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NASA NTRS1997

Formation and Combustion of Unconfined Drop Clusters in Microgravity

Single-drop and droplet array studies have become common methods to isolate and investigate the effects of any of the complexities that enter into the drop combustion process. Microgravity environments are required to allow larger drops to be studied while minimizing or eliminating the confounding effects of buoyancy. Based on the results from current isolated drop, drop array, and spray studies funded through the Microgravity Science and Applications Division, it has become clear that even with the effects of buoyancy removed, the extrapolation of results from droplet array studies to spray flames is difficult. The problem occurs because even the simplest spray systems introduce complexities of multi-disperse drop sizes and drop-drop interactions, coupled with more complicated fluid dynamics. Not only do these features make the interpretation of experimental data difficult, they also make the problem very difficult to analyze computationally. Group combustion models, in which the interaction between droplets is treated on a statistical manner, have become a popular method to investigate the behavior of large numbers of interacting droplets, particularly through the work of Ryan et al. and Bellan and co-workers. While these models idealize the actual spray systems to a point where they can be treated computationally, the experimental analogy to these models is difficult to achieve because it requires the formation and Combustion of drop clusters without the effects of buoyancy. Therefore, even though these models have provided useful and insightful information, the verification of the results by direct comparison with experimental data is still lacking.

Liu, S.↗
NASA NTRS2006

Application of Density Functional Theory to Systems Containing Metal Atoms

The accuracy of density functional theory (DFT) for problems involving metal atoms is considered. The DFT results are compared with experiment as well as results obtained using the coupled cluster approach. The comparisons include geometries, frequencies, and bond energies. The systems considered include MO2, M(OH)+n, MNO+, and MCO+2. The DFT works well for frequencies and geometries, even in case with symmetry breaking; however, some examples have been found where the symmetry breaking is quite severe and the DFT methods do not work well. The calculation of bond energies is more difficult and examples of successes as well as failures of DFT will be given.

Bauschlicher, Charles W., Jr.↗
NASA NTRS1997

Application of Density Functional Theory to Systems Containing Metal Atoms

The accuracy of density functional theory (DFT) for problems involving metal atoms is considered. The DFT results are compared with experiment as well as results obtained using the coupled cluster approach. The comparisons include geometries, frequencies, and bond energies. The systems considered include MO2, M(OH)+(sub n), MNO+, and MCO+(sub 2). The DFT works well for frequencies and geometries, even in cases with symmetry breaking; however, some examples have been found where the symmetry breaking is quite severe and the DFT methods do not work well. The calculation of bond energies is more difficult and examples of the successes as well as failures of DFT will be given.

Bauschlicher, Charles W., Jr.↗
NASA NTRS1992

Computational studies of metal-metal and metal-ligand interactions

The geometric structure of Cr(CO)6 is optimized at the modified coupled-pair functional (MCPF), single and double excitation coupled-cluster (CCSD) and CCSD(T) levels of theory (including a perturbational estimate for connected triple excitations), and the force constants for the totally symmetric representation are determined. The geometry of Cr(CO)5 is partially optimized at the MCPF, CCSD and CCSD(T) levels of theory. Comparison with experimental data shows that the CCSD(T) method gives the best results for the structures and force constants, and that remaining errors are probably due to deficiencies in the one-particle basis sets used for CO. A detailed comparison of the properties of free CO is therefore given, at both the MCPF and CCSD/CCSD(T) levels of treatment, using a variety of basis sets. With very large one-particle basis sets, the SSCD(T) method gives excellent results for the bond distance, dipole moment and harmonic frequency of free CO. The total binding energies of Cr(CO)6 and Cr(CO)5 are also determined at the MCPF, CCSD and CCSD(T) levels of theory. The CCSD(T) method gives a much larger total binding energy than either the MCPF or CCSD methods. An analysis of the basis set superposition error (BSSE) at the MCPF level of treatment points out limitations in the one-particle basis used here and in a previous study. Calculations using larger basis sets reduced the BSSE, but the total binding energy of Cr(CO)6 is still significantly smaller than the experimental value, although the first CO bond dissociation energy of Cr(CO)6 is well described. An investigation of 3s3p correlation reveals only a small effect. The remaining discrepancy between the experimental and theoretical total binding energy of Cr(CO)6 is probably due to limitations in the one-particle basis, rather than limitations in the correlation treatment. In particular an additional d function and an f function on each C and O are needed to obtain quantitative results. This is underscored by the fact that even using a very large primitive se (1042 primitive functions contracted to 300 basis functions), the superposition error for the total binding energy of Cr(CO)6 is 22 kcal/mol at the MCPF level of treatment.

