Mechanisms for the spontaneous transformation of achiral chemical systems into states of enantiomeric purity have important ramifications in modern pharmacology and potential relevance to the origins of homochirality in life on Earth. Such mechanisms for enantiopurification are needed for production of chiral pharmaceuticals and other bioactive compounds. Previously proposed chemical mechanisms leading from achiral systems to near homochirality are initiated by a symmetry-breaking step resulting in a minor excess of one enantiomer via statistical fluctuations in enantiomer concentrations. Subsequent irreversible processes then amplify the majority enantiomer concentration while simultaneously suppressing minority enantiomer production. Herein, equilibrium adsorption of amino acid enantiomer mixtures onto chiral and achiral surfaces reveals amplification of surface enantiomeric excess relative to the gas phase; i. e. enantiopurification of chiral adsorbates by adsorption. This adsorption-induced amplification of enantiomeric excess is shown to be well-describe by the 2D Ising model. More importantly, the 2D-Ising model predicts formation of homochiral monolayers from adsorption of racemic mixtures or prochiral molecules on achiral surfaces; i. e. enantiopurification with no apparent chiral driving force.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/cphc.202000881 | DOI Listing |
J Phys Chem B
December 2024
Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States.
Machine learning methods have been important in the study of phase transitions. Unsupervised methods are particularly attractive because they do not require prior knowledge of the existence of a phase transition. In this work we focus on the constant magnetization Ising model in two (2D) and three (3D) dimensions.
View Article and Find Full Text PDFJ Chem Phys
December 2024
Institute for Physical Science and Technology, Biophysics Program, University of Maryland, College Park, Maryland 20742, USA.
Clustering is a type of machine learning technique, which is used to group huge amounts of data based on their similarity into separate groups or clusters. Clustering is a very important task that is nowadays used to analyze the huge and diverse amount of data coming out of molecular dynamics (MD) simulations. Typically, the data from the MD simulations in terms of their various frames in the trajectory are clustered into different groups and a representative element from each group is studied separately.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Institut für Theoretische Physik, Universität Leipzig, IPF 231101, 04081 Leipzig, Germany.
We investigate the aging properties of phase-separation kinetics following quenches from T=∞ to a finite temperature below T_{c} of the paradigmatic two-dimensional conserved Ising model with power-law decaying long-range interactions ∼r^{-(2+σ)}. Physical aging with a power-law decay of the two-time autocorrelation function C(t,t_{w})∼(t/t_{w})^{-λ/z} is observed, displaying a complex dependence of the autocorrelation exponent λ on σ. A value of λ=3.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences, University of Science and Technology of China, Hefei 230026, China.
Optical simulators for the Ising model have demonstrated great promise for solving challenging problems in physics and beyond. Here, we develop a spatial optical simulator for a variety of classical statistical systems, including the clock, XY, Potts, and Heisenberg models, utilizing a digital micromirror device composed of a large number of tiny mirrors. Spins, with desired amplitudes or phases of the statistical models, are precisely encoded by a patch of mirrors with a superpixel approach.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455, USA.
The crystallographic restriction theorem constrains two-dimensional nematicity to display either Ising (Z_{2}) or three-state-Potts (Z_{3}) critical behaviors, both of which are dominated by amplitude fluctuations. Here, we use group theory and microscopic modeling to show that this constraint is circumvented in a 30°-twisted hexagonal bilayer due to its emergent quasicrystalline symmetries. We find a critical phase dominated by phase fluctuations of a Z_{6} nematic order parameter and bounded by two Berezinskii-Kosterlitz-Thouless (BKT) transitions, which displays only quasi-long-range nematic order.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!