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At least 325 records · Page 18

An improved guess for the variational calculation of charge-transfer excitations in large systems

Ab initio quantum-chemical methods that perform well for computing the electronic ground state are not straightforwardly transferable to electronically excited states, particularly in large molecular systems. Wave function theory offers high accuracy, but is often prohibitively expensive. Methods based on time-dependent density functional theory (TD-DFT) are crucially sensitive to the chosen exchange-correlation functional (XCF) parameterization, and system-specific tuning protocols were therefore proposed to address the method's robustness. Methods based on the variational relaxation of the excited-state electron density showcased promising results for the calculation of charge-transfer excitations, but the complex shape of the electronic hypersurface makes convergence to a specific excited state much more difficult than for the ground state when standard variational techniques are applied. We address the latter aspect by providing suitable initial guesses, which we obtain by two separate constrained algorithms. Combined with the squared-gradient minimization algorithm for all-electrons relaxation in a freeze-and-release scheme (FRZ-SGM), we demonstrate that orbital-optimized density functional theory (OO-DFT) calculations can reliably converge to the charge-transfer states of interest even for large molecular systems. We test the FRZ-SGM method on a phenothiazine-anthraquinone CT excitation in a supramolecular Pd(II) coordination cage complex as a function of the cage conformation. This compound has been studied experimentally prior to our work. We compare this freeze-and-release scheme to two XCF reparameterizations, which were recently proposed as low-cost TD-DFT-based alternatives to variational methods. Two dye-semiconductor complexes, which were previously investigated in the context of photovoltaic applications, serve as a second example to investigate the convergence and stability of the FRZ-SGM approach. Our results demonstrate that FRZ-SGM provides reliable convergence for charge-transfer excited states and avoids variational collapse to lower-lying electronic states, whereas time-dependent DFT calculations with an adequate tuning procedure for the range-separation parameter provide a computationally efficient initial estimate of the corresponding energies, with a computational cost comparable to that of configuration-interaction singles (CIS) calculations.

Bogo, Nicola↗

Hydration structure of flat and stepped MgO surfaces

We investigate the solvation structure of flat and stepped MgO(001) in neutral liquid water using ab initio molecular dynamics based on a hybrid density functional with dispersion corrections. Our simulations show that the MgO surface is covered by a densely packed layer of mixed intact and dissociated adsorbed water molecules in a planar arrangement with strong intermolecular H-bonds. The water dissociation fractions in this layer are >20% and >30% on the flat and stepped surfaces, respectively. Slightly above the first water layer, we observe metastable OH groups perpendicular to the interface, similar to those reported in low temperature studies of water monolayers on MgO. Here, these species receive hydrogen bonds from four nearby water molecules in the first layer and have their hydrophobic H end directed toward bulk water, while their associated protons are bound to surface oxygens. The formation of these OH species is attributed to the strong basicity of the MgO surface and can be relevant for understanding various phenomena from morphology evolution and growth of (nano)crystalline MgO particles to heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Liquid bicontinuous stabilized assemblies by interfacial jamming of nanoparticles

A method for preparing a stabilized assembly includes combining a first liquid phase including nanoparticles and a second, immiscible liquid phase, dissolving in the second phase a first end-functionalized polymer having a first molecular weight, and a second end-functionalized polymer having a second molecular weight, wherein the second molecular weight is greater than the first molecular weight, applying a shearing external deformation field to increase the surface area of the first phase to create a new interface, wherein the nanoparticle surfactants form a disordered, jammed assembly at the new interface, and releasing the shearing external deformation field. The polymer and the nanoparticles can interact at an interface through ligand interactions to form nanoparticle surfactants and upon releasing the external deformation field the jammed assembly at the new interface traps the first phase in a deformed state having the first liquid phase and the second liquid phase as interpenetrating domains.

