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Computational model successfully identifies the elusive transitional phases of chemical processes.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 12, 202463Views0Likes0Comments
MIT researchers have developed an approach based on machine learning that can calculate transition states of chemical reactions within seconds. The structures of these transition states, a temporary condition in the middle of a chemical reaction, can typically only be calculated using techniques based on quantum chemistry – a process that can be extremely time-consuming.…

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A computational model successfully depicts the hard-to-capture transitional stages of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 11, 202468Views0Likes0Comments
A group of MIT researchers has developed a new machine learning model which rapidly calculates the structure of transition states during chemical reactions. This fleeting moment is a crucial "point of no return" in reactions. Although this transition state is vital to understanding the pathway of the reaction, it has been notoriously difficult to observe…

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The computational model successfully records the hard-to-capture transition stages of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 11, 202469Views0Likes0Comments
A team of researchers at the Massachusetts Institute of Technology (MIT) has developed a machine learning-based method to swiftly calculate the structures of transition states, crucial moments in chemical reactions. This state, at which molecules attain the necessary energy for a reaction, is important but fleetingly transient and difficult to experimentally observe. Calculating these structures…

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A novel computational method may simplify the process of engineering beneficial proteins.

Artificial Intelligence, Biological engineering, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), DNA, Electrical Engineering & Computer Science (eecs), MIT Schwarzman College of Computing, National Institutes of Health (NIH), National Science Foundation (NSF), Proteins, Research, School of Engineering, School of Science, UncategorizedApril 3, 202466Views0Likes0Comments

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AI hastens the resolution of complex issues or situations.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 27, 202479Views0Likes0Comments
Santa Claus can deliver presents worldwide in one night, but for companies like FedEx, this task isn't so simple - and it is so complex, dedicated software is often used to solve it. Known as a mixed-integer linear programming (MILP) solver, the software breaks down this vast optimization problem into smaller pieces and then employs…

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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, 202468Views0Likes0Comments
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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AI enhances the resolution of issues in intricate situations.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 26, 202472Views0Likes0Comments
Companies like FedEx find the task of efficiently routing holiday packages massively complex, often requiring the use of specialized software to find a solution. This software, called a mixed-integer linear programming (MILP) solver, is used to break down large optimization problems into smaller bits and find the best solution using algorithms. However, this process can…

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AI hastens the resolution of difficult situations through problem-solving.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 26, 202472Views0Likes0Comments
Numerous companies like FedEx grapple with the sophisticated problem of optimising the routing of holiday packages. Specialised software known as a mixed-integer linear programming (MILP) solver is often used to split this massive optimisation issue into smaller pieces, allowing generic algorithms to locate the most suitable solution. This time-consuming process sometimes forces companies to settle…

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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, 202472Views0Likes0Comments
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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AI enhances the resolution of issues in intricate situations.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 25, 202470Views0Likes0Comments
The task of optimizing the delivery of holiday packages is a complex issue for logistics companies like FedEx, which often leverages specialized software known as a mixed-integer linear programming (MILP) solver. This software breaks down complex optimization problems into smaller parts and employs generic algorithms to find the best solutions. However, this process can take…

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AI speeds up solution-finding in intricate situations.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 25, 202463Views0Likes0Comments
Efficiently routing holiday packages is an intricate computational problem for delivery companies such as FedEx. So complex is the problem that companies often implement specialized software, termed a mixed-integer linear programming (MILP) solver. Yet, the solver may take prolonged times to offer a solution, leading companies to conclude midway, settling for suboptimal solutions bounded by…

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