Search NASA⌕ Search

SEARCH · Search NASA

Results for “Alternative data”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Demonstration of neutrinoless double beta decay searches in gaseous xenon with NEXT

The NEXT experiment aims at the sensitive search of the neutrinoless double beta decay in 136 Xe, using high-pressure gas electroluminescent time projection chambers. The NEXT-White detector is the first radiopure demonstrator of this technology, operated in the Laboratorio Subterráneo de Canfranc. Achieving an energy resolution of 1% FWHM at 2.6 MeV and further background rejection by means of the topology of the reconstructed tracks, NEXT-White has been exploited beyond its original goals in order to perform a neu- trinoless double beta decay search. The analysis considers the combination of 271.6 days of 136 Xe-enriched data and 208.9 days of 136Xe-depleted data. A detailed background modeling and measurement has been developed, ensuring the time stability of the radiogenic and cosmogenic contributions across both data samples. Limits to the neutrinoless mode are obtained in two alternative analyses: a background-model-dependent approach and a novel direct background-subtraction technique, offering results with small dependence on the background model assumptions. With a fiducial mass of only 3.50 ± 0.01 kg of 136 Xe-enriched xenon, 90% C.L. lower limits to the neutrinoless double beta decay are found in the $T^{0v}_{1/2} > 5.5 \times 10^{23} - 1.3 \times 10^{24}$ yr range, depending on the method. The presented techniques stand as a proof-of-concept for the searches to be implemented with larger NEXT detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Field validation of dynamic mechanical torque measurements using fiber-optic strain sensors for geared wind turbines

Abstract Accurate knowledge of the mechanical loads of wind turbine gearboxes has become essential in modern, highly loaded gearbox designs, as maintaining or even improving gearbox reliability with increasing torque density demands is proving to be challenging. Unfortunately, the traditional method of measuring dynamic mechanical torque using strain gauges placed on the outer surface of a rotating shaft and transmitting the resulting signal is unsuitable for serial deployment due to technical and economic constraints. An alternative method based on fiber-optic strain sensors placed on the stationary outer surface of the gearbox ring gear has been proposed. Like shaft torsion, the radial deformation of the ring gear is proportionate to the rotor torque. Placing the sensors on a stationary component is a cost-effective alternative for serial implementation because the need for complex and expensive data transfer via wireless transmission or a slip ring is eliminated. In this paper, we present the results of an extensive field experiment conducted to evaluate the torque measurement accuracy of this novel sensing solution installed on the gearbox of a Gamesa G97 2-MW wind turbine at the National Renewable Energy Laboratory’s Flatirons Campus. Torque measurements derived from fiber-optic strain sensors placed on the ring gear of the planetary stage are compared to conventional torque measurements from strain gauges placed on the main shaft. Two different torque estimation data processing methods were evaluated, with the method based on operational deflection shapes providing the most accurate results with an average normalized root mean square error below 0.7% for a load revolution distribution analysis. The effect of operating conditions on the torque estimate was also investigated, and the third planet-passing operational deflection shape was found to be the least sensitive to nontorque load-related effects. The fiber-optic strain sensors’ successful operation during the complete test campaign has demonstrated a robust and accurate solution for fleet-wide enhanced gearbox remaining useful life estimation.

17 WIND ENERGY↗
DOE OSTI2022

Economic analysis of CCUS: Accelerated development for CO 2 EOR and storage in residual oil zones under the context of 45Q tax credit