Huang, Caili↗

QForte: An Efficient State-Vector Emulator and Quantum Algorithms Library for Molecular Electronic Structure

Here, we introduce a novel open-source software package QForte, a comprehensive development tool for new quantum simulation algorithms. QForte incorporates functionality for handling molecular Hamiltonians, fermionic encoding, ansatz construction, time evolution, and state-vector emulation, requiring only a classical electronic structure package as a dependency. QForte also contains black-box implementations of a wide variety of quantum algorithms, including variational and projective quantum eigensolvers, adaptive eigensolvers, quantum imaginary time evolution, and quantum Krylov methods. We highlight two features of QForte: (i) how the Python class structure of QForte enables the facile implementation of new algorithms, and (ii) how existing algorithms can be executed in just a few lines of code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular-Level Exploration of the Structure-Function Relations Underlying Interfacial Charge Transfer in the Subphthalocyanine/C 60 Organic Photovoltaic System

The arrangement of organic molecules at the donor-acceptor interface in an organic photovoltaic (OPV) cell can have a strong effect on the generation of charge carriers and thereby cell performance. In this paper, we report the molecular-level exploration of the ensemble of interfacial donor-acceptor pair geometries and the charge-transfer (CT) rates to which they give rise. Our approach combines molecular-dynamics simulations, electronic structure calculations, machine learning, and rate theory. This approach is applied to the boron subphthalocyanine chloride (donor) and C 60 (acceptor) OPV system. In this work we find that the interface is dominated by a previously unreported donor-acceptor pair edge geometry, which contributes significantly to device performance in a manner that depends on the initial conditions. Quantitative relations between the morphology and CT rates are established, which can be used to advance the design of more efficient OPV devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Investigating the Accuracy of Water Models through the Van Hove Correlation Function

In this study, we present molecular-simulation-based calculations of the Van Hove correlation function (VHF) of water using multiple modeling approaches: classical molecular dynamics with simple three-site nonpolarizable models, with a polarizable model, and with a reactive force field; density functional tight-binding molecular dynamics; and ab initio molecular dynamics. Due to the many orders of magnitude difference in the computational cost of these approaches, we investigate how small and short the simulations can be while still yielding sufficiently accurate and interpretable results for the VHF. We investigate the accuracy of the different models by comparing them to recently published inelastic X-ray scattering measurements of the VHF. We find that all of the models exhibit qualitative agreement with the experiments, and in some models and for some properties, the agreement is quantitative. This work lays the foundation for future simulation approaches to calculating the VHF for aqueous solutions in bulk and under nanoconfinement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Manipulating Organic Semiconductor Morphology with Visible Light

A method is presented to manipulate the final morphology of roll-to-roll slot-die coated poly(3-hexylthiophene) (P3HT) by optically exciting the p-type polymer in solution while coating. These results provide a comprehensive picture of the entire knowledge chain, from demonstrating how to apply the authors’ method to a fundamental understanding of the changes in morphology and physical properties induced by exciting P3HT while coating. By combining results from density functional theory and molecular dynamics simulations with a variety of X-ray experiments, absorption spectroscopy, and THz spectroscopy, the relationship between morphology and physical properties of the thin film is demonstrated. Specifically, in P3HT films excited with light during deposition, changes in crystallinity and texture with more face-on orientation and increased out-of-plane charge mobility are observed.

36 MATERIALS SCIENCE↗

Beyond Single-Reference Fixed-Node Approximation in Ab Initio Diffusion Monte Carlo Using Antisymmetrized Geminal Power Applied to Systems with Hundreds of Electrons

Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in Fermionic systems, the projection needs to be carried out while imposing antisymmetric constraints, which is a nondeterministic polynomial hard problem. In practice, therefore, the application of DMC on electronic structure problems is made by employing the fixed-node (FN) approximation, consisting of performing DMC with the constraint of having a fixed, predefined nodal surface. How do we get the nodal surface? The typical approach, applied in systems having up to hundreds or even thousands of electrons, is to obtain the nodal surface from a preliminary mean-field approach (typically, a density functional theory calculation) used to obtain a single Slater determinant. This is known as single reference. In this paper, we propose a new approach, applicable to systems as large as the C 60 fullerene, which improves the nodes by going beyond the single reference. In practice, we employ an implicitly multireference ansatz (antisymmetrized geminal power wave function constraint with molecular orbitals), initialized on the preliminary mean-field approach, which is relaxed by optimizing a few parameters of the wave function determining the nodal surface by minimizing the FN-DMC energy. We highlight the improvements of the proposed approach over the standard single-reference method on several examples and, where feasible, the computational gain over the standard multireference ansatz, which makes the methods applicable to large systems. We also show that physical properties relying on relative energies, such as binding energies, are affordable and reliable within the proposed scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of linkage chemistry and side-chain polarity on Ion 2 transport in click-functionalized polymerized ionic liquids.