Barnes, Leslie A.↗
NASA NTRS1992

The structure and energetics of Cr(CO)6 and Cr(CO)5

The geometric structure of Cr(CO)6 is optimized at the modified coupled pair functional (MCPF), single and double excitation coupled-cluster (CCSD) and CCSD(T) levels of theory (including a perturbational estimate for connected triple excitations), and the force constants for the totally symmetric representation are determined. The geometry of Cr(CO)5 is partially optimized at the MCPF, CCSD, and CCSD(T) levels of theory. Comparison with experimental data shows that the CCSD(T) method gives the best results for the structures and force constants, and that remaining errors are probably due to deficiencies in the one-particle basis sets used for CO. The total binding energies of Cr(CO)6 and Cr(CO)5 are also determined at the MCPF, CCSD, and CCSD(T) levels of theory. The CCSD(T) method gives a much larger total binding energy than either the MCPF or CCSD methods. An analysis of the basis set superposition error (BSSE) at the MCPF level of treatment points out limitations in the one-particle basis used. Calculations using larger basis sets reduce the BSSE, but the total binding energy of Cr(CO)6 is still significantly smaller than the experimental value, although the first CO bond dissociation energy of Cr(CO)6 is well described. An investigation of 3s3p correlation reveals only a small effect. In the largest basis set, the total CO binding energy of Cr(CO)6 is estimated to be 140 kcal/mol at the CCSD(T) level of theory, or about 86 percent of the experimental value. The remaining discrepancy between the experimental and theoretical value is probably due to limitations in the one-particle basis, rather than limitations in the correlation treatment. In particular an additional d function and an f function on each C and O are needed to obtain quantitative results. This is underscored by the fact that even using a very large primitive set (1042 primitive functions contracted to 300 basis functions), the superposition error for the total binding energy of Cr(CO)6 is 22 kcal/mol at the MCPF level of treatment.

Barnes, Leslie A.↗
NASA NTRS2001

Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

LeMoigne, Jacqueline↗
NASA NTRS2005

Testing the Archivas Cluster (Arc) for Ozone Monitoring Instrument (OMI) Scientific Data Storage

The Ozone Monitoring Instrument (OMI) launched on NASA's Aura Spacecraft, the third of the major platforms of the EOS program on July 15,2004. In addition to the long term archive and distribution of the data from OM1 through the Goddard Earth Science Distributed Active Archive Center (GESDAAC), we are evaluating other archive mechanisms that can archive the data in a more immediately available method where it can be used for futher data production and analysis. In 2004, Archivas, Inc. was selected by NASA s Small Business Innovative Research (SBIR) program for the development of their Archivas Cluster (ArC) product. Arc is an online disk based system utilizing self-management and automation on a Linux cluster. Its goal is to produce a low cost solution coupled with the ease of management. The OM1 project is an application partner of the SBIR program, and has deployed a small cluster (5TB) based on the beta Archwas software. We performed extensive testing of the unit using production OM1 data since launch. In 2005, Archivas, Inc. was funded in SBIR Phase II for further development, which will include testing scalability with the deployment of a larger (35TB) cluster at Goddard. We plan to include Arc in the OM1 Team Leader Computing Facility (TLCF) hosting OM1 data for direct access and analysis by the OMI Science Team. This presentation will include a brief technical description of the Archivas Cluster, a summary of the SBIR Phase I beta testing results, and an overview of the OMI ground data processing architecture including its interaction with the Phase II Archivas Cluster and hosting of OMI data for the scientists.