Residual oil zones (ROZ) undergoing CO 2 Enhanced Oil Recovery (CO 2 -EOR) may benefit from specific strategies to maximize their value. We evaluated several strategies for producing from a Permian Basin, West Texas, USA field’s ROZ. This ROZ lies below the main pay zone (MPZ) of the field. Such brownfield ROZs occur in the Permian Basin and elsewhere. Since brownfield ROZs are hydraulically connected to the MPZs, development sequences and schemes influence oil production, CO 2 storage, and net present value (NPV). We conducted economic assessments of various CO 2 injection/production schemes in the stacked ROZ-MPZ reservoir based on flow simulations of a high-resolution geocellular model built from wireline logs and core data and calibrated through production history matching. Flow simulations of water alternating gas (WAG) injection, such as switching injection from the MPZ to the ROZ and commingled production, were studied. Simulation results showed that simultaneous CO 2 injection into the MPZ and ROZ lead to the largest oil production and, generally, the largest NPV. If instead, CO 2 was simultaneously injected into the MPZ and ROZ, then into the ROZ alone, this maximized CO 2 storage. CO 2 storage can be used as a tax credit under the Internal Revenue Code, Section 45Q. Storage performance depends on the development approach and WAG ratio. Developing the ROZ increased storage compared to only producing from the MPZ. The WAG ratio to maximize oil production did not always yield the largest NPV. These findings are potentially applied to other Brownfield ROZs, which are common below San Andres reservoirs in the Permian Basin and other basins. ROZ development can increase oilfields’ NPV and carbon storage potential. Our study can serve as an analog for similar reservoirs. Here this work provides valuable insights into the further optimization of brownfield ROZ development and information for operators to plan to develop stacked ROZ-MPZ reservoirs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Time-resolved electrical potential pump – X-ray photoelectron spectroscopy probe developments for investigating dynamic processes occurring at electrochemical interfaces

Electrode–electrolyte interfaces are of critical importance in several fields, including renewable energy, corrosion, and environmental chemistry. However, investigating these interfaces under operational conditions poses considerable challenges due to the limitations of the instrumentation employed. While recent advancements in in situ and operando techniques have enhanced our comprehension of the steady-state properties of solid-liquid interfaces, the dynamic behaviors of these systems remain inadequately explored. This study introduces a time-resolved X-ray photoelectron spectroscopy (XPS) technique designed to capture transient reaction intermediates and charging dynamics at electrified interfaces. The presented proof-of-principle study demonstrates that electrochemical processes, represented by an equivalent electrical circuit (EEC) model, can be probed and understood using square wave voltage pulses of a potentiostat synchronized to the modified data acquisition of an XPS setup. This method offers a valuable alternative to traditional pump–probe techniques, facilitating the investigation of a broader range of electrochemical systems. A dedicated software package for analyzing time- and energy-resolved XPS with a focus on extracting parameters of the EEC is geared towards benchmarking different EECs in future real-world electrochemical experiments.

Electrochemistry↗
DOE OSTI2018

Occupancy prediction through Markov based feedback recurrent neural network (M-FRNN) algorithm with WiFi probe technology

Accurate occupancy prediction can improve facility control and energy efficiency of buildings. In recent years, buildings’ exiting WiFi infrastructures have been widely studied in the research of occupancy and energy conservation. However, using WiFi to assess occupancy is challenging due to that occupancy information is often characterized stochastically and varies with time and easily disturbed by building components. To overcome such limitations, this study utilizes WiFi probe technology to actively scan WiFi connection requests and responses between access points and network devices of building occupants. With captured signals, this study proposed a Markov based feedback recurrent neural network (M-FRNN) algorithm to model and predict the occupancy profiles. One on-site experiment was conducted to collect ground truth data using camera-based video analysis and the results were used to validate the M-FRNN occupancy prediction model over a 9-day measurement period. From the results, the M-FRNN based occupancy model using WiFi probes shows best accuracies can reach 80.9%, 89.6%, and 93.9% with a tolerance of 2, 3, and 4 occupants respectively. In conclusion, this study demonstrated that WiFi data coupled with stochastic machine learning system can provide a viable alternative to determine a building's occupancy profile.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Field test and simulation evaluation of variable refrigerant flow systems performance