Post-polymerization functionalization offers precise molecular weight control and enables the high-throughput investigation of structure−property relationships in polymer research. However, post-polymerization functionalization strategies often introduce additional linkage chemistry, and its role in the physical properties of polymerized ionic liquids (PILs) has yet to be explored. In this work, a series of PILs were synthesized using Cu(I)-catalyzed azide−alkyne cycloaddition (CuAAC), with comparison made to N-alkylation substitution chemistry. The triazole ring introduced by CuAAC chemistry was found to induce extensive ion aggregation and deteriorate ion transport. The impact of linkage chemistry on ion transport can be alleviated by incorporating polar ethylene glycol spacers in the side chain, achieving an ionic conductivity of 2.1 × 10−4 S/cm at 30 °C. Furthermore, the effect of polar spacer placement was explored, revealing that overall side-chain polarity, rather than polarity in the vicinity of the ionic group, governs ion aggregation and ion transport in PILs.

Shan, Naisong↗

Evaluation of Density-Functional Tight-Binding Methods for Simulation of Protic Molecular Ion Pairs

In this work, we benchmark the accuracy of the density-functional tight-binding (DFTB) method, namely the long-range corrected second-order (LC-DFTB2) and third-order (DFTB3) models, for predicting energetics of imidazolium-based ionic liquid (IL) ion pairs. We compare the DFTB models against popular density functionals such as LC-ωPBE and B3LYP, using ab initio domain-based local pair-natural orbital coupled cluster (DLPNO-CC) energies as reference. Calculations were carried out in the gas phase, as well as in aqueous solution using implicit solvent methods. We find that the LC-DFTB2 model shows excellent performance in the gas phase and agrees well with reference energies in implicit solvent, often outperforming DFTB3 predictions for complexation energetics. Our study identifies a range of opportunities for use of the LC-DFTB method and quantifies its sensitivity to protonation states and the types of chemical interactions between ion pairs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Theory of atomic additivity in molecular hyperpolizabilities

Hyperpolarizability is a function of frequency. This is called dispersion. Because of the Kramers-Kronig relations, researchers expect that a material that is dispersing light is also absorbing it. Where there is both dispersion and absorption, the molecular polarizabilities are complex functions of the frequency. This led researchers to consider atomic additivity in both the real and imaginary parts of the ordinary and hyperpolarizabilities. This effort is desirable not only from a theoretical point of view, but also because of the existence of a large body of complex refractive index data, which may be used to test the additivity principle with the complex valued ordinary dipole polarizability.

Baird, James K.↗

Attention-based functional-group coarse-graining: a deep learning framework for molecular prediction and design

Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data, for ML training. In this study, we report a data-efficient, deep-learning framework for molecular discovery that integrates a coarse-grained functional-group representation with a self-attention mechanism to capture intricate chemical interactions. Our approach exploits group-contribution concepts to create a graph-based intermediate representation of molecules, serving as a low-dimensional embedding that substantially reduces the data demands typically required for training. Using a self-attention mechanism to learn the subtle but highly relevant chemical context of functional groups, the method proposed here consistently outperforms existing approaches for predictions of multiple thermophysical properties. In a case study focused on adhesive polymer monomers, we train on a limited dataset comprising only 6,000 unlabeled and 600 labeled monomers. The resulting chemistry prediction model achieves over 92% accuracy in forecasting properties directly from SMILES strings, exceeding the performance of current state-of-the-art techniques. Furthermore, the latent molecular embedding is invertible, enabling the design pipeline to automatically generate new monomers from the learned chemical subspace. We illustrate this functionality by targeting several properties, including high and low glass transition temperatures (Tg), and demonstrate that our model can identify new candidates with values that surpass those in the training set. The ease with which the proposed framework navigates both chemical diversity and data scarcity offers a promising route to accelerate and broaden the search for functional materials.

