EZBattery Model allows energy storage researchers to more quickly and easily identify the best performing battery designs without the need for extensive physical prototyping or computationally expensive simulations.

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

Across the United States, organic carbon concentration imposes a primary control on river sediment respiration, with additional influences from organic matter chemistry.

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

A new perspective article discusses how integrating carbon dioxide capture and conversion in solvents can lead to cheaper and more efficient carbon management systems.