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At least 325 records · Page 18

Benchmarking the extraction of statistical neutron capture cross sections on short-lived nuclei for applications using the β -Oslo method

Numerous scientific fields including astrophysics, nuclear power, and nuclear forensics require a knowledge of basic nuclear properties for large numbers of short-lived, radioactive isotopes far removed from stable nuclei. Neutron-capture cross sections are one such piece of nuclear data where direct measurements are not possible and theoretical predictions can vary by orders of magnitude. A recently developed indirect technique for inferring neutron capture rates, the β-Oslo method, has been introduced but not compared against a known, directly measured neutron capture cross section. To provide this benchmark, two indirect methods based on β decay and charged-particle reactions were used to extract the nuclear level density and γ-ray strength function of 51 Ti. The nuclear level density and γ-ray strength function from the two data sets were found to be equivalent and were used to extract the neutron capture cross section of 50 Ti which agrees with previous direct measurements at high neutron energies. Here, the results demonstrate the validity of the β-Oslo method for extracting neutron capture cross sections of short-lived nuclei and provide a sufficiently small uncertainty to be used in various applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Theoretical studies for the N{sub 2}–N{sub 2}O van der Waals complex: The potential energy surface, intermolecular vibrations, and rotational transition frequencies

Theoretical studies of the potential energy surface (PES) and bound states are performed for the N{sub 2}–N{sub 2}O van der Waals (vdW) complex. A four-dimensional intermolecular PES is constructed at the level of single and double excitation coupled-cluster method with a non-iterative perturbation treatment of triple excitations [CCSD(T)] with aug-cc-pVTZ basis set supplemented with bond functions. Two equivalent T-shaped global minima are located, in which the O atom of N{sub 2}O monomer is near the N{sub 2} monomer. The intermolecular fundamental vibrational states are assigned by inspecting the orientation of the nodal surface of the wavefunctions. The calculated frequency for intermolecular disrotation mode is 23.086 cm{sup −1}, which is in good agreement with the available experimental data of 22.334 cm{sup −1}. A negligible tunneling splitting with the value of 4.2 MHz is determined for the ground vibrational state and the tunneling splitting increases as the increment of the vibrational frequencies. Rotational levels and transition frequencies are calculated for both isotopomers {sup 14}N{sub 2}–N{sub 2}O and {sup 15}N{sub 2}–N{sub 2}O. The accuracy of the PES is validated by the good agreement between theoretical and experimental results for the transition frequencies and spectroscopic parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multimodal parameter spaces of a complex multi-channel neuron model

One of the most common types of models that helps us to understand neuron behavior is based on the Hodgkin–Huxley ion channel formulation (HH model). A major challenge with inferring parameters in HH models is non-uniqueness: many different sets of ion channel parameter values produce similar outputs for the same input stimulus. Such phenomena result in an objective function that exhibits multiple modes (i.e., multiple local minima). This non-uniqueness of local optimality poses challenges for parameter estimation with many algorithmic optimization techniques. HH models additionally have severe non-linearities resulting in further challenges for inferring parameters in an algorithmic fashion. To address these challenges with a tractable method in high-dimensional parameter spaces, we propose using a particular Markov chain Monte Carlo (MCMC) algorithm, which has the advantage of inferring parameters in a Bayesian framework. The Bayesian approach is designed to be suitable for multimodal solutions to inverse problems. We introduce and demonstrate the method using a three-channel HH model. We then focus on the inference of nine parameters in an eight-channel HH model, which we analyze in detail. We explore how the MCMC algorithm can uncover complex relationships between inferred parameters using five injected current levels. The MCMC method provides as a result a nine-dimensional posterior distribution, which we analyze visually with solution maps or landscapes of the possible parameter sets. The visualized solution maps show new complex structures of the multimodal posteriors, and they allow for selection of locally and globally optimal value sets, and they visually expose parameter sensitivities and regions of higher model robustness. We envision these solution maps as enabling experimentalists to improve the design of future experiments, increase scientific productivity and improve on model structure and ideation when the MCMC algorithm is applied to experimental data.

