SEARCH · Engineering Papers

Results for “data reduction methods”

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,009 records · Page 56

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Conservative projection-based data-driven model order reduction of a fluid-kinetic spectral solver

Kinetic simulations are computationally intensive due to six-dimensional phase space discretization. Many kinetic spectral solvers use the asymmetrically weighted Hermite expansion due to its conservation and fluid-kinetic coupling properties, i.e., the lower-order Hermite moments capture and describe the macroscopic fluid dynamics, and higher-order Hermite moments describe the microscopic kinetic dynamics. We leverage this structure by developing a parametric data-driven reduced-order model based on the proper orthogonal decomposition, which projects the higher-order kinetic moments while retaining the fluid moments intact. We demonstrate analytically and numerically that the method ensures local and global mass, momentum, and energy conservation. The numerical results show that the proposed method effectively replicates the high-dimensional spectral simulations at a fraction of the computational cost and memory, as validated on the weak Landau damping and two-stream instability benchmark problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Enhanced detection of paramagnetic fluorine-19 magnetic resonance imaging agents using zero echo time sequence and compressed sensing

Fluorine-19 ( 19 F) magnetic resonance imaging (MRI) is an emerging technique offering specific detection of labeled cells in vivo. Lengthy acquisition times and modest signal-to-noise ratio (SNR) makes three-dimensional spin-density–weighted 19 F imaging challenging. Recent advances in tracer paramagnetic metallo-perfluorocarbon (MPFC) nanoemulsion probes have shown multifold SNR improvements due to an accelerated 19 F T 1 relaxation rate and a commensurate gain in imaging speed and averages. However, 19 F T 2 -reduction and increased linewidth limit the amount of metal additive in MPFC probes, thus constraining the ultimate SNR. To overcome these barriers, we describe a compressed sampling (CS) scheme, implemented using a “zero” echo time (ZTE) sequence, with data reconstructed via a sparsity-promoting algorithm. Our CS-ZTE scheme acquires k-space data using an undersampled spherical radial pattern and signal averaging. Image reconstruction employs off-the-shelf sparse solvers to solve a joint total variation and -norm regularized least square problem. To evaluate CS-ZTE, we performed simulations and acquired 19 F MRI data at 11.7 T in phantoms and mice receiving MPFC-labeled dendritic cells. For MPFC-labeled cells in vivo, we show SNR gains of ~6.3 × with 8-fold undersampling. We show that this enhancement is due to three mechanisms including undersampling and commensurate increase in signal averaging in a fixed scan time, denoising attributes from the CS algorithm, and paramagnetic reduction of T 1 . Importantly, 19 F image intensity analyses yield accurate estimates of absolute quantification of 19 F spins. Overall, the CS-ZTE method using MPFC probes achieves ultrafast imaging, a substantial boost in detection sensitivity, accurate 19 F spin quantification, and minimal image artifacts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

A posteriori snapshot location for POD in optimal control of linear parabolic equations

In this paper we study the approximation of an optimal control problem for linear parabolic PDEs with model order reduction based on Proper Orthogonal Decomposition (POD-MOR). POD-MOR is a Galerkin approach where the basis functions are obtained upon information contained in time snapshots of the parabolic PDE related to given input data. In the present work we show that for POD-MOR in optimal control of parabolic equations it is important to have knowledge about the controlled system at the right time instances. We propose to determine the time instances (snapshot locations) by an a posteriori error control concept. The proposed method is based on a reformulation of the optimality system of the underlying optimal control problem as a second order in time and fourth order in space elliptic system which is approximated by a space-time finite element method. Finally, we present numerical tests to illustrate our approach and show the effectiveness of the method in comparison to existing approaches.

Mathematics↗

DOE OSTI2025

A Business Case Evaluation of Gas Switching Reforming (GSR) Technology: A Promising Technology for Natural Gas Reforming with Integrated CO2 Capture

