Informatics of materials 2023-2033: IDTechEx

Materials Informatics (MI) involves the use of data-centric approaches to materials science R&D. There are multiple strategic approaches and many notable successes; adoption is accelerating and missing this transition will be costly.

This report provides key insights and business insights for this emerging field. Based on primary technical interviews with 24 players, readers will gain a detailed understanding of the players, business models, technology, and strategies in this industry. Revenue for companies offering IM services is forecast to 2033, with a CAGR of 13.7% expected until then. Case studies in numerous applications highlight the wide range of materials science areas where MI adds value. Analyzing the underlying technologies demystifies this growing field of digital R&D transformation.

Main areas covered by this report. Source: IDTechEx

What is Materials Informatics?

Materials informatics is the use of data-centric approaches for the advancement of materials science. This can take many forms and influence all parts of R&D (hypothesis – data processing and acquisition – data analysis – knowledge extraction).

MI is mainly based on the use of data infrastructures and the exploitation of machine learning solutions for the design of new materials, the discovery of materials for a given application and the optimization of their processing.

MI can accelerate the “forward” direction of innovation (properties are realized for an input material), but the ideal solution is to enable the “reverse” direction (materials are designed according to desired properties ).

It is not simple and emerges from its nascent phase. In many cases, the data infrastructure is not complete and the MI algorithms are often too immature for the given experimental data. The challenge is not the same as in other AI-driven fields (like self-driving cars or social media), actors are often faced with sparse, high-dimensional, biased and noisy data; leveraging domain knowledge is an essential part of most approaches.

Contrary to what some might believe, this is not something that will displace researchers. If properly integrated, MI will become a set of enabling technologies accelerating scientists’ R&D processes while utilizing their domain expertise. For many, the dream end goal is for humans to oversee an autonomous, self-contained laboratory; although still at an early stage, there have been key improvements, spin-off companies formed, and success stories, all facilitated by MI developments.

Why now?

This is not a new approach; many industries have adopted similar design approaches for decades. But there are three main reasons why this transformative technology is impacting the materials science space right now:

  • Improvements to AI-based solutions taken from other industries.
  • Data infrastructure improvements, from open-access data repositories to cloud-based research platforms.
  • Awareness, education and the need to keep up with the underlying pace of innovation.

IDTechEx has categorized the projects undertaken into eight main categories described in detail in the report. In this context, using advanced machine learning techniques in your R&D process has three repeated benefits: improved candidate and research area selection, reduced number of experiments to develop new material (and therefore time to market) and the search for new materials. or relationships. Training data may be based on experimental, internal computer simulations and/or external data repositories; enhanced lab computing and experimentation or high-throughput computing can be an integral part of many projects.

This report examines key advancements in machine learning for MI, success stories, and how end users are actively engaging with it.

What are the strategic approaches?

Ignoring this R&D transition is a major oversight for any company designing materials or designing with materials: awareness of potential mid- and long-term missed opportunities is growing rapidly. This may be when bringing competitive products to market, developing versatility in the supply chain, finding next-generation opportunities, or being able to diversify a business unit or materials portfolio.

Many players have already started this adoption with three main approaches: operating entirely in-house, working with an external company or joining together as part of a consortium. Each of these approaches is assessed in detail in the report; choosing to embark on IM adoption is important, choosing the right path is essential.

External MI drives can come from many starting points as shown in the figure below. There is also the possibility for MI players to become a licensing company with a strong portfolio of advanced materials and also for end users to offer MI as a service. Geographically, many end-users adopting this technology are Japanese companies, many emerging external companies are American, and the most notable consortia and university labs are spread between Japan and the United States.

Interview-based profiles of all key companies are included in this IDTechEx report.

Categorization of Materials Computing Industry Players. Source: IDTechEx

Where is Materials Informatics applied?

Organic electronics, battery compositions, additive manufacturing alloys, polyurethane formulations and the development of nanomaterials are all examples of areas where IM has an immediate impact. The wide range of material use cases means industrial adoption is on the way, from electronics manufacturers to chemical companies.

There are universal challenges, but each application domain will have certain considerations, whether in the availability of existing data, domain knowledge, complexity of structure-property relationships, and more.

The final part of this report details a comprehensive range of application areas in turn, highlighting key developments, business use cases, and notable releases. This offers end users the opportunity to focus on case studies in their specific areas of interest and MI actors on areas to explore.

What will I learn from the report?

This market report comes at a time when the 10-year outlook is paramount for rapid adoption, with the average MI enterprise headcount growing 91% from 2021-22. This report goes far beyond what is available on the internet, providing key business insights based on primary interviews coupled with expertise on both this topic and many relevant application areas.

Over the past few years, there has been a significant progression in external companies providing MI solutions, more key partnerships and end-user engagements, new consortia and academic advancements, and new emerging companies. All of this is tracked, explained and analyzed throughout this industry-leading report on the subject.

Market forecasts, player profiles, investments, roadmaps, and comprehensive company listings are all provided, making it essential reading for anyone looking to advance in this field.

This report provides the following information

Technology Trends:

  • Analysis of key elements to enable a materials informatics strategy.
  • Status, developments and limitations of AI-driven approaches for materials science R&D.
  • Main academic and industrial progressions highlighted.

Company analysis:

  • Complete list, details and differentiating characteristics of all MI companies.
  • Company profiles based on interviews for 24 players.
  • Partnerships, funding and business models assessed
  • Strategic options critically assessed.
  • End-user engagement assessed.
  • National and international consortia and initiatives analysed.

Market applications and outlook

  • 10-year market forecast for external IM companies.
  • Roadmap for adoption and application.
  • Case studies and success stories in the R&D of many advanced materials and emerging applications.

All report purchases include up to 30 minutes of phone time with an expert analyst who will help you relate the report’s key findings to the business issues you are addressing. This must be used within three months of purchasing the report.

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