首页|Findings from Forschungszentrum Julich GmbH Provide New Insights into Machine Le arning (Efficient surrogate models for materials science simulations: Machine le arning-based prediction of microstructure properties)
Findings from Forschungszentrum Julich GmbH Provide New Insights into Machine Le arning (Efficient surrogate models for materials science simulations: Machine le arning-based prediction of microstructure properties)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news originating from Julich, Germany, by NewsRx editors, the research stated, “Determining, understanding, and predicting the so -called structure-property relation is an important task in many scientific disc iplines, such as chemistry, biology, meteorology, physics, engineering, and mate rials science.” Financial supporters for this research include Forschungszentrum Julich Gmbh; Eu ropean Research Council. The news journalists obtained a quote from the research from Forschungszentrum J ulich GmbH: “Structure refers to the spatial distribution of, e.g., substances, material, or matter in general, while property is a resulting characteristic tha t usually depends in a non-trivial way on spatial details of the structure. Trad itionally, forward simulations models have been used for such tasks. Recently, s everal machine learning algorithms have been applied in these scientific fields to enhance and accelerate simulation models or as surrogate models. In this work , we develop and investigate the applications of six machine learning techniques based on two different datasets from the domain of materials science: data from a two-dimensional Ising model for predicting the formation of magnetic domains and data representing the evolution of dual-phase microstructures from the Cahn- Hilliard model. We analyze the accuracy and robustness of all models and elucida te the reasons for the differences in their performances.”
Forschungszentrum Julich GmbHJulichG ermanyEuropeBusinessBusinessCyborgsEmerging TechnologiesMachine Lear ning
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