Hydrogen is essential in the transition to sustainable energy, and developing low-carbon production methods is a key research focus. Traditional steam methane reforming (SMR) dominates the hydrogen industry but contributes substantially to CO2 emissions. In response, Gas Switching Reforming (GSR) has emerged as a novel process that integrates carbon capture and utilizes process heat more efficiently. Unlike other reforming methods, GSR consolidates oxidation and reduction reactions within a single reactor, which minimizes external energy inputs and simplifies scaling. Like conventional steam methane reforming (SMR), GSR can be integrated with water-gas shift and pressure swing adsorption units for pure hydrogen production. This work presents a comprehensive business case analysis of GSR technology based on experimental results in Technology Readiness Level 3, Life Cycle Assessment (LCA) and Techno-Economic (TEA) evaluation incorporating ASPEN Plus process modeling considering different configurations and energy scenarios. The TEA incorporates data from kinetic experiments from various catalysts to evaluate the GSR process under various conditions. The goal of this work is to evaluate GSR’s potential to serve as a low-carbon alternative to SMR, focusing on global warming potential and additional impact categories to evaluate a wide spectrum of environmental impacts. Comparative assessments were conducted with SMR, chemical loop reforming (CLR), and proton exchange membrane (PEM) electrolysis to explore trade-offs across environmental metrics. The environmental impact assessment of this work encompasses the entire hydrogen production lifecycle from raw material extraction to plant decommissioning, using a cradle-to-gate boundary. Preliminary findings highlight that GSR, when integrated with low-carbon energy sources, could significantly reduce environmental impacts, making it a promising candidate for low-carbon hydrogen infrastructure. The insights from this business case evaluation aim to guide industry in scale-up and commercialization of this promising clean energy technology.

03 NATURAL GAS↗

DOE OSTI2014

Fast Charging Electric Vehicle Research & Development Project

The research and development project supported the engineering, design and implementation of on-road Electric Vehicle (“EV”) charging technologies. It included development of potential solutions for DC fast chargers (“DCFC”) capable of converting high voltage AC power to the DC power required by EVs. Additional development evaluated solutions related to the packaging of power electronic components and enclosure design, as well as for the design and evaluation of EV charging stations. Research compared different charging technologies to identify optimum applications in a municipal fleet. This project collected EV usage data and generated a report demonstrating that EVs, when supported by adequate charging infrastructure, are capable of replacing traditional internal combustion vehicles in many municipal applications. The project’s period of performance has demonstrated various methods of incorporating EVs into a municipal environment, and has identified three general categories for EV applications: Short Commute: Defined as EVs performing in limited duration, routine commutes. - Long Commute: Defined as tasks that require EVs to operate in longer daily mileage patterns. - Critical Needs: Defined as the need for EVs to be ready at every moment for indefinite periods. Together, the City of Charlottesville, VA (the “City”) and Aker Wade Power Technologies, LLC (“Aker Wade”) concluded that the EV has a viable position in many municipal fleets but with limited recommendation for use in Critical Needs applications such as Police fleets. The report also documented that, compared to internal combustion vehicles, BEVs have lower vehicle-related greenhouse gas (“GHG”) emissions and contribute to a reduction of air pollution in urban areas. The enhanced integration of EVs in a municipal fleet can result in reduced demand for imported oil and reduced municipal operating costs. The conclusions indicated in the project’s Engineering Report (see Attachment A) are intended to assist future implementation of electric vehicle technology. They are based on the cited research and on the empirical data collected and presented. The report is not expected to represent the entire operating conditions of any of the equipment under consideration within this project, and tested equipment may operate differently under other conditions.

42 ENGINEERING↗

DOE OSTI2019

Characterizing and Improving the Data Reduction Pipeline for the Keck OSIRIS Integral Field Spectrograph

OSIRIS is a near-infrared (1.0–2.4 μm) integral field spectrograph operating behind the adaptive optics system at Keck Observatory and one of the first lenslet-based integral field spectrographs. Since its commissioning in 2005, it has been a productive instrument, producing nearly half the laser guide star adaptive optics papers on Keck. The complexity of its raw data format necessitated a custom data reduction pipeline (DRP) delivered with the instrument in order to iteratively assign flux in overlapping spectra to the proper spatial and spectral locations in a data cube. Other than bug fixes and updates required for hardware upgrades, the bulk of the DRP has not been updated since initial instrument commissioning. We report on the first major comprehensive characterization of the DRP using on-sky and calibration data. We also detail improvements to the DRP, including characterization of the flux assignment algorithm, exploration of spatial rippling in the reduced data cubes, and improvements to several calibration files, including the rectification matrix, bad-pixel mask, and wavelength solution. We present lessons learned from over a decade of OSIRIS data reduction that are relevant to the next generation of integral field spectrograph hardware and data reduction software design.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Does administering iodine in radiological procedures increase patient doses?