97 MATHEMATICS AND COMPUTING↗

SU-E-T-398: Evaluation of Radiobiological Parameters Using Serial Tumor Imaging During Radiotherapy as An Inverse Ill-Posed Problem

Purpose: Combination of serial tumor imaging with radiobiological modeling can provide more accurate information on the nature of treatment response and what underlies resistance. The purpose of this article is to improve the algorithms related to imaging-based radiobilogical modeling of tumor response. Methods: Serial imaging of tumor response to radiation therapy represents a sum of tumor cell sensitivity, tumor growth rates, and the rate of cell loss which are not separated explicitly. Accurate treatment response assessment would require separation of these radiobiological determinants of treatment response because they define tumor control probability. We show that the problem of reconstruction of radiobiological parameters from serial imaging data can be considered as inverse ill-posed problem described by the Fredholm integral equation of the first kind because it is governed by a sum of several exponential processes. Therefore, the parameter reconstruction can be solved using regularization methods. Results: To study the reconstruction problem, we used a set of serial CT imaging data for the head and neck cancer and a two-level cell population model of tumor response which separates the entire tumor cell population in two subpopulations of viable and lethally damage cells. The reconstruction was done using a least squared objective function and a simulated annealing algorithm. Using in vitro data for radiobiological parameters as reference data, we shown that the reconstructed values of cell surviving fractions and potential doubling time exhibit non-physical fluctuations if no stabilization algorithms are applied. The variational regularization allowed us to obtain statistical distribution for cell surviving fractions and cell number doubling times comparable to in vitro data. Conclusion: Our results indicate that using variational regularization can increase the number of free parameters in the model and open the way to development of more advanced algorithms which take into account tumor heterogeneity, for example, related to hypoxia.

60 APPLIED LIFE SCIENCES↗

Blinding scheme for the scale-dependence bias signature of local primordial non-Gaussianity for DESI 2024

The next generation of spectroscopic surveys is expected to achieve an unprecedented level of accuracy in the measurement of cosmological parameters. To avoid confirmation bias and thereby improve the reliability of these results, blinding procedures become a standard practice in the cosmological analyses of such surveys. Blinding is especially crucial when the impact of observational systematics is important relative to the cosmological signal, and a detection of that signal would have significant implications. This is the case for local primordial non-gaussianity, as probed by the scale-dependent bias of the galaxy power spectrum at large scales that are heavily sensitive to the dependence of the target selection on the imaging quality, known as imaging systematics. We propose a blinding method for the scale-dependent bias signature of local primordial non-gaussianity at the density field level which consists in generating a set of weights for the data that replicate the scale-dependent bias. The applied blinding is predictable, and can be straightforwardly combined with other catalog-level blinding procedures that have been designed for the baryon acoustic oscillation and redshift space distortion signals. The procedure is validated through simulations that replicate data from the first year of observation of the Dark Energy Spectroscopic Instrument, but may find applications to other upcoming spectroscopic surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Anomaly detection in collider physics via factorized observables

To maximize the discovery potential of high-energy colliders, experimental searches should be sensitive to unforeseen new physics scenarios. This goal has motivated the use of machine learning for unsupervised anomaly detection. In this paper, we introduce a new anomaly detection strategy called : factorized observables for regressing conditional expectations. Our approach is based on the inductive bias of factorization, which is the idea that the physics governing different energy scales can be treated as approximately independent. Assuming factorization holds separately for signal and background processes, the appearance of nontrivial correlations between low- and high-energy observables is a robust indicator of new physics. Under the most restrictive form of factorization, a machine-learned model trained to identify such correlations will in fact converge to the optimal new physics classifier. We test on a benchmark anomaly detection task for the Large Hadron Collider involving collimated sprays of particles called jets. By teasing out correlations between the kinematics and substructure of jets, our method can reliably extract percent-level signal fractions. This strategy for uncovering new physics adds to the growing toolbox of anomaly detection methods for collider physics with a complementary set of assumptions. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

