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At least 1,081 records · Page 60

Beyond the classical kinetic model for chronic graphite oxidation by moisture in high temperature gas-cooled reactors

Four grades of nuclear graphite with various microstructures were subjected to accelerated oxidation tests in helium with traces of moisture and hydrogen in order to evaluate the effects of chronic oxidation on graphite components in high temperature gas cooled reactors. Kinetic analysis showed that the Langmuir-Hinshelwood (LH) model cannot consistently reproduce all results. In particular, at high temperatures and water partial pressures oxidation was always faster than the LH model predicts, with stronger deviations for superfine grain graphite than for medium grain grades. It was also found empirically that the apparent reaction order for water has a sigmoid-type variation with temperature which follows the integral Boltzmann distribution function. This suggests that the apparent activation with temperature of graphite reactive sites that causes deviations from the LH model is rooted in specific structural and electronic properties of surface sites on graphite. A semi-global kinetic model was proposed, whereby the classical LH model was modified with a temperature-dependent reaction order for water. The new Boltzmann-enhanced model (BLH) was shown to consistently predict experimental oxidation rates over large ranges of temperature (800-1100 oC) and partial pressures of water (3-1200 Pa) and hydrogen (0-300 Pa), not only for the four grades of graphite but also for the historic grade H-451. The BLH model offers as more reliable input for modeling the chemical environment effects during the life-time operation of new grades of graphite in advanced nuclear reactors operating at high and very high temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Asymmetrically strained quantum dots with non-fluctuating single-dot emission spectra and subthermal room-temperature linewidths

The application of colloidal semiconductor quantum dots as single-dot light sources still requires overcoming several challenges. Recently, there has been considerable progress in suppressing intensity fluctuations (blinking) by encapsulating an emitting core into a thick protective shell. However, these nanostructures still show considerable fluctuations in both emission energy and linewidth. Here we demonstrate type-I core/shell heterostructures that overcome these deficiencies. They are made by combining wurtzite semiconductors with a large, directionally anisotropic lattice mismatch, which results in strong asymmetric compression of the emitting core. This modifies the structure of band-edge excitonic states and leads to accelerated radiative decay, reduced exciton-phonon interactions, and suppressed coupling to fluctuating electrostatic environment. As a result, individual asymmetrically strained dots exhibit highly stable emission energy (<1 meV standard deviation) and a subthermal room-temperature linewidth (~20 meV), concurrent with nearly nonblinking behaviour, high emission quantum yields, and a widely tunable emission colour.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FREQUENCY SHIFTS OF RESONANT MODES OF THE SUN DUE TO NEAR-SURFACE CONVECTIVE SCATTERING

Measurements of oscillation frequencies of the Sun and stars can provide important independent constraints on their internal structure and dynamics. Seismic models of these oscillations are used to connect structure and rotation of the star to its resonant frequencies, which are then compared with observations, the goal being that of minimizing the difference between the two. Even in the case of the Sun, for which structure models are highly tuned, observed frequencies show systematic deviations from modeled frequencies, a phenomenon referred to as the “surface term.” The dominant source of this systematic effect is thought to be vigorous near-surface convection, which is not well accounted for in both stellar modeling and mode-oscillation physics. Here we bring to bear the method of homogenization, applicable in the asymptotic limit of large wavelengths (in comparison to the correlation scale of convection), to characterize the effect of small-scale surface convection on resonant-mode frequencies in the Sun. We show that the full oscillation equations, in the presence of temporally stationary three-dimensional (3D) flows, can be reduced to an effective “quiet-Sun” wave equation with altered sound speed, Brünt–Väisäla frequency, and Lamb frequency. We derive the modified equation and relations for the appropriate averaging of 3D flows and thermal quantities to obtain the properties of this effective medium. Using flows obtained from 3D numerical simulations of near-surface convection, we quantify their effect on solar oscillation frequencies and find that they are shifted systematically and substantially. We argue therefore that consistent interpretations of resonant frequencies must include modifications to the wave equation that effectively capture the impact of vigorous hydrodynamic convection.

