997 resultados para Empirical dispersion corrections
Resumo:
The performances of two parametrized functionals (namely B3LYP and B2PYLP) have been compared with those of two non-parametrized functionals (PBE0 and PBE0-DH) on a relatively large benchmark set when three different types of dispersion corrections are applied [namely the D2, D3 and D3(BJ) models]. Globally, the MAD computed using non-parametrized functionals decreases when adding dispersion terms although the accuracy not necessarily increases with the complexity of the model of dispersion correction used. In particular, the D2 correction is found to improve the performances of both PBE0 and PBE0-DH, while no systematic improvement is observed going from D2 to D3 or D3(BJ) corrections. Indeed when including dispersion, the number of sets for which PBE0-DH is the best performing functional decreases at the benefit of B2PLYP. Overall, our results clearly show that inclusion of dispersion corrections is more beneficial to parametrized double-hybrid functionals than to non-parametrized ones. The same conclusions globally hold for the corresponding global hybrids, showing that the marriage between non-parametrized functionals and empirical corrections may be a difficult deal.
Resumo:
An ab initio density functional theory (DFT) study with correction for dispersive interactions was performed to study the adsorption of N2 and CO2 inside an (8, 8) single-walled carbon nanotube. We find that the approach of combining DFT and van der Waals correction is very effective for describing the long-range interaction between N2/CO2 and the carbon nanotube (CNT). Surprisingly, exohedral doping of an Fe atom onto the CNT surface will only affect the adsorption energy of the quadrupolar CO2 molecule inside the CNT (20–30%), and not that of molecular N2. Our results suggest the feasibility of enhancement of CO2/N2 separation in CNT-based membranes by using exohedral doping of metal atoms.
Resumo:
The role of dispersion or van de Waals (VDW) interactions in imidazolium-based room-temperature ionic liquids is studied within the framework of density functional theory, using a recently developed non-empirical functional [M. Dion, H. Rydberg, E. Schroder, D. C. Langreth, and B. I. Lundqvist, Phys. Rev. Lett. 92, 246401 (2004)], as efficiently implemented in the SIESTA code [G. Roman-Perez and J. M. Soler, Phys. Rev. Lett. 103, 096102 (2009)]. We present results for the equilibrium structure and lattice parameters of several crystalline phases, finding a general improvement with respect to both the local density (LDA) and the generalized gradient approximations (GGA). Similar to other systems characterized by VDW bonding, such as rare gas and benzene dimers as well as solid argon, equilibrium distances and volumes are consistently overestimated by approximate to 7%, compared to -11% within LDA and 11% within GGA. The intramolecular geometries are retained, while the intermolecular distances and orientations are significantly improved relative to LDA and GGA. The quality is superior to that achieved with tailor-made empirical VDW corrections ad hoc [M. G. Del Popolo, C. Pinilla, and P. Ballone, J. Chem. Phys. 126, 144705 (2007)]. We also analyse the performance of an optimized version of this non-empirical functional, where the screening properties of the exchange have been tuned to reproduce high-level quantum chemical calculations [J. Klimes, D. Bowler, and A. Michaelides, J. Phys.: Condens. Matter 22, 074203 (2010)]. The results for solids are even better with volumes and geometries reproduced within 2% of experimental data. We provide some insight into the issue of polymorphism of [bmim][Cl] crystals, and we present results for the geometry and energetics of [bmim][Tf] and [mmim][Cl] neutral and charged clusters, which validate the use of empirical force fields. (C) 2011 American Institute of Physics. [doi:10.1063/1.3652897]
Resumo:
Double helical structures of DNA and RNA are mostly determined by base pair stacking interactions, which give them the base sequence-directed features, such as small roll values for the purine-pyrimidine steps. Earlier attempts to characterize stacking interactions were mostly restricted to calculations on fiber diffraction geometries or optimized structure using ab initio calculations lacking variation in geometry to comment on rather unusual large roll values observed in AU/AU base pair step in crystal structures of RNA double helices. We have generated stacking energy hyperspace by modeling geometries with variations along the important degrees of freedom, roll, and slide, which were chosen via statistical analysis as maximally sequence dependent. Corresponding energy contours were constructed by several quantum chemical methods including dispersion corrections. This analysis established the most suitable methods for stacked base pair systems despite the limitation imparted by number of atom in a base pair step to employ very high level of theory. All the methods predict negative roll value and near-zero slide to be most favorable for the purine-pyrimidine steps, in agreement with Calladine's steric clash based rule. Successive base pairs in RNA are always linked by sugar-phosphate backbone with C3-endo sugars and this demands C1-C1 distance of about 5.4 angstrom along the chains. Consideration of an energy penalty term for deviation of C1-C1 distance from the mean value, to the recent DFT-D functionals, specifically B97X-D appears to predict reliable energy contour for AU/AU step. Such distance-based penalty improves energy contours for the other purine-pyrimidine sequences also. (c) 2013 Wiley Periodicals, Inc. Biopolymers 101: 107-120, 2014.
