Journal of Chemical Physics最新文献

The XPS of pyridine: A combined theoretical and experimental analysis.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-28 DOI: 10.1063/5.0249190

Paul S Bagus, Connie J Nelin, Michel Sassi, Daniel Baranowski, Marcus A Sharp, Tom Autrey, Zdenek Dohnálek, Zbynek Novotny

引用次数: 0

Efficient sampling of free energy landscapes with functions in Sobolev spaces.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-28 DOI: 10.1063/5.0221263

Pablo F Zubieta Rico, Gustavo R Pérez-Lemus, Juan J de Pablo

引用次数: 0

Machine learning delta-T noise for temperature bias estimation.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-28 DOI: 10.1063/5.0250879

Matthew Gerry, Jonathan J Wang, Joanna Li, Ofir Shein-Lumbroso, Oren Tal, Dvira Segal

{"title":"Machine learning delta-T noise for temperature bias estimation.","authors":"Matthew Gerry, Jonathan J Wang, Joanna Li, Ofir Shein-Lumbroso, Oren Tal, Dvira Segal","doi":"10.1063/5.0250879","DOIUrl":"https://doi.org/10.1063/5.0250879","url":null,"abstract":"Delta-T shot noise is activated in temperature-biased electronic junctions, down to the atomic scale. It is characterized by a quadratic dependence on the temperature difference and a nonlinear relationship with the transmission coefficients of partially opened conduction channels. In this work, we demonstrate that delta-T noise, measured across an ensemble of atomic-scale junctions, can be utilized to estimate the temperature bias in these systems. Our approach employs a supervised machine learning algorithm to train a neural network, with input features being the scaled electrical conductance, the delta-T noise, and the mean temperature. Due to limited experimental data, we generate synthetic datasets, designed to mimic experiments. The neural network, trained on these synthetic data, was subsequently applied to predict temperature biases from experimental datasets. Using performance metrics, we demonstrate that the mean bias-the deviation of predicted temperature differences from their true value-is less than 1 K for junctions with conductance up to 4G0. Our study highlights that, while a single delta-T noise measurement is insufficient for accurately estimating the applied temperature bias due to noise contributions from other sources, averaging over an ensemble of junctions enables predictions within experimental uncertainties. This suggests that machine learning approaches can be utilized for estimation of temperature biases and similarly other stimuli in electronic junctions.","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"162 8","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143501508","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}

引用次数: 0

Two-component relativistic equation-of-motion coupled cluster for electron ionization.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-28 DOI: 10.1063/5.0248535

Stephen H Yuwono, Run R Li, Tianyuan Zhang, Xiaosong Li, A Eugene DePrince

引用次数: 0

Pulsed discharge jet laser spectroscopy of the stibino (SbH2) free radical: Hyperfine and isotopic structure in the high-resolution electronic spectrum.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-28 DOI: 10.1063/5.0256316

Fumie X Sunahori, Dennis J Clouthier

引用次数: 0

State-to-state integral cross sections for the Cl + CHD3 (vCH = 0,1) → HCl + CD3 reactions.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-21 DOI: 10.1063/5.0256166

Shu Liu, Dong H Zhang

引用次数: 0

Exploring atom-pairwise and many-body dispersion corrections for the BEEF-vdW functional.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-21 DOI: 10.1063/5.0248728

Elisabeth Keller, Volker Blum, Karsten Reuter, Johannes T Margraf

引用次数: 0

Polariton spectra under the collective coupling regime. II. 2D non-linear spectra.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-21 DOI: 10.1063/5.0249705

M Elious Mondal, A Nickolas Vamivakas, Steven T Cundiff, Todd D Krauss, Pengfei Huo