Our study aims to compare the performance of a Variable Refrigerant Flow (VRF) system with a Roof Top Unit, (RTU) and a variable-air-volume (VAV) system through field tests and energy simulations. The field test was conducted in as similar conditions as possible between the two systems, such as the installation and operating environments of heating, the ventilation and air conditioning (HVAC) system, including internal heat gain and outdoor conditions, including buildings to compare the performance of the two systems accurately. A VRF system and RTU were installed at the test building located in Oak Ridge, Tennessee, in the USA. The same internal heat gain was generated at the same operating time of the two systems using lighting, electric heaters, and humidifiers inside the building. The HVAC system was alternately operated between cooling and heating operations to acquire energy performance data and to compare energy usage. Furthermore, an hourly building energy simulation model was developed with regard to the VRF system and RTU, and then the model was calibrated using actual measured data. Then, annual energy consumption of the two systems were compared and analyzed using the calibrated model. Moreover, additional analysis was conducted when the controlled discharge air temperature in the RTU was changed. The field test result showed that when energy consumptions of two systems were compared at the same outdoor conditions, using the weather-normalized model, the VRF system exhibited an energy reduction of approximately 17% during cooling operation and of approximately 74% during heating operations. A comparison on the annual energy consumption using simulations showed that the VRF system reduced energy consumption more than that of the RTU by 60%. Furthermore, when the discharge air temperature in the RTU was controlled according to the outdoor air temperature, energy consumption of the RTU was reduced by 6% in cooling operations and by 18% in heating operation. As a result, energy consumption of the VRF system was reduced by more than that of the RTU by 55% approximately.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Mineral dissolution and precipitation during CO 2 injection at the Frio-I Brine Pilot: Geochemical modeling and uncertainty analysis

During the Frio-I Brine Pilot CO 2 injection experiment in 2004, distinct geochemical changes in response to the injection of 1600 tons of CO 2 were recorded in samples collected from the monitoring well. Previous geochemical modeling studies have considered dissolution of calcite and iron oxyhydroxides, or release of adsorbed iron, as the most likely sources of the increased ion concentrations. We explore in this modeling study possible alternative sources of the increasing calcium and iron, based on the data from the detailed petrographic characterization of the Upper Frio Formation “C”. Particularly, we evaluate whether dissolution of pyrite and oligoclase (anorthite component) can account for the observed geochemical changes. Due to kinetic limitations, dissolution of pyrite and anorthite cannot account for the increased iron and calcium concentrations on the time scale of the field test (10 days). However, dissolution of these minerals is contributing to carbonate and clay mineral precipitation on the longer time scales (1000 years). The one-dimensional reactive transport model predicts carbonate minerals, dolomite and ankerite, as well as clay minerals kaolinite, nontronite and montmorillonite, will precipitate in the Frio Formation “C” sandstone as the system progresses towards chemical equilibrium during a 1000-year period. Cumulative uncertainties associated with using different thermodynamic databases, activity correction models (Pitzer vs. B-dot), and extrapolating to reservoir temperature, are manifested in the difference in the predicted mineral phases. Furthermore, these models are consistent with regards to the total volume of mineral precipitation and porosity values which are predicted to within 0.002%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cost analysis of alternative large-scale high-temperature solid oxide electrolysis hydrogen production facilities

