Posted By: Air Force Research Lab
Category: Scientific/Engineering Partnership With: National Institute of Standards and Technology
National Science Foundation
Submission Dates: 12 a.m. ET, Jul 01, 2015 - 11:59 p.m. ET, Mar 31, 2016 Judging Dates: Apr 01, 2016 - May 11, 2016 Winners Announced: May 11, 2016
People have successfully applied advanced analysis techniques to ‘big data’ and have solved significant challenges in several areas of society including business, biology, and astronomy. Using these techniques has provided people with new and valuable information from the data that was not readily available by other means. However, materials science and engineering data has not yet been exploited to its full potential because of its complexity. This complexity also stands to provide rich insights if the mysteries the data hold can be unraveled.
To advance the National goals of the Materials Genome Initiative (MGI), we are soliciting innovative approaches to solve materials science and engineering problems primarily through the analysis of publicly accessible digital data. Areas of particular interest include discovery of new materials to meet an application need, or development of a new model describing processing-structure-property relationships in either a structural (load bearing), functional (electrical, optical or magnetic), or multifunctional material.
Emphasis will be on use of existing and accessible data sources, novelty of the approach, and validation of results.
Winners will be invited to present their work at a special session (reasonable expenses paid) during Materials Science & Technology 2016 in Salt Lake City, Utah.
This challenge requires only a written research report in a format suitable for peer-reviewed scientific publication be submitted. The challenge award will be contingent upon evaluation of the proposal by the review committee. The Air Force Research Laboratory intends to make multiple awards with the top award being $25K and no award less than $5K depending on creativity and completeness of the report.
To receive an award, the Solvers will not have to transfer their exclusive IP rights to the US Government. Instead, they will grant to the US Government non-exclusive license to practice their solutions. Other arrangements may be considered, if a license cannot be granted.
The US Government is soliciting advanced approaches to analysis of digital materials data that would provide new knowledge for materials science and engineering to a level where they would enable:
- Discovery of new material structures and/or compositions that provide previously unattained and useful properties that enable new industrial applications or products.
- Development of new models to link at least two elements in materials processing-structure-property relationships where those relationships are currently poorly described by physics-based models.
Note: Solvers can be individuals or teams from academia, industry, or any other area. Solvers can submit reports for solutions to either or both of the needs described in 1 & 2 above, but they should submit a separate report for each if responding to both. Reports must detail the source of the materials data, the research approaches used, and methods used to validate the findings.
We are not seeking submissions for the following areas: Research in biology for pharmaceutical, medical, or other biological or biomedical purposes.
Reuse or repurposing of digital scientific data has been applied in many scientific disciplines to solve important technical challenges for that discipline. Advances in computational power and data science techniques have enabled these innovations by providing new means to extract information from large datasets. Materials science and engineering progress is dependent on understanding, connecting, and applying extraordinarily complex information across large temporal and spatial scales. However, researchers often times encounter hard limits on the availability of accurate physical models to describe behavior. This lack of well-developed physics-based approaches across scales hampers advances in the discovery of new materials and an ability to link processing-structure-property relationships in such a way as to enable quantitative and predictive materials design tools. The goal of the Materials Genome Initiative is to halve the time it takes to discover, develop and deploy a new material and at a fraction of the cost compared to traditional approaches. Application of data science techniques to accessible digital materials data to develop new knowledge is expected to be part of the solution to reaching this goal.
The goal of this project is to leverage advanced computational and data science techniques to solve challenges associated with discovery, development, and production of new materials. The US Government is soliciting innovative, detailed approaches that can solve barrier issues in materials science and engineering research and offer new avenues for providing rapid and insightful information in materials research and development.
Previously unpublished materials data may be submitted here (subject to NIST approval):
More information on the Materials Genome Initiative can be found at:
OSTP article on the Materials Genome Initiative can be found here:
The materials data used in the challenge is accessible, discoverable, and has sufficient provenance
• Data used in this challenge must be publicly accessible on the internet by 1 Sep 2015, and documentation of this accessibility should be provided with submission. If desired, documentation of data availability can be established by sending a short description of the data and the accessible link to firstname.lastname@example.org no later than 1 Sep 2015.
• Data must be discoverable and cited through a means such as a resolvable Uniform Resource Identifier (URI) or, ideally, a Persistent Identifier (PID).
• Data sources used must have sufficient supporting information (metadata) to enable reuse by researchers outside the original research effort.
• While the data used is not required to be free, or licensed for unrestricted use, cost and license encumbrances will be considered during the judging to ensure that the data is not effectively inaccessible to large swathes of the research community.
• Greater weight will be given to solutions that reuse data generated by others than the solvers themselves.
If hosted on a separate site, the the link must be part of the submission.
This criteria must be met for a valid submission.
Novelty and significance of the approach
• The approach is clearly defined through a written report suitable for peer-reviewed scientific publication and makes a significant contribution to the goals of this challenge.
• The solver has employed data analysis techniques that significantly accelerate the attainment of new insights and information as compared with existing experimental or physics-based modeling means.
