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The research team led by Director Dr. Hyuneui Lim of the Korea Institute of Machinery and Materials (KIMM) is planning to commercialize a three-kilogram water harvester, to which its independently developed “portable moisture-harvesting system” has been applied.
A research team has reviewed significant progress in understanding the growth and stress response mechanisms in bermudagrass, a widely distributed and valuable grass species.
Finding the next groundbreaking polymer is always a challenge, but now Georgia Tech researchers are using artificial intelligence (AI) to shape and transform the future of the field. Rampi Ramprasad’s group develops and adapts AI algorithms to accelerate materials discovery.
Researchers are planning for an electric grid that deploys machine learning to think ahead, plan for the worst, anticipate demand, and meet consumer needs safely and securely.
Tufts University researcher Farshid Vahedifard and his team have created physics models to predict cascading hazards such as landslides and debris flows that can follow wildfires.
A multi-institutional team of researchers developed a stand-alone box model to predict aqueous and cloud chemistry of biomass-burning phenols based on laboratory measurements.
Researchers at the University of Illinois Urbana-Champaign have developed a Circularity Index that provides a comprehensive method to quantify circularity in bioeconomic systems. In a new paper, they outline the method and apply it to two case studies – a corn/soybean farming operation and the entire U.S. food and agriculture system.
Air pollution is increasing the severity of summertime thunderstorms, according to a recent study conducted by researchers at James Madison University and published in the journal Atmospheric Research.
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