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Renewable energy

The AI technique dramatically accelerates the prediction of thermal characteristics of materials.

An international team of researchers, including members from MIT (Massachusetts Institute of Technology), has developed a machine learning-based approach to predict the thermal properties of materials. This understanding could help improve energy efficiency in power generation systems and microelectronics. The research focuses on phonons - subatomic particles that carry heat. Properties of these particles affect…

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A novel approach to computer vision accelerates the screening process of electronic components.

Solar cells, transistors, LEDs, and batteries with boosted performance require better electronic materials which are often discovered from novel compositions. Scientists have turned to AI tools to identify potential materials from millions of chemical formulations, with engineers developing machines that can print hundreds of samples at a time, based on compositions identified by AI algorithms.…

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HPI-MIT’s joint design research effort fosters formidable teams.

The recent ransomware attack on ChangeHealthcare underscores the disruptive nature of supply chain attacks. Such attacks are becoming increasingly prominent and often target large corporations through the small and medium-sized vendors in their corporate supply chains. Researchers from Massachusetts Institute of Technology (MIT) and Hasso Plattner Institute (HPI) in Potsdam, Germany, are investigating different organizational…

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Obtaining hydrogen from stones.

Hydrogen, one of the most abundant elements in the Universe, mainly exists alongside other elements. However, the discovery of naturally occurring underground pockets of pure hydrogen is increasingly attracting attention as an unlimited source of carbon-free energy. In fact, the US Department of Energy recently awarded $20 million in research grants to 18 teams to…

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