Bo Thomsen, Yuki Nagai, Keita Kobayashi, Ikutaro Hamada, Motoyuki Shiga
{"title":"Self-learning path integral hybrid Monte Carlo with mixed ab initio and machine learning potentials for modeling nuclear quantum effects in water.","authors":"Bo Thomsen, Yuki Nagai, Keita Kobayashi, Ikutaro Hamada, Motoyuki Shiga","doi":"10.1063/5.0230464","DOIUrl":"https://doi.org/10.1063/5.0230464","url":null,"abstract":"<p><p>The introduction of machine learned potentials (MLPs) has greatly expanded the space available for studying Nuclear Quantum Effects computationally with ab initio path integral (PI) accuracy, with the MLPs' promise of an accuracy comparable to that of ab initio at a fraction of the cost. One of the challenges in development of MLPs is the need for a large and diverse training set calculated by ab initio methods. This dataset should ideally cover the entire phase space, while not searching this space using ab initio methods, as this would be counterproductive and generally intractable with respect to computational time. In this paper, we present the self-learning PI hybrid Monte Carlo Method using a mixed ab initio and ML potential (SL-PIHMC-MIX), where the mixed potential allows for the study of larger systems and the extension of the original SL-HMC method [Nagai et al., Phys. Rev. B 102, 041124 (2020)] to PI methods and larger systems. While the MLPs generated by this method can be directly applied to run long-time ML-PIMD simulations, we demonstrate that using PIHMC-MIX with the trained MLPs allows for an exact reproduction of the structure obtained from ab initio PIMD. Specifically, we find that the PIHMC-MIX simulations require only 5000 evaluations of the 32-bead structure, compared to the 100 000 evaluations needed for the ab initio PIMD result.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 20","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142728985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Understanding orientational disorder in crystalline assemblies of hard convex polyhedra.","authors":"Sumitava Kundu, Kaustav Chakraborty, Avisek Das","doi":"10.1063/5.0233373","DOIUrl":"https://doi.org/10.1063/5.0233373","url":null,"abstract":"<p><p>Spontaneous self-assembly of hard convex polyhedra is known to form orientationally disordered crystalline phases, where particle orientations do not follow the same pattern as the positional arrangement of the crystal. A distinct type of orientational phase with discrete rotational mobility has been reported in hard particle systems. In this paper, we present a new analysis method for characterizing the orientational phase of a crystal, which is based on algorithmic detection of unique orientations. Using this method, we collected complete statistics of discrete orientations along the Monte Carlo simulation trajectories and observed that particles were equally partitioned among them, with specific values of pairwise orientational differences. These features remained constant across the pressure range and did not depend on rotational mobility. The discrete mobility was characteristic of a distinct equilibrium thermodynamic phase, qualitatively different from the freely rotating plastic phase with continuous orientations. The high pressure behavior with frozen particle orientations was part of that same description and not a non-equilibrium arrested state. We introduced a precise notion of orientational order and demonstrated that the system was maximally disordered at the level of a unit cell, even though individual particles could only take a few discrete orientations. We report the existence of this phase in five polyhedral shapes and in systematically curated shape families constructed around two of them. The symmetry mismatch between the particle and the crystallographic point groups was found to be a predictive indicator for the occurrence of this phase.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 20","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142729008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andres Lizano-Villalobos, Benjamin Namikas, Xun Tang
{"title":"Siamese neural network improves the performance of a convolutional neural network in colloidal self-assembly state classification.","authors":"Andres Lizano-Villalobos, Benjamin Namikas, Xun Tang","doi":"10.1063/5.0244337","DOIUrl":"https://doi.org/10.1063/5.0244337","url":null,"abstract":"<p><p>Identifying the state of the colloidal self-assembly process is critical to monitoring and controlling the system into desired configurations. Recent application of convolutional neural networks with unsupervised clustering has shown a comparable performance to conventional approaches, in representing and classifying the states of a simulated 2D colloidal batch assembly system. Despite the early success, capturing the subtle differences among similar configurations still presents a challenge. To address this issue, we leverage a Siamese neural network to improve the accuracy of the state classification. Results from a Brownian dynamics-simulated electric field-mediated colloidal self-assembly system and a magnetic field-mediated colloidal self-assembly system demonstrate significant improvement from the original convolutional neural network-based approach. We anticipate the proposed improvement to further pave the way for automated monitoring and control of colloidal self-assembly processes in real time and real space.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 20","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142716177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marco Marchetta, Chiara Morassut, Julien Toulouse, Emanuele Coccia, Eleonora Luppi