Tilmes, Curt↗
NASA NTRS1996

Adaptive grid methods for RLV environment assessment and nozzle analysis

Rapid access to highly accurate data about complex configurations is needed for multi-disciplinary optimization and design. In order to efficiently meet these requirements a closer coupling between the analysis algorithms and the discretization process is needed. In some cases, such as free surface, temporally varying geometries, and fluid structure interaction, the need is unavoidable. In other cases the need is to rapidly generate and modify high quality grids. Techniques such as unstructured and/or solution-adaptive methods can be used to speed the grid generation process and to automatically cluster mesh points in regions of interest. Global features of the flow can be significantly affected by isolated regions of inadequately resolved flow. These regions may not exhibit high gradients and can be difficult to detect. Thus excessive resolution in certain regions does not necessarily increase the accuracy of the overall solution. Several approaches have been employed for both structured and unstructured grid adaption. The most widely used involve grid point redistribution, local grid point enrichment/derefinement or local modification of the actual flow solver. However, the success of any one of these methods ultimately depends on the feature detection algorithm used to determine solution domain regions which require a fine mesh for their accurate representation. Typically, weight functions are constructed to mimic the local truncation error and may require substantial user input. Most problems of engineering interest involve multi-block grids and widely disparate length scales. Hence, it is desirable that the adaptive grid feature detection algorithm be developed to recognize flow structures of different type as well as differing intensity, and adequately address scaling and normalization across blocks. These weight functions can then be used to construct blending functions for algebraic redistribution, interpolation functions for unstructured grid generation, forcing functions to attract/repel points in an elliptic system, or to trigger local refinement, based upon application of an equidistribution principle. The popularity of solution-adaptive techniques is growing in tandem with unstructured methods. The difficultly of precisely controlling mesh densities and orientations with current unstructured grid generation systems has driven the use of solution-adaptive meshing. Use of derivatives of density or pressure are widely used for construction of such weight functions, and have been proven very successful for inviscid flows with shocks. However, less success has been realized for flowfields with viscous layers, vortices or shocks of disparate strength. It is difficult to maintain the appropriate mesh point spacing in the various regions which require a fine spacing for adequate resolution. Mesh points often migrate from important regions due to refinement of dominant features. An example of this is the well know tendency of adaptive methods to increase the resolution of shocks in the flowfield around airfoils, but in the incorrect location due to inadequate resolution of the stagnation region. This problem has been the motivation for this research.

Thornburg, Hugh J.↗
NASA NTRS2016

K-Shell Photoabsorption and Photoionisation of Trace Elements I. Isoelectronic Sequences With Electron Number 3< or = N < or = 11

Context. With the recent launching of the Hitomi X-ray space observatory, K lines and edges of chemical elements with low cosmic abundances, namely F, Na, P, Cl, K, Sc, Ti, V, Cr, Mn, Co, Cu and Zn, can be resolved and used to determine important properties of supernova remnants, galaxy clusters and accreting black holes and neutron stars.Aims. The second stage of the present ongoing project involves the computation of the accurate photoabsorption and photoionisation cross sections required to interpret the X-ray spectra of such trace elements.Methods. Depending on target complexity and computer tractability, ground-state cross sections are computed either with the close-coupling Breit-Pauli R-matrix method or with the autostructure atomic structure code in the isolated-resonance approximation. The intermediate-coupling scheme is used whenever possible. In order to determine a realistic K-edge behaviour for each species, both radiative and Auger dampings are taken into account, the latter being included in the R-matrix formalism by means of an optical potential.Results. Photoabsorption and total and partial photoionisation cross sections are reported for isoelectronic sequences with electron numbers 3< or = N< or = 11. The Na sequence (N=11) is used to estimate the contributions from configurations with a 2s hole (i.e. [2s]) and those containing 3d orbitals, which will be crucial when considering sequences with N 11.Conclusions. It is found that the [2s/u] configurations must be included in the target representations of species with N> 11 as they contribute significantly to the monotonic background of the cross section between the L and K edges. Configurations with 3d orbitals are important in rendering an accurate L edge, but they can be practically neglected in the K-edge region.

atomic data / X-rays: general↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗
NASA NTRS1994

Two-fluid simulations of galaxy formation

We investigate the formation of galaxies and larger structure with a simulation modeling two gravitationally coupled fluids representing dark matter and baryons. The baryon gas dynamics are calculated with a smoothed particle hydrodynamics (SPH) method, and the physics modeled includes thermal pressure, shock heating, and radiative cooling. We simulate a 16 Mpc periodic cube with 64(exp 3) particles in each fluid and 10% baryon mass fraction. We confirm, for the first time experimentally, disk formation as a natural consequence of hierarchical clustering in a large-scale cosmological environment. The majority of isolated galaxies exhibit centrifugally supported disks. A power-law relation between cold baryonic mass and maximum rotation velocity is found, M varies as nu(sub rot)(exp alpha) with alpha = 2.5 after correcting for differential numerical resolution. Both the spatial and velocity distributions of the simulated galaxies are biased with respect to the dark matter. A counts-in-cells analysis indicates that an unphysical degree of merging in the central cluster is likely responsible for the antibias signal in the correlation function. A robust, scale-dependent velocity bias is measured. The ratio of galaxy to dark matter pairwise velocity dispersions on a scale of 1 Mpc is 0.7. The amplitude is only mildly dependent on redshift or mass cutoff and scales with separation as r(exp 0.2). The degree to which these results depend on numerical parameters is discussed. Mass resolution plays a key role in controlling the resulting fraction of cold, dense baryons. The mass fraction associated with galaxies decreases by a factor of approximately greater than 3 when the mass per particle is increased by a factor 8. Photoionization and energy input from supernova will have to be included to determine more carefully the fraction of highly dissipated material and the characteristics of the stellar component of galaxies.

