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Differential cross sections for electron impact excitation of the electronic bands of phenol

We report results from a joint theoretical and experimental investigation into electron scattering from the important organic species phenol (C{sub 6}H{sub 5}OH). Specifically, differential cross sections (DCSs) have been measured and calculated for the electron-impact excitation of the electronic states of C{sub 6}H{sub 5}OH. The measurements were carried out at energies in the range 15–40 eV, and for scattered-electron angles between 10{sup ∘} and 90{sup ∘}. The energy resolution of those experiments was typically ∼80 meV. Corresponding Schwinger multichannel method with pseudo-potentials calculations, with and without Born-closure, were also performed for a sub-set of the excited electronic-states that were accessed in the measurements. Those calculations were conducted at the static exchange plus polarisation (SEP)-level using a minimum orbital basis for single configuration interaction (MOBSCI) approach. Agreement between the measured and calculated DCSs was typically fair, although to obtain quantitative accord, the theory would need to incorporate even more channels into the MOBSCI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Going Forward with the Nancy Grace Roman Space Telescope Transient Survey: Validation of Precision Forward-modeling Photometry for Undersampled Imaging

The Nancy Grace Roman Space Telescope (Roman) is an observatory for both wide-field observations and coronagraphy that is scheduled for launch in the mid-2020s. Part of the planned survey is a deep, cadenced field or fields that enable cosmological measurements with type Ia supernovae (SNe Ia). With a pixel scale of 0$_.^"$11, the Wide Field Instrument will be undersampled, presenting a difficulty for precisely subtracting the galaxy light underneath the SNe. We use simulated data to validate the ability of a forward-model code (such codes are frequently also called “scene-modeling” codes) to perform precision supernova photometry for the Roman SN survey. Our simulation includes over 760,000 image cutouts around SNe Ia or host galaxies (~10% of a full-scale survey). To have a realistic 2D distribution of underlying galaxy light, we use the VELA simulated high-resolution images of galaxies. We run each set of cutouts through our forward-modeling code which automatically measures time-dependent SN fluxes. Given our assumed inputs of a perfect model of the instrument point-spread functions and calibration, we find biases at the millimagnitude level from this method in four red filters (Y106, J129, H158, and F184), easily meeting the 0.5% Roman inter-filter calibration requirement for a cutting-edge measurement of cosmological parameters using SNe Ia. Simulated data in the bluer Z087 filter shows larger ~ 2–3 mmg biases, also meeting this requirement, but with more room for improvement. Our forward-model code has been released on Zenodo.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-E-T-123: Dosimetric Comparison Between Portrait and Landscape Orientations in Radiochromic Film Dosimetry

Purpose: To compare the dosimetric properties of radiochromic films with different orientation. Methods: A sheet of EBT3 film was cut into eight pieces with the following sizes: 15×15 cm2 (one piece), 5x15 cm{sup 2} (two) and 4×5 cm{sup 2} (five). A set of two EBT3 sheets was used at each dose level. Two sets were used changing the delivered doses (1 and 2 Gy). The 5×15 cm{sup 2} pieces were rotated by 90 degrees in relation to each other, such that one had landscape orientation and the other had portrait orientation. All 5×15 cm2 pieces were irradiated with their long side aligned with the x-axis of the radiation field. The 15×15 cm{sup 2} pieces were irradiated rotated at 90 degrees to each other. Five pieces, (a total of ten from two sheets) were used to obtain a calibration curve. The irradiated films were scanned using an Epson ES-2200 scanner and were analyzed using ImageJ software. In this study, no correction was applied for the nonuniform scanner signal that is evident in the direction of the scanner lamp. Each film piece was scanned both in portrait and landscape orientations. Dosimetric comparisons of the beam profiles were made in terms of the film orientations (portrait and landscape) and scanner bed directions (perpendicular and parallel to the scanner movement). Results: In general, portrait orientation exhibited higher noise than landscape and was adversely affected to a great extent by the nonuniformity in the direction of the scanner lamp. A significant difference in the measured field widths between the perpendicular and parallel directions was found for both orientations. Conclusion: Without correction for the nonuniform scanner signal in the direction of the scanner lamp, a landscape orientation is preferable. A more detailed investigation is planned to evaluate quantitatively the effect of orientation on the dosimetric properties of a film.

