Using artificial intelligence to engineer materials' properties

MIT News

Applying just a bit of strain to a piece of semiconductor or other crystalline material can deform the orderly arrangement of atoms in its structure enough to cause dramatic changes in its properties, such as the way it conducts electricity, transmits light, or conducts heat. Now, a team of researchers at MIT and in Russia and Singapore have found ways to use artificial intelligence to help predict and control these changes, potentially opening up new avenues of research on advanced materials for future high-tech devices. The findings appear this week in the Proceedings of the National Academy of Sciences, in a paper authored by MIT professor of nuclear science and engineering and of materials science and engineering Ju Li, MIT Principal Research Scientist Ming Dao, and MIT graduate student Zhe Shi, with Evgeni Tsymbalov and Alexander Shapeev at the Skolkovo Institute of Science and Technology in Russia, and Subra Suresh, the Vannevar Bush Professor Emeritus and former dean of engineering at MIT and current president of Nanyang Technological University in Singapore. Already, based on earlier work at MIT, some degree of elastic strain has been incorporated in some silicon processor chips. Even a 1 percent change in the structure can in some cases improve the speed of the device by 50 percent, by allowing electrons to move through the material faster.


Design on a Diamond: AI's Potential in Advanced Materials Research

#artificialintelligence

Applying just a bit of strain to a piece of semiconductor or other crystalline material can deform the orderly arrangement of atoms in its structure enough to cause dramatic changes in its properties, such as the way it conducts electricity, transmits light, or conducts heat. Now, a team of researchers at MIT and in Russia and Singapore have found ways to use artificial intelligence to help predict and control these changes, potentially opening up new avenues of research on advanced materials for future high-tech devices. The findings appeared in early February in the Proceedings of the National Academy of Sciences, in a paper authored by MIT professor of nuclear science and engineering and of materials science and engineering Ju Li, MIT Principal Research Scientist Ming Dao, and MIT graduate student Zhe Shi, with Evgenii Tsymbalov and Alexander Shapeev at the Skolkovo Institute of Science and Technology in Russia, and Subra Suresh, the Vannevar Bush Professor Emeritus and former dean of engineering at MIT and current president of Nanyang Technological University in Singapore. Already, based on earlier work at MIT, some degree of elastic strain has been incorporated in some silicon processor chips. Even a 1% change in the structure can in some cases improve the speed of the device by 50 percent, by allowing electrons to move through the material faster.


How to bend and stretch a diamond

MIT News

Diamond is well-known as the strongest of all natural materials, and with that strength comes another tightly linked property: brittleness. But now, an international team of researchers from MIT, Hong Kong, Singapore, and Korea has found that when grown in extremely tiny, needle-like shapes, diamond can bend and stretch, much like rubber, and snap back to its original shape. The surprising finding is being reported this week in the journal Science, in a paper by senior author Ming Dao, a principal research scientist in MIT's Department of Materials Science and Engineering; MIT postdoc Daniel Bernoulli; senior author Subra Suresh, former MIT dean of engineering and now president of Singapore's Nanyang Technological University; graduate students Amit Banerjee and Hongti Zhang at City University of Hong Kong; and seven others from CUHK and institutions in Ulsan, South Korea. Experiment (left) and simulation (right) of a diamond nanoneedle being bent by the side surface of a diamond tip, showing ultralarge and reversible elastic deformation. The results, the researchers say, could open the door to a variety of diamond-based devices for applications such as sensing, data storage, actuation, biocompatible in vivo imaging, optoelectronics, and drug delivery.


AI-guided material changes could lead to diamond CPUs

Engadget

Scientists know that you can dramatically alter a crystalline material's properties by applying a bit of strain to it, but finding the right strain is another matter when there are virtually limitless possibilities. There may a straightforward solution, though: let AI do the heavy lifting. An international team of researchers has devised a way for machine learning to find strains that will achieve the best results. Their neural network algorithm predicts how the direction and degree of strain will affect a key property governing the efficiency of semiconductors, making them far more efficient without requiring educated guesses from humans. The technology could lead to semiconductor-based inventions that are far more powerful than usual with only minor changes.


Interdisciplinary materials science a key to progress

MIT News

In his introductory remarks, MRL Director Carl V. Thompson noted the appointment of Geoffrey S.D. Beach, an associate professor of materials science and engineering as co-director of the MRL and principal investigator for the National Science Foundation Materials Research Science and Engineering Center. Future gains will come from the ability to synthesize and control increasingly complex materials, Phillips said, noting progress in areas such as high-temperature superconductors, porous solids like metal organic frameworks, and metamaterials that generate new properties from combining biological materials, organics, ceramic, and metals at near molecular scale precision in ways not found in nature. "Somewhere in the fuzzy space between molecules and materials," these newer materials have very interesting properties that are still in the process of being fully explored, and they will be exploited in the years to come, Phillips noted. "It's very clear to many people that these also will be transformational as we move forward." The materials research approach, which brings together researchers from across different science and engineering fields to solve complex problems, provides a model for solving 21st century challenges in energy, environment and sustainability; health care and medicine; vulnerability to human and natural threats; and expanding and enhancing human capability and joy.