Evrard, August E.↗
NASA NTRS1999

An Intercomparison Between Radar Reflectivity and the IR Cloud Classification Technique for the TOGA-COARE Area

Satellite infrared (IR) and visible (VIS) images from the Tropical Ocean Global Atmosphere - Coupled Ocean Atmosphere Response Experiment (TOGA-COARE) experiment are investigated through the use of Clustering Analysis. The clusters are obtained from the values of IR and VIS counts and the local variance for both channels. The clustering procedure is based on the standardized histogram of each variable obtained from 179 pairs of images. A new approach to classify high clouds using only IR and the clustering technique is proposed. This method allows the separation of the enhanced convection in two main classes: convective tops, more closely related to the most active core of the storm, and convective systems, which produce regions of merged, thick anvil clouds. The resulting classification of different portions of cloudiness is compared to the radar reflectivity field for intensive events. Convective Systems and Convective Tops are followed during their life cycle using the IR clustering method. The areal coverage of precipitation and features related to convective and stratiform rain is obtained from the radar for each stage of the evolving Mesoscale Convective Systems (MCS). In order to compare the IR clustering method with a simple threshold technique, two IR thresholds (Tir) were used to identify different portions of cloudiness, Tir=240K which roughly defines the extent of all cloudiness associated with the MCS, and Tir=220K which indicates the presence of deep convection. It is shown that the IR clustering technique can be used as a simple alternative to identify the actual portion of convective and stratiform rainfall.

Carvalho, L. M. V.↗
NASA NTRS2017

Large-Scale Circulation and Climate Variability

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Perlwitz, J.↗
NASA NTRS1992

Automation of disbond detection in aircraft fuselage through thermal image processing

A procedure for interpreting thermal images obtained during the nondestructive evaluation of aircraft bonded joints is presented. The procedure operates on time-derivative thermal images and resulted in a disbond image with disbonds highlighted. The size of the 'black clusters' in the output disbond image is a quantitative measure of disbond size. The procedure is illustrated using simulation data as well as data obtained through experimental testing of fabricated samples and aircraft panels. Good results are obtained, and, except in pathological cases, 'false calls' in the cases studied appeared only as noise in the output disbond image which was easily filtered out. The thermal detection technique coupled with an automated image interpretation capability will be a very fast and effective method for inspecting bonded joints in an aircraft structure.

Prabhu, D. R.↗
NASA NTRS1994

UBV stellar photometry of the 30 Doradus region of the large Magellanic Cloud with the Hubble Space Telescope

We report on Planetary Camera observations of the central region of 30 Doradus in the Large Magellanic Cloud (LMC). These images of 30 Doradus are the first `deep' Hubble Space Telescope (HST) exposures that have appropriate photometric calibration. The B band (F439W) image, which shows R136a at the center of the PC6 charge coupled device (CCD) chip, reveals over 200 stars within 3 sec of the center of R13a, and over 800 stars in a 35 sec x 35 sec area. We used Malumuth et al.'s (1991) Point Spread Function (PSF)-fitting method to measure the magnitudes of all stars on the PC6 chip. These new B magnitudes, along with U and V magnitudes from archival PC images, yield a luminosity function, mass density profile, and initial mass function of the 30 Doradus ionizing cluster. The mass distribution is well fit by a King model with a core radius, R(sub c) = 0.96 sec (0.24 pc), a tidal radius, R(sub t) = 110 sec (28 pc), and a total mass, Mass = 16,800 solar mass. Both the luminosity function and initial mass function show evidence for mass segregation, in the sense that the central region has a higher fraction of massive stars than the outer regions. This is the first observational evidence for mass segregation in a very young cluster (age approximately 3 million years). The observations admit the hypothesis that the mass segregation occurred in the process of star formation and/or that the mass segregation is the result of dynamical evolution.