79 ASTRONOMY AND ASTROPHYSICS↗

Combination of searches for heavy resonances decaying into bosonic and leptonic final states using 36 fb - 1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

Searches for new heavy resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons, are presented using a data sample corresponding to 36.1 fb -1 of pp collisions at $ \sqrt{s}=13 $ TeV collected during 2015 and 2016 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting bosonic decay modes in the qqqq, ννqq, ℓνqq, ℓℓqq, ℓνℓν, ℓℓνν, ℓνℓℓ, ℓℓℓℓ, qqbb, ννbb, ℓνbb, and ℓℓbb final states are combined, searching for a narrow-width resonance. Likewise, analyses selecting the leptonic ℓν and ℓℓ final states are also combined. These two sets of analyses are then further combined. No significant deviation from the Standard Model predictions is observed. Three benchmark models are tested: a model predicting the existence of a new heavy scalar singlet, a simplified model predicting a heavy vector-boson triplet, and a bulk Randall-Sundrum model with a heavy spin-2 Kaluza-Klein excitation of the graviton. Cross section limits are set at the 95% confidence level using an asymptotic approximation and are compared with predictions for the benchmark models. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The data exclude a heavy vector-boson triplet with mass below 5.5 TeV in a weakly coupled scenario and 4.5 TeV in a strongly coupled scenario, as well as a Kaluza-Klein graviton with mass below 2.3 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SU-C-207B-04: Automated Segmentation of Pectoral Muscle in MR Images of Dense Breasts

Purpose: To develop and evaluate a fully automated method for segmentation of the pectoral muscle boundary in Magnetic Resonance Imaging (MRI) of dense breasts. Methods: Segmentation of the pectoral muscle is an important part of automatic breast image analysis methods. Current methods for segmenting the pectoral muscle in breast MRI have difficulties delineating the muscle border correctly in breasts with a large proportion of fibroglandular tissue (i.e., dense breasts). Hence, an automated method based on dynamic programming was developed, incorporating heuristics aimed at shape, location and gradient features.To assess the method, the pectoral muscle was segmented in 91 randomly selected participants (mean age 56.6 years, range 49.5–75.2 years) from a large MRI screening trial in women with dense breasts (ACR BI-RADS category 4). Each MR dataset consisted of 178 or 179 T1-weighted images with voxel size 0.64 × 0.64 × 1.00 mm3. All images (n=16,287) were reviewed and scored by a radiologist. In contrast to volume overlap coefficients, such as DICE, the radiologist detected deviations in the segmented muscle border and determined whether the result would impact the ability to accurately determine the volume of fibroglandular tissue and detection of breast lesions. Results: According to the radiologist’s scores, 95.5% of the slices did not mask breast tissue in such way that it could affect detection of breast lesions or volume measurements. In 13.1% of the slices a deviation in the segmented muscle border was present which would not impact breast lesion detection. In 70 datasets (78%) at least 95% of the slices were segmented in such a way it would not affect detection of breast lesions, and in 60 (66%) datasets this was 100%. Conclusion: Dynamic programming with dedicated heuristics shows promising potential to segment the pectoral muscle in women with dense breasts.

60 APPLIED LIFE SCIENCES↗

SU-F-T-181: Proton Therapy Tissue-Equivalence of 3D Printed Materials

Purpose: This work investigated the proton tissue-equivalence of various 3D printed materials. Methods: Three 3D printers were used to create 5 cm cubic phantoms made of different plastics with varying percentages of infill. White resin, polylactic acid (PLA), and NinjaFlex plastics were used. The infills ranged from 15% to 100%. Each phantom was scanned with a CT scanner to obtain the HU value. The relative linear stopping power (RLSP) was then determined using a multi-layer ion chamber in a 200 MeV proton beam. The RLSP was measured both parallel and perpendicular to the print direction for each material. Results: The HU values of the materials ranged from lung-equivalent (−820 HU σ160) when using a low infill, to soft-tissue-equivalent 159 (σ12). The RLSP of the materials depended on the orientation of the beam relative to the print direction. When the proton beam was parallel to the print direction, the RLSP was generally higher than the RLSP in the perpendicular orientation, by up to 45%. This difference was smaller (less than 6%) for the materials with 100% infill. For low infill cubes irradiated parallel to the print direction, the SOBP curve showed extreme degradation of the beam in the distal region. The materials with 15–25% infill had wide-ranging agreement with a clinical HU-RLSP conversion curve, with some measurements falling within 1% of the curve and others deviating up to 45%. The materials with 100% infill all fell within 7% of the curve. Conclusion: While some materials tested fall within 1% of a clinical HU-RLSP curve, caution should be taken when using 3D printed materials with proton therapy, as the orientation of the beam relative to the print direction can result in a large change in RLSP. Further investigation is needed to measure how the infill pattern affects the material RLSP. This work was supported by PHS grant CA180803.

