Computational design of patterned interfaces using reduced order models.

Area of Science:

• Materials Science
• Solid-State Physics
• Computational Materials Design

Background:

• Patterning is established for surface functionalization.
• Interfaces in crystalline solids contain misfit dislocations that dictate properties.
• Existing methods for interface structure prediction are computationally intensive.

Purpose of the Study:

• To extend the patterning concept to interfaces between crystalline solids.
• To develop a computational strategy for designing interfaces with controlled misfit dislocation patterns.
• To enable the design of interfaces with specific functionalities, such as enhanced diffusion.

Main Methods:

• Developed a computational strategy for designing patterned interfaces.
• Utilized tailoring of interface crystallography and composition to control misfit dislocations.
• Employed an efficient reduced order model based on anisotropic elasticity theory for interface structure prediction.
• Incorporated interface synthesis as a constraint in the design process.

Main Results:

• Validated a computational strategy for designing controlled misfit dislocation patterns at interfaces.
• Successfully predicted interface structures using an efficient reduced order model, avoiding resource-intensive atomistic simulations.
• Demonstrated the application of the approach to design interfaces with rapid, one-dimensional point defect diffusion.

Conclusions:

• Patterned interfaces offer a pathway to novel functionalities in crystalline solids.
• The developed computational strategy provides an efficient and versatile tool for designing advanced interfaces.
• Patterned interfaces hold potential for integration into composite materials to significantly improve performance.