首页|Reports from Imperial College London Highlight Recent Research in Machine Learni ng (Machine-learning structural reconstructions for accelerated point defect cal culations)
Reports from Imperial College London Highlight Recent Research in Machine Learni ng (Machine-learning structural reconstructions for accelerated point defect cal culations)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in artificial intelligence. According to news originating from Imperial College Lon don by NewsRx correspondents, research stated, "Defects dictate the properties o f many functional materials." Funders for this research include Rcuk | Engineering And Physical Sciences Resea rch Council. Our news correspondents obtained a quote from the research from Imperial College London: "To understand the behaviour of defects and their impact on physical pr operties, it is necessary to identify the most stable defect geometries. However , global structure searching is computationally challenging for high-throughput defect studies or materials with complex defect landscapes, like alloys or disor dered solids. Here, we tackle this limitation by harnessing a machine-learning s urrogate model to qualitatively explore the structural landscape of neutral poin t defects. By learning defect motifs in a family of related metal chalcogenide a nd mixed anion crystals, the model successfully predicts favourable reconstructi ons for unseen defects in unseen compositions for 90% of cases, th ereby reducing the number of first-principles calculations by 73%."
Imperial College LondonCyborgsEmergi ng TechnologiesMachine Learning
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