Si₂C₅H₂ isomers - search algorithms versus chemical intuition

Area of Science:

• Computational Chemistry
• Theoretical Chemistry
• Materials Science

Background:

• Identifying novel molecular geometries is crucial for advancing chemical and materials science.
• Automated search algorithms are increasingly used, but their completeness is often questioned.
• The silicon-carbon compound Si2C5H2 serves as a test case for evaluating search strategies.

Purpose of the Study:

• To compare the efficacy of automated search algorithms versus human chemical intuition in identifying new molecular isomers.
• To evaluate the limitations of current search algorithms in exploring the potential energy surface for Si2C5H2.
• To provide theoretical data that may guide future experimental synthesis and characterization of Si2C5H2 isomers.

Main Methods:

• Utilized computational chemistry methods, including DFT (PBE0/def2-TZVP, B3LYP/6-311++G(2d,2p)) and coupled-cluster theory (CCSD(T)/def2-TZVP, CCSD(T)/cc-pVTZ).
• Employed 'coalescence kick' and 'cuckoo' search algorithms to identify low-energy isomers.
• Applied chemical intuition to propose alternative isomers within a defined energy range (30 kcal mol-1).

Main Results:

• Search algorithms predicted only four Si2C5H2 isomers within 30 kcal mol-1.
• Chemical intuition identified fourteen isomers within the same energy threshold.
• High-level calculations confirmed that at least seven isomers predicted by intuition were missed by the algorithms.
• All eighteen isomers, including the most stable one with a planar tetracoordinate carbon, remain experimentally undiscovered.

Conclusions:

• Automated search algorithms alone are insufficient for comprehensive isomer discovery.
• Chemical intuition remains a valuable tool, complementing algorithmic approaches in theoretical chemistry.
• The predicted structural and spectroscopic data may facilitate future experimental validation of these novel Si2C5H2 isomers.