60 APPLIED LIFE SCIENCES↗

SU-F-T-186: A Treatment Planning Study of Normal Tissue Sparing with Robustness Optimized IMPT, 4Pi IMRT, and VMAT for Head and Neck Cases

Purpose: We performed a retrospective dosimetric comparison study between the robustness optimized Intensity Modulated Proton Therapy (RO-IMPT), volumetric-modulated arc therapy (VMAT), and the non-coplanar 4? intensity modulated radiation therapy (IMRT). These methods represent the most advanced radiation treatment methods clinically available. We compare their dosimetric performance for head and neck cancer treatments with special focus on the OAR sparing near the tumor volumes. Methods: A total of 11 head and neck cases, which include 10 recurrent cases and one bilateral case, were selected for the study. Different dose levels were prescribed to tumor target depending on disease and location. Three treatment plans were created on commercial TPS systems for a novel noncoplanar 4π method (20 beams), VMAT, and RO-IMPT technique (maximum 4 fields). The maximum patient positioning error was set to 3 mm and the maximum proton range uncertainty was set to 3% for the robustness optimization. Line dose profiles were investigated for OARs close to tumor volumes. Results: All three techniques achieved 98% coverage of the CTV target and most photon plans had less than 110% of the hot spots. The RO-IMPT plans show superior tumor dose homogeneity than 4? and VMAT plans. Although RO-IMPT has greater R50 dose spillage to the surrounding normal tissue than 4π and VMAT, the RO-IMPT plans demonstrate better or comparable OAR (parotid, mandible, carotid, oral cavity, pharynx, and etc.) sparing for structures closely abutting tumor targets. Conclusion: The RO-IMPT’s ability of OAR sparing is benchmarked against the C-arm linac based non-coplanar 4π technique and the standard VMAT method. RO-IMPT consistently shows better or comparable OAR sparing even for tissue structures closely abutting treatment target volume. RO-IMPT further reduces treatment uncertainty associated with proton therapy and delivers robust treatment plans to both unilateral and bilateral head and neck cancer patients with desirable treatment time.

60 APPLIED LIFE SCIENCES↗

TU-G-204-05: The Effects of CT Acquisition and Reconstruction Conditions On Computed Texture Feature Values of Lung Lesions

Purpose: Texture features have been investigated as a biomarker of response and malignancy. Because these features reflect local differences in density, they may be influenced by acquisition and reconstruction parameters. The purpose of this study was to investigate the effects of radiation dose level and reconstruction method on features derived from lung lesions. Methods: With IRB approval, 33 lung tumor cases were identified from clinically indicated thoracic CT scans in which the raw projection (sinogram) data were available. Based on a previously-published technique, noise was added to the raw data to simulate reduced-dose versions of each case at 25%, 10% and 3% of the original dose. Original and simulated reduced dose projection data were reconstructed with conventional and two iterative-reconstruction settings, yielding 12 combinations of dose/recon conditions. One lesion from each case was contoured. At the reference condition (full dose, conventional recon), 17 lesions were randomly selected for repeat contouring (repeatability). For each lesion at each dose/recon condition, 151 texture measures were calculated. A paired differences approach was employed to compare feature variation from repeat contours at the reference condition to the variation observed in other dose/recon conditions (reproducibility). The ratio of standard deviation of the reproducibility to repeatability was used as the variation measure for each feature. Results: The mean variation (standard deviation) across dose levels and kernel was significantly different with a ratio of 2.24 (±5.85) across texture features (p=0.01). The mean variation (standard deviation) across dose levels with conventional recon was also significantly different with 2.30 (7.11) (p=0.025). The mean variation across reconstruction settings of original dose has a trend in showing difference with 1.35 (2.60) among all features (p=0.09). Conclusion: Texture features varied considerably with variations in dose and reconstruction condition. Care should be taken to standardize these conditions when using texture as a quantitative feature. This effort supported in part by a grant from the National Cancer Institute’s Quantitative Imaging Network (QIN): U01 CA181156; The UCLA Department of Radiology has a Master Research Agreement with Siemens Healthcare; Dr. McNitt-Gray has previously received research support from Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗

Power increases using wind direction spatial filtering for wind farm control: Evaluation using FLORIS, modified for dynamic settings

As wind energy plays a growing role in the energy sector, new methods for controlling wind turbines and wind farms to maximize performance are garnering industry interest. A developing body of research treats the entire wind farm as a control system, with individual turbines acting as agents in a network, allowing farm-level objectives to be considered. Two promising developments in this research are wake steering control, which seeks to increase the power generated at a wind farm by directing the wakes of upstream turbines away from downstream ones, and communication-based spatial filtering, which seeks to improve the quality of information used by turbine- and farm-level controllers by combining measurements of the wind field collected at the individual turbines. The latter method has been shown to improve the estimates of wind direction at the turbines; however, the resulting potential for increased power capture warrants further investigation. With this paper, we begin to address this gap by combining wake steering with wind direction spatial filtering. To do so, we present a preliminary method for assessing the power capture of dynamic controllers using wind farm codes designed for time-averaged simulation. This allows us to generate results much more rapidly than would be possible using high-fidelity wind farm simulators and may be useful in many wind farm control design applications.

