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Characterizing Atmospheric Oxidation and Cloud Condensation Nuclei Activity of Polystyrene Nanoplastic Particles
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Condensed-Phase Ethanol Conversion to Higher Alcohols over Bimetallic Catalysts
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Combined First-Principles Calculations of Electron–Electron and Electron–Phonon Self-Energies in Condensed Systems
In this work, we present a method to efficiently combine the computation of electron–electron and electron–phonon self-energies, which enables the evaluation of electron–phonon coupling at the G 0 W 0 level of theory for systems with hundreds of atoms. In addition, our approach, which is a generalization of a method recently proposed for molecules [J. Chem. Theory Comput.2018, 14, 6269–6275], enables the inclusion of nonadiabatic and temperature effects at no additional computational cost. We present results for diamond and defects in diamond and discuss the importance of numerically accurate G 0 W 0 band structures to obtain robust predictions of zero point renormalization (ZPR) of band gaps, and of the inclusion of nonadiabatic effects to accurately compute the ZPR of defect states in the band gap.
Velocity-Gauge Real-Time Time-Dependent Density Functional Tight-Binding for Large-Scale Condensed Matter Systems
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Condensed Phase Water Molecular Multipole Moments from Deep Neural Network Models Trained on Ab Initio Simulation Data
Ionic solvation phenomena in liquids involve intense interactions in the inner solvation shell. For interactions beyond the first shell, the ion–solvent interaction energies result from the sum of many smaller-magnitude contributions that can still include polarization effects. Deep neural network (DNN) methods have recently found wide application in developing efficient molecular models that maintain near-quantum accuracy. In this work, we extend the DeePMD-kit code to produce accurate molecular multipole moments in the bulk and near interfaces. The new method is validated by comparing the DNN moments with those generated by ab initio simulations. The moments are used to compute the electrostatic potential at the center of a molecular-sized hydrophobic cavity in water. The results show that the fields produced by the DNN models are in quantitative agreement with the AIMD-derived values. These efficient methods will open the door to more accurate solvation models for large solutes such as proteins.
Modeling Absolute Redox Potentials of Ferrocene in the Condensed Phase
Absolute thermodynamic quantities for critical chemical reactions are needed to determine the role of solvents and reactive environments in catalysis and electrocatalysis beyond the relative scales typically employed. In principle, theoretical methods can provide such quantification but are often hindered by the innate complexity of strong electron correlation and dynamic relaxation of solvent environments. Here, we present and validate a protocol for calculating the redox potentials of ferrocene/ferrocenium redox pair in the acetonitrile. Equation-of-motion ionization potential coupled-cluster single-double (EOM-IP-CCSD) and effective fragment potential (EFP) methods are used to characterize the adiabatic and vertical ionization potentials (IP) as well as the electron affinity processes. We benchmark molecular mechanics against the EFP model to show the differences in ferrocene electronic polarizability in two redox states. Our best estimate of the redox potential (4.94 eV) agrees well with the experimental value (4.93 eV). This demonstrated the ability of modern computational methods to predict absolute redox potentials quantitatively and, more critically, quantify the correlation of dynamic effects, which underlie their origin.
Synthesis of Long Chain Oxygenates via Aldol Condensation of Furfural and Acetone over Metal–Organic Frameworks
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Condensed Layer Deposition of Nanoscopic TiO 2 Overlayers on High-Surface-Area Electrocatalysts
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Structural Basis for Enzymatic Off-Loading of Hybrid Polyketides by Dieckmann Condensation
Abstract not provided
Plug-and-Play Molecular Approach for Room Temperature Polariton Condensation
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Structure and Function of a Dehydrating Condensation Domain in Nonribosomal Peptide Biosynthesis
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Impact of Anthropogenic Aerosol Transport on Cloud Condensation Nuclei Activity During Summertime in Qilian Mountain, in the Northern Tibetan Plateau
Here in this study, we conducted field campaigns at two mountain-top observatories on the Qilian Mountains (QLM) in the northeastern Tibetan Plateau of China, which plays a vital role in sustaining water resources for the downstream arid and semi-arid regions. The two observatories, Waliguan Baseline Observatory (WLG) and Laohugou station (LHG), are situated on the eastern and western edge of the QLM, respectively. The objectives of this study were to examine the properties of atmospheric aerosols, CCN concentrations (NCCN) at varying supersaturation levels (SS = 0.2%–1.0%), and the hygroscopic nature of aerosols in the QLM, especially during the formation of orographic cloud. Notably, the average aerosol concentration and N CCN was approximately 2–3 factors higher at WLG compared to LHG. The chemical compositions of aerosols were primarily dominated by sulfate and organic aerosol (OA) at these two sites. A very high hygroscopicity parameter of aerosol calculated using chemical composition was observed at these two sites (0.37 ± 0.03 at LHG vs. 0.30 ± 0.04 at WLG). Enhanced aerosol loading episodes impacted by anthropogenic emission were observed at these two sites. Exploration on high-loading cases at each site, we found that the CCN activity was dominated by aerosol size, but the chemical processes of aerosol during the formation of orographic cloud could also be important in CCN activity, especially for low SS conditions. These findings collectively underscore the significant impact of anthropogenic air plumes on CCN concentrations in the QLM and their potential influence on precipitation patterns.