60 APPLIED LIFE SCIENCES↗

Preliminary results on the feasibility of using ultrasound to monitor intrafractional motion during radiation therapy for pancreatic cancer

Purpose: Substantial intrafraction organ motion during radiation therapy (RT) for pancreatic cancer is well recognized as a major limiting factor for accurate delivery of RT. The aim of this work is to determine the feasibility of monitoring the intrafractional motion of the pancreas or surrounding structures using ultrasound for RT delivery. Methods: Transabdominal ultrasound (TAUS) and 4DCT data were acquired on ten pancreatic cancer patients during radiation therapy process in a prospective study. In addition, TAUS and MRI were collected for five healthy volunteers. The portal vein (PV) and the head of the pancreas (HP) along with other structures were contoured on these images. Volume changes, distance between the HP and PV, and motion difference between the HP and PV were measured to examine whether PV can be used as a motion surrogate for HP. TAUS images were acquired and processed using a research version of the Clarity autoscan ultrasound system (CAUS). Motion monitoring was performed with the ultrasound probe mounted on an arm fixed to the couch. Video segments of the monitoring sessions were captured. Results: On TAUS, PV is better visualized than HP. The measured mean volume deviation for all patients for the HP and PV was 1.4 and 0.6 ml, respectively. The distance between the HP and PV was close to a constant with 0.22 mm mean deviation throughout the ten breathing phases. The mean of the absolute motion difference for all patients was 1.7 ± 0.8 mm in LR, 1.5 ± 0.5 mm in AP, and 2.3 ± 0.7 mm in SI, suggesting that the PV is a good surrogate for HP motion estimation. By using this surrogate, the HP motion tracking using TAUS was demonstrated. Conclusions: Large intrafractional organ motion due to respiratory and/or bowel motion is a limiting factor in administering curative radiation doses to pancreatic tumors. The authors investigate the use of real-time ultrasound to track pancreas motion. Due to the poor visibility of the pancreas head on an ultrasound image, the portal vein is identified as a surrogate. The authors have demonstrated the feasibility of tracking HP motion through the localization of the PV using TAUS. This will potentially allow real-time tracking of intrafractional motion to justify small PTV-margins and to account for unusual motions, thus, improving normal tissue sparing.

60 APPLIED LIFE SCIENCES↗

Multi-channel search for squarks and gluinos in $\sqrt{s}=7\mbox{ TeV}$ pp collisions with the ATLAS detector at the LHC

A search for supersymmetric particles in final states with zero, one, and two leptons, with and without jets identified as originating from b-quarks, in 4.7 fb -1 of √s=7 TeV pp collisions produced by the Large Hadron Collider and recorded by the ATLAS detector is presented. The search uses a set of variables carrying information on the event kinematics transverse and parallel to the beam line that are sensitive to several topologies expected in supersymmetry. Mutually exclusive final states are defined, allowing a combination of all channels to increase the search sensitivity. No deviation from the Standard Model expectation is observed. Upper limits at 95 % confidence level on visible cross-sections for the production of new particles are extracted. Results are interpreted in the context of the constrained minimal supersymmetric extension to the Standard Model and in supersymmetry-inspired models with diverse, high-multiplicity final states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

TU-F-CAMPUS-J-04: Setup Uncertainties in the Mediastinum Area for IMRT Treatment of Lymphoma Patients