Purpose: The authors investigated the changes in the pattern of energy deposition in tissue equivalent phantoms following the introduction of iodinated contrast media. Methods: The phantom consisted of a small “contrast sphere,” filled with water or iodinated contrast, located at the center of a 28 cm diameter water sphere. Monte Carlo simulations were performed using MCNP5 codes, validated by simulating irradiations with analytical solutions. Monoenergetic x-rays ranging from 35 to 150 keV were used to simulate exposures to spheres containing contrast agent with iodine concentrations ranging from 1 to 100 mg/ml. Relative values of energy imparted to the contrast sphere, as well as to the whole phantom, were calculated. Changes in patterns of energy deposition around the contrast sphere were also investigated. Results: Small contrast spheres can increase local absorbed dose by a factor of 13, but the corresponding increase in total energy absorbed was negligible (<1%). The highest localized dose increases were found to occur at incident photon energies of about 60 keV. For a concentration of about 10 mg/ml, typical of clinical practice, localized absorbed doses were generally increased by about a factor of two. At this concentration of 10 mg/ml, the maximum increase in total energy deposition in the phantom was only 6%. These simulations demonstrated that increases in contrast sphere doses were offset by corresponding dose reductions at distal and posterior locations. Conclusions: Adding iodine can result in values of localized absorbed dose increasing by more than an order of magnitude, but the total energy deposition is generally very modest (i.e., <10%). Their data show that adding iodine primarily changes the pattern of energy deposition in the irradiated region, rather than increasing patient doses per se.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Revisiting a Drag Partition Model For Canopy-Like Roughness Elements

Turbulent flows over a large surface area (S) covered by n obstacles experience an overall drag due to the presence of the ground and the protruding obstacles into the flow. The drag partition between the roughness obstacles and the ground is analyzed using an analytical model proposed by Raupach (Boundary-Layer Meteorol 60:375-395, 1992) and is hereafter referred to as R92. The R92 is based on the premise that the wake behind an isolated roughness element can be described by a shelter area A and a shelter volume V. The individual sizes of A and V without any interference from other obstacles can be determined from scaling analysis for the spread of wakes. To upscale from an individual roughness element to n/S elements where wakes may interact, R92 adopted a background stress re-normalizing instead of reducing A or V with each element addition. This work demonstrates that R92’s approach results in a linear background stress reduction in A and V only when the ratio of n/S is small, due to a low probability of wake interactions. This probabilistic nature suggests that up-scaling from individual to multiple roughness elements can be re-formulated using stochastic averaging methods proposed here. The two approaches are shown to recover R92 under plausible conditions. An alternative scaling for the shelter volume is also proposed here using thermodynamic arguments of work and dissipation though the final outcome remains similar to R92. Comparisons between R92 and available data spanning more than two decades after R92 on blocks and vegetation-like roughness elements confirm the practical utility of R92. The agreement between R92 and this updated databases of experiments and simulations confirm the potential use of R92 in large-scale models provided that the relevant parameters accommodate certain features of the roughness element type (cube versus vegetation-like) and, to a lesser extent, their configuration throughout S. Last, a comparison between R92 and models based on first-order closure principles with constant mixing length suggests that R92 can outperform such models when evaluated across a wide range of roughness densities.

canopy turbulence↗

DOE OSTI2013

Biological Oxidation of Fe(II) in Reduced Nontronite Coupled with Nitrate Reduction by Pseudogulbenkiania sp. Strain 2002

Nitrate contamination in soils, sediments, and water bodies is a significant issue. Although much is known about nitrate degradation in these environments, especially via microbial pathways, a complete understanding of all degradation processes, especially in clay mineral-rich soils, is still lacking. The objective of this study was to study the potential of removing nitrate contaminant using structural Fe(II) in clay mineral nontronite. Specifically, the coupled processes of microbial oxidation of Fe(II) in microbially reduced nontronite (NAu-2) and nitrate reduction by Pseudogulbenkiania species strain 2002 was investigated. Bio-oxidation experiments were conducted in bicarbonate-buffered medium under both growth and nongrowth conditions. The extents of Fe(II) oxidation and nitrate reduction were measured by wet chemical methods. X-ray diffraction (XRD), scanning and transmission electron microscopy (SEM and TEM), and 57Fe-Mössbauer spectroscopy were used to observe mineralogical changes associated with Fe(III) reduction and Fe(II) oxidation in nontronite. The bio-oxidation extent under growth and nongrowth conditions reached 93% and 57%, respectively. Over the same time period, nitrate was completely reduced under both conditions to nitrogen gas (N2), via an intermediate product nitrite. Magnetite was a mineral product of nitrate-dependent Fe(II) oxidation, as evidenced by XRD data and TEM diffraction patterns. The results of this study highlight the importance of iron-bearing clay minerals in the global nitrogen cycle with potential applications in nitrate removal in soils.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2021

Elucidating Electron Storage and Distribution within the Pentaheme Scaffold of Cytochrome c Nitrite Reductase (NrfA)

