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36 Current news about the topic machine-learningrss
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Scientists are developing an autonomous artificial intelligence system that can selectively grip and move individual molecules
Molecules are the building blocks of everyday life. Many materials are composed of them, a little like a LEGO model consists of a multitude of different bricks. But while individual LEGO bricks can be simply shifted or removed, this is not so easy in the nanoworld. Atoms and molecules behave in a ...
Machine learning models can rapidly and accurately estimate key chemical parameters related to molecular reactivity
Creating computers that can teach themselves how chemical structure dictates the fundamental properties of molecules and then using that knowledge to predict the properties of novel molecules could help to design cleaner energy and industrial systems. KAUST researchers have developed a machine ...
Artificial intelligence is sometimes met with scepticism but it has earned our trust
A research team at TU Darmstadt headed by Professor Kristian Kersting describes how to achieve this using a clever approach to interactive learning in the magazine “Nature Machine Intelligence”. Imagine the following situation: A company wants to teach an artificial intelligence (AI) to ...
Simulations refute earlier theories on long-range charge transfer between organic and inorganic materials
Oliver Hofmann and his research group at the Institute of Solid State Physics at TU Graz are working on the optimization of modern electronics. A key role in their research is played by interface properties of hybrid materials consisting of organic and inorganic components, which are used, for ...
With this cooperation, chembid and Evonik want to simplify the processes from the production to the sale of coating products for their customers
chembid and the Coating Additives Business Line of Evonik announce their cooperation. The platforms have set themselves the goal of making processes and decisions for chemical companies more efficient and driving forward the digitization in the chemical industry. The basis for this are ...
Chemists look to the future of materials design
Scientists at the University of South Carolina and Columbia University have developed a faster way to design and make gas-filtering membranes that could cut greenhouse gas emissions and reduce pollution. Their new method, published in Science Advances, mixes machine learning with synthetic ...
Artificial intelligence techniques accurately calculate the energy required to make -- or break -- simple molecules
A new machine learning tool can calculate the energy required to make -- or break -- a molecule with higher accuracy than conventional methods. While the tool can currently only handle simple molecules, it paves the way for future insights in quantum chemistry. "Using machine learning to solve ...
High-Tech Gründerfonds and Bayern Kapital invest in IT start-up
High-Tech Gründerfonds (HTGF) together with Bayern Kapital has invested a seven-figure sum in Munich-based IT start-up Erium as part of a seed financing round. SAR Elektronic GmbH is also on board as a co-investor. Erium’s software solution HALerium is used to model and optimise highly complex ...
Lab reactor, liquefied catalyst, and machine learning for more efficient polymerization design
The synthesis of plastic precursors, such as polymers, involves specialized catalysts. However, the traditional batch-based method of finding and screening the right ones for a given result consumes liters of solvent, generates large quantities of chemical waste, and is an expensive, ...
Researchers have designed a machine learning method that can predict battery health with 10x higher accuracy than current industry standard, which could aid in the development of safer and more reliable batteries for electric vehicles and consumer electronics. The researchers, from Cambridge and ...