SU-E-T-27: A Tool for Routine Quality Assurance of Radiotherapy Dose Calculation Software

Purpose: Dose calculation software is thoroughly evaluated when it is commissioned; however, evaluation of periodic software updates is typically limited in scope due to staffing constraints and the need to quickly return the treatment planning system to clinical service. We developed a tool for quickly and comprehensively testing and documenting dose calculation software against measured data. Methods: A tool was developed using MatLab (The MathWorks, Natick, MA) for evaluation of dose calculation algorithms against measured data. Inputs to the tool are measured data, reference DICOM RT PLAN files describing the measurements, and dose calculations in DICOM format. The tool consists of a collection of extensible modules that can perform analysis of point dose, depth dose curves, and profiles using dose difference, distance-to-agreement, and the gamma-index. Each module generates a report subsection that is incorporated into a master template, which is converted to final form in portable document format (PDF). Results: After each change to the treatment planning system, a report can be generated in approximately 90 minutes. The tool has been in use for more than 5 years, spanning 5 versions of the eMC and 4 versions of the AAA. We have detected changes to the algorithms that affected clinical practice once during this period. Conclusion: Our tool provides an efficient method for quality assurance of dose calculation software, providing a complete set of tests for an update. Future work includes the addition of plan level tests, allowing incorporation of, for example, the TG-119 test suite for IMRT, and integration with the treatment planning system via an application programming interface. Integration with the planning system will permit fully-automated testing and reporting at scheduled intervals.

07 ISOTOPE AND RADIATION SOURCES↗

Use of local noise power spectrum and wavelet analysis in quantitative image quality assurance for EPIDs

Purpose: To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). Methods: A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanel of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Results: Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two calibration methods. With wavelet analysis, defective pixels and inter-subpanel flat-fielding artifacts were clearly identified as spikes after thresholding the inversely transformed images. Conclusions: The proposed local NPS (r-square values) showed superior sensitivity to the noise level variations of individual subpanels compared with global quantitative metrics such as MTF, NPS, and DQE. Wavelet analysis was effective in detecting isolated defective pixels and inter-subpanel flat-fielding artifacts. The proposed methods are promising for the early detection of imaging artifacts of EPIDs.

