Materials informatics: Industry activity steps up to accelerate R&D, says IDTechEx

IDTechEx has released their latest report Materials Informatics 2022-2032, which gives the a detailed assessment of this area including interview-based company profiles, critical technology analysis, adoption roadmap, business model appraisals, and granular application case studies.

According to IDTechEx, the ability to develop new materials and bring them to market ever faster is an obvious goal. There continues to be countless developments that improve chemistry and materials science R&D, but perhaps none represent the same paradigm shift that materials informatics offers. Major industry players are waking up to this as the technology matures. Overlooking this transition could be costly.

Materials informatics (MI) is based on using data infrastructures and leveraging machine learning solutions for the design of new materials, the discovery of materials for a given application, and optimization of how they are processed. MI can accelerate the “forward” direction of innovation (properties are realized for an input material) but the idealized solution is to enable the “inverse” direction (materials are designed given desired properties).

Despite the hype, this is not straightforward and is still at a nascent stage. In many cases, the data infrastructure is not comprehensive and MI algorithms are often too immature for the given experimental data. The challenge is not the same as in other AI-led areas (such as autonomous cars or social media), the players are often dealing with sparse, high-dimensional, biased, and noisy data; leveraging domain knowledge is an essential part of most approaches.