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School of Engineering

Bridging the gap between designing and manufacturing in the field of optical devices.

Photolithography, a process used to create computer chips and optical devices, can often have tiny deviations during production, causing the final product to fall short of the initial design. To address this, researchers from MIT and the Chinese University of Hong Kong have used machine learning to develop a digital simulator that more accurately models…

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The computational model successfully encapsulates the hard-to-capture transitional stages of chemical reactions.

In a breakthrough study at MIT, researchers have used machine learning (ML) to calculate the ephemeral transition state in chemical reactions, representing a significant step forward for computational chemistry. The transition state occurs when molecules in a reaction gain energy to the point where the reaction becomes irreversible. Researchers have struggled to observe this pivotal…

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A computer science expert explores new limits of geometry.

More than 2,000 years after Greek mathematician Euclid laid the groundwork for geometry, Justin Solomon, an associate professor at the MIT Department of Electrical Engineering and Computer Science, is leveraging modern geometric techniques to solve complex problems that seemingly have no connection to shapes. Solomon's work involves using geometrical structures in comparing datasets to predict…

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Bridging the gap between design and production for optical instruments.

Researchers from MIT and the Chinese University of Hong Kong have developed a machine learning technique to bridge the gap between the design and manufacturing processes in photolithography. Photolithography, a technique commonly used in fabricating computer chips and optical devices like lenses, often falls short of the designers' expectations due to minute deviations during manufacturing.…

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The computational model accurately encapsulates the hard-to-detect transitional phases of chemical reactions.

Scientists at MIT have devised a machine learning-based method that can rapidly calculate the transitional states of molecules during a chemical reaction. The transient nature of these states has made observation particularly challenging. Understanding these states is key to developing catalysts or deciphering how natural systems induce specific changes. The MIT team constructed their computational approach…

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A computer engineer is expanding the limits of geometric theory.

Justin Solomon, an associate professor at the Massachusetts Institute of Technology (MIT), is applying modern geometric techniques to solve complex problems in data science, computer graphics, and artificial intelligence. He draws upon the principles of geometry— the study of shapes—pioneered over 2,000 years ago by Greek mathematician Euclid. The relevance of geometric principles extends beyond…

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Narrowing the gap between design and production in the field of optical devices.

Researchers from MIT and the Chinese University of Hong Kong have developed a machine-learning based digital simulator that can more precisely model specific photolithography manufacturing processes used in creating computer chips and optical devices like lenses. The simulator is designed to help close the gap between design and manufacturing, as tiny deviations during the manufacturing…

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The computational model successfully captures the hard-to-detect transition states in chemical reactions.

During a chemical reaction, molecules gain energy until they reach a point known as the transition state, a pivotal moment where the reaction must proceed. The structures of these states can be determined using quantum chemistry methods, but these calculations are time-intensive. To tackle this issue, a team of MIT researchers developed a machine learning-based…

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A computer technologist advances the limits of geometry.

Justin Solomon, an Associate Professor in the MIT Department of Electrical Engineering and Computer Science (EECS), is using geometric techniques to solve complex computing problems. Solomon says this method is ideally suited to finding solutions in data science, as it can enable a deeper understanding of the distances, similarities, curvature and shape data. About half…

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Bridging the gap between designing and manufacturing for optical equipment.

Researchers from the Massachusetts Institute of Technology (MIT) and the Chinese University of Hong Kong have developed a digital simulator using machine learning to optimize the manufacturing process used in fabricating devices like computer chips and lenses. This technology, known as photolithography, manipulates light to precisely etch features onto a surface, but minute deviations can…

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The computational model successfully documents the hard-to-detect transition phases of chemical reactions.

During a chemical reaction, molecules gain energy until they reach a position termed the transition state. Existing at a level of energy where the reaction has no choice but to proceed, the transition state's transient nature makes it extremely difficult to observe experimentally. Its structures can be calculated using quantum chemistry-based techniques, but these are…

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A computer scientist is advancing the limits of geometry.

Justin Solomon, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), is using advanced geometric techniques to deal with complex issues that don't seemingly have any connection with geometry. Solomon explains that geometric terms like distance, similarity, and…

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