Malumuth, Eliot M.↗
NASA NTRS2007

Enhanced Elliptic Grid Generation

An enhanced method of elliptic grid generation has been invented. Whereas prior methods require user input of certain grid parameters, this method provides for these parameters to be determined automatically. "Elliptic grid generation" signifies generation of generalized curvilinear coordinate grids through solution of elliptic partial differential equations (PDEs). Usually, such grids are fitted to bounding bodies and used in numerical solution of other PDEs like those of fluid flow, heat flow, and electromagnetics. Such a grid is smooth and has continuous first and second derivatives (and possibly also continuous higher-order derivatives), grid lines are appropriately stretched or clustered, and grid lines are orthogonal or nearly so over most of the grid domain. The source terms in the grid-generating PDEs (hereafter called "defining" PDEs) make it possible for the grid to satisfy requirements for clustering and orthogonality properties in the vicinity of specific surfaces in three dimensions or in the vicinity of specific lines in two dimensions. The grid parameters in question are decay parameters that appear in the source terms of the inhomogeneous defining PDEs. The decay parameters are characteristic lengths in exponential- decay factors that express how the influences of the boundaries decrease with distance from the boundaries. These terms govern the rates at which distance between adjacent grid lines change with distance from nearby boundaries. Heretofore, users have arbitrarily specified decay parameters. However, the characteristic lengths are coupled with the strengths of the source terms, such that arbitrary specification could lead to conflicts among parameter values. Moreover, the manual insertion of decay parameters is cumbersome for static grids and infeasible for dynamically changing grids. In the present method, manual insertion and user specification of decay parameters are neither required nor allowed. Instead, the decay parameters are determined automatically as part of the solution of the defining PDEs. Depending on the shape of the boundary segments and the physical nature of the problem to be solved on the grid, the solution of the defining PDEs may provide for rates of decay to vary along and among the boundary segments and may lend itself to interpretation in terms of one or more physical quantities associated with the problem.

Kaul, Upender K.↗
NASA NTRS1995

Disruption of the Globular Cluster Pal 5

Orbit calculations suggest that the sparse globular cluster, Pal 5, will pass within 7 kpc of the Galactic center the next time it crosses the plane, where it might be destroyed by tidal stresses. We study this problem, treating Pal 5 as a self-consistent dynamical system orbiting through an external potential that represents the Galaxy. The first part of the problem is to find suitable analytic approximations to the Galactic potential. They must be valid in all regions the cluster is likely to explore. Observed velocity and positional data for Pal 5 are used as initial conditions to determine the orbit. Methods we used for a different problem some 12 years ago have been adapted to this problem. Three experiments have been run, with M/L= 1, 3, and 10, for the cluster model. The cluster blew up shortly after passing through the Galactic plane (about 130 Myrs after the beginning of the run) with M/L=1. At M/L = 3 and 10 the cluster survived, although it got quite a kick in the fundamental mode on passing through the plane. But the fundamental mode oscillation died out in a couple of oscillation cycles at M/L=10. Pal 5 will probably be destroyed on its next crossing of the Galactic plane if M/L=1, but it can survive (albeit with fairly heavy damage) if NI/L=3. We haven't tried to trap the mass limits more closely than that. Pal 5 comes through pretty well unscathed at M/L=10. An interesting follow-up experiment would be to back the cluster up along its orbit to look at its previous passage through the Galactic plane, to see what kind of object it might have been at earlier times.

Miller, R. H.↗
NASA NTRS1993

The (FHCl)- molecular anion - Structural aspects, global surface, and vibrational eigenspectrum

State of the art ab initio electronic structure methods have been used to investigate the (FHCl)- molecular anion. It is proposed that the geometric structure and binding energies of the complex are r(e)(H-F) = 0.963 +/- 0.003 A, R(e)(H-Cl) = 1.925 +/- 0.015 A, and D0(HF + Cl(-)) = 21.8 +/- 0.4 kcal/mol. A Morokuma decomposition of the ion-molecular bonding give the following electrostatic, polarization, exchange repulsion, dispersion, and charge-transfer plus higher-order mixing components of the vibrationless complexation energy: -27.3, -5.2, +18.3, -4.5, and -5.0 kcal/mol, respectively. A couples cluster single and doubles global surface is constructed from 208 and 228 energy points for linear and bent configurations, respectively, these being fit to rms errors of only 3.9 and 9.3/cm, respectively, below 8000/cm. Converged J = 0 and J = 1 variational eigenstates of the (FHCl)- surface to near the HF + Cl(-) dissociation threshold are determined. The fundamental vibrational frequencies are found to be nu1 = 247/cm, nu2 = 876/cm, and nu3 = 2884/cm. The complete vibrational eigenspectrum is analyzed.

Klepeis, Neil E.↗