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At least 271 records · Page 15

Understanding and Predicting the Spatially Resolved Adsorption Properties of Nanoporous Materials

Using knowledge from statistical thermodynamics and crystallography, we develop an image–image translation model, called SorbIIT, that uses three-dimensional grids of adsorbate–adsorbent interaction energies as input to predict the spatially resolved loading surface of nanoporous materials over a broad range of temperatures and pressures. SorbIIT consists of a closed-form differential model for loading-surface prediction and a U-Net to generate spatial differential distributions from the energy grids. SorbIIT is trained using the energy grids and adsorbate distributions (obtained from high-throughput simulations) of 50 synthesized and 70 hypothetical zeolites and applied for predicting the adsorption of carbon dioxide, hydrogen sulfide, n-butane, 2-methylpropane, krypton, and xenon in other zeolites from 256 to 400 K. In conclusion, employing a quadratic isotherm model for the local differentiation, SorbIIT yields mean R 2 values of 0.998 for total adsorption and 0.6904 for local adsorption with a resolution of 0.2 Å, and a value of 0.721 for the structural similarity of the local loading distribution.

Sun, Yangzesheng↗

The Localized Active Space Method with Unitary Selective Coupled Cluster

Here, we introduce a hybrid quantum-classical algorithm, the localized active space unitary selective coupled cluster singles and doubles (LAS-USCCSD) method. Derived from the localized active space unitary coupled cluster (LAS-UCCSD) method, LAS-USCCSD first performs a classical LASSCF calculation, then selectively identifies the most important parameters (cluster amplitudes used to build the multireference UCC ansatz) for restoring interfragment interaction energy using this reduced set of parameters with the variational quantum eigensolver method. We benchmark LAS-USCCSD against LAS-UCCSD by calculating the total energies of (H 2 ) 2 , (H 2 ) 4 , and trans-butadiene, and the magnetic coupling constant for a bimetallic compound [Cr 2 (OH) 3 (NH 3 ) 6 ] 3+ . For these systems, we find that LAS-USCCSD reduces the number of required parameters and thus the circuit depth by at least 1 order of magnitude, an aspect which is important for the practical implementation of multireference hybrid quantum-classical algorithms like LAS-UCCSD on near-term quantum computers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

pyEF: A Python Framework for QM and QM/MM Atom-Wise Electric Field Analysis

We introduce pyEF, a software package for computing molecular electric fields, electrostatic interaction energies, and electrostatic potentials from quantum mechanical (QM) atom-centered multipole expansions with atom-wise decomposable contributions. We demonstrate the computational efficiency and accuracy of this QM-derived electric field evaluation tool through several tests. To assess the influence of the underlying QM method and charge partitioning scheme on these electrostatic quantities, we analyze over 250 configurations of an acetone solute molecule in five solvents of variable polarity. We find that electric field calculations are highly sensitive to the choice of charge partitioning method. Even among real-space charge schemes, acetone Stark tuning rates differ by up to a factor of 2. Benchmarking computed solvent dipole moments against experimental bulk values, we conclude that the CM5, ADCH, and Hirshfeld-I charge schemes most reliably capture solvent electrostatics and therefore provide a more faithful foundation for computing electric fields. When constructed from these real-space charges, electric fields are nearly insensitive to basis set size and monotonically increase in magnitude with higher Fock exchange. We also demonstrate efficient convergence of QM electrostatics when more distant molecules are represented solely by MM point charges, reducing computational overhead. Leveraging these findings, we demonstrate the use of pyEF to deduce environmental effects on a transition metal complex from a Ga 4 L 6 12– nanocage and quantify the dominant role of organic linkers in orchestrating electrostatic preorganization.

electric fields↗

Reaction Profiles and Kinetics for Radical–Radical Hydrogen Abstraction via Multireference Coupled Cluster Theory

