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At least 631 records · Page 35

Iterative reconstruction using a Monte Carlo based system transfer matrix for dedicated breast positron emission tomography

To maximize sensitivity, it is desirable that ring Positron Emission Tomography (PET) systems dedicated for imaging the breast have a small bore. Unfortunately, due to parallax error this causes substantial degradation in spatial resolution for objects near the periphery of the breast. In this work, a framework for computing and incorporating an accurate system matrix into iterative reconstruction is presented in an effort to reduce spatial resolution degradation towards the periphery of the breast. The GATE Monte Carlo Simulation software was utilized to accurately model the system matrix for a breast PET system. A strategy for increasing the count statistics in the system matrix computation and for reducing the system element storage space was used by calculating only a subset of matrix elements and then estimating the rest of the elements by using the geometric symmetry of the cylindrical scanner. To implement this strategy, polar voxel basis functions were used to represent the object, resulting in a block-circulant system matrix. Simulation studies using a breast PET scanner model with ring geometry demonstrated improved contrast at 45% reduced noise level and 1.5 to 3 times resolution performance improvement when compared to MLEM reconstruction using a simple line-integral model. The GATE based system matrix reconstruction technique promises to improve resolution and noise performance and reduce image distortion at FOV periphery compared to line-integral based system matrix reconstruction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Detonability of white dwarf plasma: turbulence models at low densities

We investigate the conditions required to produce self-sustained detonations in turbulent, carbon–oxygen degenerate plasma at low densities. We perform a series of three-dimensional hydrodynamic simulations of turbulence driven with various degrees of compressibility. The average conditions in the simulations are representative of models of merging binary white dwarfs. We find that material with very short ignition times is abundant in case turbulence is driven compressively. This material forms contiguous structures that persist over many ignition times, and that we identify as prospective detonation kernels. Detailed analysis of prospective kernels reveals that these objects are centrally condensed and their shape is characterized by low curvature, supportive of self-sustained detonations. The key characteristic of the newly proposed detonation mechanism is thus high degree of compressibility of turbulent drive. The simulated detonation kernels have sizes notably smaller than the spatial resolution of any white dwarf merger simulation performed to date. The resolution needed to resolve kernels is 0.1 km. Our results indicate a high probability of detonations in such well-resolved simulations of carbon–oxygen white dwarf mergers. These simulations will likely produce detonations in systems of lower total mass, thus broadening the population of white dwarf binaries capable of producing Type Ia supernovae. Consequently, we expect a downward revision of the lower limit of the total merger mass that is capable of producing a prompt detonation. We review application of the new detonation mechanism to various explosion scenarios of single, Chandrasekhar-mass white dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗

TU-EF-204-10: A Preliminary Study Evaluating Calculation Variations of Local Noise Power Spectra for CT Simulation in Radiation Therapy

Purpose: Local noise power spectrum (NPS) properties are significantly affected by calculation variables and CT acquisition and reconstruction parameters, but a thoughtful analysis of these effects is absent. In this study, we performed a complete analysis of the effects of calculation and imaging parameters on the NPS. Methods: The uniformity module of a Catphan phantom was scanned with a Philips Brilliance 64-slice CT simulator using various scanning protocols. Images were reconstructed using both FBP and iDose4 reconstruction algorithms. From these images, local NPS were calculated for regions of interest (ROI) of varying locations and sizes, using four image background removal methods. Additionally, using a predetermined ground truth, NPS calculation accuracy for various calculation parameters was compared for computer simulated ROIs. A complete analysis of the effects of calculation, acquisition, and reconstruction parameters on the NPS was conducted. Results: The local NPS varied with ROI size and image background removal method, particularly at low spatial frequencies. The image subtraction method was the most accurate according to the computer simulation study, and was also the most effective at removing low frequency background components in the acquired data. However, first-order polynomial fitting using residual sum of squares and principle component analysis provided comparable accuracy under certain situations. Similar general trends were observed when comparing the NPS for FBP to that of iDose4 while varying other calculation and scanning parameters. However, while iDose4 reduces the noise magnitude compared to FBP, this reduction is spatial-frequency dependent, further affecting NPS variations at low spatial frequencies. Conclusion: The local NPS varies significantly depending on calculation parameters, image acquisition parameters, and reconstruction techniques. Appropriate local NPS calculation should be performed to capture spatial variations of noise; calculation methodology should be selected with consideration of image reconstruction effects and the desired purpose of CT simulation for radiotherapy tasks.

