Download PDF Fall Bridge on the Materials Genome Initiative September 29, 2025 Volume 55 Issue 3 The Fall 2025 issue explores the Materials Genome Initiative’s progress and future outlook, showcasing advances in autonomous experimentation, sustainable polymers, next-generation batteries, and the broader role of AI in engineering. Revolutionizing Materials Science and Technology to Secure Our Future Tuesday, September 30, 2025 Author: Richard A. Vaia, Germano Iannacchione, and Anthony D. Rollett Our future depends on making our materials faster, better, and smarter. In our pursuit of economic, societal, and defense security through technology, let us not forget that everything is made of something. There is a common saying paraphrased from the writings of the Nobel Laureate Sir George Paget Thomson: A civilization is both developed and limited by the materials at its disposal. We are within a historical time of consequence, a critical period in which decisions and actions will have a lasting, foundational impact. If we are to meet this challenge, advanced materials (AdvMat) can and should be reinvented by leveraging today’s information technology revolution and re-imaging partnerships between academia, industry, and government. This goal requires a national AdvMat initiative to harness the unique capabilities of all stakeholders ensuring that the modernization of materials science and technology (S&T) anticipates the accelerated rate of change in other sectors—colloquially, ensuring the right stuff is available to make the future. In a time of disruptive change, determining how to close this impedance gap cost-effectively is not only a competitive advantage but also a critical national capability. This imperative has been answered before. From the Bronze and Iron Ages to the modern era of silicon-based electronics and photonics, breakthroughs in materials have driven societal progress (Miodownik 2014). For instance, the mastery of smelting and alloying technologies led to the production of bronze, iron, and steel. This enabled the development of sophisticated tools for agriculture and the rise of complex civilizations, from the city-states of Ur and Babylon to the later Assyrian and Persian Empires. Similarly, in ancient China, the cultivation of silk—rooted in a deep, albeit empirical understanding of biology and textile manufacturing—fostered economic growth and global cultural influence. The advent of modern technologies is also witness to the profound impact of AdvMat. Aerospace is an exemplar, where material innovations enabled first powered flight and their lack resulted in tragedy. Charles Taylor’s innovative thin-wall casting technique, which significantly strengthened the aluminum crankcase by the formation of Guinier–Preston zones. This reduced the engine’s weight making the Wright Brothers’ pioneering 1903 flight possible (Gayle and Goodway 1994). In contrast, insufficient understanding of material performance, inspection techniques and manufacturing process controls led to catastrophes, such as the first fatality during powered flight (Howard 1998), or the structural failure of the world’s first commercial jet airliner, the original de Havilland DH.106 Comet, due to metal fatigue (FAA n/d). These tragedies highlight that it is more than discovery; a fundamental understanding of materials behavior for reliability and safety is just as important. The challenges posed by modern technologies catalyzed the formation of the materials science and engineering discipline in the 1960s. Its purpose, conceptualized as the “Materials Tetrahedron” (Deagan et al. 2022), is to understand, manipulate, and employ: a) the relationships between a material’s composition and hierarchical structure; b) how processing and environment optimizes that composition and structure from the atomic to the macro level; and c) ultimately using this information to forecast physical properties in service. The performance required for advanced technology is designed using materials and processes informed by the optimization of properties and attributes like cost, manufacturability and sustainability. The meaning of the term “advanced materials” evolves as new technologies continually expand the boundary of extreme performance. Consequently, the nation that discovers, understands, and utilizes AdvMat is best positioned for prosperity and security in that future “Age.” Today, many nations recognize the pivotal role of AdvMat in future economic growth and prioritize sustained research and development in this area to overtake competitors, such as the ones outlined in the Australian Strategic Policy Institute’s Critical Technology Tracker (Leung et al. 2024). The 2024 Nature Index found that eight leading nations in Materials Science research, including China, South Korea, Singapore, Japan, and Russia, dedicate more than 25% of their research articles to this field (Nature Index 2024). Moreover, access to critical elements, minerals, and materials—including their source and refinement—are the foundation of modern supply chains and employed today as a tool for global economic leverage. Whether one considers metals, ceramics, semiconductors, polymers, biomaterials, complex fluids, or a combination of them, the innovation landscape for human health, defense, energy, sustainability, and information depends on an affordable supply of trusted materials that are integrated with engineering design tools and manufacturing processes. The impact of such investment on future leadership is currently being discussed in academic, economic, futurist, and policy circles. These impacts are driving a revolution in the process of materials research and development (R&D). Traditionally, materials R&D has relied heavily on teams of expert researchers exploring