Computational metrology for materials.

Area of Science:

• Materials Science
• Open Science
• Computational Science

Background:

• Advanced materials development faces hurdles in characterization, modeling, and production.
• Proprietary tools and segregated processes hinder open scientific advancement.
• Reproducibility in materials science is challenged by closed methodologies.

Purpose of the Study:

• To introduce computational metrology by integrating open-source principles into materials science instrumentation.
• To demonstrate how open instrumentation can provide complete computational descriptions for measurement reproducibility.
• To extend this approach for measuring predictive computational models, not just parameters.

Main Methods:

• Applying open-source software and hardware principles to develop novel materials science instrumentation.
• Integrating custom instrumentation with off-the-shelf components to create versatile research tools.
• Developing a Rheoprinter capable of rheological characterization and predictive modeling.

Main Results:

• Successfully developed open instrumentation enabling reproducible measurements with full computational descriptions.
• Demonstrated the extension of computational metrology to measure predictive computational models.
• Created a Rheoprinter that combines 3D printing with rheological characterization capabilities.

Conclusions:

• Computational metrology, leveraging open-source practices, significantly enhances reproducibility and accessibility in materials science.
• The developed open instrumentation and computational metrology framework facilitate the adoption of advanced materials.
• The Rheoprinter serves as a practical example of integrating characterization and modeling for complex materials.