Highly precise and controllable single-atom catalysts are affected by reaction conditions, which can alter the bonding around the atoms and the activity.
A PNNL team’s analysis of new-housing data concludes that single-family homes in lower-income counties are less energy-code-compliant than in higher-income counties, a finding that could shape strategies for enhanced code adoption.
PNNL and University of Texas at El Paso leverage partnership and joint appointment program for a laboratory directed research and development project.
PNNL’s extensive portfolio of buildings-grid research included three projects that helped answer some of the technical questions related to leveraging energy consumption in buildings to enhance grid operations.
PNNL’s ARENA test bed analyzes how electrical cables degrade in extreme environments and how nondestructive examination inspection technologies can detect and locate damage.
The ChemSpace Tool, when fully developed, is intended to divide chemical space into three subsets: the detectable space, the identifiable space, and the region that includes compounds that are not detectable or identifiable.
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.
The Northwest Connected Communities Summit brought together representatives of five Department of Energy-funded Connected Communities Projects to share ideas and discuss potential collaboration opportunities.
PNNL welcomes new joint appointments to expand the research productivity and scientific impact of both PNNL and the university partners, broadening the base of expertise at each institution and helping to build interdisciplinary teams.
A PNNL-developed computational framework accurately predicts the thermomechanical history and microstructure evolution of materials designed using solid phase processing, allowing scientists to custom design metals with desired properties.
Cesar Moriel from University of Texas at El Paso will be interning at the PNNL over the summer as part of the Energy Environment Diversity Internship Program.
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.