Cytochrome c nitrite reductases (CcNIR or NrfA) play important roles in the global nitrogen cycle by conserving the usable nitrogen in the soil. Here, the electron storage and distribution properties within the pentaheme scaffold of Geobacter lovleyi NrfA were investigated via EPR spectroscopy coupled with chemical titration experiments. Initially, a chemical reduction method was established to sequentially add electrons to the fully oxidized protein, one equivalent at a time. The step–by–step reduction of the hemes was then followed using UV–Vis and EPR spectroscopy. EPR–spectral simulations elucidate the sequence of heme reduction within the pentaheme scaffold, and identify the signals of all five hemes in the EPR spectra. Electrochemical experiments ascertain the reduction potentials for each heme, observed in a narrow +11 (Heme 5) to –212 mV (Heme 3) range (vs SHE). Based on quantitative analysis/simulation of the EPR data, we demonstrate that Hemes 4 and 5 are reduced first (before the active site Heme 1) and serve the purpose of an electron storage unit within the protein. To probe the role of the central Heme 3, a H108M NrfA variant was generated where the reduction potential of Heme 3 is shifted positively (from –212 mV to +29 mV). Here, the H108M mutation significantly impacts the distribution of electrons within the pentaheme scaffold and the reduction potentials of the hemes, reducing the catalytic activity of the enzyme to 3% compared to wild–type. We propose that this is due to Heme 3’s important role as an electron gateway in the wild–type enzyme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Exploring Telematics Big Data for Truck Platooning Opportunities

NREL completed a temporal and geospatial analysis of telematics data to estimate the fraction of platoonable miles traveled by class 8 tractor trailers currently in operation. This paper discusses the value and limitations of very large but low time-resolution data sets, and the fuel consumption reduction opportunities from large scale adoption of platooning technology for class 8 highway vehicles in the US based on telematics data. The telematics data set consist of about 57,000 unique vehicles traveling over 210 million miles combined during a two-week period. 75% of the total fuel consumption result from vehicles operating in top gear, suggesting heavy highway utilization. The data is at a one-hour resolution, resulting in a significant fraction of data be uncategorizable, yet significant value can still be extracted from the remaining data. Multiple analysis methods to estimate platoonable miles are discussed. Results indicate that 63% of total miles driven at known hourly-average speeds happens at speeds amenable to platooning. When also considering availability of nearby partner vehicles, results indicate 55.7% of all classifiable miles driven were platoonable. Analysis also address the availability of numerous partners enabling platoons greater than 2 trucks and the percentage of trucks that would be required to be equipped with platooning equipment to realize more than 50% of the possible savings.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2014

Method for discovering relationships in data by dynamic quantum clustering

Data clustering is provided according to a dynamical framework based on quantum mechanical time evolution of states corresponding to data points. To expedite computations, we can approximate the time-dependent Hamiltonian formalism by a truncated calculation within a set of Gaussian wave-functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition and/or feature filtering.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Method for discovering relationships in data by dynamic quantum clustering

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Data for Photoenzymatic Stereoablative Enantioconvergence of γ-chiral Oximes via Hydrogen Atom Transfer

Producing enantioenriched molecules from racemic mixtures is essential for manufacturing. Traditional methods such as resolution, deracemization and enantioconvergent catalysis primarily involve separating or converting enantiomers without altering their structures, or functionalization of stereocentres at or proximal to functional groups. However, there are challenges in enantioselectively forging C–H bonds that are remote from functional groups via hydrogen atom transfer (HAT) with these methods. Here we introduce a strategy for the photoenzymatic stereoablative enantioconvergence of γ-chiral oximes using repurposed flavin-dependent ene-reductases. A photoinduced single-electron reduction of the γ-chiral oxime by an ene-reductase generates an iminyl radical, which then undergoes stereoablative 1,5-HAT at the γ-stereocentre. Subsequent chiral reconstruction through enzymatic HAT and spontaneous imine hydrolysis yields the γ-chiral ketone with high enantioselectivity. This work provides a robust method for remote stereoablative enantioconvergent HAT and broadens the synthetic utility of photobiocatalysis.