{"title":"Time-dependent ab initio molecular-orbital decomposition for high-harmonic generation spectroscopy.","authors":"Marco Marchetta, Chiara Morassut, Julien Toulouse, Emanuele Coccia, Eleonora Luppi","doi":"10.1063/5.0235179","DOIUrl":"https://doi.org/10.1063/5.0235179","url":null,"abstract":"<p><p>We propose a real-time time-dependent ab initio approach within a configuration-interaction-singles ansatz to decompose the high-harmonic generation (HHG) signal of molecules in terms of individual molecular-orbital (MO) contributions. Calculations have been performed by propagating the time-dependent Schrödinger equation with complex energies, in order to account for ionization of the system, and by using tailored Gaussian basis sets for high-energy and continuum states. We have studied the strong-field electron dynamics and the HHG spectra in aligned CO2 and H2O molecules. Contribution from MOs in the strong-field dynamics depends on the interplay between the MO ionization energy and the coupling between the MO and the laser-pulse symmetries. Such contributions characterize different portions of the HHG spectrum, indicating that the orbital decomposition encodes nontrivial information on the modulation of the strong-field dynamics. Our results correctly reproduce the MO contributions to HHG for CO2 as described in the literature experimental and theoretical data and lead to an original analysis of the role of the highest occupied molecular orbitals HOMO, HOMO-1, and HOMO-2 of H2O according to the polarization direction of the laser pulse.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 20","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142728990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A reaction network model of microscale liquid-liquid phase separation reveals effects of spatial dimension.","authors":"Jinyoung Kim, Sean D Lawley, Jinsu Kim","doi":"10.1063/5.0235456","DOIUrl":"https://doi.org/10.1063/5.0235456","url":null,"abstract":"<p><p>Proteins can form droplets via liquid-liquid phase separation (LLPS) in cells. Recent experiments demonstrate that LLPS is qualitatively different on two-dimensional (2D) surfaces compared to three-dimensional (3D) solutions. In this paper, we use mathematical modeling to investigate the causes of the discrepancies between LLPS in 2D and 3D. We model the number of proteins and droplets inducing LLPS by continuous-time Markov chains and use chemical reaction network theory to analyze the model. To reflect the influence of space dimension, droplet formation and dissociation rates are determined using the first hitting times of diffusing proteins. We first show that our stochastic model reproduces the appropriate phase diagram and is consistent with the relevant thermodynamic constraints. After further analyzing the model, we find that it predicts that the space dimension induces qualitatively different features of LLPS, which are consistent with recent experiments. While it has been claimed that the differences between 2D and 3D LLPS stem mainly from different diffusion coefficients, our analysis is independent of the diffusion coefficients of the proteins since we use the stationary model behavior. Our results thus give new hypotheses about how space dimension affects LLPS.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 20","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142728956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Helical-photon-dressed states determining unidirectional π-electron rotations in aromatic ring molecules.","authors":"Hirobumi Mineo, Quang Huy Ho, Ngoc Loan Phan, Gap-Sue Kim, Yuichi Fujimura","doi":"10.1063/5.0215065","DOIUrl":"https://doi.org/10.1063/5.0215065","url":null,"abstract":"<p><p>We theoretically demonstrated that helical-photon-dressed states determine the rotational directions of the π-electrons of aromatic ring molecules formed by a circularly polarized or an elliptically polarized laser. This theory was verified using a minimal three-electronic-state model under the frozen nuclei condition. The model consists of the ground state and either a doubly degenerate electronic excited state or two quasi-degenerate excited states. Three helical-photon-dressed states were derived by solving the time-dependent Schrödinger equation within the semi-classical treatment of light-molecule interactions and rotating wave approximation. The angular momenta of the two helical-photon-dressed states represent the classical rotational direction, and that of the remaining state represents the opposite rotation, that is, non-classical rotation. Classical rotation means that π-electrons have the same rotational direction as that of a given helical electric field vector and obeys the classical equations of motion. Non-classical rotation indicates that the rotational direction is opposite to that of the helical electric field vector. Non-classical rotation is forbidden in an aromatic ring molecule with high symmetry formed by a circularly polarized laser but is allowed in a low symmetric aromatic ring molecule. The sum of the angular momenta of the three dressed states is zero. This is called the sum law for the angular momentum components in this paper. Benzene (D6h) and toluene (CS) were adopted as typical aromatic ring molecules of high and low symmetries, respectively. Finally, considering the effects of nuclear vibrations in the adiabatic approximation, an expression for the π-electron angular momentum was derived and applied to toluene.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 19","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142681913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Second harmonic generation null angle polarization analysis for determining interfacial potential at charged interfaces.","authors":"Celestine C Egemba, Paul E Ohno","doi":"10.1063/5.0231408","DOIUrl":"https://doi.org/10.1063/5.0231408","url":null,"abstract":"<p><p>Methods of quantifying the electrostatics of charged interfaces are important in a range of research areas. The surface-selective nonlinear optical technique second harmonic generation (SHG) is a sensitive probe of interfacial electrostatics. Recent work has shown that detection of the SHG phase in addition to its amplitude enables direct quantification of the interfacial potential. However, the experimental challenge of directly detecting the phase interferometrically with sufficient