Han, Ming [Univ. of Chicago, IL (United States)]↗

Solvent Dynamics Are Critical to Understanding Carbon Dioxide Dissolution and Hydration in Water

Simulations of carbon dioxide (CO 2 ) in water may aid in understanding the impact of its accumulation in aquatic environments and help advance technologies for carbon capture and utilization (via, e.g., mineralization). Quantum mechanical (QM) simulations based on static molecular models with polarizable continuum solvation poorly reproduce the energetics of CO 2 hydration to form carbonic acid in water, independent of the level of QM theory employed. Only with density-functional-theory-based molecular dynamics and rare-event sampling, followed by energy corrections based on embedded correlated wavefunction theory (in conjunction with density functional embedding theory), can a close agreement between theory and experiment be achieved. Such multilevel simulations can serve as benchmarks for simpler, less costly models, giving insight into potential errors of the latter. The strong influence of sampling/averaging over dynamical solvent configurations on the energetics stems from the difference in polarity of both the transition state and product (both polar) versus the reactant (nonpolar). When a solute undergoes a change in polarity during reaction, affecting its interaction with the solvent, careful assessment of the energetic contribution of the solvent response to this change is critical. Here, we show that static models (without structural sampling) that incorporate three explicit water molecules can yield far superior results than models with more explicit water molecules because fewer water molecules yield less configurational artifacts. Static models intelligently incorporating both explicit (molecules directly participating in the reaction) and implicit solvation, along with a proper QM theory, e.g., CCSD(T) for closed-shell systems, can close the accuracy gap between static and dynamic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cyclodextrin-Derived Porous Liquids Enabled by In Situ Solvation Shell Formation

Porous liquids (PLs) represent a unique platform for molecular separations by combining permanent porosity with liquid-phase mobility. However, it remains a formidable challenge to construct and stabilize PLs with sub-5 Å pores using readily available porous host and liquid media. Here, we report the construction of cyclodextrin (CD)-derived PLs enabled by in situ solvation shell formation. The acid–base neutralization reaction between CD and an organic base was leveraged to generate a thin ionic solvation shell around the CD host, effectively liquefying CD and preventing its segregation in the liquid base medium while preserving accessible molecular-scale cavities. Spectroscopic analysis, neutron scattering, density functional theory calculations, and molecular dynamics simulations collectively confirm the structural evolution and existence of abundant internal porosity in PLs. The unique architectures of CD-derived PLs enable highly selective encapsulation of fluorinated alkanes and significantly enhanced uptake of inert gases. This facile and generalizable strategy enables construction of high-quality PLs with engineered ultramicroporosity to facilitate molecular separations.

Cavities↗

A hemoprotein with a zinc-mirror heme site ties heme availability to carbon metabolism in cyanobacteria

Abstract Heme has a critical role in the chemical framework of the cell as an essential protein cofactor and signaling molecule that controls diverse processes and molecular interactions. Using a phylogenomics-based approach and complementary structural techniques, we identify a family of dimeric hemoproteins comprising a domain of unknown function DUF2470. The heme iron is axially coordinated by two zinc-bound histidine residues, forming a distinct two-fold symmetric zinc-histidine-iron-histidine-zinc site. Together with structure-guided in vitro and in vivo experiments, we further demonstrate the existence of a functional link between heme binding by Dri1 (Domain related to iron 1, formerly ssr1698) and post-translational regulation of succinate dehydrogenase in the cyanobacterium Synechocystis , suggesting an iron-dependent regulatory link between photosynthesis and respiration. Given the ubiquity of proteins containing homologous domains and connections to heme metabolism across eukaryotes and prokaryotes, we propose that DRI (Domain Related to Iron; formerly DUF2470) functions at the molecular level as a heme-dependent regulatory domain.