17 WIND ENERGY↗

Discovering invariant spatial features in electron energy loss spectroscopy images on the mesoscopic and atomic levels

Over the last two decades, Electron Energy Loss Spectroscopy (EELS) imaging with a scanning transmission electron microscope has emerged as a technique of choice for visualizing complex chemical, electronic, plasmonic, and phononic phenomena in complex materials and structures. The availability of the EELS data necessitates the development of methods to analyze multidimensional data sets with complex spatial and energy structures. Traditionally, the analysis of these data sets has been based on analysis of individual spectra, one at a time, whereas the spatial structure and correlations between individual spatial pixels containing the relevant information of the physics of underpinning processes have generally been ignored and analyzed only via the visualization as 2D maps. Here, we develop a machine learning-based approach and workflows for the analysis of spatial structures in 3D EELS data sets using a combination of dimensionality reduction and multichannel rotationally invariant variational autoencoders. This approach is illustrated for the analysis of both the plasmonic phenomena in a system of nanowires and in the core excitations in functional oxides using low loss and core-loss EELS, respectively. The code developed in this manuscript is open sourced and freely available and provided as a Jupyter notebook for the interested reader.

36 MATERIALS SCIENCE↗

Use of Monte Carlo simulation to quantify CIPS risk

Crud Induced Power Shift (CIPS), caused by the accumulation of boron compounds in corrosion product deposits on high power fuel assemblies, is an important operational issue for Pressurized Water Reactors (PWRs). The Boron-induced Offset Analysis (BOA) computer code has been developed by EPRI in collaboration with Westinghouse to help utility engineers avoid onset of CIPS. The code, used with an established procedure, predicts the maximum boron mass that will be accumulated in the upcoming cycle for a given core design and plant chemistry and operating program. The calculated boron mass above a given threshold predicts the risk of CIPS to the upcoming cycle. BOA has been successful in correctly predicting the risk for onset or lack of CIPS in many cycles. However, like most codes modeling complex physical phenomena, it is subject to uncertainties in several of the inputs used to describe these phenomena. The current BOA procedure results in a single 'best estimate' prediction, which has been judged to provide engineers with a practical way to assess CIPS risk. As such, however, there is a probability that the actual plant CIPS performance may be underestimated. This paper describes a method to assess the probability (with an associated confidence level) of no CIPS, mild to moderate CIPS, or severe CIPS using BOA for a given core design. This is accomplished through the use of a Monte Carlo simulation. The simulation is applied to several plant examples, and the results are evaluated in terms of the likelihood of mild or severe CIPS. A suggested set of criteria for decision making regarding CIPS risk is presented in the conclusion. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Accurate Binding Energies for Lithium Polysulfides and Assessment of Density Functionals for Lithium–Sulfur Battery Research

Lithium–sulfur batteries have high theoretical energy density, but a better knowledge of their intimate structural details will be helpful in improving their conductivity and long-term cycling behavior. In order to identify the stationary configurations of lithium polysulfides (Li 2 S n , 2 ≤ n ≤ 8) formed in the charging and discharging processes of the lithium–sulfur batteries, ab initio molecular dynamics was employed to sample the configuration space of Li 2 S n , followed by optimization of structures by CCSD(T)-F12b/aug-cc-pVDZ. Here, using the optimized stationary points, we have created the LiSAE38 benchmark database of atomization energies (AEs) of 38 lithium polysulfide isomers by using the higher-level WMS and W3X-L methods. In addition, the performances of 39 density functionals have been assessed against the benchmark AEs and the relative stabilities of Li 2 S n isomers. On the basis of the assessments with the def2-QZVP basis set, the PW6B95, B97-1, B3LYP-D3, TPSS, and DSD-PBEP86 density functionals are the most accurate for the AEs, whereas the mPW2-PLYP-D, DSD-PBEP86, PW6B95, HSE06, and PBEQIDH functionals are most accurate for the relative energies. Local functionals are of special interest because of their lower cost (faster timings in terms of computer resources) for large systems; among the tested local functionals, MN15-L and revM06-L are the most accurate for the calculations of relative stabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Ground State Electronic Energy of Benzene