precision and stability has led to the proposal and development of alternative techniques to recover the same information, notably through wavelength scanning or angle scanning, each of which has their own associated experimental challenges. Here, we propose a new polarization-based approach to recover the required phase information, building upon the previously established nonlinear optical null ellipsometry (NONE) technique. Although NONE directly returns only relative phase information between different tensor elements of the second-order susceptibility, it is shown that a symmetry relation that connects the tensor elements of the potential-dependent third-order susceptibility can be used to generate the absolute phase reference required to calculate the interfacial potential. The sensitivity of the technique to potential at varying surface charge densities and ionic strengths is explored by means of simulated data of the silica:water interface. The error associated with the use of the linearized Poisson-Boltzmann approximation is discussed and compared to the error associated with the precision of the measured NONE null angles. Overall, the results suggest that NONE is a promising approach for performing phase-resolved SHG based quantification of interfacial potentials that experimentally requires only the addition of standard polarization optics to the basic single-wavelength, fixed-angle SHG apparatus.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 19","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142681942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Single parameter aging and density scaling.","authors":"Tina Hecksher, Kristine Niss","doi":"10.1063/5.0234620","DOIUrl":"https://doi.org/10.1063/5.0234620","url":null,"abstract":"<p><p>In a recent paper, Di Lisio et al. [J. Chem. Phys. 159, 064505 (2023)] analyzed a series of temperature down-jumps using the single-parameter aging (SPA) ansatz combined with a specific assumption about density scaling in the out-of-equilibrium system and did not find a good prediction for the largest down-jumps. In this paper, we show that SPA in its original form does work for all their data, including large jumps of ΔT > 20 K. Furthermore, we discuss different approaches to the extension of the density scaling concept to out-of-equilibrium systems.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 19","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142675946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Is the mechanism of \"fast sound\" the same in liquids with long-range interactions and disparate mass metallic alloys?","authors":"Taras Bryk, Ari Paavo Seitsonen, Giancarlo Ruocco","doi":"10.1063/5.0239921","DOIUrl":"10.1063/5.0239921","url":null,"abstract":"<p><p>We present ab initio simulations of a large system of 2400 particles of molten NaCl to investigate the behavior of collective mode dispersion beyond the hydrodynamic regime. In particular, we aim to explain the unusually strong increase in the apparent speed of sound with wave number, which significantly exceeds the typical positive sound dispersion of 10%-25% observed in simple liquids. We compare dispersions of \"bare\" acoustic and optic modes in NaCl with ab initio simulations of other ionic melts such as CuCl and LiBr, metallic liquid alloys such as Pb44Bi56 and Li4Tl, and the regular Lennard-Jones KrAr liquid simulated by classical molecular dynamics. Analytical expressions for the \"bare\" acoustic and optic branches of collective excitations help us to identify the impact of the high-frequency optic branch on the emergence of \"fast sound\" in binary melts. Our findings show that in ionic melts, the high-frequency speed of sound is much larger than in the simple Lennard-Jones liquids and metallic melts, leading to an observed strong viscoelastic increase in the apparent speed of sound-more than double its adiabatic value.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 19","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Transferable performance of machine learning potentials across graphene-water systems of different sizes: Insights from numerical metrics and physical characteristics.","authors":"Dongfei Liu, Jianzhong Wu, Diannan Lu","doi":"10.1063/5.0233395","DOIUrl":"10.1063/5.0233395","url":null,"abstract":"<p><p>Machine learning potentials (MLPs) are promising for various chemical systems, but their complexity and lack of physical interpretability challenge their broad applicability. This study evaluates the transferability of the deep potential (DP) and neural equivariant interatomic potential (NequIP) models for graphene-water systems using numerical metrics and physical characteristics. We found that the data quality from density functional theory calculations significantly influences MLP predictive accuracy. Prediction errors in transferring systems reveal the particularities of quantum chemical calculations on the heterogeneous graphene-water systems. Even for supercells with non-planar graphene carbon atoms, k-point mesh is necessary to obtain accurate results. In contrast, gamma-point calculations are sufficiently accurate for water molecules. In addition, we performed molecular dynamics (MD) simulations using these two models and compared the physical features such as atomic density profiles, radial distribution functions, and self-diffusion coefficients. It was found that although the NequIP model has higher accuracy than the DP model, the differences in the above physical features between them were not significant. Considering the stochasticity and complexity inherent in simulations, as well as the statistical averaging of physical characteristics, this motivates us to explore the meaning of accurately predicting atomic force in aligning the physical characteristics evolved by MD simulations with the actual physical features.</p>","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"161 19","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142667483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}