Systematic control of experimental inconsistency in combinatorial materials science

Area of Science:

• Materials Science
• Chemical Engineering
• Computational Chemistry

Background:

• High-throughput combinatorial experiments often suffer from experimental inconsistency, a critical issue impacting reproducibility and reliability.
• This problem significantly hinders the discovery of novel materials with desired properties.

Purpose of the Study:

• To develop a systematic method for controlling experimental inconsistency in high-throughput combinatorial materials science.
• To simultaneously optimize material properties and minimize experimental inconsistency.
• To discover novel phosphors with enhanced photoluminescence (PL) intensity and reproducibility.

Main Methods:

• A multiobjective evolutionary optimization-assisted combinatorial materials search (MOEO combinatorial material search) strategy was employed.
• Experimental inconsistency and material property (photoluminescence intensity) were treated as dual objective functions for simultaneous optimization.
• A tetravalent manganese-doped alkali earth germanium/titanium oxide system served as the model system for screening.

Main Results:

• The MOEO combinatorial material search successfully minimized experimental inconsistency while maximizing PL intensity.
• A novel halide-detached deep red phosphor was identified through the MOEO reiteration process.
• The discovered phosphor exhibits improved PL intensity and reliable reproducibility.

Conclusions:

• The developed MOEO strategy offers a robust solution for addressing experimental inconsistency in combinatorial materials discovery.
• This method facilitates the identification of high-performance materials with consistent and reproducible properties.
• The findings pave the way for more efficient and reliable materials development in high-throughput settings.