A materials data framework and dataset for elastomeric foam impact mitigating materials

Area of Science:

• Materials Science
• Mechanical Engineering
• Biomechanics

Background:

• Limited availability of open datasets for impact-mitigating materials, particularly foams used in protective gear.
• Existing data often focuses on application-level performance (e.g., helmet impacts) rather than constituent material behavior.
• Understanding the structure-property relationships of foams is critical for designing effective impact protection.

Purpose of the Study:

• To introduce a new FAIR (findable, accessible, interoperable, reusable) data framework for impact protection foams.
• To provide comprehensive structural and mechanical response data for an example elastic impact protection foam.
• To facilitate advanced modeling and design of foam materials for impact mitigation.

Main Methods:

• Micro-computed tomography for structural imaging.
• Finite deformation mechanical testing with full-field strain and displacement measurement.
• Dynamic mechanical analysis to determine visco-thermo-elastic properties.

Main Results:

• A structured dataset encompassing foam microstructure, mechanical response under finite deformation, and dynamic visco-thermo-elastic properties.
• Demonstration of the data framework's utility for characterizing rate and temperature-sensitive foam behavior.
• Implementation of the data framework using services from the Materials Data Facility.

Conclusions:

• The developed FAIR data framework addresses the critical need for accessible materials data in impact protection.
• The comprehensive dataset enables improved modeling techniques such as homogenization and direct numerical simulation.
• This initiative supports advancements in the design and development of next-generation protective materials.