We report here on the findings of a blind challenge devoted to determining the frozen-core, full configuration interaction (FCI) ground-state energy of the benzene molecule in a standard correlation-consistent basis set of double-ζ quality. As a broad international endeavor, our suite of wave function-based correlation methods collectively represents a diverse view of the high-accuracy repertoire offered by modern electronic structure theory. In our assessment, the evaluated high-level methods are all found to qualitatively agree on a final correlation energy, with most methods yielding an estimate of the FCI value around -863 mE H . However, we find the root-mean-square deviation of the energies from the studied methods to be considerable (1.3 mE H ), which in light of the acclaimed performance of each of the methods for smaller molecular systems clearly displays the challenges faced in extending reliable, near-exact correlation methods to larger systems. While the discrepancies exposed by our study thus emphasize the fact that the current state-of-the-art approaches leave room for improvement, we still expect the present assessment to provide a valuable community resource for benchmark and calibration purposes going forward.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

From minimum-viable-products to full models: a step-wise development of diagnostic forward models in support of design, analysis and modelling on the ST40 tokamak

Like most magnetic confined fusion experiments, the ST40 tokamak started off with a small subset of diagnostics and gradually increased the diagnostic set to include more complex and comprehensive systems. To make the most of each operational phase, forward models of various diagnostics are used and developed to aid design, provide consistency-checks during commissioning, test analysis methods, and build workflows to constrain high-level parameters to inform interpretation, theory and modelling. For new models and new analysis workflows, minimum-viable-products are released early, and their complexity is increased in a step-wise manner, facilitating the support of all programme phases on multiple parallel applications, while enabling learning opportunities and feedback loops. In this contribution we review the philosophy, scope and architecture of the framework under development. We discuss the details of some forward models, with examples on how they are used to aid diagnostic design, to investigate analysis methodologies through synthetic data, and how they are embedded in experimental analysis workflows. We compare previously published experimental results with new, more advanced analysis workflows employing more recent, detailed models and new diagnostic data, providing confirmation of the published material from the 2021–22 experimental campaign.

integrated data analysis↗

Search for single production of vector-like quarks decaying to a top quark and a $\mathrm {W} $ boson in proton–proton collisions at $\sqrt{s} = 13 \,\text {TeV} $

A search is presented for the single production of vector-like quarks in proton–proton collisions at $\sqrt{s}=13\,\text {TeV} $. The data, corresponding to an integrated luminosity of 35.9 $\,\text {fb}^{-1}$, were recorded with the CMS experiment at the LHC. The analysis focuses on the vector-like quark decay into a top quark and a $\mathrm {W} $ boson, with one muon or electron in the final state. The mass of the vector-like quark candidate is reconstructed from hadronic jets, the lepton, and the missing transverse momentum. Methods for the identification of $\mathrm {b}$ quarks and of highly Lorentz boosted hadronically decaying top quarks and $\mathrm {W} $ bosons are exploited in this search. No significant deviation from the standard model background expectation is observed. Exclusion limits at 95% confidence level are set on the product of the production cross section and branching fraction as a function of the vector-like quark mass, which range from 0.3 to 0.03 $\,\text {pb}$ for vector-like quark masses of 700 to 2000 $\,\text {GeV}$. Mass exclusion limits up to 1660 $\,\text {GeV}$ are obtained, depending on the vector-like quark type, coupling, and decay width. Furthermore, these represent the most stringent exclusion limits for the single production of vector-like quarks in this channel.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Conotoxin Prediction: New Features to Increase Prediction Accuracy

