Deciphering High-Order Structural Correlations within Fluxional Molecules from Classical and Quantum Configurational...

Area of Science:

• Computational Chemistry
• Chemical Physics
• Molecular Dynamics

Background:

• Fluxional molecules exhibit complex structural dynamics.
• Understanding high-order correlations is crucial for molecular behavior.
• Protonated acetylene serves as a model for large-amplitude motion.

Purpose of the Study:

• To apply a parameter-free, entropy-based method to decode high-order structural correlations.
• To investigate the temperature dependence and impact of nuclear quantum effects on these correlations.
• To analyze the transition from quantum to classical descriptions of molecular correlations.

Main Methods:

• Utilized the kth nearest-neighbor estimator of configurational entropy.
• Employed machine learning techniques with high-dimensional neural network potential energy surfaces.
• Exhaustively sampled classical and quantum ensembles of protonated acetylene.

Main Results:

• High-order correlations are significant in fluxional molecules beyond simple bivariate analysis.
• Quantum delocalization and zero-point vibrations substantially reduce correlations at low temperatures.
• A quantum-to-classical crossover regime was identified between 100-800 K, with quantitative agreement only above 1000 K.

Conclusions:

• The developed entropy-based method effectively reveals complex many-body correlations.
• Nuclear quantum effects play a critical role in molecular correlations at low temperatures.
• The findings provide insights transferable to other molecular systems and experimental analyses.