60 APPLIED LIFE SCIENCES↗

INSIGHT INTO THE FORMATION OF THE MILKY WAY THROUGH COLD HALO SUBSTRUCTURE. III. STATISTICAL CHEMICAL TAGGING IN THE SMOOTH HALO

We find that the relative contribution of satellite galaxies accreted at high redshift to the stellar population of the Milky Way's smooth halo increases with distance, becoming observable relative to the classical smooth halo about 15 kpc from the Galactic center. In particular, we determine line-of-sight-averaged [Fe/H] and [{alpha}/Fe] in the metal-poor main-sequence turnoff (MPMSTO) population along every Sloan Extension for Galactic Understanding and Exploration (SEGUE) spectroscopic line of sight. Restricting our sample to those lines of sight along which we do not detect elements of cold halo substructure (ECHOS), we compile the largest spectroscopic sample of stars in the smooth component of the halo ever observed in situ beyond 10 kpc. We find significant spatial autocorrelation in [Fe/H] in the MPMSTO population in the distant half of our sample beyond about 15 kpc from the Galactic center. Inside of 15 kpc however, we find no significant spatial autocorrelation in [Fe/H]. At the same time, we perform SEGUE-like observations of N-body simulations of Milky Way analog formation. While we find that halos formed entirely by accreted satellite galaxies provide a poor match to our observations of the halo within 15 kpc of the Galactic center, we do observe spatial autocorrelation in [Fe/H] in the simulations at larger distances. This observation is an example of statistical chemical tagging and indicates that spatial autocorrelation in metallicity is a generic feature of stellar halos formed from accreted satellite galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Solid-State Side-Chain Functionalization of Conjugated Polymers for Expanded Chemical and Functional Versatility

Conjugated polymers that integrate diverse chemical functionalities with high electronic performance are essential for advanced organic electronic, optoelectronic, and biointerfaced technologies. Achieving such multifunctionality typically requires grafting functional units onto polymer side chains. However, conventional solution-phase approaches remain constrained by solubility limitations, side-chain-induced packing disruptions, and challenges in preserving charge transport. Here, we introduce a solid-state side-chain functionalization strategy that exploits a swellable polar side-chain architecture and azide–alkyne click chemistry to enable efficient molecular diffusion and reaction throughout predeposited polymer thin films. This approach substantially broadens the chemical compatibility of graftable units and mitigates the adverse effects on the electrical property. Moreover, the method supports spatially selective functionalization within a continuous film, enabling the patterned incorporation of chemically distinct groups to produce spatially defined optical properties. Here, this solid-state strategy thus provides a versatile platform for constructing conjugated polymers with expanded chemical versatility, preserved electronic performance, and programmable spatial functionality.

Conjugated polymers↗

From h to p efficiently: optimal implementation strategies for explicit time-dependent problems using the spectral/ hp element method: FROM h TO p EFFICIENTLY

We investigate the relative performance of a second-order Adams–Bashforth scheme and second-order and fourth-order Runge–Kutta schemes when time stepping a 2D linear advection problem discretised using a spectral/hp element technique for a range of different mesh sizes and polynomial orders. Numerical experiments explore the effects of short (two wavelengths) and long (32 wavelengths) time integration for sets of uniform and non-uniform meshes. The choice of time-integration scheme and discretisation together fixes a CFL limit that imposes a restriction on the maximum time step, which can be taken to ensure numerical stability. The number of steps, together with the order of the scheme, affects not only the runtime but also the accuracy of the solution. Through numerical experiments, we systematically highlight the relative effects of spatial resolution and choice of time integration on performance and provide general guidelines on how best to achieve the minimal execution time in order to obtain a prescribed solution accuracy. The significant role played by higher polynomial orders in reducing CPU time while preserving accuracy becomes more evident, especially for uniform meshes, compared with what has been typically considered when studying this type of problem.

42 ENGINEERING↗

Multi-objective optimization of sustainable aviation fuel production pathways in the U.S. Corn Belt

As a potential source of low-carbon transportation energy, biofuels offer certain advantages over vehicle electrification (e.g., lower societal vulnerability to grid failures, and improved range of sustainable aviation), but also several challenges, including cost, carbon intensity, and land usage. There are also well-founded concerns that biofuel supply chains could be disrupted if extreme weather events impact feedstock yields. In this paper, we explore the use of multi-objective optimization to identify biofuel production pathways that balance cost, greenhouse gas emissions, and supply vulnerability to extreme weather. We compare the use of three different many-objective evolutionary algorithms and linear programming in optimizing biomass cultivation decisions in the U.S. Corn Belt under weather uncertainty using historical, modeled, and synthetic yield data. We consider four feedstock choices (corn, soy, switchgrass, and algae) with two land types (agricultural and marginal lands) and evaluate decisions using three alternative spatial resolutions (ranging from the USDA agricultural district level to the state level). Results show that feedstock choice is the primary driver of objective performance (i.e., the position and shape of 3D, approximate Pareto frontiers). Spatial diversification is a less effective tool in reducing exposure to weather-caused drops in crop yield.