potential applications or applying existing knowledge to solve engineering issues. Even interpolating within a class of materials for a solution can take a decade and hundreds of millions of dollars to mature a promising concept into a reliable, cost-effective solution with certification, databases, standards, and supply chains. Material researchers develop application-driven solutions for entrepreneurs, businesses and engineers who assess their utility when responding to product designers and commercialization requirements. However, this traditional, sequential, 15–20-plus-year process is out of sync with modern 1–3-year design–production cycles. In a time of disruptive change, determining how to close this impedance gap cost-effectively is not only a competitive advantage but also a critical national capability, since everything is made of something. In the United States, the decade-old Materials Genome Initiative (MGI) foresaw the necessity of dealing with this issue, envisioning the deployment of “advanced materials twice as fast and at a fraction of the cost compared to traditional methods” via integration of models, machine learning, robotics, high-performance computing, and automation (MGI 2025). In 2024, the MGI crafted Challenges such as “Point of Care Tissue-Mimetic Materials for Biomedical Devices and Implants” and “Agile Manufacturing of Affordable Multi-Functional Composites” to stimulate a nexus between data-centric materials frameworks and the necessary partnerships along the technology development pathway (MGI 2024). Numerous professional societies are becoming centers of exchange and community advocacy, such as The Minerals, Metals & Materials Society; The Materials Research Society; and the Materials Research Data Alliance. Examples are also exploding of how these digital approaches are addressing materials challenges early in research (Stach et al. 2021). Similarly, MGI-enabled products are occurring in some industries, such as alloy development at Mercury Marine, Pratt and Whitney, General Electric, Apple, SpaceX, and QuesTek, among others (TMS 2018; Warren 2024). Additionally, use of digital materials concepts, such as digital twins (NASEM 2024a) and data-validated material models, are beginning to occur within the US defense industrial base to accelerate advanced development, prototyping, design and acquisition. While digital tools such as artificial intelligence (AI) and autonomous self-driving laboratories offer powerful capabilities, accelerating individual steps in research does not automatically translate to an overall acceleration of new technology or their use. The significant time and effort required to overcome the various obstacles along the discovery–development–demonstration– deployment–decommission (D5) life cycle (Figure 1 [Left]) underscore the adage that “the best promise of a new material is often its first report.” The ecosystem, acumen, and tools necessary for success at each stage are different. However, the data are interrelated and need to flow both ways, whether via scientific principles or performance requirements. For example, to integrate materials innovation into initial design optimization of a component, a digital materials framework must not only facilitate discovery but also provide a foundation for anticipating development and deployment challenges like scale-up, integration, reproducibility, availability, reliability, survivability, manufacturability, and affordability (NRC 2024). Such a framework must be trusted by all communities by empowering their unique processes. Thus, the framework must embrace the convergence of distinct perspectives. A high MML platform provides increased agility, enhanced predictivity, and improved availability at lower cost to various systems during their life cycle by merging materials knowledge developed for and across various systems. Framing such a data pipeline is central to translating successful case studies of one material into the broader material S&T discipline. Because investment and engineering decisions are grounded by data, “assessments” and the associated “levels” used for understanding risk along a maturation pathway provide a framework for understanding the role and value of a data pipeline. Figure 1 (Left) summarizes a way in which such risk assessment frameworks help traverse the life cycle of a given system. Most prominent are Technology Readiness Levels (TRLs), developed by NASA in the 1970s, which describe a progression of events that represent systematic reduction of risk during the development of a complex system (Kimmel et al. 2020). Readiness to deploy and meet customer requirements, however, depends on many elements beyond technology integration, including maturity of sub-component technologies, software, manufacturing processes (DOD 2022), markets, and business models (DOE 2024), as well as materials. Each of these elements has spurred complementary frameworks that must be simultaneously addressed for successful system maturation. Recently, the concept of Material Maturation Levels (MMLs) has been proposed (Rollett et al. 2025). This concept recognizes the strategic advantage of de-risking a new material and its processing as a technology platform that continuously evolves to address the requirements of different systems as well as how these change throughout their life cycle. This contrasts with considering material readiness only within the confines of the requirements of a specific system, where simultaneous discovery and development of a bespoke material solution in parallel with components incurs substantial system-level risk and thus favors the use of existing material solutions. Effectively, material maturation argues for a broader aperture that is informed by, and informs, a set of various