Jingshan Du, a postdoctoral scientist at PNNL whose research focuses on crystallization pathways of water and other materials, was named a 2025 CAS Future Leader.
Machine learning and autonomous experimentation are poised to revolutionize how scientists grow very thin films on surfaces, important for technologies like microelectronics and quantum computing.
Researchers developed a robust, cost-effective, and easy-to-use cap-based technique for spatial proteome mapping, addressing the lack of accessible proteomics technologies for studying tissue heterogeneity and microenvironments.
A new analysis shows how renewable energy sources like solar, wind and hydropower respond to climate patterns, and how utilities can use this data to save money and invest in energy storage.
Alicia Amerson's passion for science communication, expertise in marine mammal research, and experience in wildlife photography provide a robust foundation for her new role with the Clallam County Marine Resources Committee.
A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.
Controlling the nanostructure of silk fibroin—a protein found in silk—is a key step toward designing and fabricating electronics that leverage the material’s promising mechanical, optical and biocompatible properties.
Sergei Kalinin honored with the David Adler Lectureship Award for contributions to materials physics through automated experimentation and ferroelectric materials work.
Ultra-thin layers of silk deposited on graphene in perfect alignment represent a key advance for the control needed in microelectronics and advanced neural network development.
Although climate change may bring increased precipitation to many parts of the United States, some areas may face drier conditions and lower streamflow, resulting in decreased hydropower generation.
