Seeing the Plasma Edge of Fusion Experiments in New Ways with Artificial Intelligence. MIT researchers are testing a simplified turbulence theory’s ability to model complex plasma phenomena using a novel machine-learning technique. #News #Fusion #Energy #MachineLearning #Plasma
Machine Learning: The Importance of Artificial Intelligence for Additive Manufacturing. For many companies, digitization and automation are the keys to the further development of additive manufacturing. Thus, more and more manufacturers are relying on cloud-based solutions and integrating...
Scientists Could Discover Physical Laws Faster Using New Machine Learning Technique. It can take decades for scientists to identify physical laws, statements that explain anything from how gravity affects objects to why energy can’t be created or destroyed. Purdue University researchers have...
Machine Learning in Catalysis. Molecular research, particularly in catalysis, is predominantly driven by intuition-biased trial-and-error experiments, screening approaches, mechanistic studies, and machine learning methods, such as supervised learning. Although these methods have proven to be...
New Computational Approach Predicts Chemical Reactions at High Temperatures. A Columbia University engineering team have invented a method that combines quantum mechanics with machine learning to accurately predict oxide reactions at high temperatures when no experimental data is available;...
Researchers Develop Artificial Iintelligence to Advance Energy Technologies. Hongliang Xin, an associate professor of chemical engineering in the College of Engineering, Virginia Tech and his collaborators have devised a new artificial intelligence framework that can accelerate discovery of...
Modeling Quantum Spin Liquids Using Machine Learning. The properties of a complex and exotic state of a quantum material can be predicted using a machine learning method created by a RIKEN researcher and a collaborator. This advance could aid the development of future quantum computers. The...
Big Data Privacy for Machine Learning Just got 100 Times Cheaper. Rice University computer scientists have discovered an inexpensive way for tech companies to implement a rigorous form of personal data privacy when using or sharing large databases for machine learning. The paper is available ...
A peptide sensor to detect water-soluble polymers in wastewater, a major contributor to pollution on par with microplastics, has been developed by scientists from Tokyo Institute of Technology. The new technique takes advantage of the bonding that occurs between peptides and different polymers...
Accelerating the Discovery of New Materials for 3D Printing. The growing popularity of 3D printing for manufacturing all sorts of items, from customized medical devices to affordable homes, has created more demand for new 3D printing materials designed for very specific uses. To cut down on...
© 2022 MaterialsMatrix
Invite