We extend our past cost analysis of gigawatt-scale solid oxide electrolysis (SOE) facilities that produce high purity hydrogen gas from water by estimating construction and operating costs for three new alternative design cases: (1) offsite feed steam generation; (2) near-atmospheric pressure (NAP) stack; and (3) onsite electric boiler feed steam generation. Pressure effects on hydrogen electrode-(cathode-)supported SOE cell (SOEC) stack performance are estimated for the same assumed cell and stack construction and used to determine facility-wide stack capital costs for achieving a fixed H2 production at different pressures. Modular balance of plant (BOP) process equipment capital costs are estimated for each new alternative design case using our past equipment sizing, design, and cost data and scaling relationships. Furthermore, we update BOP equipment sizing and design for the NAP case using Aspen®. Vendor quotes for electric boilers are used to estimate costs for the electric boiler design case. Factory and onsite assembly and installation costs for SOEC stacks and BOP equipment are calculated using our past simplified first-principles approach. First-of-a-kind (FOAK) and N th -of-a-kind (NOAK) production maturity cost estimates are included for all results. The case with NAP stacks offers the lowest facility total capital cost (TCC, ~23% lower than base) while use of small electric boilers requires the highest TCC (~3% higher than base). H 2 production prices decrease from the base of ~$\$2.17$ /kgH 2 to ~$\$1.92$/kgH 2 for 1 GW e DC SIP facilities utilizing NAP stacks supplied by offsites steam situated in large modules and blocks for $\$0.030$/kWh e and $0.009/kWh t prices for electricity and thermal energy, respectively. We report all costs in 2021 US dollars.

Balance of plant (BOP) process equipment↗
DOE OSTI2025

Machine learning for reactor power monitoring with limited labeled data

Real-time reactor power monitoring is critical for a variety of nuclear applications, spanning safety, security, operations, and maintenance. While machine learning methods have shown promise in monitoring reactor power levels, there is limited research on their efficacy in label-starved environments. The goal of this work is to assess the feasibility of classifying nuclear reactor power level using multisource data in scenarios with limited labels. Data were collected using low-resolution multisensors at four nuclear reactor facilities: two large research reactors and two TRIGA reactors. Within each pair, one reactor dataset served as the source and the other as the target in a transfer learning paradigm. Twenty-three supervised models were trained on labeled sequences of magnetic field and acceleration data from each of the target sites. Self-learning and transfer learning methods were applied to the top performing models to assess their classification performance with increasing amounts of labeled data. While reactor power level classification was achieved with a Matthews Correlation Coefficient of up to 0.739 ± 0.003 and 0.622 ± 0.009 with only 400 sequences per power state for the large research reactor and TRIGA target sites, respectively, self-learning and transfer learning leveraging source site data did not improve target classification performance. These findings suggest that alternative methods, such as higher sensitivity sensors, digital twins, or the use of physics-informed models, are required to enable high-performance classification in machine learning approaches to reactor monitoring with a dearth of target ground truth.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A Bayesian model for multivariate discrete data using spatial and expert information with application to inferring building attributes

When modeling sparsely observed multivariate data, strong prior information elicited from experts can be used to bolster predictive accuracy and counteract sampling bias. Similarly, modeling autocorrelation in space can help make use of co-occurrence patterns present in many types of spatial data. To make use of both expert prior information and spatial structure, we propose a novel graphical model for a spatial Bayesian network developed specifically to address challenges in inferring the attributes of buildings from geographically sparse observational data. This model is implemented as the sum of a spatial multivariate Gaussian random field and a tabular conditional probability function in real-valued space prior to projection onto the probability simplex. This modeling form is especially suitable for the usage of prior information in the form of sets of atomic rules obtained from experts. To perform inference with missing data, we implement a Markov chain Monte Carlo scheme composed of alternating steps of Gibbs sampling of missing entries and Hamiltonian Monte Carlo for model parameters. A case study in building attribution is presented to highlight the advantages and limitations of this approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Semi-Automated, Object-Based Tomography of Dislocation Structures

The characterization of the three-dimensional arrangement of dislocations is important for many analyses in materials science. Dislocation tomography in transmission electron microscopy is conventionally accomplished through intensity-based reconstruction algorithms. Although such methods work successfully, a disadvantage is that they require many images to be collected over a large tilt range. Here, we present an alternative, semi-automated object-based approach that reduces the data collection requirements by drawing on the prior knowledge that dislocations are line objects. Our approach consists of three steps: (1) initial extraction of dislocation line objects from the individual frames, (2) alignment and matching of these objects across the frames in the tilt series, and (3) tomographic reconstruction to determine the full three-dimensional configuration of the dislocations. Drawing on innovations in graph theory, we employ a node-line segment representation for the dislocation lines and a novel arc-length mapping scheme to relate the dislocations to each other across the images in the tilt series. We demonstrate the method for a dataset collected from a dislocation network imaged by diffraction-contrast scanning transmission electron microscopy. Based on these results and a detailed uncertainty analysis for the algorithm, we discuss opportunities for optimizing data collection and further automating the method.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Combustion chemistry of ethanol: Ignition and speciation studies in a rapid compression facility [On the combustion chemistry of ethanol: Ignition and speciation studies in a rapid compression facility]

