首页|Researchers from University of Florida Report on Findings in Machine Learning (V alidation Workflow for Machine Learning Interatomic Potentials for Complex Ceram ics)
Researchers from University of Florida Report on Findings in Machine Learning (V alidation Workflow for Machine Learning Interatomic Potentials for Complex Ceram ics)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating in Gainesville, F lorida, by NewsRx journalists, research stated, “The number of published Machine Learning Interatomic Potentials (MLIPs) has increased significantly in recent y ears. These new data-driven potential energy approximations often lack the physi cs-based foundations that inform many traditionally-developed interatomic potent ials and hence require robust validation methods for their accuracy, computation al efficiency, and applicability to the intended applications.” The news reporters obtained a quote from the research from the University of Flo rida, “This work presents a sequential, three-stage workflow for MLIP validation : (i) preliminary validation, (ii) static property prediction, and (iii) dynamic property prediction. This material-agnostic procedure is demonstrated in a tuto rial approach for the development of a robust MLIP for boron carbide (B4C), a wi dely employed, structurally complex ceramic that undergoes a deleterious deforma tion mechanism called ‘amorphization’ under high-pressure loading.”
GainesvilleFloridaUnited StatesNor th and Central AmericaCyborgsEmerging TechnologiesMachine LearningUniver sity of Florida
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