59 BASIC BIOLOGICAL SCIENCES↗

Accuracy of XAS theory for unraveling structural changes of adsorbates: CO on Ni(100)

Studying surface reactions using ultrafast optical pump and X-ray probe experiments relies on accurate calculations of X-ray spectra of adsorbates for correct identification of the spectral signatures and their dynamical evolution. We show that experimental XAS can be well reproduced for the different binding sites in a static prototype system CO/Ni(100) at a standard DFT (GGA) level of theory, using a plane-wave basis and pseudopotentials. This validates its utility in analyzing ultrafast X-ray probe experiments. The accuracy of computed relative core level binding energies is about 0.2 eV, representing a lower limit for which spectral features can be resolved with this method. We also show that the commonly used Z +1 approximation gives very good core binding energy shifts overall. However, we find a discrepancy for CO adsorbed in the hollow site, which we assign to the significantly stronger hybridization in hollow bonding than in on-top.

74 ATOMIC AND MOLECULAR PHYSICS↗

Structure and Dynamics of CO 2 at the Air–Water Interface from Classical and Neural Network Potentials

The accurate description of the structure and dynamics of CO 2 at the instantaneous air–water interface, along with the effects of surface fluctuations on the CO 2 -transport processes, is essential for the development of negative emission technologies aimed at minimizing climate change. In this study, we performed molecular dynamics simulations of CO 2 at the air–water interface using neural network potentials (NNPs) trained on ab initio data generated through density-functional-theory-based molecular dynamics simulations. We compared these results with classical force fields to assess their performance in modeling interfacial CO 2 behavior. Our findings revealed that the asymmetric interactions, coupled with thermal surface fluctuations at the air–water interface, significantly influence CO 2 transport into the aqueous phase. The simulations demonstrate that classical force fields underestimate both the free energy of CO 2 transport and the strength of its interactions at the interface compared with the neural network potentials. In conclusion, the free energy and the interfacial dynamics of CO 2 are primarily influenced by the distribution of water within the instantaneous interfacial water layer, responsible for creating an asymmetric intermolecular interaction environment within the interfacial region.

Ab initio molecular dynamics↗

Surface Charge at an Oil/Water Interface Promoting the Enhancement and Assignment of Water Combination Bands

Given the different polarities and distinct chemical structures, it is no wonder that oil and water are incompatible neighbors. They can be forced to cooperate if provided sufficient energy or a suitable intermediary. Emulsions are the result of such a cooperation, where an emulsifying agent (the intermediary) in the form of a surfactant or a cocktail of surface stabilizing compounds allows for the ‘mixing’ of oil and water. Surfactant stabilized emulsions that are nanoscale in size (nanoemulsions) have caught the attention of many because of their newly discovered use in the synthesis of nanomaterials, oil recovery, drug delivery, and food science. Unlike smaller emulsions (e.g. microemulsions with 2-20 nm diameters), very little is known about the molecular level properties of nanoemulsions (NEs) whose diameters are in the 100-500 nm range. One thing that is well known is the macroscopic properties of droplets from these two size regimes are dramatically different, often for reasons not yet fully understood. Nanoemulsions do not form spontaneously and require an external shear beyond ordinary procedures used to create micelles. This shear is required to overcome the effects of surface tension and create droplets in the nanoscale regime. Once formed, however, they can be stable for long periods of time, making them very attractive for commercial and pharmaceutical products requiring a long shelf life. What is not well known is the interfacial molecular processes that lead to the formation and stability of nanoemulsions including those stabilized by surfactants and/or polymers. Such knowledge is important in understanding the molecular structure-function relationship that assists in predicting what additives and solvents are necessary for a specific application. Key to advancing nanoemulsion utility is to develop the needed molecular-level understanding of the structure and bonding interactions present at the surface of these soft nanoparticles.

36 MATERIALS SCIENCE↗