ArticleMRS bulletin2022
The materials tetrahedron has a "digital twin".
Article in MRS bulletin, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- ML-extendable framework for multiphysics-multiscale simulation workflow and data management using Kadi4Mat.Scientific data · 2025Article
- Materials designed to degrade: structure, properties, processing, and performance relationships in polyhydroxyalkanoate biopolymers.Polymer chemistry · 2025Review
- A Vision for the Future of Materials Innovation and How to Fast-Track It with Services.ACS physical chemistry Au · 2024Review
- The carbon footprint of predicting COiScience · 2024Article
- Community action on FAIR data will fuel a revolution in materials research.MRS bulletin · 2024Article
- FAIR for AI: An interdisciplinary and international community building perspective.Scientific data · 2023Article
- Community Resource for Innovation in Polymer Technology (CRIPT): A Scalable Polymer Material Data Structure.ACS central science · 2023Article
- Exploring the Conformers of an Organic Molecule on a Metal Cluster with Bayesian Optimization.Journal of chemical information and modeling · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abstract: 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.