Resumo:
Opening up a band gap and finding a suitable substrate material are two big challenges for building graphene-based nanodevices. Using state-of-the-art hybrid density functional theory incorporating long range dispersion corrections, we investigate the interface between optically active graphitic carbon nitride (g-C3N4) and electronically active graphene. We find an inhomogeneous planar substrate (g-C3N4) promotes electronrich and hole-rich regions, i.e., forming a well-defined electron−hole puddle, on the supported graphene layer. The composite displays significant charge transfer from graphene to the g-C3N4 substrate, which alters the electronic properties of both components. In particular, the strong electronic coupling at the graphene/g-C3N4 interface opens a 70 meV gap in g-C3N4-supported graphene, a feature that can potentially allow overcoming the graphene’s band gap hurdle in constructing field effect transistors. Additionally, the 2-D planar structure of g-C3N4 is free of dangling bonds, providing an ideal substrate for graphene to sit on. Furthermore, when compared to a pure g-C3N4 monolayer, the hybrid graphene/g-C3N4 complex displays an enhanced optical absorption in the visible region, a promising feature for novel photovoltaic and photocatalytic applications.
Resumo:
Carbon nanotubes with specific nitrogen doping are proposed for controllable, highly selective, and reversible CO2 capture. Using density functional theory incorporating long-range dispersion corrections, we investigated the adsorption behavior of CO2 on (7,7) single-walled carbon nanotubes (CNTs) with several nitrogen doping configurations and varying charge states. Pyridinic-nitrogen incorporation in CNTs is found to induce an increasing CO2 adsorption strength with electron injecting, leading to a highly selective CO2 adsorption in comparison with N2. This functionality could induce intrinsically reversible CO2 adsorption as capture/release can be controlled by switching the charge carrying state of the system on/off. This phenomenon is verified for a number of different models and theoretical methods, with clear ramifications for the possibility of implementation with a broader class of graphene-based materials. A scheme for the implementation of this remarkable reversible electrocatalytic CO2-capture phenomenon is considered.
Resumo:
The accuracy and reliability of popular density functional approximations for the compounds giving origin to room temperature ionic liquids have been assessed by computing the T=0 K crystal structure of several 1-alkyl-3-methyl-imidazolium salts. Two prototypical exchange-correlation approximations have been considered, i.e., the local density approximation (LDA) and one gradient corrected scheme [PBE-GGA, Phys. Rev. Lett. 77, 3865 (1996)]. Comparison with low-temperature x-ray diffraction data shows that the equilibrium volume predicted by either approximations is affected by large errors, nearly equal in magnitude (~10%), and of opposite sign. In both cases the error can be traced to a poor description of the intermolecular interactions, while the intramolecular structure is fairly well reproduced by LDA and PBE-GGA. The PBE-GGA optimization of atomic positions within the experimental unit cell provides results in good agreement with the x-ray structure. The correct system volume can also be restored by supplementing PBE-GGA with empirical dispersion terms reproducing the r-6 attractive tail of the van der Waals interactions.
Resumo:
Abstract The dehydrogenation of cyclohexanol to cyclohexanone is very important in the manufacture of nylon. Copper-based catalysts are the most popular catalysts for this reaction, and on these catalysts the reaction mechanism and active site are in debate. In order to elucidate the mechanism and active site of the cyclohexanol dehydrogenation on copper-based catalysts, density functional theory with dispersion corrections were performed on up to six facets of copper in two different oxidation states: monovalent copper and metallic copper. By calculating the surface energies of these facets, Cu(111) and Cu2O(111) were found to be the most stable facets for metallic copper and for monovalent copper, respectively. On these two facets, all the possible elementary steps in the dehydrogenation pathway of cyclohexanol were calculated, including the adsorption, dehydrogenation, hydrogen coupling and desorption. Two different reaction pathways for dehydrogenation were considered on both surfaces. It was revealed that the dehydrogenation mechanisms are different on these two surfaces: on Cu(111) the hydrogen belonging to the hydroxyl is removed first, then the hydrogen belonging to the carbon is subtracted, while on Cu2O(111) the hydrogen belonging to the carbon is removed followed by the subtraction of the hydrogen in the hydroxyl group. Furthermore, by comparing the energy profiles of these two surfaces, Cu2O(111) was found to be more active for cyclohexanol dehydrogenation than Cu(111). In addition, we found that the coordinatively unsaturated copper sites on Cu2O(111) are the reaction sites for all the steps. Therefore, the coordinatively unsaturated copper site on Cu2O(111) is likely to be the active site for cyclohexanol dehydrogenation on the copper-based catalysts.