Conotoxins are toxic, disulfide-bond-rich peptides from cone snail venom that target a wide range of receptors and ion channels with multiple pathophysiological effects. Conotoxins have extraordinary potential for medical therapeutics that include cancer, microbial infections, epilepsy, autoimmune diseases, neurological conditions, and cardiovascular disorders. Despite the potential for these compounds in novel therapeutic treatment development, the process of identifying and characterizing the toxicities of conotoxins is difficult, costly, and time-consuming. This challenge requires a series of diverse, complex, and labor-intensive biological, toxicological, and analytical techniques for effective characterization. While recent attempts, using machine learning based solely on primary amino acid sequences to predict biological toxins (e.g., conotoxins and animal venoms), have improved toxin identification, these methods are limited due to peptide conformational flexibility and the high frequency of cysteines present in toxin sequences. This results in an enumerable set of disulfide-bridged foldamers with different conformations of the same primary amino acid sequence that affect function and toxicity levels. Consequently, a given peptide may be toxic when its cysteine residues form a particular disulfide-bond pattern, while alternative bonding patterns (isoforms) or its reduced form (free cysteines with no disulfide bridges) may have little or no toxicological effects. Similarly, the same disulfide-bond pattern may be possible for other peptide sequences and result in different conformations that all exhibit varying toxicities to the same receptor or to different receptors. We present here new features, when combined with primary sequence features to train machine learning algorithms to predict conotoxins, that significantly increase prediction accuracy.

collisional cross section↗

Comparison of wind-farm control strategies under realistic offshore wind conditions: wake quantities of interest

Wind-farm control strategies aim to increase the efficiency, and therefore lower the levelized cost of energy, of wind farms. This is done by using turbine settings such as the yaw angle, blade pitch angles, or generator torque to manipulate the wake that negatively affects downstream turbines in the farm. Two inherently different wind-farm control methods have been identified in the literature: wake steering (WS) and active wake mixing (AWM). As one of two companion papers focused on understanding practical aspects of these two wind-farm control strategies using large-eddy simulation (LES), we below analyze the wake quantities of interest for a single wind turbine performing WS and AWM, while the companion article (Frederik et al., 2025) focuses on turbine quantities of interest including power and structural loads for the same computational setup and also includes two-turbine arrays with full and partial wake overlap. The simulations, which are based in the LES solver AMR-Wind, are tailored to have inflow conditions representative of measurements from a site off the East Coast of the US, including with strong veer and low turbulence. The turbine, which is modeled in OpenFAST and coupled to the LES, is the IEA 15 MW, an open-source offshore design. After presenting an overview of the wake recovery for the different wake-control cases, the analysis probes the fluid-dynamic causes for the different performance of the arrays reported in the companion article by examining control volumes around the wakes and the budget of the mean-flow kinetic energy (MKE) within these volumes. In the high veer environment considered, the MKE recovery is dominated by mean convection, and this is shown to especially benefit the WS strategy when a neighboring turbine is directly downstream: there is ≈65 % more available power for a downstream turbine than in the baseline case, and this power is gained primarily through mean convection on the left-tip and top-tip faces of the control volume. However, the case with imperfect knowledge of the exact wind direction favors the pulse-type AWM strategy, largely because of ≈9 % increased turbulent entrainment from aloft versus the baseline that could be related to an apparent resistance to skewing in the pulsed wake. The general reduced effectiveness of helix-type and other individual-pitch-based AWM strategies for inflow with high veer and low turbulence as reported in the companion paper is due, in part, to low magnitudes of phase-averaged turbulent entrainment. Two main findings of this study are thus that veer has a significant impact on the effectiveness of different wake-control strategies and that pulse-type AWM may be a useful strategy when the objective is power maximization in realistic, offshore flow environments with imperfect knowledge of the exact wake overlap position on the downstream turbine.

17 WIND ENERGY↗

Parameterizing the Variability and Uncertainty of Wind and Solar in CEMs

We present current and improved methods for estimating the capacity value and curtailment impacts from variable generation (VG) in capacity expansion models (CEMs). The ideal calculation of these variability metrics is through an explicit co-optimized investment-dispatch model using multiple years of VG and load data. Because of data and computational limitations, existing CEMs typically approximate these metrics using a subset of all hours from a single year and/or using statistical methods, which often do not capture the tail-event impacts or the broader set of interactions between VG, storage, and conventional generators. In our proposed new methods, we use hourly generation and load values across all hours of the year to characterize the (1) contribution of VG to system capacity during high load hours, (2) the curtailment level of VG, and (3) the reduction in VG curtailment due to storage and shutdown of select thermal generators. Using CEM model outputs from a preceding model solve period, we apply these methods to exogenously calculate capacity value and curtailment metrics for the subsequent model solve period. Preliminary results suggest that these hourly methods offer improved capacity value and curtailment representations of VG in the CEM from existing approximation methods without additional computational burdens.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

R2 relaxometry based MR imaging for estimation of liver iron content: A comparison between two methods

