Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

W4Λ: Leveraging Λ Coupled-Cluster for Accurate Computational Thermochemistry Approaches.

ABSTRACT: High-accuracy composite wave function methods like Weizmann-4 (W4) theory, high-accuracy extrapolated ab initio thermochemistry (HEAT), and the Feller-Peterson-Dixon (FPD) approach enable sub-kJ/mol accuracy in gas-phase thermochemical properties. Their biggest computational bottleneck is the evaluation of the valence post-CCSD(T) correction term. We demonstrate here, for the W4-17 thermochemistry benchmark and subsets thereof, that the Λ coupled-cluster expansion converges more rapidly and smoothly than the regular coupled-cluster series. By means of CCSDT(Q)_Λ and CCSDTQ(5)_Λ, we can considerably (up to an order of magnitude) accelerate W4- and W4.3-type calculations without loss in accuracy, leading to the W4Λ and W4.3Λ computational thermochemistry protocols.

SUBMITTER: Semidalas E

PROVIDER: S-EPMC10926103 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

W4Λ: Leveraging Λ Coupled-Cluster for Accurate Computational Thermochemistry Approaches.

Semidalas Emmanouil E Karton Amir A Martin Jan M L JML

The journal of physical chemistry. A 20240224 9

High-accuracy composite wave function methods like Weizmann-4 (W4) theory, high-accuracy extrapolated ab initio thermochemistry (HEAT), and the Feller-Peterson-Dixon (FPD) approach enable sub-kJ/mol accuracy in gas-phase thermochemical properties. Their biggest computational bottleneck is the evaluation of the valence post-CCSD(T) correction term. We demonstrate here, for the W4-17 thermochemistry benchmark and subsets thereof, that the Λ coupled-cluster expansion converges more rapidly and smoo ...[more]

PMID: 38400740

Similar Datasets

Simplified Multireference Coupled-Cluster Methods: Hybrid Approaches With Averaged Coupled Pair Theories.

Project description:We define an approximation to the internally contracted multireference coupled-cluster method with single and double excitations by a hybrid approach. The rationale is to treat the external pair energy contributions by the coupled-cluster method, which provides accurate results for a large part of the correlation energy while being tractable as the involved pair cluster operators commute. For the internal and semi-internal contributions, for which the coupled-cluster part becomes involved due to non-commuting operators, a linearized approach based on the coupled-electron pair approximation (CEPA) is used. For the latter, the CEPA(0) method, the averaged coupled pair functional (ACPF), the averaged quadratic coupled-cluster (AQCC) method, and the averaged CEPA method are tested. We test the methods concerning size consistency, potential energy curves for C2, N2, CN, and O3 and for the singlet-triplet splitting of ortho-, meta-, and para-benzynes. Our results show that AQCC provides the most accurate results and stable performance. The main drawback of the method is that it shows small violations of size consistency.

| S-EPMC11754727 | biostudies-literature

Accurate molecular polarizabilities with coupled cluster theory and machine learning.

Project description:The molecular dipole polarizability describes the tendency of a molecule to change its dipole moment in response to an applied electric field. This quantity governs key intra- and intermolecular interactions, such as induction and dispersion; plays a vital role in determining the spectroscopic signatures of molecules; and is an essential ingredient in polarizable force fields. Compared with other ground-state properties, an accurate prediction of the molecular polarizability is considerably more difficult, as this response quantity is quite sensitive to the underlying electronic structure description. In this work, we present highly accurate quantum mechanical calculations of the static dipole polarizability tensors of 7,211 small organic molecules computed using linear response coupled cluster singles and doubles theory (LR-CCSD). Using a symmetry-adapted machine-learning approach, we demonstrate that it is possible to predict the LR-CCSD molecular polarizabilities of these small molecules with an error that is an order of magnitude smaller than that of hybrid density functional theory (DFT) at a negligible computational cost. The resultant model is robust and transferable, yielding molecular polarizabilities for a diverse set of 52 larger molecules (including challenging conjugated systems, carbohydrates, small drugs, amino acids, nucleobases, and hydrocarbon isomers) at an accuracy that exceeds that of hybrid DFT. The atom-centered decomposition implicit in our machine-learning approach offers some insight into the shortcomings of DFT in the prediction of this fundamental quantity of interest.

| S-EPMC6397574 | biostudies-literature

Hydrogen-Bond-Dependent Conformational Switching: A Computational Challenge from Experimental Thermochemistry.