systems and their life cycles, as depicted by the numerous MML arcs (red) inside D5 loops for different system concepts (Figure 1 [Left]). Figure 1 (Right) summarizes the key features of MMLs, emphasizing that curiosity-driven studies, materials discovery, use-inspired R&D, prototyping, manufacturing, and certification cannot be decoupled, but instead their unique acumen and culture must be tied together with two-way bridges so as to yield a successful material technology platform. The process is not linear but ebbs and flows across the bridges embracing push, which imagines orthogonal approaches based on an expanded state of possibility, as much as pull, which solves application-derived requirements with new science, materials, and/or engineering. A high MML platform provides increased agility, enhanced predictivity, and improved availability at lower cost to various systems during their life cycle by merging materials knowledge developed for and across various systems. A new material technology with a high MML will reduce early system-level risks when it is used by a low TRL concept. Additionally, a digital artifact that reflects the material platform knowledge will allow exploration of a wider system design space, potentially revealing novel architectures that leverage the tailorability of new AdvMat. Since requirements shift during the life cycle, additional MML assessments are important to re-establish risk posture and effective mitigation strategies (such as for repair and sustainment after deployment) or for recycling and disposal during decommissioning. The “Digital Twin of the Materials Tetrahedron” is an example of a construct that could unify materials data across MMLs, affording integration and analysis of vast datasets on materials properties and processing parameters, as well as defining the knowledge deliverables in terms of modern digital engineering and manufacturing tools (Deagen et al. 2022). Risk Assessments and Levels During the Life Cycle of Systems As already noted, a system’s life cycle may be conceptualized in five stages: Discovery (curiosity and use-inspired research to expand the state of the possible), Development (demonstration of stable, predictable, and implementable components and the means for integration), Design (meet requirements by engineering, optimization, and integration of qualified components for an application), Deployment (established means for producibility, fielding, and sustainment of a solution that meets market or customer demand), and Decommission (methods of the system’s retirement, disposal, or repurposing) (Figure 1 [Left]). The duration of each stage is variable, and there is substantial ebb, flow, and iterations along the path. Each stage is dominated by an ecosystem with different perspectives and motivations, necessitating convergent teams to shepherd the most promising opportunities. Temporal impedance within and between stages nominally underscores success or failure, while using established components is much faster than creating new components. Overall, assessments and their associated levels are common frameworks used for quantifying risks during the process and are critical to determining additional investment. TRLs, MRLs, and Adoption Readiness Levels (ARLs) are examples that help mapping through different stages and provide measures to track gaps, impact, and value. Platform technologies that are foundational throughout the life cycle are the central hub, and are also supported by frameworks, such as MMLs. Material Maturation Valleys MMLs provide a framework to identify, assess, and address risks as the valleys are traversed between exploration, scaling, and certification. Materials exploration encompasses early curiosity and use-inspired research to discover new materials, and to understand the limits of their properties via determining their structure–composition–processing correlations, the effect of the environment, and subsequent interdependences. To reduce the ensuing investment risk of scaling, approaches to capacity beyond the lab-scale, demonstrating integration methods, verifying reproducibility, developing predictive models with quantified uncertainties for sets of properties, and quantifying the temporal impact of operational and manufacturing environments (i.e., survivability) must be overcome. These establish a scaled, stable, qualified material technology platform that can be used for development of design methods, prototypes, and fabrication processes that afford integration and tunability. If successful, even greater investment is required to validate manufacturability, reliability, availability, safety, affordability, and supportability, among other factors, in order to realize a certified material solution that conforms to standards, specifications, and a process design kit for use in a component or system. Success for each stage requires a unique acumen and culture, and the bridges require the convergence of these communities. A digital representation of the knowledge developed along this pipeline creates a “Digitized Materials Tetrahedron.” This MML deliverable ensures a fully acceptable, trusted material solution by empowering modern digital engineering, production, techno-economic analysis, and support tools across the life cycle. The benefits provided by this digital twin includes earlier evaluation of potential improvement to users by assessing the impact of material tunability on system performance, production costs, or lifetime; sensitivity analysis of changes in suppliers; insight to focus resources on critical path gaps to accelerate development; and rapid response to material failures during deployment with root-cause analysis. Given all this—the criticality of materials, the opportunities afforded by digital