Radical-radical abstractions in hydrocarbon oxidation chemistry are disproportionation reactions that are generally exothermic with little or no barrier yet are underappreciated and poorly studied. Such challenging multireference electronic structure problems are tackled here using the recently developed state-specific multireference coupled cluster methods Mk-MRCCSD and Mk-MRCCSD(T), as well as the companion perturbation theory Mk-MRPT2 and the established MRCISD, MRCISD+Q, and CASPT2 approaches. Reaction paths are investigated for five prototypes involving radical-radical hydrogen abstraction: H + BeH → H 2 + Be, H + NH 2 → H 2 + NH, CH 3 + C 2 H 5 → CH 4 + C 2 H 4 , H + C2H 5 → H 2 + C 2 H 4 , and H + HCO → H 2 + CO. Full configuration interaction (FCI) benchmark computations for the H + BeH, H + NH 2 , and H + HCO reactions prove that Mk-MRCCSD(T) provides superior accuracy for the interaction energies in the entrance channel, with mean absolute errors less than 0.3 kcal mol(-1) and percentage deviations less than 10% over the fragment separations of relevance to kinetics. To facilitate combustion studies, energetics for the CH 3 + C 2 H 5 , H + C 2 H 5 , and H + HCO reactions were computed at each level of theory with correlation-consistent basis sets (cc-pVXZ, X = T, Q 5) and extrapolated to the complete basis set (CBS) limit. These CBS energies were coupled with CASPT2 projected vibrational frequencies along a minimum energy path to obtain rate constants for these three reactions. The rigorous Mk-MRCCSD(T)/CBS results demonstrate unequivocally that these three reactions proceed with no barrier in the entrance channel, contrary to some earlier predictions. Mk-MRCCSD(T) also reveals that the economical CASPT2 method performs well for large interfragment separations but may deteriorate substantially at shorter distances.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Charge Transfer and Spin Dynamics in a Zinc Porphyrin Donor Covalently Linked to One or Two Naphthalenediimide Acceptors

We report quantum coherence effects on charge transfer and spin dynamics in a system having two degenerate electron acceptors are studied using a zinc 5,10,15-tri(n-pentyI)-20-phenylporphyrin (ZnP) electron donor covalently linked to either one or two naphthalene-1,8:4,5-bis(dicarboximide) (NDI) electron acceptors using an anthracene (An) spacer, ZnP-An-NDI (1) and ZnP-An-NDI 2 (2), respectively. Following photoexcitation of 1 and 2 in toluene at 295 K, femtosecond transient absorption spectroscopy shows that the electron transfer (ET) rate constant for 2 is about three times larger than that of 1, which can be accounted for by the statistical nature of incoherent ET as well as the electron couplings for the charge separation reactions. In contrast, the rate constant for charge recombination (CR) of 1 is about 25% faster than that of 2. Using femtosecond transient infrared spectroscopy and theoretical analysis, we find that the electron on NDI 2 ∙- in 2 localizes onto one of the two NDIs prior to CR, thus precluding electronically coherent CR from NDI 2 ∙- . Conversely, CR in both 1 and 2 is spin coherent as indicated by the observation of a resonance in the 3* ZnP yield following CR as a function of applied magnetic field, giving spin-spin exchange interaction energies of 2J = 210 and 236 mT, respectively, where the line width of the resonance for 2 is greater than 1. These data show that while CR is a spin-coherent process, incoherent hopping of the electron between the two NDIs in 2, consistent with the lack of delocalization noted above, results in greater spin decoherence in 2 relative to 1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Flexibility in Molecular Simulations of Carbon Dioxide Adsorption and Diffusion in a Cuprous Triazolate Framework

Using fixed atom force fields to model gas adsorption in flexible metal organic frameworks (MOFs) is known to pose difficulties in accurately reproducing and predicting experimental results. This paper studies the difference in accuracy between flexible and fixed atom force fields in reproducing CO 2 adsorption measurements in MAF-2 ([Cu(etz)]∞ (MAF-2, Hetz) 3,5-diethyl-1,2,4-triazole), an NbO-type triazolate scaffold with a bcu cavity system and attached ethyl groups. The flexible force field used to run the hybrid molecular dynamics and grand canonical Monte Carlo calculations were generated using the QuickFF software incorporating van der Waals parameters from the Universal Force Field (UFF) and density derived electrostatic and chemical (DDEC) charges. The fixed atom force field used was composed of UFF van der Waals parameters together with DDEC charges. The calculations were run at 298 K and at pressures of 0.1, 0.3, 0.5, 0.8, and 1 bar. It was observed that for this MOF the rigid force field overpredicted gas adsorption, whereas the flexible force field values closely matched experimental data. In the flexible structure, the freely moving ethyl groups of MAF-2 hindered adsorption, reducing the interaction energy between CO 2 and the N atoms of the triazolate framework as well as reducing the size of the largest cavity diameter. Here, the combination of these factors led to improved prediction of adsorption values with the flexible forcefield as compared to the rigid forcefield, demonstrating the need for modeling MOFs in a way more indicative of their behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Charge Transfer and Recombination Pathways through Fullerene Guests in Porphyrin-Based MOFs