Purpose: Despite daily image guidance setup uncertainties can be high when treating large areas of the body. The aim of this study was to measure local uncertainties inside the PTV for patients receiving IMRT to the mediastinum region. Methods: Eleven lymphoma patients that received radiotherapy (breath-hold) to the mediastinum were included in this study. The treated region could range all the way from the neck to the diaphragm. Each patient had a CT scan with a CT-on-rails system prior to every treatment. The entire PTV region was matched to the planning CT using automatic rigid registration. The PTV was then split into 5 regions: neck, supraclavicular, superior mediastinum, upper heart, lower heart. Additional auto-registrations for each of the 5 local PTV regions were performed. The residual local setup errors were calculated as the difference between the final global PTV position and the individual final local PTV positions for the AP, SI and RL directions. For each patient 4 CT scans were analyzed (1 per week of treatment). Results: The residual mean group error (M) and standard deviation of the inter-patient (or systematic) error (Σ) were lowest in the RL direction of the superior mediastinum (0.0mm and 0.5mm) and highest in the RL direction of the lower heart (3.5mm and 2.9mm). The standard deviation of the inter-fraction (or random) error (σ) was lowest in the RL direction of the superior mediastinum (0.5mm) and highest in the SI direction of the lower heart (3.9mm) The directionality of local uncertainties is important; a superior residual error in the lower heart for example keeps it in the global PTV. Conclusion: There is a complex relationship between breath-holding and positioning uncertainties that needs further investigation. Residual setup uncertainties can be significant even under daily CT image guidance when treating large regions of the body.

60 APPLIED LIFE SCIENCES↗

Dynamic Ride-Matching for Large-Scale Transportation Systems

Efficient dynamic ride-matching (DRM) in large-scale transportation systems is a key driver in transport simulations to yield answers to challenging problems. Although the DRM problem is simple to solve, it quickly becomes a computationally challenging problem in large-scale transportation system simulations. Therefore, this study thoroughly examines the DRM problem dynamics and proposes an optimization-based solution framework to solve the problem efficiently. To benefit from parallel computing and reduce computational times, the problem’s network is divided into clusters utilizing a commonly used unsupervised machine learning algorithm along with a linear programming model. Then, these sub-problems are solved using another linear program to finalize the ride-matching. At the clustering level, the framework allows users adjusting cluster sizes to balance the trade-off between the computational time savings and the solution quality deviation. A case study in the Chicago Metropolitan Area, U.S., illustrates that the framework can reduce the average computational time by 58% at the cost of increasing the average pick up time by 26% compared with a system optimum, that is, non-clustered, approach. Another case study in a relatively small city, Bloomington, Illinois, U.S., shows that the framework provides quite similar results to the system-optimum approach in approximately 62% less computational time.

33 ADVANCED PROPULSION SYSTEMS↗

Influence of regional nighttime atmospheric regimes on canopy turbulence and gradients at a closed and open forest in mountain-valley terrain

Stable stratification of the nocturnal lower boundary layer inhibits convective turbulence, such that turbulent vertical transfer of ecosystem carbon dioxide (CO 2 ), water vapor (H 2 O) and energy is driven by mechanically forced turbulence, either from frictional forces near the ground or top of a plant canopy, or from shear generated aloft. The significance of this last source of turbulence on canopy flow characteristics in a closed and open forest canopy is addressed in this paper. We present micrometeorological observations of the lower boundary layer and canopy air space collected on nearly 200 nights using a combination of atmospheric laser detection and ranging (lidar), eddy covariance (EC), and tower profiling instrumentation. Two AmeriFlux/Fluxnet sites in mountain-valley terrain in the Western U.S. are investigated: Wind River, a tall, dense conifer canopy, and Tonzi Ranch, a short, open oak canopy. On roughly 40% of nights lidar detected down-valley or downslope flows above the canopy at both sites. Nights with intermittent strong bursts of “top-down” forced turbulence were also observed above both canopies. The strongest of these bursts increased sub-canopy turbulence and reduced canopy virtual potential temperature (θv) gradient at Tonzi, but did not appear to change the flow characteristics within the dense Wind River canopy. At Tonzi we observed other times when high turbulence (via friction velocity, u*) was found just above the trees, yet CO2 and θv gradients remained large and suggested flow decoupling. These events were triggered by regional downslope flow. Lastly, a set of turbulence parameters is evaluated for estimating canopy turbulence mixing strength. The relationship between turbulence parameters and canopy θv gradients was found to be complex, although better agreement between the canopy θv gradient and turbulence was found for parameters based on the standard deviation of vertical velocity, or ratios of 3-D turbulence to mean flow, than for u*. These findings add evidence that the relationship between canopy turbulence, static stability, and canopy mixing is far from straightforward even within an open canopy.