tools and information technology, and a broader aperture for material technology maturation and its impact on future systems—what is missing that limits a market-driven solution? One view is that market forces lack the patience to bring new materials through these frameworks. In this case, the federal government has crucial roles to fulfill. For example, basic science often generates non-excludable knowledge that underpins future innovations but is difficult for firms to fully quantify in terms of benefits to help them with selling new or improved products. Additionally, some critical technology platforms, such as advanced materials and manufacturing processes, require substantial long-term investments in research, development, and workforce education with uncertain returns. Private-sector investment alone would be too risky and impatient in the face of uncertain return on investment. For highly complex technologies, information asymmetry may also hinder innovation, where a lack of comprehensive expertise, facilities, tools, software, training, information access, or partnerships challenge small and medium enterprises to leverage innovations of others and to communicate the value they provide. In all these cases, the government acts as a broker through leadership, policy, and resources, from facilitating competition to connecting commercial innovation to activities providing a public good such as national defense. Government resources, expertise, facilities, and policies ensure technological advancements that complement and integrate those of the private sector so that federal procurement delivers the most capable defense systems. For a data-centric materials revolution that empowers all the nation’s innovators, these brokerage roles are not just crucial but imperative. The Impact of the Materials Genome Initiative The MGI laid the foundation for the materials science and technology revolution by convening 19 federal agencies and their laboratories. As a coalition, the agencies engage stakeholders across materials science and its intersection with various technologies. For example, NSF, the Department of Energy (DOE) Office of Basic Energy Sciences, and DoD’s Basic Research Offices (e.g., ARO, ONR, AFOSR) drive curiosity-driven exploration of data-centric methods to accelerate materials discovery. DOE’s Office of Energy Efficiency and Renewable Energy, NASA, National Institute of Standards and Technology (NIST), and DoD’s laboratories and agencies (e.g., ARL, NRL, AFRL, DARPA, MDA) create public–private communities that address high risk, use-inspired material challenges through grants, contracts, innovation challenges, and partnerships. All of the agencies develop and sustain pre-competitive user facilities that are democratizing materials innovation and demonstrating the impact of artifact intelligence and autonomy. These range from unique collections of synthesis, computation, and fabrication capabilities to one-of-a-kind instrumentation, open-access data banks, and emerging manufacturing technologies. Finally, federal teams are partnering with the private sector to develop policy and regulatory support, ranging from data-sharing policies (National Institutes of Health, NSF, DOE) and championing standards (NIST, DoD). Recent summaries of these activities include an NSF-led assessment of the US infrastructure that is relevant to autonomy-enabled materials R&D (NSF 2024), a National Academies examination of the impact of basic science programs to achieve the MGI vision (NASEM 2023), a report on creating the next generation materials workforce (TMS 2019), and an OSTP assessment of the impact of AI (Hendrix 2024). These reports demonstrate that increased coordination among the federal AdvMat community, and with private institutions, is setting a foundation for a national capability in digitized AdvMat innovation. Such products and forums facilitate communication and awareness between stakeholders and ensure that teams specialize appropriately to maximize leveraging and impact, while minimizing duplication. Notable examples of efforts to establish a data-centric materials revolution through public–private stakeholder teams are discussed below. Developing a Data-Centric Materials Research Culture The Designing Materials to Revolutionize and Engineer our Future (DMREF) initiative is an NSF-wide, multi-agency, biannual interdisciplinary teams program that seeks to promote the design, discovery, and development of materials and accelerate their path to deployment. DMREF emphasizes (1) a deep integration of experiments, computation, and theory; (2) the use of accessible digital data across the materials development continuum; and (3) the strengthening of connections among theorists, computational scientists, data scientists, mathematicians, statisticians, and experimentalists. Leveraging AI, autonomy, and automation, researchers not only discover new materials but uncover hidden patterns and predict material behavior with greater accuracy. In addition, multiple federal partners (Departments of the Air Force, Navy, and Army; DOE; NIST) participate through either direct funding or via collaborations with their intermural researchers and facilities. Recently, international partners (United States-Israel Binational Science Foundation; Department of Science and Technology, Government of India; Natural Sciences and Engineering Research Council of Canada; and Deutsche Forschungsgemeinschaft) have been integrated. DMREF exemplifies the power of collaborative and coordinated federal activities as well as connecting public and federal scientists (TMS 2019). Creating Unique Data-Centric Materials Facilities Large center-level “aggregators” of significant and unique instrumentation play especially crucial roles in exploring