Porphyrin-based metal–organic frameworks (MOFs) offer a unique platform for building porous donor–acceptor networks that exhibit long-lived charge separation and transport upon incorporation of electron acceptor guest species. Here, in this work, porphyrin-based MOFs, PCN-222(H 2 ) and PCN-222(Zn), synthesized as nanoparticle suspensions, are successfully infiltrated with fullerene acceptor molecules, C 60 or PC 61 BM, in both polar and nonpolar solvent environments. The location and relative binding strength of these guest species are evaluated through a combination of N 2 physisorption measurements, photoluminescence quenching, and UV–vis absorption titration experiments. Semiempirical tight binding calculations are used to screen potential locations of the fullerene guest within the MOF pores, and hybrid density functional theory (DFT)-computed interaction energies confirm the energetically favorable positions. The fundamental photophysics of these donor–acceptor host–guest combinations are probed using ultrafast transient absorption spectroscopy. Sub-picosecond electron transfer involving initial exciplex population is observed, with slow charge recombination lifetimes on the order of τ ~1 ns for all systems in both dimethylformamide and 1,4-dioxane. Charge recombination occurs through population of fullerene and/or framework porphyrin triplet states depending on the porphyrin metalation status. The photophysics of the fullerene-loaded MOFs are discussed in the context of relevant porphyrin–fullerene donor–acceptor molecules to highlight the unique role of the framework environment in dictating photoinduced electron transfer and decay pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evolution and Degradation Patterns of Electrochemical Cells Based on the Analysis of Interfacial Phenomena at Li Metal Anode/Electrolyte Interfaces

In this work, we report the results of a theoretical–computational analysis of the solid electrolyte interphase (SEI) growth and degradation dynamics occurring in lithium metal batteries during cycling. We use ab initio-kinetic Monte Carlo simulations to generate a synthetic data set, which is analyzed by machine learning methods. We aim to determine: (i) how modifications in interfacial interaction energies between solid electrolyte interphase (SEI) blocks and between Li ions and SEI facets impact the Coulombic efficiency (CE) of the battery and (ii) what factors, including reactions, microscopic transport, and other interfacial events, may lead to cell performance “failure” during prolonged charge and discharge cycles, signaled as a sharp decay in the CE over cycling. The demonstration of our approach is done on a cell including a Li metal surface interfacing with a previously introduced state-of-the-art electrolyte, and the idea can be applied to any electrochemical system. Outcomes include the identification of the leading chemical, physical, and structural variables causing cell failure and relating them to the electrolyte formulation, thus paving the way to future more refined analysis and electrolyte design.

batteries↗

Machine Learning-Based Upscaling of Finite-Size Molecular Dynamics Diffusion Simulations for Binary Fluids

Molecular diffusion coefficients calculated using molecular dynamics (MD) simulations suffer from finite-size (i.e., finite box size and finite particle number) effects. Results from finite-sized MD simulations can be upscaled to infinite simulation size by applying a correction factor. For self-diffusion of single-component fluids, this correction has been well-studied by many researchers including Yeh and Hummer (YH); for binary fluid mixtures, a modified YH correction was recently proposed for correcting MD-predicted Maxwell–Stephan (MS) diffusion rates. In this study we use both empirical and machine learning methods to identify improvements to the finite-size correction factors for both self-diffusion and MS diffusion of binary Lennard-Jones (LJ) fluid mixtures. Using artificial neural networks (ANNs), the error in the corrected LJ fluid diffusion is reduced by an order of magnitude versus existing YH corrections, and the ANN models perform well for mixtures with large dissimilarities in size and interaction energies where the YH correction proves insufficient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanoconfinement of High Hydrogen-to-Metal Ratio Lanthanum Hydrides in Functionalized Carbon Hosts

