scholarly journals Xe⋯OCS: relatively straightforward?

2020 ◽  
Vol 22 (10) ◽  
pp. 5615-5624 ◽  
Author(s):  
Peter Kraus ◽  
Daniel A. Obenchain ◽  
Sven Herbers ◽  
Dennis Wachsmuth ◽  
Irmgard Frank ◽  
...  
Keyword(s):  
Interaction Energies ◽  
Experimental Interaction ◽  
Equilibrium Structures

Spectroscopy meets theory in a study of Xe⋯OCS complex: accurate near-equilibrium structures, experimental interaction energies, and CCSD(T)/CBS results presented.

Intermolecular interactions in crystals of small unsubstituted cyclic ethers and substituted epoxides

2018 ◽  
Vol 233 (9-10) ◽  
pp. 641-648 ◽  
Author(s):  
Mark A. Spackman
Keyword(s):  
Intermolecular Interactions ◽  
Cyclic Ethers ◽  
Interaction Energies ◽  
X Ray Diffraction ◽  
Weakly Bound ◽  
X Ray ◽  
Experimental Interaction ◽  
Lattice Energies ◽  
Experimental Electron Density ◽  
Careful Investigation

Abstract CE-B3LYP model energies are used to investigate intermolecular interactions in crystals of the relatively weakly bound cyclic ethers, as well as a number of substituted epoxides that have been the focus of high-quality experimental electron density studies. This approach readily provides a complete picture of all intermolecular interactions in these molecular crystals, and CE-B3LYP lattice energies for the unsubstituted cyclic ethers are in excellent agreement with available thermodynamic data. When compared with the outcomes of multipole modelling of X-ray diffraction data, these results suggest that experimental interaction energies are typically underestimated and, contrarily, experimental lattice energies are typically overestimated. These observations deserve careful investigation.

Intrinsic Stacking Interactions of Natural and Artificial Nucleobases

2019 ◽  
Author(s):  
Drew P. Harding ◽  
Laura J. Kingsley ◽  
Glen Spraggon ◽  
Steven Wheeler
Keyword(s):  
Gas Phase ◽  
Electrostatic Interactions ◽  
Density Functional ◽  
Molecular Descriptors ◽  
Stacking Interactions ◽  
Interaction Energies ◽  
Functional Theory ◽  
Binding Partner ◽  
Heavy Atoms ◽  
Wide Range

The intrinsic (gas-phase) stacking energies of natural and artificial nucleobases were explored using density functional theory (DFT) and correlated ab initio methods. Ranking the stacking strength of natural nucleobase dimers revealed a preference in binding partner similar to that seen from experiments, namely G > C > A > T > U. Decomposition of these interaction energies using symmetry-adapted perturbation theory (SAPT) showed that these dispersion dominated interactions are modulated by electrostatics. Artificial nucleobases showed a similar stacking preference for natural nucleobases and were also modulated by electrostatic interactions. A robust predictive multivariate model was developed that quantitively predicts the maximum stacking interaction between natural and a wide range of artificial nucleobases using molecular descriptors based on computed electrostatic potentials (ESPs) and the number of heavy atoms. This model should find utility in designing artificial nucleobase analogs that exhibit stacking interactions comparable to those of natural nucleobases. Further analysis of the descriptors in this model unveil the origin of superior stacking abilities of certain nucleobases, including cytosine and guanine.

On the Nature of Halide-Water Interactions: Insights from Many-Body Representations and Density Functional Theory

2019 ◽  
Author(s):  
Brandon B. Bizzarro ◽  
Colin K. Egan ◽  
Francesco Paesani
Keyword(s):  
Density Functional Theory ◽  
Charge Transfer ◽  
Molecular Orbital ◽  
Density Functional ◽  
Decomposition Analysis ◽  
Orbital Energy ◽  
Energy Decomposition Analysis ◽  
Interaction Energies ◽  
Many Body ◽  
Functional Theory

<div> <div> <div> <p>Interaction energies of halide-water dimers, X<sup>-</sup>(H<sub>2</sub>O), and trimers, X<sup>-</sup>(H<sub>2</sub>O)<sub>2</sub>, with X = F, Cl, Br, and I, are investigated using various many-body models and exchange-correlation functionals selected across the hierarchy of density functional theory (DFT) approximations. Analysis of the results obtained with the many-body models demonstrates the need to capture important short-range interactions in the regime of large inter-molecular orbital overlap, such as charge transfer and charge penetration. Failure to reproduce these effects can lead to large deviations relative to reference data calculated at the coupled cluster level of theory. Decompositions of interaction energies carried out with the absolutely localized molecular orbital energy decomposition analysis (ALMO-EDA) method demonstrate that permanent and inductive electrostatic energies are accurately reproduced by all classes of XC functionals (from generalized gradient corrected (GGA) to hybrid and range-separated functionals), while significant variance is found for charge transfer energies predicted by different XC functionals. Since GGA and hybrid XC functionals predict the most and least attractive charge transfer energies, respectively, the large variance is likely due to the delocalization error. In this scenario, the hybrid XC functionals are then expected to provide the most accurate charge transfer energies. The sum of Pauli repulsion and dispersion energies are the most varied among the XC functionals, but it is found that a correspondence between the interaction energy and the ALMO EDA total frozen energy may be used to determine accurate estimates for these contributions. </p> </div> </div> </div>

