Abstract: A property prediction device includes a processor; and a memory storing program instructions that cause the processor to: create a prediction model by using a training dataset of a composite material including raw materials in first and second categories to perform machine learning of a correspondence relationship between a property of the composite material, which is an objective variable, versus a mixing amount of the raw material in the first category and a weighted feature of the raw material in the second category, which are explanatory variables; and input, as explanatory variables, a mixing amount of a raw material in the first category and a weighted feature of a raw material in the second category, created based on prediction data of a composite material whose property is to be predicted, into the prediction model so as to predict the property of the composite material corresponding to the prediction data.

Abstract: A physical property prediction device for predicting a physical property of a compound including: a generation unit configured to generate a first stage trained model, by using, as training data, first stage synthesis information and synthesis result information; a generation unit configured to generate second stage through last stage trained models, by using, as training data, n-th stage (n?2) synthesis information, n-th stage synthesis result information, and n?1-th stage synthesis result information; a reception unit configured to receive a synthesis information setting for the compound for which the physical property is predicted; a prediction unit configured to predict a physical property value of a product synthesized by the first stage chemical reaction of the compound; a prediction unit configured to repeat, from a second stage chemical reaction to a last stage chemical reaction of the compound, a process of predicting a physical property value of a product synthesized by the n-th stage chemical react

Abstract: A material design apparatus is provided that can derive an optimal solution of a design condition of a polymer that satisfies desired and required physical properties.

Abstract: A material design system includes an expert terminal capable of using a model learning interface for performing machine learning of a model that inputs and outputs a correspondence between a design condition and a material property value of the material to be designed, and a plurality of general-purpose terminals configured to use a material design interface for estimating the material property value based on the design condition or estimating the design condition based on the material property value, by using a learned model that is created by the expert terminal and is for the material to be designed.