Chemical Engineer Yong Wang explains the influence and opportunity for joint appointments. Wang maintains one of the longest joint appointment tenures at PNNL.

PNNL scientists investigate the promising properties of a common, Earth-abundant salt.

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

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Water affects the intermediates present on the surface of a metal oxide catalyst during ketonization.

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.

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.

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.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

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

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.

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

HiSVSIM enables large-scale quantum simulations through graph partitioning.

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.