Constraint structure optimization to a specific minimum using ionization energy.

Area of Science:

• Computational Chemistry
• Theoretical Chemistry
• Chemical Physics

Background:

• Exploring molecular structures with specific electronic properties is crucial for understanding chemical reactivity.
• Traditional optimization methods may not efficiently target structures based on electronic characteristics like ionization energy.

Purpose of the Study:

• To develop and validate a novel structure optimization method incorporating an ionization energy constraint.
• To demonstrate the method's capability in finding molecular geometries corresponding to predefined ionization energies.

Main Methods:

• A structure optimization approach was developed utilizing the Levine-Coe-Martínez penalty function.
• The penalty function incorporates predefined core-ionization and inner-shell ionization energies.
• The method was tested on diverse chemical systems including S_N2 reactions, platinum complex isomerization, proton transfer, and CO adsorption on Pd clusters.

Main Results:

• The developed method successfully identified targeted energy minima for all tested chemical systems.
• The optimization process yielded structures with ionization energies matching the input constraints.
• Analysis of the objective function's shape and penalty function parameters provided insights into the optimization dynamics.

Conclusions:

• The structure optimization method with an ionization energy constraint is effective for exploring specific electronic states of molecules.
• The study provides a foundation for future work, including automated parameter setting and addressing potential challenges in computational chemistry.
• This approach offers a valuable tool for computational chemists seeking to design or understand molecules with tailored electronic properties.