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Materials that conduct protons could potentially lead to the development of novel eco-friendly energy solutions.

Artificial Intelligence, DMSE, Energy, Machine learning, Materials science and engineering, Research, School of Engineering, Sustainability, UncategorizedJuly 24, 202438Views0Likes0Comments
MIT engineers have identified new materials that could be more efficient conductors of protons – the nucleus of a hydrogen atom – which could pave the way for a number of climate-protecting technologies. Today's proton-conducting materials require very high temperatures, but lower-temperature alternatives could boost new technologies such as fuel cells that produce clean electricity…

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Machine learning divulges the mysteries of high-tech alloys.

Artificial Intelligence, Computer modeling, DMSE, Electrical Engineering & Computer Science (eecs), Machine learning, Materials science and engineering, Metals, Research, School of Engineering, UncategorizedJuly 19, 202433Views0Likes0Comments
Researchers from the Massachusetts Institute of Technology (MIT) are using machine learning to explore the concept of short-range order (SRO) in metallic alloys at atomic levels. The team believes that understanding SRO is key to creating high-performance alloys with unique properties but this has been a challenging area to explore. High-entropy alloys are of particular…

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Machine learning reveals the mysteries behind sophisticated alloys.

Artificial Intelligence, Computer modeling, DMSE, Electrical Engineering & Computer Science (eecs), Machine learning, Materials science and engineering, Metals, Research, School of Engineering, UncategorizedJuly 19, 202445Views0Likes0Comments
The Short-Range Order (SRO), the arrangement of atoms over small distances, plays a crucial role in materials’ properties, yet it has been understudied in metallic alloys. However, recent attention has been drawn to this concept as it is a contributing step towards developing high-performing alloys known as high-entropy alloys. Understanding how atoms self-arrange can pose…

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The Engineering Department extends a warm welcome to its latest professors.

Aeronautical and astronautical engineering, Artificial Intelligence, Biological engineering, Broad Institute, Chemical engineering, Civil and environmental engineering, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Cryptography, Data, DMSE, Economics, Electrical Engineering & Computer Science (eecs), Electronics, Environment, Faculty, Human-computer interaction, human-robot interaction, IDSS, Immunology, Laboratory for Information and Decision Systems (LIDS), Machine learning, Media Lab, Medicine, MIT Schwarzman College of Computing, Music, Music and theater arts, Research Laboratory of Electronics, Robotics, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, UncategorizedMay 24, 202443Views0Likes0Comments

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Obtaining hydrogen from stones.

Alternative energy, Artificial Intelligence, Climate change, Department of Energy (DoE), DMSE, Energy, Faculty, Funding, Geology, Grants, Mechanical engineering, Renewable energy, Robotics, School of Engineering, Sustainability, UncategorizedApril 9, 202440Views0Likes0Comments
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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Engineers at MIT have devised a method to ascertain the behaviour of material surfaces.

Artificial Intelligence, Chemistry, Department of Defense (DoD), DMSE, Machine learning, Materials science and engineering, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 27, 202435Views0Likes0Comments
A group of MIT researchers has developed a machine learning (ML) approach that could revolutionize the way we design catalysts for chemical reactions. The method simplifies the intricate process of designing new compounds or alloys, traditionally dependent on the intuition of experienced chemists, by using ML to provide more detailed information than conventional techniques can. The…

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Engineers at MIT have devised a method to ascertain the behavior of material surfaces.

Artificial Intelligence, Chemistry, Department of Defense (DoD), DMSE, Machine learning, Materials science and engineering, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 26, 202435Views0Likes0Comments
Researchers from MIT have developed a machine learning approach that could replace the intuition-based methods typically used in the creation of catalysts. The team, led by graduate student Xiaochen Du, devised a system that offers more detailed insights than conventional techniques, identifying previously undiscovered atomic configurations in a material that had been researched for three…

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Engineers from MIT have devised a method to decipher the behavior of material surfaces.

Artificial Intelligence, Chemistry, Department of Defense (DoD), DMSE, Machine learning, Materials science and engineering, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 7, 202439Views0Likes0Comments
MIT researchers have developed a machine learning-based method for designing new compounds or alloys for use as catalysts in chemical reactions. Traditional methods of designing such materials rely on static observations of a single configuration, out of millions of possibilities, and the intuition of experienced chemists. However, the new method employs machine learning algorithms to…

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MIT’s Generative AI Week promotes conversation among different fields.

academics, Algorithms, Architecture, Artificial Intelligence, Biology, Civil and environmental engineering, Comparative Media Studies/Writing, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, DMSE, EAPS, Education, Electrical Engineering & Computer Science (eecs), Ethics, Faculty, Health, Laboratory for Information and Decision Systems (LIDS), Machine learning, Media Lab, MIT Morningside Academy for Design, MIT Schwarzman College of Computing, MIT Sloan School of Management, Robotics, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Special events and guest speakers, Staff, Students, teaching, Technology and society, UncategorizedMarch 7, 202441Views0Likes0Comments
In late November, Massachusetts Institute of Technology (MIT) held a Generative AI Week involving faculty, staff, and students from the institution. The event served as a platform to discuss the opportunities and important applications of generative artificial intelligence technologies across varied disciplines. The week's agenda included a main symposium and four subject-specific symposia. MIT President…

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