over-the-horizon discovery and de-risking development with industrial participation. Notable efforts at NSF include the Materials Innovation Platforms, Engineering Research Centers, and Industry-University Cooperative Research Centers. DOE supports crucial data and computational infrastructure investments, including the Materials Project, its Computational Materials and Chemical Science programs, and the Energy Materials Network. Joint federal/industry/academic investments in large-scale instrumentation are especially important in transferring data-centric materials practice to industry, such as DOE’s Light and Neutron Sources, Cornell’s Center for High-Energy X-ray Sciences (CHEXS), the NIST/NCNR Center for High-Resolution Neutron Scattering, and NIST’s Materials Data Repository. These efforts demonstrate how to fuse data from disparate experimental and modeling sources and integrate AI, automation, and autonomy into digital workflows for discovery, design, and manufacturing. Catalyzing Data-Centric Materials Communities for National Priorities The nation’s federal laboratories are vital centers of excellence within the US S&T ecosystem. They attract top scientists and engineers from all disciplines, cultivating global technological leadership for national priorities in economic, energy, health, and defense security. Their unique environments and public–private collaborations result in revolutionary innovations that complement the market by enabling the entire material spectrum, such as high-precision instrumentation, theory and computation methods, first-of-a-kind synthetic approaches, new characterization techniques, and gold-standard reference data. As the public’s independent deep-technical experts, the civilian scientists and engineers also play many vital roles by focusing on high-risk material concepts, providing unbiased assessment, and targeting mission-relevant capability gaps to guarantee technological advantages necessary for national strength. Such catalyzing leadership by engineers and scientists at NIST, DoD’s service laboratories, and many others, are creating pervasive data-centric tools from material data repositories to autonomy-enabled research platforms for accelerated validation, reducing barriers to entry via open architecture standards, and manufacturing via materials-informed digital twins. Despite the impact of these federal activities, substantial challenges remain in accelerating materials discovery to market impact and delivering solutions to national priorities. These challenges go beyond deepening the convergence of information sciences with materials discovery and research communities. Rather, they reflect a complex mix of technology, culture, policy, and resources that extend beyond individual segments of the D5 or MML processes. Some examples that necessitate additional federal leadership and partnerships with the private sector follow. Valuation of Materials Data Maximal impact of AI is predicated on interoperable data. Notwithstanding the extensive array of current and planned material data bases and automated or autonomy-driven materials R&D facilities, they are generally isolated, geographically and virtually. Interconnectivity, such as via the Cloud, reflects a substantial opportunity to drive exponential growth, but necessitates accessibility to AI-ready and FAIR (Findable, Accessible, Interoperable, and Reusable) compliant data (Brinson et al. 2024). The lack of standardized data formats, application program interfaces, and techniques to measure impact and assess value of data archiving and sharing, encourages data silos and hinder efficient sharing and integration of materials data across all stakeholders, from academia, small businesses, and government to emerging and established supply chains. For example, federal agencies can convene the community to develop and adopt data standards, to validate usage of Large Language Models, and to establish workflow frameworks for research, validation, and certification. Such community practices should balance sharing and accessibility with the protection of intellectual property rights and national security by building on cybersecurity innovations in health, financial, and intelligence communities. These characteristics are foundational to transforming databases, where information is archived, into data banks where information can be deposited, updated, and retrieved such that the process creates value (Himanen et al. 2019; NASEM 2024b). These and other innovations are necessary for the establishment of viable business models that simultaneously accelerate open innovation, deliver data interoperability, maintain information rights, and provide for the long-term sustainability of the infrastructure, data curation, and software in which a future data-centric AdvMat discipline will be based. Transferability of Digital Materials Tetrahedra Another challenge is the compartmentalization of efforts across materials and technology sectors, which not only hampers sharing of successful approaches but fosters niche solutions that lack interoperability through MMLs and across readiness levels. While the pursuit of a universal solution is quixotic, developing strategic plans and roadmaps fosters collaboration among sectors and provides a means to align priorities, eliminate redundancies, and identify gaps to maximize the impact of investments. Such a shift from vertical integration with a few participants to precompetitive partnerships across a common supply chain has occurred historically due to the need for exponentially more complex and costly technologies to meet market demand, such as SEMATECH and other consortiums for microelectronics. The success of an agile vertical with many participants depends on a common vision and shared