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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

New fractional derivatives applied to the Korteweg–de Vries and Korteweg–de Vries–Burger’s equations

In this paper, we extend the model of the Korteweg–de Vries (KDV) and Korteweg–de Vries–Burger’s (KDVB) to new model time fractional Korteweg–de Vries (TFKDV) and time fractional Korteweg–de Vries-Burger’s (TFKDVB) with Liouville–Caputo (LC), Caputo–Fabrizio (CF), and Atangana-Baleanu (AB) fractional time derivative equations, respectively. We utilize the q-homotopy analysis transform method (q-HATM) to compute the approximate solutions of TFKDV and TFKDVB using LC, CF and AB in Liouville–Caputo sense. We study the convergence analysis of q-HATM by computing the Residual Error Function (REF) and finding the interval of the convergence through the h-curves. Also, we find the optimal values of h so that, we assure the convergence of the approximate solutions. The results are very effective and accurate in solving the TFKDV and TFKDVB.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,↗
DOE OSTI2015

SU-E-I-71: Quality Assessment of Surrogate Metrics in Multi-Atlas-Based Image Segmentation

Purpose: With the ever-growing data of heterogeneous quality, relevance assessment of atlases becomes increasingly critical for multi-atlas-based image segmentation. However, there is no universally recognized best relevance metric and even a standard to compare amongst candidates remains elusive. This study, for the first time, designs a quantification to assess relevance metrics’ quality, based on a novel perspective of the metric as surrogate for inferring the inaccessible oracle geometric agreement. Methods: We first develop an inference model to relate surrogate metrics in image space to the underlying oracle relevance metric in segmentation label space, with a monotonically non-decreasing function subject to random perturbations. Subsequently, we investigate model parameters to reveal key contributing factors to surrogates’ ability in prognosticating the oracle relevance value, for the specific task of atlas selection. Finally, we design an effective contract-to-noise ratio (eCNR) to quantify surrogates’ quality based on insights from these analyses and empirical observations. Results: The inference model was specialized to a linear function with normally distributed perturbations, with surrogate metric exemplified by several widely-used image similarity metrics, i.e., MSD/NCC/(N)MI. Surrogates’ behaviors in selecting the most relevant atlases were assessed under varying eCNR, showing that surrogates with high eCNR dominated those with low eCNR in retaining the most relevant atlases. In an end-to-end validation, NCC/(N)MI with eCNR of 0.12 compared to MSD with eCNR of 0.10 resulted in statistically better segmentation with mean DSC of about 0.85 and the first and third quartiles of (0.83, 0.89), compared to MSD with mean DSC of 0.84 and the first and third quartiles of (0.81, 0.89). Conclusion: The designed eCNR is capable of characterizing surrogate metrics’ quality in prognosticating the oracle relevance value. It has been demonstrated to be correlated with the performance of relevant atlas selection and ultimate label fusion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-D-207B-01: A Prediction Model for Distinguishing Radiation Necrosis From Tumor Progression After Gamma Knife Radiosurgery Based On Radiomics Features From MR Images

Purpose: To develop and validate a prediction model using radiomics features extracted from MR images to distinguish radiation necrosis from tumor progression for brain metastases treated with Gamma knife radiosurgery. Methods: The images used to develop the model were T1 post-contrast MR scans from 71 patients who had had pathologic confirmation of necrosis or progression; 1 lesion was identified per patient (17 necrosis and 54 progression). Radiomics features were extracted from 2 images at 2 time points per patient, both obtained prior to resection. Each lesion was manually contoured on each image, and 282 radiomics features were calculated for each lesion. The correlation for each radiomics feature between two time points was calculated within each group to identify a subset of features with distinct values between two groups. The delta of this subset of radiomics features, characterizing changes from the earlier time to the later one, was included as a covariate to build a prediction model using support vector machines with a cubic polynomial kernel function. The model was evaluated with a 10-fold cross-validation. Results: Forty radiomics features were selected based on consistent correlation values of approximately 0 for the necrosis group and >0.2 for the progression group. In performing the 10-fold cross-validation, we narrowed this number down to 11 delta radiomics features for the model. This 11-delta-feature model showed an overall prediction accuracy of 83.1%, with a true positive rate of 58.8% in predicting necrosis and 90.7% for predicting tumor progression. The area under the curve for the prediction model was 0.79. Conclusion: These delta radiomics features extracted from MR scans showed potential for distinguishing radiation necrosis from tumor progression. This tool may be a useful, noninvasive means of determining the status of an enlarging lesion after radiosurgery, aiding decision-making regarding surgical resection versus conservative medical management.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Mechanistic understanding of pH effects on the oxygen evolution reaction