Metal hydrides with a high hydrogen content are important for materials-based hydrogen storage and high-temperature superconductivity. Nanoconfinement of metal hydrides in porous hosts is a promising strategy to tune the thermodynamic stability and control the hydrogen-to-metal ratio. However, lanthanum hydride (LaH x ) nanoconfinement in porous materials has been limited due to the challenges associated with isolating and stabilizing nanoparticles of La or La-hydrides. Here we successfully demonstrated the chemical reduction of La­(III) salts to La(0), and subsequent infiltration into pure CMK-3 and nitrogen-doped CMK-3 (NCMK-3) porous carbons. Transmission electron microscopy measurements revealed a uniform distribution of LaH x species within the carbon hosts, while X-ray absorption and photoelectron spectroscopy provided detailed information about the local chemical environment. Sieverts measurements indicate that LaH x @NCMK-3 could desorb up to 0.75 wt % hydrogen, which is higher than non-nitrogen-functionalized CMK-3 (0.43 wt % H). Density Functional Theory and ab initio molecular dynamics calculations indicate that host–guest interaction energies are favorable for porous carbon with nitrogen defects, which is supported by experimental evidence. Moreover, high-pressure synchrotron X-ray diffraction measurements were conducted using a diamond anvil cell up to 60 GPa and reveal that the nitrogen-functionalized nanoporous carbon host favors the formation of higher H:La ratios in the presence of ammonia borane compared to the pure CMK-3 host. This approach could serve as a suitable platform for developing nanoscale superconducting materials at lower pressures and temperatures compared to bulk.

Shivanna, Mohana↗

The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture

Direct air capture (DAC) of CO 2 with porous adsorbents such as metal-organic frameworks (MOFs) has the potential to aid large-scale decarbonization. Previous screening of MOFs for DAC relied on empirical force fields and ignored adsorbed H 2 O and MOF deformation. We performed quantum chemistry calculations overcoming these restrictions for thousands of MOFs. The resulting data enable efficient descriptions using machine learning.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Transferable Force Field for Predicting Adsorption and Diffusion of Water in Cationic Zeolites with Coupled Cluster Accuracy

We present a transferable force field for water in proton-exchanged, alkali (Li, Na, K, Rb, and Cs) metal-exchanged, and alkaline-earth (Mg, Ca, Sr, and Ba) metal-exchanged zeolites. The fitting methodology is based on adsorbate–adsorbent interaction energies obtained from periodic density functional theory calculations and corrected using the coupled-cluster method applied to small model clusters. To ensure an accurate prediction of both adsorption and diffusion properties of water, sets of configurations that sample both adsorption sites and intracrystalline hopping transition states were used in the fitting. The quality of the force field is assessed for a wide range of zeolites with different topologies and chemical compositions, demonstrating good agreement between theoretical predictions and experimental measurements of water adsorption and diffusion.

Adsorption↗

Surface-Enhanced Raman Scattering Optophysiology Nanofibers for the Detection of Heavy Metals in Single Breast Cancer Cells

Mercury(II) ions (Hg2+) and silver ions (Ag+) are two of the most hazardous pollutants causing serious damage to human health. Here, we constructed surface enhanced Raman scattering (SERS)-active nanofibers covered with 4-mercaptopyridine (4-Mpy)-modified gold nanoparticles (AuNPs) to detect Hg2+ and Ag+. Experimental evidence suggests that the observed spectral changes originate from the combined effect of (i) the coordination between the nitrogen on 4-Mpy and the metal ions and (ii) the 4-Mpy molecular orientation (from flatter to more perpendicular with respect to the metal surface). The relative intensity of a pair of characteristic Raman peaks (at ~428 and ~708 cm-1) was used to quantify the metal ion concentration, greatly increasing the reproducibility of the measurement compared to signal-on or signal-off detection based on a single SERS peak. The detection limit of this method for Hg2+ is lower than that for the Ag+ (5 nM vs 100 nM), which can be explained by the stronger interaction energy between Hg2+ and N compared to Ag+ and N, as demonstrated by density functional theory (DFT) calculations. The Hg2+ and Ag+ ions can be masked by adding ethylenediaminetetraacetate (EDTA) and Cl-, respectively, to the Hg2+ and Ag+ samples. The good sensitivity, high reproducibility and excellent selectivity of these nanosensors were also demonstrated. Furthermore, detection of Hg2+ in living breast cancer cells at the subcellular level is possible thanks to the nanometric size of the herein described SERS nanosensors, allowing high spatial resolution and minimal cell damage.