Project description:We have compiled an experimental data set (SWITCH10) of equilibrium constants for a series of hydrogen-bond-dependent conformational switches. These organic molecules possess common functionalities and are representative in terms of size and composition of systems routinely studied computationally. They exist as two well-defined conformations which serve as a useful tool to benchmark computational estimates of experimental Gibbs energy differences. We examine the performance of HF theory and a variety of density functionals (B3LYP, B3LYP-D3, CAM-B3LYP, ωB97X-D, M06-2X) against these experimental benchmarks. Surprisingly, despite a strong similarity between the two switch conformations, the average errors (0.4-1.7 kcal·mol-1) obtained across the data set for all methods are larger than obtained with HF calculations. B3LYP was found to outperform implicitly and explicitly dispersion-corrected functionals, with an average error smaller by 1 kcal·mol-1. Unsystematic errors in the optimized structures were found to contribute to the relatively poor performance obtained, while quasi-rigid rotor harmonic oscillator thermal contributions are important in improving the accuracy of computed Gibbs energy differences. These results emphasize the challenge of quantitative accuracy in computing solution-phase thermochemistry for flexible systems and caution against the often used (but unstated) assumption of favorable error cancellation in comparing conformers or stereoisomers.

| S-EPMC6467729 | biostudies-literature

Accurate Excited-State Geometries: A CASPT2 and Coupled-Cluster Reference Database for Small Molecules.

Project description:We present an investigation of the excited-state structural parameters determined for a large set of small compounds with the dual goals of defining reference values for further works and assessing the quality of the geometries obtained with relatively cheap computational approaches. In the first stage, we compare the excited-state geometries obtained with ADC(2), CC2, CCSD, CCSDR(3), CC3, and CASPT2 and large atomic basis sets. It is found that CASPT2 and CC3 results are generally in very good agreement with one another (typical differences of ca. 3 × 10-3 Å) when all electrons are correlated and when the aug-cc-pVTZ atomic basis set is employed with both methods. In a second stage, a statistical analysis reveals that, on the one hand, the excited-state (ES) bond lengths are much more sensitive to the selected level of theory than their ground-state (GS) counterparts and, on the other hand, that CCSDR(3) is probably the most cost-effective method delivering accurate structures. Indeed, CCSD tends to provide too compact multiple bond lengths on an almost systematic basis, whereas both CC2 and ADC(2) tend to exaggerate these bond distances, with more erratic error patterns, especially for the latter method. The deviations are particularly marked for the polarized CO and CN bonds, as well as for the puckering angle in formaldehyde homologues. In the last part of this contribution, we provide a series of CCSDR(3) GS and ES geometries of medium-sized molecules to be used as references in further investigations.

| S-EPMC5729545 | biostudies-literature

Reconciling Local Coupled Cluster with Multireference Approaches for Transition Metal Spin-State Energetics.

Project description:Spin-state energetics of transition metal complexes remain one of the most challenging targets for electronic structure methods. Among single-reference wave function approaches, local correlation approximations to coupled cluster theory, most notably the domain-based local pair natural orbital (DLPNO) approach, hold the promise of bringing the accuracy of coupled cluster theory with single, double, and perturbative triple excitations, CCSD(T), to molecular systems of realistic size with acceptable computational cost. However, recent studies on spin-state energetics of iron-containing systems raised doubts about the ability of the DLPNO approach to adequately and systematically approximate energetics obtained by the reference-quality complete active space second-order perturbation theory with coupled-cluster semicore correlation, CASPT2/CC. Here, we revisit this problem using a diverse set of iron complexes and examine several aspects of the application of the DLPNO approach. We show that DLPNO-CCSD(T) can accurately reproduce both CASPT2/CC and canonical CCSD(T) results if two basic principles are followed. These include the consistent use of the improved iterative (T1) versus the semicanonical perturbative triple corrections and, most importantly, a simple two-point extrapolation to the PNO space limit. The latter practically eliminates errors arising from the default truncation of electron-pair correlation spaces and should be viewed as standard practice in applications of the method to transition metal spin-state energetics. Our results show that reference-quality results can be readily achieved with DLPNO-CCSD(T) if these principles are followed. This is important also in view of the applicability of the method to larger single-reference systems and multinuclear clusters, whose treatment of dynamic correlation would be challenging for multireference-based approaches.

| S-EPMC9202354 | biostudies-literature

Regularized Second-Order Moller-Plesset Theory: A More Accurate Alternative to Conventional MP2 for Noncovalent Interactions and Transition Metal Thermochemistry for the Same Computational Cost.