The oxygen-evolution reaction (OER) is pivotal in many energy-conversion technologies as it is an important counter reaction to others that convert stable chemicals to higher-value products using electrochemistry. The local microenvironment and pH for the anode OER can vary from acidic to neutral to alkaline depending on the system being explored, making definitive mechanistic insights difficult. In this paper, we couple experiments, first-principles calculations based on density functional theory, microkinetics, and transport modeling to explore the entire pH range of the OER. At low current densities, neutral pH values unexpectedly perform better than the acidic and alkaline conditions, and this trend is reversed at higher current densities (> 20 mA cm -2 ). Using multiscale modeling, this switch is rationalized by a change from a dual-reaction mechanism to a single rate-determining step. The model also shows how the alkaline reaction rates dominate in the middle to high pH range. Furthermore, we explore that the local pH for near-neutral conditions is much different (e.g., 2.4 at the reaction surface vs. 9 in the bulk) than the pH extremes, demonstrating the criticality that transport phenomena plays in kinetic activity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep representation learning improves prediction of LacI-mediated transcriptional repression

Significance The understanding of protein function increases with new experimental and evolutionary datasets. A major challenge is to apply machine learning to these datasets to capture essential features of protein function. Here, we analyze the experimentally determined repression function for tens of thousands of mutants of the LacI protein. This study provides a continuous, noncategorical repression value across a majority of all single mutations and for thousands of higher-order mutations. To develop a top-performing model for the prediction of repression by LacI, we compare several leading variant effect prediction algorithms. A deep representation learning paradigm, first trained across millions of proteins from all known protein families and then fine-tuned using LacI experimental data, offers the highest predictive performance of repression function.

42 ENGINEERING↗
DOE OSTI2021

Spatially Quasi-Periodic Water Waves of Infinite Depth

Abstract We formulate the two-dimensional gravity-capillary water wave equations in a spatially quasi-periodic setting and present a numerical study of solutions of the initial value problem. We propose a Fourier pseudo-spectral discretization of the equations of motion in which one-dimensional quasi-periodic functions are represented by two-dimensional periodic functions on a torus. We adopt a conformal mapping formulation and employ a quasi-periodic version of the Hilbert transform to determine the normal velocity of the free surface. Two methods of time-stepping the initial value problem are proposed, an explicit Runge–Kutta (ERK) method and an exponential time-differencing (ETD) scheme. The ETD approach makes use of the small-scale decomposition to eliminate stiffness due to surface tension. We perform a convergence study to compare the accuracy and efficiency of the methods on a traveling wave test problem. We also present an example of a periodic wave profile containing vertical tangent lines that is set in motion with a quasi-periodic velocity potential. As time evolves, each wave peak evolves differently, and only some of them overturn. Beyond water waves, we argue that spatial quasi-periodicity is a natural setting to study the dynamics of linear and nonlinear waves, offering a third option to the usual modeling assumption that solutions either evolve on a periodic domain or decay at infinity.

Wilkening, Jon (ORCID:0000000327827596)↗
DOE OSTI2017

Evaluation of a multi-scale WRF-CAM5 simulation during the 2010 East Asian Summer Monsoon