60 APPLIED LIFE SCIENCES↗

Application of Point Precipitation Frequency Estimates to Watersheds

This report documents work sponsored by the U.S. Nuclear Regulatory Commission (NRC) at the Oak Ridge National Laboratory (ORNL) as part of the RES project, “Application of Point Precipitation Frequency Estimates to Watersheds.” This project was implemented as part of the Probabilistic Flood Hazard Assessment (PFHA) Research Program. The objective of the PFHA Research Program is to develop tools and guidance on the use of PFHA methods to risk-inform NRC’s licensing of new facilities as well as licensing and oversight of currently operating facilities as they relate to flooding hazards. Many nuclear power plants (NPPs) are located on or near rivers so riverine flooding hazards need to be considered in their design and operation. Probabilistic riverine flood models are important tools for realistic assessment of flooding risks. However, these models require areal estimates of the depth, duration, and frequency of rainfall distributed over the watershed, which are not often available. Point precipitation frequency estimates are more widely available. For example, the National Oceanic and Atmospheric Administration (NOAA) has published NOAA Atlas 14, which provides point precipitation frequency estimates for 5-minute through 60-day durations at average recurrence intervals of 1-year through 1,000-year. The research documented in this report addresses areal reduction factors (ARFs), which can be used to convert the widely available point precipitation frequency estimates, to estimates of areal precipitation frequency over a watershed. The most widely used ARF source is Technical Paper 29 (TP-29) published by the then U.S. Weather Bureau in 1958. However, both the methods and the underlying precipitation data used to produce TP-29 are seriously out of date. For example, due to the small gauge network available at the time of TP-29’s compilation, ARF estimates developed are only for watersheds smaller than about 400 square miles. Due to the relatively short record lengths of precipitation data available, frequency considerations could not be accurately determined. Other factors such as regional climate and seasonality were not addressed. Several newer methods have been published since TP-29 was developed and both the type and quantity of precipitation data have increased significantly, along with computational resources and analytical tools such as geographic information systems. This report reviewed and assessed the available precipitation products and methods for conducting ARF analysis. The work applied up-to-date precipitation data products and analysis methods with a novel watershed-based approach to investigate how ARF estimates vary across different methods, data sources, geographical locations, return periods, and seasons. The overall findings reported here regarding basic ARF trends are in line with other recent studies showing that ARFs decrease with increasing area, increase with increasing duration, and decrease with increasing return period. This study found significant differences among the available ARF methods. This work also found a strong geographical variability across different US hydrologic regions, suggesting that the ARF are specific to regional climate patterns and geographical characteristics and should not be applied arbitrarily to other locations. The results also reveal the importance of data record length, especially for high return level ARFs. The work reported in NUREG/CR-7271 will assist NRC staff in assessing different classes of ARF methods in conjunction with available rainfall data sets. It will also support the development of guidance for application of point precipitation data in PFHAs. It should be noted that the ARF values presented in this report for any location or region were developed for the purposes of comparing methods and investigating the factors that influence ARFs. They should not be considered official and should not be used in leu of a site-specific analysis.

54 ENVIRONMENTAL SCIENCES↗

MOSAiC Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed many instruments on board a German ice breaker, the Research Vessel (RV) Polarstern, for one year from October 2019 to October 2020. The purpose of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign was to study the decline in the sea-ice pack around the North Pole, and what factors may be at play. After the campaign ended, efforts were undertaken to provide a calibrated radar data set for future studies. MOSAiC presented new challenges to this process, as existing methodologies often were not applicable for the frozen environment with little to no ground clutter, and concurrent engineering updates or calibrations could not be accomplished once the ship set off. Like the previous Cloud, Aerosol, and Complex Terrain Interactions (CACTI) and Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) documentation (Hardin et al. 2020, Matthews et al. 2023), the data correction and calibration process is known in ARM as creating a “b1” datastream. This means that the radar datastreams have been well characterized to the best possible quality. This report will detail the status of the raw “a1” level data sets during the MOSAiC campaign, the corrections that were applied to create the “b1” data files, and the details of the applied methods.

54 ENVIRONMENTAL SCIENCES↗

Federal Metering Guidance

The Federal Metering Guidance documents the metering provisions in EO 13834, Efficient Federal Operations and other metering related statutory requirements. This document provides the meter-related reporting requirements for Federal agencies, specifies a method to verify the existence of currently installed building-level meters, provides guidelines on prioritizing the implementation of advanced energy and water meters, sets the schedule for agencies to update their five-year metering plans, provides the minimum requirements that agencies must meet when updating their five-year metering plans along with recommend elements for an effective plan.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An Open-Access Nuclear Knowledge and Innovation Toolkit to Make Use of Nuclear World and Increase Collaboration