Zhao, Xingjuan↗

Deep Eutectic Solvents for Efficient Fractionation of Lignocellulose to Produce Uncondensed Lignin and High-Quality Cellulose

Simultaneously inhibiting lignin condensation and cellulose degradation remains a major challenge for achieving holistic valorization of lignocellulose. Here, we developed a deep eutectic solvent (DES), composed of l-cysteine (Cys) and lactic acid (LA), to fractionate both uncondensed lignin and high-quality cellulose from eucalyptus wood by leveraging the unique properties of Cys, i.e., highly nucleophilic groups (–SH) and hydrogen bond acceptor/donor groups (–NH 2 and –COOH). The nucleophilic –SH in Cys effectively quenches the benzylic carbocations (C α + ions, formed at the benzylic sites of lignin) that lead to lignin condensation. This enables the high yield of uncondensed lignin (81%) with high retention of β–O–4 bonds (up to 90%). The separated uncondensed lignin is further depolymerized to prepare monophenols in a satisfactory 43% yield, equivalent to 73% of the theoretical yield. Moreover, the –NH 2 and –COOH groups in Cys form extensive hydrogen bonds with the hydroxyl groups in cellulose, thus decreasing the interaction energy of DES on cellulose. As a result, the cellulose achieves an astonishing 99% retention and maintains a high degree of polymerization of 1160. The obtained high-quality cellulose is further conversed into cellulose nanofibers for strong and transparent films. Furthermore, this study provides new insights into the efficient separation of uncondensed lignin and high-quality cellulose from lignocellulose by a novel DES system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis and Computational Analysis of Uranium(III)-Pnictogen Bonds

In this report, we describe the synthesis and characterization of two novel complexes that contain uranium(III)-pnictogen (P: 1-PMes 2 ; As: 1-AsMes 2 ) bonds to elucidate the degrees of covalency among these bonds. To our knowledge, this is the first reported uranium(III)-arsenic complex to be synthesized and characterized. Analysis of the phosphorus and arsenic bonds reveals a similar electronic environment, assessed by UV–vis NIR, that is comparable to other previously reported uranium(III) complexes. A computational analysis of these compounds and their congeners, N, Sb, and Bi, was performed to identify trends in the overall bonding character of the complexes. This analysis shows that bond covalency decreases as the pnictogen becomes heavier and that overall the interaction energy and its components decrease down the group. Here, this study provides an in-depth analysis and understanding of the nature of bonding between hard actinide and soft pnictogen centers.

Actinides↗

Many-Body Potential for Simulating Self-Assembly of Polymer-Grafted Nanoparticles in a Polymer Matrix

Many-body interactions between polymer-grafted nanoparticles (NPs) play a key role in promoting their assembly into low-dimensional structures within polymer melts, even when the particles are spherical and isotropically grafted. However, capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive, even using coarse-grained models. Here, we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach. The approach involves using permutationally invariant polynomials to fit two- and three-body interactions derived from the potential of mean force calculations. The potential developed here reduces the computational cost by several orders of magnitude, thereby, allowing us to explore assembly behavior over large length and time scales. We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets, which generally cannot be achieved using isotropic two-body potentials, but can also help discover interesting phases such as networks, clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two- and three-body interactions. Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior.

36 MATERIALS SCIENCE↗

Magnetic-field-induced Wigner crystallization of charged interlayer excitons in van der Waals heterostructures

Abstract Ever since its inception, coherent excited states of semiconductors have been the focus of semiconductor materials research to evolve into a vibrant field of low-dimensional solid-state physics. The field is gaining new momentum these days due to emerging transdimensional semiconductors such as van der Waals bound layers of transition metal dichalcogenides (TMDs) of controlled thickness. Here, we develop the theory of magnetic-field-induced Wigner crystallization for charged interlayer excitons (CIE) discovered recently in TMD heterobilayers. We derive the ratio of the potential interaction energy to the kinetic energy for the many-particle CIE system in the perpendicular magnetostatic field of an arbitrary strength and predict the crystallization effect in the strong field regime. We show that magnetic-field-induced Wigner crystallization and melting of CIEs can be observed in magneto-photoluminescence experiments with TMD bilayers of systematically varied electron-hole doping concentrations. Our results advance the capabilities of this new generation of transdimensional quantum materials.

36 MATERIALS SCIENCE↗