BAND NN: A Deep Learning Framework For Energy Prediction and Geometry Optimization of Organic Small Molecules

2019 ◽  
Author(s):  
Siddhartha Laghuvarapu ◽  
Yashaswi Pathak ◽  
U. Deva Priyakumar
Keyword(s):  
Machine Learning ◽  
Density Functional ◽  
Computational Cost ◽  
Geometry Optimization ◽  
Dft Methods ◽  
Energy Prediction ◽  
Machine Learning Model ◽  
Equilibrium Structures ◽  
High Level ◽  
Non Equilibrium

Recent advances in artificial intelligence along with development of large datasets of energies calculated using quantum mechanical (QM)/density functional theory (DFT) methods have enabled prediction of accurate molecular energies at reasonably low computational cost. However, machine learning models that have been reported so far requires the atomic positions obtained from geometry optimizations using high level QM/DFT methods as input in order to predict the energies, and do not allow for geometry optimization. In this paper, a transferable and molecule-size independent machine learning model (BAND NN) based on a chemically intuitive representation inspired by molecular mechanics force fields is presented. The model predicts the atomization energies of equilibrium and non-equilibrium structures as sum of energy contributions from bonds (B), angles (A), nonbonds (N) and dihedrals (D) at remarkable accuracy. The robustness of the proposed model is further validated by calculations that span over the conformational, configurational and reaction space. The transferability of this model on systems larger than the ones in the dataset is demonstrated by performing calculations on select large molecules. Importantly, employing the BAND NN model, it is possible to perform geometry optimizations starting from non-equilibrium structures along with predicting their energies.

Ion solvation by dipolar aprotic solvents. An ab initio study

1987 ◽  
Vol 52 (1) ◽  
pp. 6-13 ◽  
Author(s):  
Petr Kyselka ◽  
Zdeněk Havlas ◽  
Ivo Sláma
Keyword(s):  
Ab Initio ◽  
Geometry Optimization ◽  
Molecular Structures ◽  
Dimethyl Sulphoxide ◽  
Ion Solvation ◽  
Interaction Energies ◽  
Ab Initio Study ◽  
Solvation Energies ◽  
Dipolar Aprotic Solvents ◽  
Complete Geometry Optimization

The paper deals with the solvation of Li+, Be2+, Na+, Mg2+, and Al3+ ions in dimethyl sulphoxide, dimethylformamide, acetonitrile, and water. The ab initio quantum chemical method was used to calculate the solvation energies, molecular structures, and charge distributions for the complexes water···ion, acetonitrile···ion, dimethyl sulphoxide···ion, and dimethylformamide···ion. The interaction energies were corrected for the superposition error. Complete geometry optimization was performed for the complex water···ion. Some generalizations are made on the basis of the results obtained.

scholarly journals Interactions between large molecules pose a puzzle for reference quantum mechanical methods

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yasmine S. Al-Hamdani ◽  
Péter R. Nagy ◽  
Andrea Zen ◽  
Dennis Barton ◽  
Mihály Kállay ◽  
...  
Keyword(s):  
Experimental Information ◽  
Quantum Mechanical ◽  
Interaction Energies ◽  
Small Organic Molecules ◽  
Large Molecules ◽  
Reference Information ◽  
Mechanical Methods ◽  
Non Covalent Interactions ◽  
Semi Empirical ◽  
Covalent Interactions

AbstractQuantum-mechanical methods are used for understanding molecular interactions throughout the natural sciences. Quantum diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] are state-of-the-art trusted wavefunction methods that have been shown to yield accurate interaction energies for small organic molecules. These methods provide valuable reference information for widely-used semi-empirical and machine learning potentials, especially where experimental information is scarce. However, agreement for systems beyond small molecules is a crucial remaining milestone for cementing the benchmark accuracy of these methods. We show that CCSD(T) and DMC interaction energies are not consistent for a set of polarizable supramolecules. Whilst there is agreement for some of the complexes, in a few key systems disagreements of up to 8 kcal mol−1 remain. These findings thus indicate that more caution is required when aiming at reproducible non-covalent interactions between extended molecules.

scholarly journals Tunable thermo-reversible bicontinuous nanoparticle gel driven by the binary solvent segregation

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yuyin Xi ◽  
Ronald S. Lankone ◽  
Li-Piin Sung ◽  
Yun Liu
Keyword(s):  
Phase Separation ◽  
Domain Size ◽  
Binary Solvent ◽  
Colloidal Systems ◽  
Colloidal Assembly ◽  
Structures And Properties ◽  
Wide Range ◽  
Equilibrium Process ◽  
Equilibrium Structures ◽  
Non Equilibrium

AbstractBicontinuous porous structures through colloidal assembly realized by non-equilibrium process is crucial to various applications, including water treatment, catalysis and energy storage. However, as non-equilibrium structures are process-dependent, it is very challenging to simultaneously achieve reversibility, reproducibility, scalability, and tunability over material structures and properties. Here, a novel solvent segregation driven gel (SeedGel) is proposed and demonstrated to arrest bicontinuous structures with excellent thermal structural reversibility and reproducibility, tunable domain size, adjustable gel transition temperature, and amazing optical properties. It is achieved by trapping nanoparticles into one of the solvent domains upon the phase separation of the binary solvent. Due to the universality of the solvent driven particle phase separation, SeedGel is thus potentially a generic method for a wide range of colloidal systems.

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