Nuclear engineering began as an urgent weapons development program in the early 1940s, involving work in enrichment, reactor design, shielding design, and isotope production. This work led to investigations of peaceful uses of nuclear technology, including nuclear power production and applications of radiation. Such peaceful technologies, often derived from experience gained through the weapons program, often maintained some level or attitude of secrecy. As the field continued to develop, that secrecy led to different specializations developing with different sets of terminology and methods of computation. For example, radiation safety used buildup and shielding factors while reactor designers use diffusivity and cross sections. Impressive amounts of work went into theory and application development in each sub-field over the next few decades, with much of the work left without adequate documentation or with important documentation made only within the organization. This situation has led to a loss of knowledge and experience, a lack of collaboration across nuclear sub-fields, and immense amounts of time and effort spent on redundant work. This paper proposes an open-access system that combines preserving and passing on the knowledge in all nuclear sub-fields with tools to make that knowledge useful, referred to as the Nuclear Knowledge and Innovation Toolkit (NuKIT). Knowledge would be captured in user-entered and expert-verified databases of reactors, applications of radiation, isotope production methods, and other pertinent nuclear information complete with technical information and tags that can be used to organize and investigate the data. Tools include community tools like forums and the ability to create collaborative projects; visualization and presentation tools; and an online programming system that allows code sharing, collaborative editing, database manipulation, and integration with all other tools. Finally, NuKIT is envisioned to include commercialization tools to allow freelance work and to compensate data entry/moderation work to help encourage participation. Eventually, integration with industry-standard tools like MCNP, SCALE, etc. is expected. This paper will present some proposed work in the context of its use for isotopes and radiation application, as well as possible work to be done in the context of the Combined Materials Experimental Toolkit (CoMET) being developed by the Nuclear Science User Facilities (NSUF) program. It should be noted that any work done towards this system, by any group, will advance the full system. It should also be noted that similar work previously done can be integrated into NuKIT.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A BLIND METHOD TO DETREND INSTRUMENTAL SYSTEMATICS IN EXOPLANETARY LIGHT CURVES

The study of the atmospheres of transiting exoplanets requires a photometric precision, and repeatability, of one part in ∼10{sup 4}. This is beyond the original calibration plans of current observatories, hence the necessity to disentangle the instrumental systematics from the astrophysical signals in raw data sets. Most methods used in the literature are based on an approximate instrument model. The choice of parameters of the model and their functional forms can sometimes be subjective, causing controversies in the literature. Recently, Morello et al. (2014, 2015) have developed a non-parametric detrending method that gave coherent and repeatable results when applied to Spitzer/IRAC data sets that were debated in the literature. Said method is based on independent component analysis (ICA) of individual pixel time-series, hereafter “pixel-ICA”. The main purpose of this paper is to investigate the limits and advantages of pixel-ICA on a series of simulated data sets with different instrument properties, and a range of jitter timescales and shapes, non-stationarity, sudden change points, etc. The performances of pixel-ICA are compared against the ones of other methods, in particular polynomial centroid division, and pixel-level decorrelation method. We find that in simulated cases pixel-ICA performs as well or better than other methods, and it also guarantees a higher degree of objectivity, because of its purely statistical foundation with no prior information on the instrument systematics. The results of this paper, together with previous analyses of Spitzer/IRAC data sets, suggest that photometric precision and repeatability of one part in 10{sup 4} can be achieved with current infrared space instruments.

79 ASTRONOMY AND ASTROPHYSICS↗

Structure of Offshore Low-Level Jet Turbulence and Implications to Mesoscale-to-Microscale Coupling

This paper explores realistic nonstationary atmospheric boundary layer (ABL) turbulence arising from nonstationarity at the mesoscale, particularly within offshore low-level jets with implications to offshore wind farms, using high-fidelity multiscale large-eddy simulations (LES). To this end, we analyzed the single-point turbulence statistical structure of a North-Atlantic offshore LLJ event simulated using high-resolution LES (AMR-Wind). The nonstationary LLJ is simulated using a mesoscale-to-microscale coupled (MMC) simulation procedure involving data assimilation of mesoscale velocity and temperature data from the Weather Research and Forecasting (WRF) model. Unlike the assimilation of mesoscale velocity data into the LES, the direct assimilation of temperature profiles had a strong impact on turbulence stratification, thereby causing erroneous predictions of turbulence both above and within the jet layer. Various approaches to mitigate this effect have resulted in multiple (four) variants of this MMC strategy. Outcomes from this work clearly show that the turbulence within the low-level jet is a strong function of the MMC approach as the turbulence structure within the low-level jet is dependent on the flux of residual turbulence from outside the jet, which in turn depends on the temperature forcing history. Additionally, the turbulence predicted by all these different methods (as well as the observation data) show similar deviations from equilibrium as evidenced by comparisons with idealized atmospheric turbulence structure obtained using the same numerical method. In general, we observe that the predicted LLJ turbulence tends to differ from canonical ABL turbulence with comparable shear. Particularly, the combination of shear and turbulence observed in such nonstationary low-level turbulence cannot be matched using equilibrium settings and therefore, represents a critical use-case for both testing and leveraging meso–micro coupling strategies.

