Polymeric materials are integral components of nearly every aspect of modern life. However, developing cheminformatic solutions for polymers has been difficult since they are large stochastic molecules with hierarchical structures spanning multiple length scales. Here we present the design for a general material data model that underpins the Community Resource for Innovation in Polymer Technology (CRIPT) data ecosystem.

Transfer molding offers a low-cost approach to large-area fabrication of isolated structures in a variety of materials when recessed features of the open-faced mold are filled without leaving a residual layer on the plateaus of the mold. Considering both macroscale dewetting and microscale capillary flow, a proposed map of wetting regimes for blade meniscus coating provides a guide for achieving discontinuous dewetting at maximum throughput. Dependence of meniscus morphology on the azimuthal orientation of the stamp provides insight into the dominant mechanisms for discontinuous dewetting of one-dimensional (1-D) patterns. Critical meniscus velocity is measured and residual-layer-free filling is demonstrated for 1-D patterned soft molds (stamps) with periods ranging from 140 nm to 6 μm. Transfer of isolated lines, and multilayer woodpile structures were achieved through plasma bonding. These results are relevant to other roll-to-roll compatible processes for scalable production of high-resolution structures across large areas.

With the advent of the materials genome initiative (MGI) in the United States and a similar focus on materials data around the world, a number of materials data resources and associated vocabularies, tools, and repositories have been developed. While the majority of systems focus on slices of computational data with an emphasis on metallic alloys, NanoMine is an open source platform with the goal of curating and storing widely varying experimental data on polymer nanocomposites (polymers doped with nanoparticles) and providing access to characterization and analysis tools with the long-term objective of promoting facile nanocomposite design. Data on over 2500 samples from the literature and individual laboratories has been curated to date into NanoMine, including 230 samples from the papers bound in this virtual issue. This virtual issue represents an experiment of the flexibility of the data repository to capture the unique experimental metadata requirements of many data sets at one time and to challenge the authors to participate in the curation of their research data associated with a given publication. In principle, NanoMine offers a FAIR platform in which data published in papers becomes directly Findable and Accessible via simple search tools, with open metadata standards that are Interoperable with larger materials data registries, and allows easy Reuse of data, e.g. benchmarking against new results. Our hope is that with time, platforms such as this one could capture much of the newly published data on materials and form nodes in an interconnected materials data ecosystem which would allow researchers to robustly archive their data, add to the growing body of readily accessible data, and enable new forms of discovery by application of data analysis and design tools.

For over three decades, the materials tetrahedron has captured the essence of materials science and engineering with its interdependent elements of processing, structure, properties, and performance. As modern computational and statistical techniques usher in a new paradigm of data-intensive scientific research and discovery, the rate at which the field of materials science and engineering capitalizes on these advances hinges on collaboration between numerous stakeholders. Here, we provide a contemporary extension to the classic materials tetrahedron with a dual framework—adapted from the concept of a “digital twin”—which offers a nexus joining materials science and information science. We believe this high-level framework, the materials–information twin tetrahedra (MITT), will provide stakeholders with a platform to contextualize, translate, and direct efforts in the pursuit of propelling materials science and technology forward. Impact statement This article provides a contemporary reimagination of the classic materials tetrahedron by augmenting it with parallel notions from information science. Since the materials tetrahedron (processing, structure, properties, performance) made its first debut, advances in computational and informational tools have transformed the landscape and outlook of materials research and development. Drawing inspiration from the notion of a digital twin, the materials–information twin tetrahedra (MITT) framework captures a holistic perspective of materials science and engineering in the presence of modern digital tools and infrastructures. This high-level framework incorporates sustainability and FAIR data principles (Findable, Accessible, Interoperable, Reusable)—factors that recognize how systems impact and interact with other systems—in addition to the data and information flows that play a pivotal role in knowledge generation. The goal of the MITT framework is to give stakeholders from academia, industry, and government a communication tool for focusing efforts around the design, development, and deployment of materials in the years ahead. Graphic abstract

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