Purpose: To compare the reproducibility and accuracy of R2-relaxometry MRI for estimation of liver iron concentration (LIC) between in-house analysis and FDA-approved commercially available third party results. Methods: All MR studies were performed on a 1.5T scanner. Multi-echo spin-echo scans with a fixed TR and increasing TE values of 6 ms, 9 ms, 12 ms, 15 ms, and 18 ms (spaced at 3 ms intervals) were used. Post-processing of the images to calculate mean relaxivity, R2, included drawing of regions of interest to include the whole liver on mid-slice. The relationship between liver R2 values and estimated LIC calculated with in-house analysis and values reported by an external company (FerriScan{sup ®}, Resonance Health, Australia) were assessed with correlation coefficients and Bland–Altman difference plots. Continuous variables are presented as mean ± standard deviation. Significance was set at p value < 0.05. Results: 474 studies from 175 patients were included in the study (mean age 10.4 ± 4.2 years (range 1–18 years); 254 studies from girls, 220 studies from boys). LIC ranged from 0.6 to 43 mg/g dry tissue, covering a broad range from normal levels to extremely high iron levels. Linearity between proprietary and in-house methods was excellent across the observed range for R2 (31.5 to 334.8 s{sup −1}); showing a correlation coefficient of r = 0.87, p < 0.001. Bland–Altman R2 difference plot between the two methods shows a mean bias of + 21.5 s{sup −1} (range − 47.0 to + 90.0 s{sup −1} between two standard deviations). LIC reported by FerriScan{sup ®} compared with LIC estimated in-house with R2 as reported by FerriScan{sup ®} agreed strongly, (r = 1.0, p < 0.001). Conclusion: R2 relaxometry MR imaging for liver iron concentration estimation is reproducible between proprietary FDA-approved commercial software and in-house analysis methods.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Exploiting a Shortcoming of Coupled-Cluster Theory: The Extent of Non-Hermiticity as a Diagnostic Indicator of Computational Accuracy

The fundamental non-Hermitian nature of the forms of the coupled-cluster (CC) theory widely used in quantum chemistry has usually been viewed as a negative, but the present paper shows how this can be used to an advantage. Specifically, the non-symmetric nature of the reduced one-particle density matrix (in the molecular orbital basis) is advocated as a diagnostic indicator of computational quality. In the limit of the full coupled-cluster theory [which is equivalent to full configuration interaction (FCI)], the electronic wave function and correlation energy are exact within a given one-particle basis set, and the symmetric character of the exact density matrix is recovered. The extent of the density matrix asymmetry is shown to provide a measure of “how difficult the problem is” (like the well-known T 1 diagnostic), but its variation with the level of theory also gives information about “how well this particular method works”, irrespective of the difficulty of the problem at hand. The proposed diagnostic is described and applied to a select group of small molecules, and an example of its overall utility for the practicing quantum chemist is illustrated through its application to the beryllium dimer (Be 2 ). Future application of this idea to excited states, open-shell systems, and symmetry-breaking problems and an extension of the method to the two-particle density are then proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Composite vibrational spectroscopy of the group 12 difluorides: ZnF{sub 2}, CdF{sub 2}, and HgF{sub 2}

The vibrational spectra of group 12 difluorides, MF{sub 2} (M = Zn, Cd, Hg), were investigated via coupled cluster singles, doubles, and perturbative triples, CCSD(T), including core correlation, with a series of correlation consistent basis sets ranging in size from triple-zeta through quintuple-zeta quality, which were then extrapolated to the complete basis set (CBS) limit using a variety of extrapolation procedures. The explicitly correlated coupled cluster method, CCSD(T)-F12b, was employed as well. Although exhibiting quite different convergence behavior, the F12b method yielded the CBS limit estimates closely matching more computationally expensive conventional CBS extrapolations. The convergence with respect to basis set size was examined for the contributions entering into composite vibrational spectroscopy, including those from higher-order correlation accounted for through the CCSDT(Q) level of theory, second-order spin-orbit coupling effects assessed within four-component and two-component relativistic formalisms, and vibrational anharmonicity evaluated via a perturbative treatment. Overall, the composite results are in excellent agreement with available experimental values, except for the CdF{sub 2} bond-stretching frequencies compared to spectral assignments proposed in a matrix isolation infrared and Raman study of cadmium difluoride vapor species [Loewenschuss et al., J. Chem. Phys. 50, 2502 (1969); Givan and Loewenschuss, J. Chem. Phys. 72, 3809 (1980)]. These assignments are called into question in the light of the composite results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