A path integral ground state (PIGS) approach for the simulation of asymmetric top rotors is presented. The method is based on Monte Carlo sampling of angular degrees of freedom. A symmetry-adapted rotational density matrix is used to account for nuclear spin statistics. To illustrate the method, ground-state properties of collections of para-water molecules confined to a one-dimensional lattice are computed. Those include energetic and structural observables. An advantage of the PIGS method is that expectation values can be obtained directly since the square of the wavefunction is sampled during a simulation. To benchmark the method, ground state energies and orientational distributions are computed using exact diagonalization for a single para-water molecule in an external field using a finite basis of symmetric top eigenfunctions. Benchmark results are also provided for N = 2 para-water molecules pinned to lattice sites at various distances to sample the crossover from hydrogen bonding to the dipole-dipole interaction regime. Excellent agreement between the PIGS results and the finite basis set calculations is observed. A thorough analysis of the convergence in terms of the imaginary time propagation length and systematic Trotter error is performed. The PIGS approach is then applied to a chain of N = 11 water molecules, and an equation of state is constructed in terms of the intermolecular separation. Ordering effects are also studied, and a transition between hydrogen bonding to dipole-dipole alignment is observed. The method is scalable and can also be applied in higher dimensions.
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http://dx.doi.org/10.1063/5.0053051 | DOI Listing |
Phys Chem Chem Phys
January 2025
Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, Hubei Key Laboratory of Materials Chemistry and Service Failure, Hubei Key Laboratory of Bioinorganic Chemistry and Materia Medica, Hubei Engineering Research Center for Biomaterials and Medical Protective Materials, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
A full-scale structural search was performed using density functional theory calculations and a universal structural prediction evolutionary algorithm. This produced a lowest energy two-dimensional (2D) CoB structure. The CoB-1 global minimum structure has unusual inverse double sandwich features.
View Article and Find Full Text PDFBackground: Running-related overuse injuries are common among recreational runners; however, there is currently little prospective research investigating the role of running characteristics on overuse injury development.
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Study Design: Cohort study; Level of evidence, 2.
ACS Catal
January 2025
Department of Pure and Applied Chemistry, University of Strathclyde, 295 Cathedral Street, Glasgow G1 1XL, United Kingdom.
An aryl radical assay is used to provide information about the formation of aryl radicals from aryl halides in coupling reactions to arenes in the presence of palladium sources and under LED irradiation (λ = 456 nm). The assay uses 2-halo--xylenes as substrates. Aryl radical formation is indicated both by a defined product composition and by signature deuterium isotope effects.
View Article and Find Full Text PDFFront Oncol
January 2025
Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Background: The carcinogenesis mechanism of early-stage lung cancer (ESLC) remains unclear. Microbial dysbiosis is closely related to tumor development. This study aimed to analyze the relationship between microbiota dysbiosis in ESLC.
View Article and Find Full Text PDFQuant Imaging Med Surg
January 2025
Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China.
Fatty acid can potentially serve as biomarker for evaluating metabolic disorder and inflammation condition, and quantifying the double bonds is the key for revealing fatty acid information. This study presents an assessment of a deep learning approach utilizing deep image prior (DIP) for the quantification of double bonds and methylene-interrupted double bonds of triglyceride derived from chemical-shift encoded multi-echo gradient echo images, all achieved without the necessity for network training. The methodology implemented a cost function grounded in signal constraints to continually refine the neural network's parameters on a single slice of images through iterative processes.
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