17 WIND ENERGY↗

Communication: Unambiguous comparison of many-electron wavefunctions through their overlaps

A simple and powerful method for comparing many-electron wavefunctions constructed at different levels of theory is presented. By using wavefunction overlaps, it is possible to analyze the effects of varying wavefunction models, molecular orbitals, and one-electron basis sets. The computation of wavefunction overlaps eliminates the inherent ambiguity connected to more rudimentary wavefunction analysis protocols, such as visualization of orbitals or comparing selected physical observables. Instead, wavefunction overlaps allow processing the many-electron wavefunctions in their full inherent complexity. The presented method is particularly effective for excited state calculations as it allows for automatic monitoring of changes in the ordering of the excited states. A numerical demonstration based on multireference computations of two test systems, the selenoacrolein molecule and an iridium complex, is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Method for the Quantification of Model Form Error Associated with Physical Systems

In the process of model validation, models are often declared valid when the differences between model predictions and experimental data sets are satisfactorily small. However, little consideration is given to the effectiveness of a model using parameters that deviate slightly from those that were fitted to data, such as a higher load level. Furthermore, few means exist to compare and choose between two or more models that reproduce data equally well. These issues can be addressed by analyzing model form error, which is the error associated with the differences between the physical phenomena captured by models and that of the real system. This report presents a new quantitative method for model form error analysis and applies it to data taken from experiments on tape joint bending vibrations. Two models for the tape joint system are compared, and suggestions for future improvements to the method are given. As the available data set is too small to draw any statistical conclusions, the focus of this paper is the development of a methodology that can be applied to general problems.

97 MATHEMATICS AND COMPUTING↗

Best practices for building energy codes compliance

Building energy codes are a proven policy mechanism to achieve economy-wide energy savings in buildings. In 2021, the International Energy Agency Energy in Buildings and Communities Programme (IEA EBC) Building Energy Codes Working Group (BECWG) set out to survey the diverse codes compliance practices across BECWG member countries. While codes vary in format and approach, attaining the energy reduction potential of building energy codes requires effective implementation and compliance. This is a large undertaking for countries, as effective compliance checking requires adequate resources, technical knowledge, capacity, and strong institutions. Many nations face the same compliance issues, such as requiring faster and easier methods to verify codes and coordinating among numerous stakeholders and levels of government. This paper explores the need for stronger institutional approaches to enforce building energy codes that will lead to code compliance. Specifically, this report sets out to address the question of what practices result in effective building energy code compliance in selected BECWG member countries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Orbital breathing effects in the computation of x-ray d -ion spectra in solids by ab initio wave-function-based methods

In existing theoretical approaches to core-level excitations of transition-metal ions in solids relaxation and polarization effects due to the inner core hole are often ignored or described phenomenologically. Here, we set up an ab initio computational scheme that explicitly accounts for such physics in the calculation of x-ray absorption and resonant inelastic x-ray scattering spectra. Good agreement is found with experimental transition-metal L-edge data for the strongly correlated d 9 cuprate Li 2 CuO 2 , for which we also determine the absolute scattering intensities. The newly developed methodology opens the way for the investigation of even more complex d n electronic structures of group VI B to VIII B correlated oxide compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