09 BIOMASS FUELS↗

Feature-space assessment of electrical impedance tomography coregistered with computed tomography in detecting multiple contrast targets

Purpose: Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets. Methods: EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance and diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures. Results: In detecting distilled and normal saline water in bolus medium, EIT as a stand-alone imaging system showed contrast discrimination of 47%, while the CT imaging system showed a discrimination of only 1.5%. The structural similarity index measure showed a drop of 24% with EIT imaging compared to CT imaging. The average detectability measure for CT imaging was found to be 2.375 ± 0.19 before fusion. After complementing with EIT information, the detectability measure increased to 11.06 ± 2.04. Based on the feature metrics, the functional imaging quality of CT and EIT were found to be 2.29% and 86%, respectively, before fusion. Structural imaging quality was found to be 66% for CT and 16% for EIT. After fusion, functional imaging quality improved in CT imaging from 2.29% to 42% and the structural imaging quality of EIT imaging changed from 16% to 66%. The improvement in image quality was also observed in detecting objects of different sizes. Conclusions: The authors found a significant improvement in the contrast detectability performance of CT imaging when complemented with functional imaging information from EIT. Along with the feature assessment metrics, the concept of complementing CT with EIT imaging can lead to an EIT/CT imaging modality which might fully utilize the functional imaging abilities of EIT imaging, thereby enhancing the quality of care in the areas of cancer diagnosis and radiotherapy treatment planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Scaling and statistics of bottom-up synthesized armchair graphene nanoribbon transistors

Bottom-up assembled nanomaterials and nanostructures allow for the studies of rich and unprecedented quantum-related and mesoscopic transport phenomena. However, it can be difficult to quantify the correlations between the geometrical or structural parameters obtained from advanced microscopy and measured electrical characteristics when they are made into macroscopic devices. Here, we propose a strategy to connect the nanomaterial morphologies and the device performance through a Monte Carlo device model and apply it to understand the scaling trends of bottom-up synthesized armchair graphene nanoribbon (GNR) transistors. A new nanofabrication process is developed for GNR transistors with channel length down to 7 nm. Further, the impacts of the GNR spatial distributions and the device geometries on the device performance are investigated systematically through comparison of experimental data with the model. Through this study, challenges and opportunities of transistor technologies based on bottom-up synthesized GNRs are pinpointed, paving the way to the further improvement of the GNR device performance for future transistor technology nodes.

36 MATERIALS SCIENCE↗

Universal linear intensity transformations using spatially incoherent diffractive processors

Abstract Under spatially coherent light, a diffractive optical network composed of structured surfaces can be designed to perform any arbitrary complex-valued linear transformation between its input and output fields-of-view (FOVs) if the total number ( N ) of optimizable phase-only diffractive features is ≥~2 N i N o , where N i and N o refer to the number of useful pixels at the input and the output FOVs, respectively. Here we report the design of a spatially incoherent diffractive optical processor that can approximate any arbitrary linear transformation in time-averaged intensity between its input and output FOVs. Under spatially incoherent monochromatic light, the spatially varying intensity point spread function ( H ) of a diffractive network, corresponding to a given, arbitrarily-selected linear intensity transformation, can be written as H ( m , n ; m ′, n ′) = | h ( m , n ; m ′, n ′)| 2 , where h is the spatially coherent point spread function of the same diffractive network, and ( m , n ) and ( m ′, n ′) define the coordinates of the output and input FOVs, respectively. Using numerical simulations and deep learning, supervised through examples of input-output profiles, we demonstrate that a spatially incoherent diffractive network can be trained to all-optically perform any arbitrary linear intensity transformation between its input and output if N ≥ ~2 N i N o . We also report the design of spatially incoherent diffractive networks for linear processing of intensity information at multiple illumination wavelengths, operating simultaneously. Finally, we numerically demonstrate a diffractive network design that performs all-optical classification of handwritten digits under spatially incoherent illumination, achieving a test accuracy of >95%. Spatially incoherent diffractive networks will be broadly useful for designing all-optical visual processors that can work under natural light.