understanding of gaps, achieved through road-mapping that includes all stakeholders. Knowledge and data sharing of materials and manufacturing processes affords early and evolving analysis of alternatives as well as the ability to target resources on the challenges most impactful to market needs. This alignment through the discovery–development–deployment arc is especially important to focus discovery on the most impactful problems, as well as fully understand the potential extent of system-level impact of new materials as they ascend the maturity ladder. For such goals, industry must collaboratively define a value proposition balanced across the ecosystem and individual entities, while developing incentive policies for data sharing, streamlining regulatory processes to reduce barriers to new material adoption, and addressing gaps such as access to mid-scale production for validation of emerging materials or enabling the economic viability of solutions requiring only small production runs (NASEM 2025). Examples of such activities in which public–private partnerships are incubating the value of digital materials artifacts in different communities include the Manufacturing USA Institutes (NASEM 2017), MGI’s CHIPs for America program on Accelerating Material R&D for Sustainable Semiconductor Materials, and federal approaches to ensure reliable critical materials and minerals (NAE 2024). Other approaches are based on regional networks for innovation and economic development, such as NSF’s Regional Innovation Engines and AFRL’s Regional Networks. Common across these activities is the need for public funding to not only incentivize partnerships but provide stability as trust is established among the diverse stakeholders. Further success and scalability will require a national conversation of incentives, resources, and culture. Ensuring the Future Workforce Finally, an expanded workforce will be necessary to compete globally and employ these data-centric material innovations across the life cycle. A participant must not only be cognizant of information technology and materials science, but thrive in diverse teams that merge materials science, engineering, manufacturing, and digital technologies seamlessly. Not only is an understanding of the complexities of materials required, but also their role and impact on system design, product development, producibility, and profitability. Continuous career learning should also be portable across sectors, enhancing talent flow and providing updated skills to retrain staff. Such a shift in materials education necessitates curriculum and offerings beyond those offered in traditional bachelor’s, master’s, and doctoral programs. For example, new complementary models for graduate education that embed students in multidisciplinary, team-based cohorts comprised of members with disciplines beyond STEM and embracing internships with industry (established companies or startups), could revolutionize materials innovation. In parallel, a diversity of appropriately sized research funding constructs or grand-challenge prizes that are focused on cross-organization teams will ensure future practitioners have hands-on experiential learning. Technology challenges aligned with national priorities and academic-industry high-risk high-reward projects would provide young materials innovators with experiences at the intersection of basic research and commercialization, serving as steppingstones into US industry. A broader conversation between educators and workforce employers on how we educate the future innovators is imperative if the nation is to stay competitive and transform the potential of a data-centric materials revolution to solutions for economic, societal, and defense security. Concluding Observations So, what do we need to do? Materials science and engineering are and will remain crucial to economic and national security. Materials knowledge not only enables emerging technologies and provides differentiators to existing technologies, but also ensures affordable manufacturing, reliability and sustainability. To match the rate of modern technology cycles and deliver discontinuous innovation, the information technology revolution must continue to infuse the entirety of material maturation and adoption pipelines—transforming the “how” of AdvMat so it can continue to deliver as the definition of “advanced” evolves in the future. This goal necessitates a national AdvMat initiative to accelerate the transformation of research culture, facilities, and communities spearheaded by the MGI. Continuing the MGI Challenges’ calls to action will provide priority challenges to rally the community to demonstrate cost-effective acceleration of AdvMat solutions with game-changing impact. Federal leadership, investment, and curation of such public–private teams are required to address the complex interplay of technology, culture, policy, and resourcing facing the next challenges of data valuation, interoperability, and workforce. Such efforts, if successful, will build a resilient, responsive, and interconnected materials innovation infrastructure, crucial to securing US leadership in future technology revolutions. References Brinson LC, Bartolo LM, Blaiszik B, Elbert D, Foster I, Strachan A, Voorhees P. 2024. Community action on FAIR data will fuel a revolution in materials research. MRS Bulletin 49(1):12–16. 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About the Author:Richard A. Vaia (NAE) is chief scientist, Materials and Manufacturing, Air Force Research Laboratory. Germano Iannacchione is director, Division of Materials Research, National Science Foundation. Anthony D. Rollett is the US Steel Professor of Metallurgical Engineering and Materials Science and Engineering at Carnegie Mellon University.