Here, ethanol remains the most important alternative fuel for the transportation sector. This work presents new experimental data on ethanol ignition, including stable species measurements, obtained with the University of Michigan rapid compression facility. Ignition delay times were determined from pressure histories of ignition experiments with stoichiometric ethanol–air mixtures at pressures of ~3–10 atm. Temperatures (880–1150 K) were controlled by varying buffer gas composition (Ar, N 2 , CO 2 ). High-speed imaging was used to record chemiluminescence during the experiments, which showed homogeneous ignition events. The results for ignition delay time agreed well with trends on the basis of previous experimental measurements. Speciation experiments were performed using fast gas sampling and gas chromatography to identify and quantify ethanol and 11 stable intermediate species formed during the ignition delay period. Simulations were carried out using a chemical kinetic mechanism available in the literature, and the agreement with the experimental results for ignition delay time and the intermediate species measured was excellent for the majority of the conditions studied. From the simulation results, ethanol + HO 2 was identified as an important reaction at the experimental conditions for both the ignition delay time and intermediate species measurements. Further studies to improve the accuracy of the rate coefficient for ethanol + HO 2 would improve the predictive understanding of intermediate and low-temperature ethanol combustion.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Toward Fullerene-Free PIN Perovskite Solar Cells

We highlight opportunities for a transformative shift in perovskite solar cell design by expanding electron transport layers (ETLs) beyond fullerenes. Fullerenes have known limitations, including constraints on open-circuit voltage, stability, and mechanical integrity. Recently, fullerene-free p-i-n cells with power conversion efficiencies exceeding 25% have been demonstrated via both naphthalene diimide-SnO x bilayers and nonfullerene acceptor-based ETLs. Despite successes, fullerenes remain the de facto ETLs for perovskites. Drawing lessons from organic photovoltaics, where it took decades to transition from fullerenes to more broadly available and efficient materials, we explore pathways to accelerate the development and adoption of fullerene-free ETLs. This requires understanding the similarities and differences between organic and perovskite solar cells, which will necessitate carefully designing fullerene replacements with both, high efficiency and also, critically, durability under operation. Here, we incorporate literature data to facilitate comparisons, and independently conduct fracture energy measurements for alternative ETL configurations to motivate their adoption.

14 SOLAR ENERGY↗
DOE OSTI2018

Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives

Abstract The cloud droplet number concentration ( N d ) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol‐cloud interactions. Current standard satellite retrievals do not operationally provide N d , but it can be inferred from retrievals of cloud optical depth ( τ c ) cloud droplet effective radius ( r e ) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel‐level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. N d uncertainty is dominated by errors in r e , and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high‐quality ground‐based observations are examined.