36 MATERIALS SCIENCE↗

A robust geometry estimation method for spiral, sequential and circular cone-beam micro-CT

Purpose: The authors propose a novel method for misalignment estimation of micro-CT scanners using an adaptive genetic algorithm. Methods: The proposed algorithm is able to estimate the rotational geometry, the direction vector of table movement and the displacement between different imaging threads of a dual source or even multisource scanner. The calibration procedure does not rely on dedicated calibration phantoms and a sequence scan of a single metal bead is sufficient to geometrically calibrate the whole imaging system for spiral, sequential, and circular scan protocols. Dual source spiral and sequential scan protocols in micro-computed tomography result in projection data that-besides the source and detector positions and orientations-also require a precise knowledge of the table direction vector to be reconstructed properly. If those geometric parameters are not known accurately severe artifacts and a loss in spatial resolution appear in the reconstructed images as long as no geometry calibration is performed. The table direction vector is further required to ensure that consecutive volumes of a sequence scan can be stitched together and to allow the reconstruction of spiral data at all. Results: The algorithm's performance is evaluated using simulations of a micro-CT system with known geometry and misalignment. To assess the quality of the algorithm in a real world scenario the calibration of a micro-CT scanner is performed and several reconstructions with and without geometry estimation are presented. Conclusions: The results indicate that the algorithm successfully estimates all geometry parameters, misalignment artifacts in the reconstructed volumes vanish, and the spatial resolution is increased as can be shown by the evaluation of modulation transfer function measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Simulated performance of the optical Thomson scattering diagnostic designed for the National Ignition Facility

An optical Thomson scattering diagnostic has been designed for the National Ignition Facility to characterize under-dense plasmas. We report on the design of the system and the expected performance for different target configurations. The diagnostic is designed to spatially and temporally resolve the Thomson scattered light from laser driven targets. The diagnostic will collect scattered light from a 50 × 50 × 200 μm volume. The optical design allows operation with different probe laser wavelengths. A deep-UV probe beam (λ{sub 0} = 210 nm) will be used to Thomson scatter from electron plasma densities of ∼5 × 10{sup 20} cm{sup −3} while a 3ω probe will be used for plasma densities of ∼1 × 10{sup 19} cm{sup −3}. The diagnostic package contains two spectrometers: the first to resolve Thomson scattering from ion acoustic wave fluctuations and the second to resolve scattering from electron plasma wave fluctuations. Expected signal levels relative to background will be presented for typical target configurations (hohlraums and a planar foil).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Digital Speckle Photography of Subpixel Displacements of Speckle Structures Based on Analysis of Their Spatial Spectra

We have investigated the capabilities of the method of digital speckle interferometry for determining subpixel displacements of a speckle structure formed by a displaceable or deformable object with a scattering surface. An analysis of spatial spectra of speckle structures makes it possible to perform measurements with a subpixel accuracy and to extend the lower boundary of the range of measurements of displacements of speckle structures to the range of subpixel values. The method is realized on the basis of digital recording of the images of undisplaced and displaced speckle structures, their spatial frequency analysis using numerically specified constant phase shifts, and correlation analysis of spatial spectra of speckle structures. Transformation into the frequency range makes it possible to obtain quantities to be measured with a subpixel accuracy from the shift of the interference-pattern minimum in the diffraction halo by introducing an additional phase shift into the complex spatial spectrum of the speckle structure or from the slope of the linear plot of the function of accumulated phase difference in the field of the complex spatial spectrum of the displaced speckle structure. The capabilities of the method have been investigated in natural experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Developing a bright 17 keV x-ray source for probing high-energy-density states of matter at high spatial resolution

A set of experiments were performed on the National Ignition Facility (NIF) to develop and optimize a bright, 17 keV x-ray backlighter probe using laser-irradiated Nb foils. High-resolution one-dimensional imaging was achieved using a 15 μm wide slit in a Ta substrate to aperture the Nb He{sub α} x-rays onto an open-aperture, time integrated camera. To optimize the x-ray source for imaging applications, the effect of laser pulse shape and spatial profile on the target was investigated. Two laser pulse shapes were used—a “prepulse” shape that included a 3 ns, low-intensity laser foot preceding the high-energy 2 ns square main laser drive, and a pulse without the laser foot. The laser spatial profile was varied by the use of continuous phase plates (CPPs) on a pair of shots compared to beams at best focus, without CPPs. A comprehensive set of common diagnostics allowed for a direct comparison of imaging resolution, total x-ray conversion efficiency, and x-ray spectrum between shots. The use of CPPs was seen to reduce the high-energy tail of the x-ray spectrum, whereas the laser pulse shape had little effect on the high-energy tail. The measured imaging resolution was comparably high for all combinations of laser parameters, but a higher x-ray flux was achieved without phase plates. This increased flux was the result of smaller laser spot sizes, which allowed us to arrange the laser focal spots from multiple beams and produce an x-ray source which was more localized behind the slit aperture. Our experiments are a first demonstration of point-projection geometry imaging at NIF at the energies (>10 keV) necessary for imaging denser, higher-Z targets than have previously been investigated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Residual stress analysis of aluminum nitride piezoelectric micromachined ultrasonic transducers using Raman spectroscopy

