Materials Informatics: IDTechEx Investigates the AI-Designed Materials Revolution

Materials Informatics: IDTechEx Investigates the AI-Designed Materials Revolution Author: Sam Dale, Senior Technology Analyst at IDTechEx ,Materials informatics represents the data revolution’s impact on materials R&D. Data-centric approaches, including AI and machine learning, are transforming the way materials scientists and engineers work, getting materials to market faster and driving development in new directions. A range of strategic approaches have emerged, with leading players and commercialized materials developed via data-driven methods emerging.

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IDTechEx has been tracking this field since its early days: the newest edition of its research report, “Materials Informatics 2024-2034: Markets, Strategies, Players”, provides key insights and commercial outlooks into the state of this emerging industry.  Built upon technical primary interviews with 27 players, readers will get a detailed understanding of the players, business models, technology, and strategies in this industry. The revenue of firms offering materials informatics services is forecast to 2034, with 11.5% CAGR expected until then. The impact of the ongoing AI boom is considered, and numerous relevant projects across materials science are covered. Analysis of the underlying technologies demystifies this fast-growing area of digital transformation in R&D.

What is materials informatics?

Primarily, materials informatics is based on using data infrastructures and leveraging machine learning solutions for the design of new materials, discovery of materials for a given application, and optimization of how they are processed. Numerous methods are involved here, with the influence of data-driven methods stretching from the beginning to the end of an R&D process, encompassing the creation of a hypothesis, the handling, acquisition, and analysis of data, and the final extraction of knowledge.

Not only can materials informatics be used to predict the properties of a given material, but it can even be used for the inverse design of materials from their desired properties, shortening the costly trial-and-repeat searches that are common in materials design.

The challenges in materials informatics are often very different from other AI-led areas, such as autonomous cars or social media. Sparse, high-dimensional, biased, and noisy data is common: leveraging domain knowledge is an essential part of most approaches. Ultimately, the role of a provider of materials informatics software is to connect the work of materials scientists to that of data scientists, with methodologies here evolving over time. If integrated correctly, materials informatics will become a set of enabling technologies accelerating scientists’ R&D processes while capitalizing on their specialized knowledge.

What’s new in materials informatics?

In recent years, awareness of the requirement for digital transformation in R&D has led to an acceleration in the adoption of materials informatics processes by materials industry players, from startups to established giants. As the AI boom hit in 2023, interest in materials informatics only increased, with industry players telling IDTechEx during interviews for its report that, where adoption push had usually come from the bottom up within organizations in the past, drive was increasingly coming from executives eager to show the impact of AI in their business. The year ended as the healthiest year for investment in materials informatics SaaS firms yet, surpassing the previous high of 2019.

The results of generative AI were being applied in materials informatics far before the term became widely known to the public, marking some of the earliest success stories here. The impact of generative models generally was wide in 2023, with the newly powerful large language models (LLMs) behind services like ChatGPT grabbing many headlines.

LLMs are also bringing changes to materials informatics, with the power of retrieval augmented generation to turn them into queryable experts in specialized fields being felt in services from new entrants like Fehrmann MaterialsX and established players, including Citrine Informatics. IDTechEx’s report lays out the exciting potential of LLMs for materials research: one impact is the potential expansion of the customer base of materials informatics software to materials end-users by flattening learning curves, using natural language as an interface.

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Adopting materials informatics, as laid out in the report, usually takes several core approaches: operate fully in-house, work with an external company, or join forces as part of a consortium or joint venture. Major players like Hitachi have previously offered in-house developed materials informatics platforms externally, but a new approach emerged in 2023. Henkel spun off its end-to-end research platform Albert Invent as an external company, continuing to engage it as a customer while allowing the startup to grow as a more agile but very well-funded smaller organization. Perhaps 2024 could see more similar spin-offs as companies seek to gain even more ROI from their in-house developed platforms while avoiding the conflict of interest of engaging with competitors themselves.

Key questions answered

IDTechEx’s new report, “Materials Informatics 2024-2034: Markets, Strategies, Players”, is now in its fourth update and is informed by first-hand interviews with the industry’s major players. It answers questions including:

• What are the strategic approaches to materials informatics, and how do they compare?
• How do MI’s practitioners solve the problem of sparse experimental datasets?
• Where and how is materials informatics applied across a diverse range of fields of materials science?
• What companies are involved with materials informatics, and how do they stack up against one another?
• Which algorithmic approach is appropriate to solve various problems in MI?
• What have been the major developments in the field of materials informatics in the last year?
• How has the AI boom impacted the materials informatics industry?
• What should be expected for the future of materials informatics adoption?
• How will materials informatics and self-driving labs synergize to shape the future of materials R&D?

Market forecasts, player profiles, investments, roadmaps, and comprehensive company lists are all provided, making this essential reading for anyone wanting to get ahead in this field.

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