Catalysts that efficiently transfer hydrogen for storage in organic hydrogen carriers are key for more sustainable generation and use of hydrogen. New research identifies activity descriptors that can accelerate novel catalyst development.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

Researchers designed ultra-low radiation cables to reduce background noise for highly sensitive neutrino and dark matter detectors.

1-propanol converts from a monomer into a trimer at aluminum sites within zeolite pores.

Studying single crystal reactions provides molecular-level insight into catalytic processes.

A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.

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

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

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

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

A new approach broadens the reach of quantum computers to previously challenging systems.

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

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

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

Researchers isolated a molecular copper hydride monomer for the first time.

A new simple and scalable synthesis produces nanoparticle assemblies that can perform catalytic hydrogen sensing at room temperature for the first time.

A study that combined experiments and theory showed how model enzymes control challenging reactions involving highly reactive carbocations.

By decreasing the amount of precious metal in a catalyst, the system increased its efficiency and selectivity for breaking apart plastics.

PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.

Combining advanced powder synthesis with solid state processing allows researchers to streamline oxide dispersion-strengthened steel fabrication.