Optimizing the formation of solid solutions with components of different shapes.

Area of Science:

• Materials Science
• Chemical Engineering
• Computational Chemistry

Background:

• Engineering ordered solids from co-assembling, differently shaped building blocks presents a significant challenge.
• Predicting maximal mutual ordered-phase compatibility (MaxOC) requires understanding particle characteristics, particularly entropy disparity and inter-species selectivity.

Purpose of the Study:

• To formulate and validate predictive rules for maximizing mutual ordered-phase compatibility (MaxOC) in co-assembling systems.
• To investigate the role of component size ratios and "substitutional symmetry" in minimizing free-energy costs for ordered solid formation.

Main Methods:

• Utilized Monte Carlo simulations for hard-core mixtures of octahedra and spheres.
• Analyzed previously studied mixtures to validate proposed MaxOC predictive rules.
• Employed molecular simulations to explore the formation of stoichiometric compounds through orientation-dependent attractions.

Main Results:

• Proposed that maximizing "substitutional symmetry" via component size ratios minimizes free-energy costs for ordered phases.
• Found that packing entropy favors substitutionally disordered solid solutions over stoichiometric compounds in hard-core mixtures.
• Demonstrated that orientation-dependent attractions can enable the formation of stoichiometric compounds, aligning with experimental findings.

Conclusions:

• Component size ratio is a key factor in achieving maximal mutual ordered-phase compatibility.
• While entropy favors disorder, specific interactions like orientation-dependent attractions are essential for forming ordered stoichiometric compounds.