Published September 2025 | Version Published
Journal Article Open

Materials Maturity Levels: A Systematic Approach to Evaluating Materials Development

  • 1. ROR icon Carnegie Mellon University
  • 2. ROR icon Institute For Defense Analyses
  • 3. ROR icon California Institute of Technology
  • 4. ROR icon University of Maryland, College Park
  • 5. ROR icon United States Department of Defense

Abstract

Materials development is a complex task that may start with a predicted property for a material that exists only in a computer. To arrive at a maturity level for a specific application that will use the material requires substantial synthesis, scale-up, and testing to prove reliability, demonstrate that a new material has the required properties, and thereby gain the trust of the relevant design community. A multi-year process is typically required to reach such an end-state with many cases of failure along the way when funding runs out or an application imposes demands beyond the capability of a given material. This report proposes a framework of Materials Maturity Levels for such a development sequence that systematizes the various stages of materials development and maturation. A spreadsheet is provided as a checklist for evaluating or assessing the current maturity level of a material. The need is explained for increasing involvement of an intended application with advances in maturity, leading to an emphasis on the value of co-design (i.e., that the application and the material should be designed hand-in-hand because each affects the other). The extent to which any given material must be embedded in a composite structure is discussed because this is commonly required for electronic materials (more so than structural materials). Simulation of processing, microstructure, and properties at each level is crucial to track and accelerate the entire maturation process which is well described by the Materials Genome Initiative (MGI). Currently, simulation makes the strongest contribution to materials discovery but is expected to become increasingly useful for predicting development, processing, and manufacturing workflows. This, in turn, points out the importance of verification and validation (V&V) in software tools, as well as uncertainty quantification (UQ).

Copyright and License (English)

© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Acknowledgement (English)

The authors state that the ideas embodied in this paper arose from discussions with numerous colleagues in a wide variety of scientific meetings and workshops. No external funding was used in writing this paper.

Funding (English)

Open Access funding provided by Carnegie Mellon University.

Data Availability (English)

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Additional details

Related works

Describes
Journal Article: https://rdcu.be/eLwKL (ReadCube)

Funding

Carnegie Mellon University

Dates

Accepted
2025-07-14
Available
2025-08-20
Published online

Caltech Custom Metadata

Caltech groups
GALCIT, Division of Engineering and Applied Science (EAS)
Publication Status
Published