The Weather Research and Forecasting model with Chemistry (WRF-Chem) with the physics package of the Community Atmosphere Model Version 5 (CAM5) has been applied at multiple scales over Eastern China (EC) and the Yangtze River Delta (YRD) to evaluate how increased horizontal resolution with physics designed for a coarser resolution climate model impacts aerosols and clouds, and the resulting precipitation characteristics and performance during the 2010 East Asian Summer Monsoon (EASM). Despite large underpredictions in surface aerosol concentrations and aerosol optical depth, there is good spatial agreement with surface observations of chemical predictions, and increasing spatial resolution tends to improve performance. Model bias and normalized root mean square values for precipitation predictions are relatively small, but there are significant differences when comparing modeled and observed probability density functions for precipitation in EC and YRD. Increasing model horizontal resolution tends to reduce model bias and error for precipitation predictions. The surface and column aerosol loading is maximized between about 32N and 42N in early to mid-May during the 2010 EASM, and then shifts north while decreasing in magnitude during July and August. Changing model resolution moderately changes the spatiotemporal relationships between aerosols, cloud properties, and precipitation during the EASM, thus demonstrating the importance of model grid resolution in simulating EASM circulation and rainfall patterns over EC and the YRD. Results from this work demonstrate the capability and limitations in the aerosol, cloud, and precipitation representation of WRF-CAM5 for regional-scale applications down to relatively fine horizontal resolutions. Further WRF-CAM5 model development and application in this area is needed.

Campbell, Patrick↗
DOE OSTI2020

Effective spin-mixing conductance of topological-insulator/ferromagnet and heavy-metal/ferromagnet spin-orbit-coupled interfaces: A first-principles Floquet-nonequilibrium Green function approach

The spin-mixing conductance (SMC) is a key quantity determining efficiency of spin transport across interfaces. Thus, knowledge of its precise value is required for accurate measurement of parameters quantifying numerous effects in spintronics, such as spin-orbit torque, spin Hall magnetoresistance, spin Hall effect, and spin pumping. However, the standard expression for SMC, provided by the scattering theory in terms of the reflection probability amplitudes, is inapplicable when strong spin-orbit coupling (SOC) is present directly at the interface. This is the precisely the case of topological-insulator/ferromagnet and heavy-metal/ferromagnet interfaces of great contemporary interest. We introduce an approach where first-principles Hamiltonian of these interfaces, obtained from noncollinear density functional theory (ncDFT) calculations, is combined with charge-conserving Floquet-nonequilibrium-Green-function formalism to compute directly the pumped spin current $I^{S_z}_L$ into semi-infinite left lead of two-terminal heterostructures Cu/X/Co/Cu or Y/Co/Cu—where X = Bi 2 Se 3 and Y = Pt or W—due to microwave-driven steadily precessing magnetization of the Co layer. This allows us to extract an effective SMC as a prefactor in $I^{S_z}_L$ versus precession cone angle θ dependence, as long as it remains the same, $I^{S_z}$ ∝ sin 2 θ , as in the case where SOC is absent. By comparing calculations where SOC in switched off versus switched on in ncDFT calculations, we find that SOC consistently reduces the pumped spin current and therefore the effective SMC.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Shapiro steps and stability of skyrmions interacting with alternating anisotropy under the influence of ac and dc drives

Here we use atomistic simulations to examine the sliding dynamics of a skyrmion in a two-dimensional system containing a periodic one-dimensional stripe pattern of variations between low and high values of the perpendicular magnetic anisotropy. The skyrmion changes in size as it crosses the interface between two anisotropy regions. On applying combined dc and ac driving in either parallel or perpendicular directions, we observe a wide variety of Shapiro steps, Shapiro spikes, and phase-locking phenomena. The phase-locked orbits have two-dimensional dynamics due to the gyrotropic or Magnus dynamics of the skyrmions and are distinct from the phase-locked orbits found for strictly overdamped systems. Along a given Shapiro step when the ac drive is perpendicular to the dc drive, the velocity parallel to the ac drive is locked while the velocity in the perpendicular direction increases with increasing drive to form Shapiro spikes. At the transition between adjacent Shapiro steps, the parallel velocity jumps up to the next step value, and the perpendicular velocity drops. The skyrmion Hall angle shows a series of spikes as a function of increasing dc drive, where the jumps correspond to the transition between different phase-locked steps. At high drives, the Shapiro steps and Shapiro spikes are lost. When both the ac and dc drives are parallel to the stripe periodicity direction, Shapiro steps appear, while if the dc drive is parallel to the stripe periodicity direction and the ac drive is perpendicular to the stripe periodicity, then there are only two locked phases, and the skyrmion motion consists of a combination of sliding along the interfaces between the two anisotropy values and jumping across the interfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Interpretable machine learning-guided design of Fe-based soft magnetic alloys