58 GEOSCIENCES↗
DOE OSTI2023

A sample of dust attenuation laws for Dark Energy Survey supernova host galaxies

Type Ia supernovae (SNe Ia) are useful distance indicators in cosmology, provided their luminosity is standardized by applying empirical corrections based on light-curve properties. One factor behind these corrections is dust extinction, which is accounted for in the color–luminosity relation of the standardization. This relation is usually assumed to be universal, which can potentially introduce systematics into the standardization. The “mass step” observed for SN Ia Hubble residuals has been suggested as one such systematic. We seek to obtain a more complete view of dust attenuation properties for a sample of 162 SN Ia host galaxies and to probe their link to the mass step. We inferred attenuation laws toward hosts from both global and local (4 kpc) Dark Energy Survey photometry and composite stellar population model fits. We recovered a relation between the optical depth and the attenuation slope, best explained by differing star-to-dust geometry for different galaxy orientations, which is significantly different from the optical depth and extinction slope relation observed directly for SNe. We obtain a large variation of attenuation slopes and confirm these change with host properties, such as the stellar mass and age, meaning a universal SN Ia correction should ideally not be assumed. Analyzing the cosmological standardization, we find evidence for a mass step and a two-dimensional “dust step”, both more pronounced for red SNe. Although comparable, the two steps are not found to be completely analogous. We conclude that host galaxy dust data cannot fully account for the mass step, using either an alternative SN standardization with extinction proxied by host attenuation or a dust-step approach.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

The Design of a Distributed Key-Value Store for Petascale Hot Storage in Data Acquisition Systems

Data acquisition systems for high energy physics experiments readout terabytes of data per second from a large number of electronic components. They are thus inherently distributed systems and require fast online data selection, otherwise requirements for permanent storage would be enormous. Still, incoming data need to be buffered while waiting for this selection to happen. Each minute of an experiment can produce hundreds of terabytes that cannot be lost before a selection decision is made. In this context, we present the design of DAQDB (Data Acquisition Database) - a distributed key-value store for high-bandwidth, generic data storage in event-driven systems. DAQDB offers not only high-capacity and low-latency buffer for fast data selection, but also opens a new approach in high-bandwidth data acquisition by decoupling the lifetime of the data analysis processes from the changing event rate due to the duty cycle of the data source. This is achievable by the option to extend its capacity even up to hundreds of petabytes to store hours of an experiment’s data. Our initial performance evaluation shows that DAQDB is a promising alternative to generic database solutions for the high luminosity upgrades of the LHC at CERN.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Evaluating Water Assets Using Water Efficiency Framework for Infrastructure Intensive Agency

Water infrastructure-intensive organizations should incorporate sustainability principles when making decisions on infrastructure investments to ensure the long-term resilience of mission-critical equipment and components. A water efficiency evaluation framework to inform infrastructure investments is discussed and applied to three federal campuses. The methodology considered emphasizes the iterative process between data analysis and decision-making; evaluates cost-sharing solution alternatives when making final recommendations; considers both internal and external stakeholder perceptions of project outcomes and future planning; and makes explicit government and community preferences when evaluating projects. Case study findings underscore condition evaluations for infrastructure that are critical to setting a baseline for system performance and determining desired potential upgrades and sustainment strategies. Such a holistic approach has demonstrated effectiveness for understanding, classifying, and recommending innovative water asset solutions that are necessary for the public sector to consider in today’s complex, modern planning environment.

Asset Management, Alternative Water, evaluation, P↗
DOE OSTI2014

Electronic and magnetic properties of iron doped zirconia: Theory and experiment

We systematically investigated, both theoretically and experimentally, Zr{sub 1−x}Fe{sub x}O{sub 2−y} ranging from diluted (x ≈ 0.05) up to large (x ≈ 0.25) Fe concentration. By atomic layer deposition, we grew thin films of high-κ zirconia in cubic phase with Fe uniformly distributed in the film, as proven by time of flight secondary ion mass spectrometry and transmission electron microscopy measurements. Iron is in Fe{sup 3+} oxidation state suggesting the formation of oxygen vacancies with y concentration close to x/2. By ab-initio simulations, we studied the phase diagram relating the stability of monoclinic vs. tetragonal phase as a function of Fe doping and film thickness: the critical thickness at which the pure zirconia is stabilized in the tetragonal phase is estimated ranging from 2 to 6 nm according to film morphology. Preliminary results by X-ray magnetic circular dichroism and alternating gradient force magnetometry are discussed in comparison to ab initio data enlightening the role of oxygen vacancies in the magnetic properties of the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