{"title":"Polariton spectra under the collective coupling regime. II. 2D non-linear spectra.","authors":"M Elious Mondal, A Nickolas Vamivakas, Steven T Cundiff, Todd D Krauss, Pengfei Huo","doi":"10.1063/5.0249705","DOIUrl":"https://doi.org/10.1063/5.0249705","url":null,"abstract":"In our previous work [Mondal et al., J. Chem. Phys. 162, 014114 (2025)], we developed several efficient computational approaches to simulate exciton-polariton dynamics described by the Holstein-Tavis-Cummings (HTC) Hamiltonian under the collective coupling regime. Here, we incorporated these strategies into the previously developed Lindblad-partially linearized density matrix (L-PLDM) approach for simulating 2D electronic spectroscopy (2DES) of exciton-polariton under the collective coupling regime. In particular, we apply the efficient quantum dynamics propagation scheme developed in Paper I to both the forward and the backward propagations in the PLDM and develop an efficient importance sampling scheme and graphics processing unit vectorization scheme that allow us to reduce the computational costs from O(K2)O(T3) to O(K)O(T0) for the 2DES simulation, where K is the number of states and T is the number of time steps of propagation. We further simulated the 2DES for an HTC Hamiltonian under the collective coupling regime and analyzed the signal from both rephasing and non-rephasing contributions of the ground state bleaching, excited state emission, and stimulated emission pathways.","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"162 7","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143458174","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}

引用次数: 0

Scattering-based structural inversion of soft materials via Kolmogorov-Arnold networks.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-21 DOI: 10.1063/5.0253877

Chi-Huan Tung, Lijie Ding, Ming-Ching Chang, Guan-Rong Huang, Lionel Porcar, Yangyang Wang, Jan-Michael Y Carrillo, Bobby G Sumpter, Yuya Shinohara, Changwoo Do, Wei-Ren Chen

{"title":"Scattering-based structural inversion of soft materials via Kolmogorov-Arnold networks.","authors":"Chi-Huan Tung, Lijie Ding, Ming-Ching Chang, Guan-Rong Huang, Lionel Porcar, Yangyang Wang, Jan-Michael Y Carrillo, Bobby G Sumpter, Yuya Shinohara, Changwoo Do, Wei-Ren Chen","doi":"10.1063/5.0253877","DOIUrl":"https://doi.org/10.1063/5.0253877","url":null,"abstract":"Small-angle scattering techniques are indispensable tools for probing the structure of soft materials. However, traditional analytical models often face limitations in structural inversion for complex systems, primarily due to the absence of closed-form expressions of scattering functions. To address these challenges, we present a machine learning framework based on the Kolmogorov-Arnold Network (KAN) for directly extracting real-space structural information from scattering spectra in reciprocal space. This model-independent, data-driven approach provides a versatile solution for analyzing intricate configurations in soft matter. By applying the KAN to lyotropic lamellar phases and colloidal suspensions-two representative soft matter systems-we demonstrate its ability to accurately and efficiently resolve structural collectivity and complexity. Our findings highlight the transformative potential of machine learning in enhancing the quantitative analysis of soft materials, paving the way for robust structural inversion across diverse systems.","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"162 7","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143448315","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}

引用次数: 0

A NEMD approach to the melt-front evolution under gravity.

IF 3.1 2区化学

Journal of Chemical Physics Pub Date : 2025-02-21 DOI: 10.1063/5.0242807

Mauro Ferrario, Giovanni Ciccotti, Daniela Mansutti, Antonio DiCarlo

{"title":"A NEMD approach to the melt-front evolution under gravity.","authors":"Mauro Ferrario, Giovanni Ciccotti, Daniela Mansutti, Antonio DiCarlo","doi":"10.1063/5.0242807","DOIUrl":"https://doi.org/10.1063/5.0242807","url":null,"abstract":"Modeling the evolution of the melt front under gravity in the presence of a horizontal thermal gradient is a challenging issue, hitherto tackled exclusively with the concepts and tools of computational continuum thermomechanics, too phenomenologically driven to have satisfactory predictive capabilities. Here, we show that this complex phenomenon is amenable to treatment by the methods and tools of Non-Equilibrium Molecular Dynamics (NEMD). To do so, we addressed all the difficulties caused by the necessity of applying suitable boundary conditions and minimizing surface effects so that the bulk behavior of the system in non-equilibrium conditions can be detected. Sufficient adiabatic separation of the time scales permits us to use macroscopically relatively short-but microscopically long enough-time averages to get the macroscopic bulk behavior of the system accurately. To get an adequate signal-to-noise ratio, we had to use an unphysically large value of the gravity. However, we know from NEMD simulations in transport studies that the phenomena produced are stable over many orders of magnitude. In conclusion, our work proves that molecular simulation can be a good tool to study this family of non-equilibrium phenomena, although further work is needed to achieve quantitative predictive capabilities.","PeriodicalId":15313,"journal":{"name":"Journal of Chemical Physics","volume":"162 7","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143449252","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}

引用次数: 0