.

Wendy Shaw begins an initial two-year term on the Advisory Board of Chemical Society Reviews.

In a water-containing system, the open circuit potential stabilizes positively charged species and lowers the energy barrier of the reaction.

A paper by PNNL researchers has been chosen as one of 32 NIEHS Papers of the Year—a top 1% honor in the research field.

Radha Kishan Motkuri lends skill and knowledge to co-lead special edition journal.

Johannes Lercher receives award from the North American Catalysis Society and the European Federation of Catalysis Societies.

PNNL scientists carve a path to profit from carbon capture by creating a system that efficiently captures CO2 and converts it into one of the world’s most widely used chemicals: methanol.

Findings show method to better prepare human lung tissue for study; it represents the latest mass spectrometry-based omics advances.

PNNL’s contributions over the last year span scientific discovery, sustainable energy and national security.

New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.

Silicone wristbands could be more convenient option for collecting exposure data.

A new deep learning approach allows researchers to rapidly analyze three-dimensional representations of multi-component catalysts.

Where molybdenum dopants sit within catalytic material affects catalysis at a mechanistic level.

Using electrocatalysis offers a different path for reactions involving polar groups.