• If the approach identifies a new material composition, material structure, or family of compositions, the solution will be evaluated against the degree to which the predicted and/or demonstrated range of properties provide significant improvement over currently known materials for a specific or variety of industrial applications. An analysis of the ability for or actual demonstration of practical synthesis of the material composition should be addressed in the report.
• If the approach addresses modeling the linkage between at least two elements of material processing, structure, and/or property, a quantitative description of material structure (e.g. microstructure) must be included in the model. The solution will be evaluated against the degree to which the new physical insight improves gaps in our ability to accurately model material behavior across length and/or temporal scales.
Validity of solution
• Scientifically sound steps have been taken and described to demonstrate that the approach has produced a valid solution, within a reasonable confidence level.
Uniqueness of approach or model
• The approach is primarily based on using data analytical techniques (e.g. machine learning, Bayesian Neural Networks, etc.) with existing accessible data to derive new information in materials science and engineering.
• The results of the approach must not have been previously publicly presented nor published
This is a disqualifying criteria.
Fill out the submission form for personal contact information.
Submit the solution as an attached file in the attached solver submission format without any personally identifying information (all entries will be anonymous to the judging team)
Previously unpublished data can be published in the NIST Materials Data Repository:
Add to the Discussion
1 Sep 2015 All data sources used must be published in accessible data repositories. Unpublished data can be submitted to the NIST materials repository at
31 Mar 2016 Final deadline for submitting a research report for consideration.
11 May 2016 Winners are announced
16 Oct 2016 Invited winners present their work at Materials Science & Technology 2016 in Salt Lake City, UT.
This challenge requires only a written research report in the format of a peer-reviewed scientific publication to be submitted. The submitted report should include the following:
- A clear and concise description of the technical approach (methods) used to solve one of the two Challenges listed in the challenge description.
- The approach should primarily be based on data analytic techniques (e.g. machine learning, Bayesian Neural Networks, etc.) using existing accessible data to derive new information in materials science and engineering.
- A discussion of how this approach and solution compares against the state of the art.
- If the approach identifies a new material composition, material structure, or family of compositions, the solution will be evaluated against the degree to which the predicted and/or demonstrated range of properties provide significant improvement over currently known materials for a specific or variety of industrial applications. An analysis of the ability for or actual demonstration of practical synthesis of the material composition should be addressed in the report.
- If the approach addresses modeling the linkage between at least two elements of material processing, structure, and/or property, a quantitative description of material structure (e.g. microstructure) must be included in the model. The solution will be evaluated against the degree to which the new physical insight solves longstanding gaps in our ability to accurately model material behavior across length and/or temporal scales.
- For either Challenge, the report should address steps taken to validate the solution. The solution will be evaluated against the degree to which commonly accepted means of validation were used (e.g. complementary experimental testing, use of training versus validation data, etc.).
- The new techniques and/or knowledge generated in this work will be evaluated for their likelihood to significantly advance the state-of-the-art in materials science and engineering or provide a path forward for a new industrial product.
- Citation(s) to the accessible data used in solving the Challenge and other relevant literature.
- All materials data used in the challenge must meet the following criteria:
- Accessibility: data must be publically available via the internet. Solvers wishing to use their own materials data for analysis in this challenge must post the data in a data repository that is accessible.
- Provenance: data sources used must have sufficient supporting information (metadata) to enable reuse by researchers outside the original research effort.
- Discoverability: data must be discoverable and citable through a means such as a resolvable Uniform Resource Identifier (URI) or, ideally, a Persistent Identifier (PID).
- The results of the approach must not have been previously publically presented nor published
The awards will be paid to the best submission(s) as solely determined by the review committee. The total payout will be $50,000, with at least one award being no smaller than $25,000 and no award being smaller than $5,000.
In addition to the monetary awards, winning Solvers will be invited to participate (present their research and engage the audience in a question and answer session) in a conference session at Materials Science & Technology 2016, to be held October 24-27, 2016, Salt Lake City, Utah. Travel expenses associated with attending and presenting at the conference will be covered by the Air Force Research Laboratory (AFRL) up to a maximum of $3,000 per submission.
All submitted ideas may be made publicly available (at the AFRL’s discretion) in their entirety, to foster open discussion and evaluation of the content generated by the Challenge.
- To receive an award, the Solvers will not have to transfer their exclusive IP rights to the US Government , instead, they will grant to the US Government non-exclusive license to practice their solutions. Other arrangements might be considered, if a license cannot be granted.
- Submissions to this Challenge must be received by 11:59 PM (US Eastern Time) on 31-Mar-2016. Late submissions will not be considered.
- After the Challenge deadline, the Seeker will complete the review process and make a decision with regard to the Winning Solution(s). All Solvers that submitted a proposal will be notified on the status of their submissions; however, no detailed evaluation of individual submissions will be provided.
Eligibility: Employees of the US Government organizations (U.S. Air Force Research Laboratory, National Institute of Standards and Technology, and the National Science Foundation) may participate in the Challenge and receive Honorable Mention in the MS&T 2016 conference session but are ineligible to receive award money or travel funds to MS&T 2016.