54 ENVIRONMENTAL SCIENCES↗

Electrical anisotropy and coexistence of structural transitions and superconductivity in IrT e 2

In this work, we report experimental investigations of the electrical transport, magnetic, and thermodynamic properties of IrTe 2 single crystals. The resistivity, magnetization, and specific heat display anomalies at T S1 ≈ 283K,T S2 ≈ 167K, and T c ≈2.5K, corresponding to two structural and one superconducting phase transitions, respectively, demonstrating the coexistence of all of these transitions in high-quality stoichiometric samples. While there is little magnetic anisotropy, a large ab-plane (ρab) and c-axis (ρc) electrical resistivity ratio (ρ c /ρ ab ≈730 at T=4K) is observed. This two-dimensional (2D) electronic character is further reflected in the disparate temperature dependences of ρ ab and ρ c , with ρab exhibiting a Fermi-liquid-like T 2 dependence below ~25K, while ρc deviates significantly from this standard metallic behavior. In contrast, the magnetization is almost isotropic and negative over a wide temperature range. Furthermore, this can be explained by larger diamagnetism induced by electronic structure reconstruction as probed by the Hall effect and smaller positive contribution from itinerant electrons due to a low density of states (DOS) at the Fermi level. A small electronic specific heat coefficient with γ ≈ 1.8mJ/molK 2 confirms this assertion. This implies that IrTe 2 is a weakly coupled superconductor. The connection between the superconductivity and the two structural transitions is discussed.

36 MATERIALS SCIENCE↗

SU-E-T-427: Cell Surviving Fractions Derived From Tumor-Volume Variation During Radiotherapy for Non-Small Cell Lung Cancer: Comparison with Predictive Assays

Purpose: To show that a distribution of cell surviving fractions S{sub 2} in a heterogeneous group of patients can be derived from tumor-volume variation curves during radiotherapy for non-small cell lung cancer. Methods: Our analysis was based on two data sets of tumor-volume variation curves for heterogeneous groups of 17 patients treated for nonsmall cell lung cancer with conventional dose fractionation. The data sets were obtained previously at two independent institutions by using megavoltage (MV) computed tomography (CT). Statistical distributions of cell surviving fractions S{sup 2} and cell clearance half-lives of lethally damaged cells T1/2 have been reconstructed in each patient group by using a version of the two-level cell population tumor response model and a simulated annealing algorithm. The reconstructed statistical distributions of the cell surviving fractions have been compared to the distributions measured using predictive assays in vitro. Results: Non-small cell lung cancer presents certain difficulties for modeling surviving fractions using tumor-volume variation curves because of relatively large fractional hypoxic volume, low gradient of tumor-volume response, and possible uncertainties due to breathing motion. Despite these difficulties, cell surviving fractions S{sub 2} for non-small cell lung cancer derived from tumor-volume variation measured at different institutions have similar probability density functions (PDFs) with mean values of 0.30 and 0.43 and standard deviations of 0.13 and 0.18, respectively. The PDFs for cell surviving fractions S{sup 2} reconstructed from tumor volume variation agree with the PDF measured in vitro. Comparison of the reconstructed cell surviving fractions with patient survival data shows that the patient survival time decreases as the cell surviving fraction increases. Conclusion: The data obtained in this work suggests that the cell surviving fractions S{sub 2} can be reconstructed from the tumor volume variation curves measured during radiotherapy with conventional fractionation. The proposed method can be used for treatment evaluation and adaptation.

60 APPLIED LIFE SCIENCES↗

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts of data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes. This means that the majority of our estimates are within 6.5 minutes of the actual wait time. Conclusion: The goal of this project was to define an appropriate machine learning algorithm to estimate waiting times based on the collective knowledge and experience learned from previous patients. Our results offer an opportunity to improve the information that is provided to patients and family members regarding the amount of time they can expect to wait for radiotherapy treatment at our centre. AJ acknowledges support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and from the 2014 Q+ Initiative of the McGill University Health Centre.