Here, we present a machine learning (ML) guided approach to predict saturation magnetization (𝑀 S ) and coercivity (𝐻 C ) in Fe-rich soft magnetic alloys, particularly Fe-Si-B systems. ML models trained on experimental data reveal that increasing Si and B content reduces 𝑀 S from 1.81 T (DFT ≈ 2.04 T) to ≈1.54 T (DFT ≈ 1.56T) in Fe-Si-B, which is attributed to decreased magnetic density and structural modifications. Experimental validation of ML predicted magnetic saturation on Fe-1Si-1B (2.09 T), Fe-5Si-5B (2.01 T), and Fe-10Si-10B (1.54 T) alloy compositions further supports our findings. These trends are consistent with density functional theory predictions, which link increased electronic disorder and band broadening to lower 𝑀 S values. Experimental validation on selected alloys confirms the predictive accuracy of the ML model, with good agreement across compositions. Beyond predictive accuracy, detailed uncertainty quantification and model interpretability including through feature importance and partial dependence analysis reveal that 𝑀 S is governed by a nonlinear interplay between Fe content and early transition metal ratios, while 𝐻 C is more sensitive to processing conditions such as ribbon thickness and thermal treatment windows. The ML framework was further applied to Fe-Si-B/Cr/Cu/Zr/Nb alloys in a pseudoquaternary compositional space, which shows comparable magnetic properties to NANOMET (Fe 84.8 ⁢Si 0.5 ⁢B 9.4 ⁢Cu 0.8⁢ P 3.5 ⁢C 1 ), FINEMET (Fe 73.5 ⁢Si 13.5 ⁢B 9 Cu 1 ⁢Nb 3 ), NANOPERM (Fe 88 ⁢Zr 7⁢ B 4 ⁢Cu 1 ), and HITPERM (Fe 44 ⁢Co 44 ⁢Zr 7⁢ B 4 ⁢Cu 1 . Our findings demonstrate the potential of the ML framework for accelerated search of high-performance soft magnetic materials.

density functional theory↗
DOE OSTI2019

Quartz conditioning crystal for X-ray rocking curve topography

A large α-quartz crystal designed to condition the monochromatic beam at beamline 1-BM of the Advanced Photon Source is presented. The purpose of this crystal was to provide a precise match to the Bragg angle of quartz crystals that are commonly used to make analyzers for plasma diagnostics. In order to characterize these analyzers, area detectors need to be positioned at distances from the analyzer at upwards of 1000 mm. As a result of this precise matching, a Bragg-reflected beam from such an analyzer is precisely parallel to the beam incident on the conditioning crystal. This situation alleviates the need to adjust the position of the area detector as the distance between the analyzer and the area detector is varied. That is, there is no need to account for vertical displacement of the diffracted-beam image as a function of this distance. Additionally, verification that the analyzer is set to the correct Bragg reflection is obtained by scanning this distance, because only for a spurious reflection will there be a vertical displacement. This is a very useful check. To commission the conditioning crystal, diffraction from a high-quality flat quartz crystal was mapped using a CCD. Bragg diffraction from the 40$\bar{40}$ reflection at 8.5 keV was studied over an area of 23 × 31 mm. The theoretical Darwin width of the flat sample in this case was 4.7 µrad. An FWHM value near 6 µrad was measured over almost the entire mapped area. These data demonstrate that the resolution function for this four-crystal arrangement is ~4 µrad. Data are also presented for a 0.1 mm-thick α-quartz wafer pressed into a concave form, having a nominal radius of 500 mm and intended for use as an analyzer. Because analyzers are bent crystals, diffraction occurs in narrow bands. When a multiple exposure is made as a function of rocking angle a striped pattern is obtained, which is commonly referred to as a zebra-stripe pattern. A series of zebra stripes from the 30$\bar{33}$ Bragg reflection of the bent wafer over its 25 mm-diameter area were recorded on a CCD. The zebra-stripe pattern was analyzed to show a uniform bending to a radius of 497.0 ± 0.3 mm, in support of the nominal value. An r.m.s. slope error of 7 µrad was also obtained from this analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Adversarial autoencoder ensemble for fast and probabilistic reconstructions of few-shot photon correlation functions for solid-state quantum emitters