Project description:Second-order Møller-Plesset theory (MP2) notoriously breaks down for π-driven dispersion interactions and dative bonds in transition metal complexes. Herein, we investigate three physically justified forms of single-parameter, energy-gap dependent regularization which can yield high and transferable accuracy for a variety of noncovalent interactions (including S22, S66, and L7 test sets) and (mostly closed shell) transition metal thermochemistry. Regularization serves to damp overestimated pairwise additive contributions, renormalizing first-order amplitudes such that the effects of higher-order correlations are incorporated. The optimal parameter values for the noncovalent and transition metal sets are 1.1, 0.7, and 0.4 for κ, σ, and σ2 regularizers, respectively. However, such regularization slightly degrades the accuracy of conventional MP2 for some small-molecule test sets, most of which have relatively large average frontier energy gaps. Our results suggest that appropriately regularized MP2 models may improve double hybrid density functionals, at no additional cost over conventional MP2.

| S-EPMC10037552 | biostudies-literature

Probing the Chemistry of Sulfurous Pollutants: Accurate Thermochemistry Determination of Extensive Sulfur-Containing Species.

Project description:Sulfur-containing fuels, such as petroleum fuels, natural gas, and biofuels, produce SO2, SO3, and other highly toxic gases upon combustion, which are harmful to human health and the environment, making it essential to understand their thermochemical properties. This study used high-level quantum chemistry calculations to determine thermodynamic parameters, including entropy, enthalpy, and specific heat capacity for an extensive set of sulfur-containing species. The B3LYP/cc-pVTZ level of theory was used for geometry optimization, vibration frequency, and dihedral scan calculations. To determine an appropriate ab initio method for energy calculation, the Bland-Altman diagram, a statistical analysis method, was employed to visualize the 298 K enthalpy value between experimental data and three sets of ab initio methods: G3, CBS-QB3, and the average of G3 plus CBS-QB3. The CBS-QB3 method exhibited the highest accuracy and was eventually selected for the energy calculation in this study. Thermochemical property parameters were then calculated with the MultiWell program suite for all these sulfur-containing species, and the results were in good agreement with the thermochemical data of organic compounds and the National Institute of Standards and Technology Chemistry WebBook databases. The thermochemical property database established in this study is essential to studying sulfur-containing species in desulfurization.

| S-EPMC11007698 | biostudies-literature

Doubly hybrid density functional for accurate descriptions of nonbond interactions, thermochemistry, and thermochemical kinetics.

Project description:We develop and validate a density functional, XYG3, based on the adiabatic connection formalism and the Görling-Levy coupling-constant perturbation expansion to the second order (PT2). XYG3 is a doubly hybrid functional, containing 3 mixing parameters. It has a nonlocal orbital-dependent component in the exchange term (exact exchange) plus information about the unoccupied Kohn-Sham orbitals in the correlation part (PT2 double excitation). XYG3 is remarkably accurate for thermochemistry, reaction barrier heights, and nonbond interactions of main group molecules. In addition, the accuracy remains nearly constant with system size.

| S-EPMC2664054 | biostudies-literature

Pairing double hybrid functionals with a tailored basis set for an accurate thermochemistry of hydrocarbons.

Project description:A collection of five challenging datasets, including noncovalent interactions, reaction barriers and electronic rearrangements of medium-sized hydrocarbons, has been selected to verify the robustness of double-hybrid functionals used in conjunction with the small DH-SVPD basis set, especially developed for noncovalent interactions. The analysis is completed by other, more standard functionals, for a total of 17 models, including also empirical corrections for dispersion. The obtained results show that the chemical accuracy threshold, that is an error lower than 1.0 kcal mol-1, can be obtained by pairing the nonempirical PBE-QIDH functional with the DH-SVPD basis set, as well as by other semi-empirical functionals, such as DSD-PBEP86, using larger basis sets and empirical corrections. More in general, a significant improvement can be obtained using the DH-SVPD basis set with DHs, without resorting to any empirical corrections. This choice leads to a fast computational protocol that, avoiding any empirical potential, remains on a fully quantum ground.

| S-EPMC9037073 | biostudies-literature

Computational approaches to fMRI analysis.

Project description:Analysis methods in cognitive neuroscience have not always matched the richness of fMRI data. Early methods focused on estimating neural activity within individual voxels or regions, averaged over trials or blocks and modeled separately in each participant. This approach mostly neglected the distributed nature of neural representations over voxels, the continuous dynamics of neural activity during tasks, the statistical benefits of performing joint inference over multiple participants and the value of using predictive models to constrain analysis. Several recent exploratory and theory-driven methods have begun to pursue these opportunities. These methods highlight the importance of computational techniques in fMRI analysis, especially machine learning, algorithmic optimization and parallel computing. Adoption of these techniques is enabling a new generation of experiments and analyses that could transform our understanding of some of the most complex-and distinctly human-signals in the brain: acts of cognition such as thoughts, intentions and memories.

| S-EPMC5457304 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data