Bioproducts↗

DOE OSTI2022

Efficient hybrid explicit-implicit learning for multiscale problems

Splitting method is a powerful method to handle application problems by splitting physics, scales, domain, and so on. Many splitting algorithms have been designed for efficient temporal discretization. Here, in this paper, our goal is to use temporal splitting concepts in designing machine learning algorithms and, at the same time, help splitting algorithms by incorporating data and speeding them up. We propose a machine learning assisted splitting scheme which improves the efficiency of the scheme meanwhile preserves the accuracy. We consider a recently introduced multiscale splitting algorithms, where the multiscale problem is solved on a coarse grid. To approximate the dynamics, only a few degrees of freedom are solved implicitly, while others explicitly. This splitting concept allows identifying degrees of freedom that need implicit treatment. In this paper, we use this splitting concept in machine learning and propose several strategies. First, the implicit part of the solution can be learned as it is more difficult to solve, while the explicit part can be computed. This provides a speed-up and data incorporation for splitting approaches. Secondly, one can design a hybrid neural network architecture because handling explicit parts requires much fewer communications among neurons and can be done efficiently. Thirdly, one can solve the coarse grid component via PDEs or other approximation methods and construct simpler neural networks for the explicit part of the solutions. We discuss these options and implement one of them by interpreting it as a machine translation task. This interpretation of the splitting scheme successfully enables us using the Transformer since it can perform model reduction for multiple time series and learn the connection between them. We also find that the splitting scheme is a great platform to predict the coarse solution with insufficient information of the target model: the target problem is partially given and we need to solve it through a known problem which approximates the target. Our machine learning model can incorporate and encode the given information from two different problems and then solve the target problems. We conduct four numerical examples and the results show that our method is stable and accurate.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Synthesis, characterization, and properties of reduced europium molybdates and tungstates

Single crystals of K{sub 0.094}Eu{sub 0.906}MoO{sub 4}, K{sub 0.097}Eu{sub 0.903}WO{sub 4}, EuWO{sub 4}, and EuMoO{sub 4} were grown from molten chloride fluxes contained in vacuum-sealed fused silica and structurally characterized via single crystal X-ray diffraction. The in situ reduction of Eu{sup 3+} to Eu{sup 2+} was carried out using Mo, W, and Zn as metal reducing agents. All four compounds crystallize in the tetragonal space group of I4{sub 1}/a and adopt the scheelite (CaWO{sub 4}) structure type. The magnetic susceptibility of the reported compounds shows paramagnetic behavior down to 2 K. {sup 151}Eu Mössbauer spectroscopy was used to analyze the relative Eu{sup 2+} and Eu{sup 3+} content of the samples. All the compounds were further characterized by EPR, and UV-vis spectroscopy. - Graphical abstract: TOC Caption Two new reduced europium containing quaternary oxides, K{sub 0.094}Eu{sub 0.906}MoO{sub 4} and K{sub 0.097}Eu{sub 0.903}WO{sub 4}, and two previously reported ternary reduced oxides, EuWO{sub 4} and EuMoO{sub 4}, were synthesized via an in situ reduction of Eu{sup 3+} to Eu{sup 2+} under flux method using Mo, W, and Zn as metal reducing agents. {sup 151}Eu Mössbauer spectroscopy was used to analyze the relative Eu{sup 2+} and Eu{sup 3+} content of the samples. - Highlights: • K{sub 0.094}Eu{sub 0.906}MoO{sub 4}, K{sub 0.097}Eu{sub 0.903}WO{sub 4}, EuWO{sub 4}, and EuMoO{sub 4} have been synthesized and characterized. • The in situ reduction of Eu{sup 3+} to Eu{sup 2+} was carried out using Mo, W, and Zn as metal reducing agents. • Magnetic susceptibility data were collected. • {sup 151}Eu Mössbauer spectroscopy was used to analyze Eu{sup 2+} and Eu{sup 3+} content.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

The simplest equivalent circuit of a pulsed dielectric barrier discharge and the determination of the gas gap charge transfer

The concept of the simplest equivalent circuit for a dielectric barrier discharge (DBD) is critically reviewed. It is shown that the approach is consistent with experimental data measured either in large-scale sinusoidal-voltage driven or miniature pulse-voltage driven DBDs. An expression for the charge transferred through the gas gap q(t) is obtained with an accurate account for the displacement current and the values of DBD reactor capacitance. This enables (i) the significant reduction of experimental error in the determination of q(t) in pulsed DBDs, (ii) the verification of the classical electrical theory of ozonizers about maximal transferred charge q{sub max}, and (iii) the development of a graphical method for the determination of q{sub max} from charge-voltage characteristics (Q-V plots, often referred as Lissajous figures) measured under pulsed excitation. The method of graphical presentation of q{sub max} is demonstrated with an example of a Q-V plot measured under pulsed excitation. The relations between the discharge current j{sub R}(t), the transferred charge q(t), and the measurable parameters are presented in new forms, which enable the qualitative interpretation of the measured current and voltage waveforms without the knowledge about the value of the dielectric barrier capacitance C{sub d}. Whereas for quantitative evaluation of electrical measurements, the accurate estimation of the C{sub d} is important.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

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

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

36 MATERIALS SCIENCE↗