Second-order photon correlation measurements [g (2) (τ) functions] are widely used to classify single-photon emission purity in quantum emitters or to measure the multiexciton quantum yield of emitters that can simultaneously host multiple excitations – such as quantum dots – by evaluating the value of g (2) (τ = 0). Accumulating enough photons to accurately calculate this value is time consuming and could be accelerated by fitting of few-shot photon correlations. Here, we develop an uncertainty-aware, deep adversarial autoencoder ensemble (AAE) that reconstructs noise-free g (2) (τ) functions from noise-dominated, few-shot inputs. The model is trained with simulated g (2) (τ) functions that are facilely generated by Poisson sampling time bins. The AAE reconstructions are performed orders-of-magnitude faster, with reconstruction errors and estimates of g (2) (τ = 0) that are lower in variance and similar in accuracy compared to Maximum likelihood estimation and Levenberg-Marquardt least-squares fitting approaches, for simulated and experimentally measured few-shot g (2) (τ) functions (~100 two-photon events) of InP/ZnS/ZnSe and CdS/CdSe/CdS quantum dots. The deep-ensemble model comprises eight individual autoencoders, allowing for probabilistic reconstructions of noise-free g (2) (τ) functions, and we show that the predicted variance scales inversely with number of shots, with comparable uncertainties to computationally intensive Markov chain Monte Carlo sampling. Furthermore, this work demonstrates the advantage of machine learning models to perform uncertainty-aware, fast, and accurate reconstructions of simple Poisson-distributed photon correlation functions, allowing for on-the-fly reconstructions and accelerated materials characterization of solid-state quantum emitters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

SU-F-I-58: Image Quality Comparisons of Different Motion Magnitudes and TR Values in MR-PET

Purpose: The aim of this work is to evaluate the accuracy and sensitivity of a respiratory-triggered MR-PET protocol in detecting four different sized lesions at two different magnitudes of motion, with two different TR values, using a novel PET-MR-CT compatible respiratory motion phantom. Methods: The eight-compartment torso phantom was setup adjacent to the motion stage, which moved four spherical compartments (28, 22, 17, 10 mm diameter) in two separate (1 and 2 cm) linear motion profiles, simulating a 3.5 second respiratory cycle. Scans were acquired on a 3T MR-PET system (Biograph mMR; Siemens Medical Solutions, Germany). MR measurements were taken with: 1) Respiratory-triggered T2-weighted turbo spin echo (BLADE) sequence in coronal orientation, and 2) Real-time balanced steady-state gradient echo sequence (TrueFISP) in coronal and sagittal planes. PET was acquired simultaneously with MR. Sphere geometries and motion profiles were measured and compared with ground truths for T2 BLADE-TSE acquisitions and real time TrueFISP images. PET quantification and geometry measurements were taken using standardized uptake values, voxel intensity plots and were compared with known values, and examined alongside MR-based attenuation maps. Contrast and signal-to-noise ratios were also compared for each of the acquisitions as functions of motion range and TR. Results: Comparison of lesion diameters indicate the respiratory triggered T2 BLADE-TSE was able to maintain geometry within −2 mm for 1 cm motion for both TR values, and within −3.1 mm for TR = 2000 ms at 2 cm motion. Sphere measurements in respiratory triggered PET images were accurate within +/− 5 mm for both ranges of motion for 28, 22, and 17 mm diameter spheres. Conclusion: Hybrid MR-PET systems show promise in imaging lung cancer in non-compliant patients, with their ability to acquire both modalities simultaneously. However, MR-based attenuation maps are still susceptible to motion derived artifacts and pose the potential to affect PET accuracy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

New York Solar Smart DG Hub-Resilient Solar Project: Economic and Resiliency Impact of PV and Storage on New York Critical Infrastructure