In this study, the Raman biaxial stress coefficients K II and strain-free phonon frequencies ω 0 have been determined for the E 2 (low), E 2 (high), and A 1 (LO) phonon modes of aluminum nitride, AlN, using both experimental and theoretical approaches. The E 2 (high) mode of AlN is recommended for the residual stress analysis of AlN due to its high sensitivity and the largest signal-to-noise ratio among the studied modes. The E 2 (high) Raman biaxial stress coefficient of ₋3.8 cm₋1/GPa and strain-free phonon frequency of 656.68 cm ₋1 were then applied to perform both macroscopic and microscopic stress mappings. For macroscopic stress evaluation, the spatial variation of residual stress was measured across an AlN-on-Si wafer prepared by sputter deposition. A cross-wafer variation in residual stress of ~150 MPa was observed regardless of the average stress state of the film. Microscopic stress evaluation was performed on AlN piezoelectric micromachined ultrasonic transducers (pMUTs) with submicrometer spatial resolution. These measurements were used to assess the effect of device fabrication on residual stress distribution in an individual pMUT and the effect of residual stress on the resonance frequency. At ~20 μm directly outside the outer edge of the pMUT electrode, a large lateral spatial variation in residual stress of ~100 MPa was measured, highlighting the impact of metallization structures on residual stress in the AlN film.

36 MATERIALS SCIENCE↗

The suitability of differentiable, physics-informed machine learning hydrologic models for ungauged regions and climate change impact assessment

As a genre of physics-informed machine learning, differentiable process-based hydrologic models (abbreviated as δ or delta models) with regionalized deep-network-based parameterization pipelines were recently shown to provide daily streamflow prediction performance closely approaching that of state-of-the-art long short-term memory (LSTM) deep networks. Meanwhile, δ models provide a full suite of diagnostic physical variables and guaranteed mass conservation. Here, we ran experiments to test (1) their ability to extrapolate to regions far from streamflow gauges and (2) their ability to make credible predictions of long-term (decadal-scale) change trends. We evaluated the models based on daily hydrograph metrics (Nash–Sutcliffe model efficiency coefficient, etc.) and predicted decadal streamflow trends. For prediction in ungauged basins (PUB; randomly sampled ungauged basins representing spatial interpolation), δ models either approached or surpassed the performance of LSTM in daily hydrograph metrics, depending on the meteorological forcing data used. They presented a comparable trend performance to LSTM for annual mean flow and high flow but worse trends for low flow. For prediction in ungauged regions (PUR; regional holdout test representing spatial extrapolation in a highly data-sparse scenario), δ models surpassed LSTM in daily hydrograph metrics, and their advantages in mean and high flow trends became prominent. In addition, an untrained variable, evapotranspiration, retained good seasonality even for extrapolated cases. The δ models' deep-network-based parameterization pipeline produced parameter fields that maintain remarkably stable spatial patterns even in highly data-scarce scenarios, which explains their robustness. Combined with their interpretability and ability to assimilate multi-source observations, the δ models are strong candidates for regional and global-scale hydrologic simulations and climate change impact assessment.

54 ENVIRONMENTAL SCIENCES↗

Imaging of the Li spatial distribution within V 2 O 5 cathode in a coin cell by neutron computed tomography

An understanding of Lithium (Li) spatial distribution within the electrodes of a Li-ion cell, during charge and discharge cycles, is essential to optimize the electrode parameters for increased performance under cycling. In this work, it is demonstrated that the spatial distribution of Li within Vanadium Pentoxide (V 2 O 5 ) electrodes of a small coin cell can be imaged by neutron computed tomography. The neutron attenuation data has been used to construct the three-dimensional Li spatial images. Specifically, it is shown that there is sufficient neutron imaging contrast between lithiated and delithiated regions of V 2 O 5 electrode making it possible to map Li distributions even in small electrodes with thicknesses <1 mm. The images reveal that the Li spatial distribution is inhomogeneous and a relatively higher C-rate leads to more non-uniform Li distribution after Li insertion. The non-uniform distribution suggests the limitation of Li diffusion within the electrode during the lithiation process under the relatively high cycling rates.

25 ENERGY STORAGE↗