60 APPLIED LIFE SCIENCES↗

Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

Feng, Zhiyue↗

Speeding up equation of motion coupled cluster theory with the chain of spheres approximation

In the present paper, the chain of spheres exchange (COSX) approximation is applied to the highest scaling terms in the equation of motion (EOM) coupled cluster equations with single and double excitations, in particular, the terms involving integrals with four virtual labels. It is found that even the acceleration of this single term yields significant computational gains without compromising the desired accuracy of the method. For an excitation energy calculation on a cluster of five water molecules using 585 basis functions, the four virtual term is 9.4 times faster using COSX with a loose grid than using the canonical implementation, which yields a 2.6 fold acceleration for the whole of the EOM calculation. For electron attachment calculations, the four virtual term is 15 times and the total EOM calculation is 10 times faster than the canonical calculation for the same system. The accuracy of the new method was tested using Thiel’s test set for excited states using the same settings and the maximum absolute deviation over the whole test set was found to be 12.945 cm{sup −1} (59 μHartree) for excitation energies and 6.799 cm{sup −1} (31 μHartree) for electron attachments. Using MP2 amplitudes for the ground state in combination with the parallel evaluation of the full EOM equations in the manner discussed in this paper enabled us to perform calculations for large systems. Electron affinity values for the two lowest states of a Zn protoporphyrine model compound (224 correlated electrons and 1120 basis functions) were obtained in 3 days 19 h using 4 cores of a Xeon E5-2670 processor allocating 10 GB memory per core. Calculating the lowest two excitation energies for trans-retinal (114 correlated electrons and 539 basis functions) took 1 day 21 h using eight cores of the same processor and identical memory allocation per core.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AN APPLICATION OF THE WIENER HERMITE EXPANSION TO THE NONLINEAR EVOLUTION OF DARK MATTER

We apply the Wiener Hermite (WH) expansion to the nonlinear evolution of the large-scale structure and obtain an approximate expression for the matter power spectrum in the full order of the expansion. This method allows us to expand any random function in terms of an orthonormal basis in the space of random functions in such a way that the first order of the expansion expresses the Gaussian distribution, and others are the deviations from Gaussianity. It is proved that the WH expansion is mathematically equivalent to the {Gamma}-expansion approach in the renormalized perturbation theory (RPT). While exponential behavior in the high-k limit has been proved for the mass density and velocity fluctuations of dark matter in the RPT, we prove the behavior again in the context of the WH expansion using the result of the standard perturbation theory (SPT). We propose a new approximate expression for the matter power spectrum which interpolates the low-k expression corresponding to the 1-loop level in SPT and the high-k expression obtained by taking a high-k limit of the WH expansion. The validity of our prescription is specifically verified by comparing with the 2-loop solutions of the SPT. The proposed power spectrum agrees with the result of the N-body simulation with accuracy better than 1% or 2% in a range of baryon acoustic oscillation scales, where the wave number is about k = 0.2-0.4 h Mpc{sup -1} at z = 0.5-3.0. This accuracy is comparable to or slightly less than the ones in the closure theory, the fractional difference of which from the N-body result is within 1%. One merit of our method is that the computational time is very short because only single and double integrals are involved in our solution.

79 ASTRONOMY AND ASTROPHYSICS↗

Impurity induced confinement effects in size-separated Mn-doped CsPbCl 3 nanocrystals

Beyond quantum confinement, impurity doping of semiconductor nanocrystals (NCs) offers a degree of control over their optical and electronic properties, which are of interest for potential applications. Manganese (Mn)-doped CsPbCl 3 NCs, for example, show synergistic effects in the visible, with large enhancements in both blue (exciton) and red (dopant) emission over a narrow range of dopant concentration. Although Mn concentration is the primary parameter, NC size offers an additional degree of control over the number of dopants per NC. Size-resolved CsPbCl 3 NCs prepared in the limit of strong Mn doping highlight the emergence of defective NCs with deviations from anticipated confinement trends. In conclusion, the transition correlates with a redshift and increase in the amplitude of dopant emission, and we discuss these observations in the context of atomistic simulations of Ruddlesden-Popper defects in CsPbCl 3 .

36 MATERIALS SCIENCE↗