Resilient PV, which is solar paired with storage ('solar-plus-storage'), provides value both during normal grid operation and power outages as opposed to traditional solar PV, which functions only when the electric grid is operating. During normal grid operations, resilient PV systems help host sites generate revenue and/or reduce electricity bill charges. During grid outages, resilient PV provides critical emergency power that can help people in need and ease demand on emergency fuel supplies. The combination of grid interruptions during recent storms, the proliferation of solar PV, and the growing deployment of battery storage technologies has generated significant interest in using these assets for both economic and resiliency benefits. This report analyzes the technical and economic viability for resilient PV on three critical infrastructure sites in New York City (NYC): a school that is part of a coastal storm shelter system, a fire station, and a NYCHA senior center that serves as a cooling center during heat emergencies. This analysis differs from previous solar-plus-storage studies by placing a monetary value on resiliency and thus, in essence, modeling a new revenue stream for the avoided cost of a power outage. Analysis results show that resilient PV is economically viable for NYC's critical infrastructure and that it may be similarly beneficial to other commercial buildings across the city. This report will help city building owners, managers, and policymakers better understand the economic and resiliency benefits of resilient PV. As NYC fortifies its building stock against future storms of increasing severity, resilient PV can play an important role in disaster response and recovery while also supporting city greenhouse gas emission reduction targets and relieving stress to the electric grid from growing power demands.

14 SOLAR ENERGY↗
DOE OSTI2026

Optimization of Desalination Systems with Detailed Water Chemistry through Integration of Reaktoro in WaterTAP

Chemistry predictions are critical for an accurate estimation of performance and costs in desalination process models, which allows for the estimation of the value of new technologies and the viability of treating new water sources. Herein, we present how an implicit function formulation can be used to integrate the chemical modeling package, Reaktoro, into the techno-economic assessment and modeling platform, WaterTAP. This approach resolves the critical issues of integrating large-scale thermodynamic models and databases into equation-oriented process models while allowing more flexibility relative to previously presented surrogate-based methods. We describe how this integration into Pyomo and WaterTAP models is implemented and used through the open-source package Reaktoro-PSE . We first validate this integration approach by performing optimization on a previously presented desalination treatment train with softening and acid addition as the pretreatment steps. Then, to demonstrate the value of this approach, we extend the cost-optimization problem to include the simultaneous addition of lime and soda ash for softening, and HCl and H 2 SO 4 in the acidification steps. Finally, we were able to confirm the previously established results that were obtained by using surrogate models and demonstrate that the implicit function approach enables exploration of different feedwater compositions and a larger number of chemicals and their combinations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A novel approach to background subtraction in contrast-enhanced dual-energy digital mammography with commercially available mammography devices: Polychromaticity correction

Purpose: Contrast-enhanced digital mammography is an image subtraction technique that is able to improve the detectability of lesions in dense breasts. One of the main sources of error, when the technique is performed by means of commercial mammography devices, is represented by the intrinsic polychromaticity of the x-ray beams. The aim of the work is to propose an iterative procedure, which only assumes the knowledge of a small set of universal quantities, to take into account the polychromaticity and correct the subtraction results accordingly. Methods: In order to verify the procedure, it has been applied to an analytical simulation of a target containing a contrast medium and to actual radiographs of a breast phantom containing cavities filled with a solution of the same medium. Results: The reconstructed densities of contrast medium were compared, showing very good agreement between the theoretical predictions and the experimental results already after the first iteration. Furthermore, the convergence of the iterative procedure was studied, showing that only a small number of iterations is necessary to reach limiting values. Conclusions: The proposed procedure represents an efficient solution to the polychromaticity issue, qualifying therefore as a viable alternative to inverse-map functions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Flat-space holography and correlators of Robinson–Trautman stress tensor

We propose a quasi-local stress tensor for the four-dimensional asymptotically flat Robinson–Trautman geometries by taking the flat-space limit from the corresponding asymptotically AdS solutions. This stress tensor results in the correct charges of the generators of BMS symmetry if we define conformal infinity by an anisotropic scaling of the metric components. Using flat-space holography this stress tensor is related to expectation values of the stress tensor in a dual field theory called BMS-invariant field theory (BMSFT). We also calculate the two and three point functions of the proposed stress tensor.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