TSUKUBA, Japan, May 25, 2022 - (ACN Newswire via SEAPRWire.com) - Researchers from Konica Minolta and the Nara Institute of Science and Technology in Japan have developed a machine learning method to identify sustainable alternatives for composite materials. Their findings were published in the journal Science and Technology of Advanced Materials: Methods.Researchers are looking for sustainable options, such as recyclable materials or biomass, to substitute the constituent materials in composites which are used in various applications including electrical and information technologies.Composite materials are compounds made of two or more constituent materials. Due to the complex nature of the interactions between the different components, their performance can greatly exceed that of single materials. Composite materials, such as fibre-reinforced plastics, are very important for a wide range of industries and applications, including electrical and information technologies.In recent years, there has been increasing demand for more environmentally sustainable materials that help reduce industrial waste and plastic use. One way to achieve this is to substitute the constituent materials ...