Resumo:
Optimal estimation (OE) improves sea surface temperature (SST) estimated from satellite infrared imagery in the “split-window”, in comparison to SST retrieved using the usual multi-channel (MCSST) or non-linear (NLSST) estimators. This is demonstrated using three months of observations of the Advanced Very High Resolution Radiometer (AVHRR) on the first Meteorological Operational satellite (Metop-A), matched in time and space to drifter SSTs collected on the global telecommunications system. There are 32,175 matches. The prior for the OE is forecast atmospheric fields from the Météo-France global numerical weather prediction system (ARPEGE), the forward model is RTTOV8.7, and a reduced state vector comprising SST and total column water vapour (TCWV) is used. Operational NLSST coefficients give mean and standard deviation (SD) of the difference between satellite and drifter SSTs of 0.00 and 0.72 K. The “best possible” NLSST and MCSST coefficients, empirically regressed on the data themselves, give zero mean difference and SDs of 0.66 K and 0.73 K respectively. Significant contributions to the global SD arise from regional systematic errors (biases) of several tenths of kelvin in the NLSST. With no bias corrections to either prior fields or forward model, the SSTs retrieved by OE minus drifter SSTs have mean and SD of − 0.16 and 0.49 K respectively. The reduction in SD below the “best possible” regression results shows that OE deals with structural limitations of the NLSST and MCSST algorithms. Using simple empirical bias corrections to improve the OE, retrieved minus drifter SSTs are obtained with mean and SD of − 0.06 and 0.44 K respectively. Regional biases are greatly reduced, such that the absolute bias is less than 0.1 K in 61% of 10°-latitude by 30°-longitude cells. OE also allows a statistic of the agreement between modelled and measured brightness temperatures to be calculated. We show that this measure is more efficient than the current system of confidence levels at identifying reliable retrievals, and that the best 75% of satellite SSTs by this measure have negligible bias and retrieval error of order 0.25 K.
Resumo:
Nowadays, dispersion correction applied on layered semiconductors is a topic of interest. Among the known layered semiconductors, SnS2 polytypes are wide gap semiconductors with a van der Waals interaction between their layers, which could form good materials to be used in photovoltaic applications. The present work gives an approach to the SnS2 geometrical and electronic characterization using an empirical dispersion correction added to the Perdew–Burke–Ernzerhof functional and subsequent actualization of the electronic charge density using the screened hybrid Heyd–Scuseria–Ernzerhof functional using a density functional code. The obtained interlayer distance and band-gap are in good agreement with experimental values when van der Waals dispersion forces are included.
Resumo:
The DAPPLE (Dispersion of Air Pollutants and their Penetration into the Local Environment) project seeks to characterise near-field urban atmospheric dispersion using a multidisciplinary approach. In this paper we report on the first tracer dispersion experiment carried out in May 2003. Results of concurrent meteorological measurements are presented. Variations of receptor tracer concentration with time are presented. Meteorological observations suggest that in-street channelling and flow-switching at intersections take place. A comparison between roof top and surface measurements suggest that rapid vertical mixing occurs, and a comparison between a simple dispersion model and maximum concentrations observed are presented
Resumo:
Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites
Resumo:
This paper investigates relationship between traffic conditions and the crash occurrence likelihood (COL) using the I-880 data. To remedy the data limitations and the methodological shortcomings suffered by previous studies, a multiresolution data processing method is proposed and implemented, upon which binary logistic models were developed. The major findings of this paper are: 1) traffic conditions have significant impacts on COL at the study site; Specifically, COL in a congested (transitioning) traffic flow is about 6 (1.6) times of that in a free flow condition; 2)Speed variance alone is not sufficient to capture traffic dynamics’ impact on COL; a traffic chaos indicator that integrates speed, speed variance, and flow is proposed and shows a promising performance; 3) Models based on aggregated data shall be interpreted with caution. Generally, conclusions obtained from such models shall not be generalized to individual vehicles (drivers) without further evidences using high-resolution data and it is dubious to either claim or disclaim speed kills based on aggregated data.
Resumo:
In this paper, a class of fractional advection–dispersion models (FADMs) is considered. These models include five fractional advection–dispersion models, i.e., the time FADM, the mobile/immobile time FADM with a time Caputo fractional derivative 0 < γ < 1, the space FADM with two sides Riemann–Liouville derivatives, the time–space FADM and the time fractional advection–diffusion-wave model with damping with index 1 < γ < 2. These equations can be used to simulate the regional-scale anomalous dispersion with heavy tails. We propose computationally effective implicit numerical methods for these FADMs. The stability and convergence of the implicit numerical methods are analysed and compared systematically. Finally, some results are given to demonstrate the effectiveness of theoretical analysis.
Resumo:
We consider the space fractional advection–dispersion equation, which is obtained from the classical advection–diffusion equation by replacing the spatial derivatives with a generalised derivative of fractional order. We derive a finite volume method that utilises fractionally-shifted Grünwald formulae for the discretisation of the fractional derivative, to numerically solve the equation on a finite domain with homogeneous Dirichlet boundary conditions. We prove that the method is stable and convergent when coupled with an implicit timestepping strategy. Results of numerical experiments are presented that support the theoretical analysis.