Stochastic chiral symmetry breaking process besides the deterministic one

Literature Information

Publication Date 2017-10-12
DOI 10.1039/C7CP04674J
Impact Factor 3.676
Authors

L. Silva-Dias, A. López-Castillo


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Abstract

In chiral symmetry breaking, populations with initial enantiomeric excess (EE) are probabilistically favored if statistical fluctuation is present, as in nature. Stochastic methods correctly describe chiral symmetry breaking by taking into account the quantitative enantiomeric difference (excess or deficiency) and the statistical fluctuation amplitude, which is inversely proportional to the absolute size of the populations involved. From this, we obtain a law, which indicates that such a favoring probability decreases exponentially [P(EE) = 1/(eαEE + 1)] with an initial enantiomeric deficiency mediated by statistical fluctuation. Obviously, chiral symmetry breaking equally favors populations without enantiomeric excess [P(0) = 1/2]. However, if deterministic methods are considered, chiral symmetry breaking will strictly favor the population with an initial enantiomeric excess (EE). To study these stochastic chiral symmetry breaking processes the autocatalytic Frank model was considered. Summarizing, our results show that the initial enantiomeric excesses are not entirely responsible for the final state configuration of autocatalytic finite systems.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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