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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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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Satellite-based remote sensing data set of global surface water storage change from 1992 to 2018

The recent availability of freely and openly available satellite remote sensing products has enabled the implementation of global surface water monitoring at a level not previously possible. Here we present a global set of satellite-derived time series of surface water storage variations for lakes and reservoirs for a period that covers the satellite altimetry era. Our goals are to promote the use of satellite-derived products for the study of large inland water bodies and to set the stage for the expected availability of products from the Surface Water and Ocean Topography (SWOT) mission, which will vastly expand the spatial coverage of such products,expected from 2021 on. Our general strategy is to estimate global surface water storage changes (1V) in large lakes and reservoirs using a combination of paired water surface elevation (WSE) and water surface area (WSA)extent products. Specifically, we use data produced by multiple satellite altimetry missions (TOPEX/Poseidon,Jason-1, Jason-2, Jason-3, and Envisat) from 1992 on, with surface extent estimated from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000 on. We leverage relationships between elevation and surface area (i.e., hypsometry) to produce estimates of 1 Veven during periods when either of the variables was not available. This approach is successful provided that there are strong relationships between the two variables during an overlapping period. Our target is to produce time series of1Vas well as of WSE and WSA fora set of 347 lakes and reservoirs globally for the 1992–2018 period. The data sets presented and their respective algorithm theoretical basis documents are publicly available and distributed via the Physical Oceanography Dis-tributed Active Archive Center (PO DAAC; https://podaac.jpl.nasa.gov/, last access: 13 May 2020) of NASA’sJet Propulsion Laboratory. Specifically, the WSE data set is available at https://doi.org/10.5067/UCLRS-GREV2(Birkett et al., 2019), the WSA data set is available at https://doi.org/10.5067/UCLRS-AREV2 (Khandelwal and Kumar, 2019), and the 1V data set is available at https://doi.org/10.5067/UCLRS-STOV2 (Tortini et al., 2019).The records we describe represent the most complete global surface water time series available from the launch of TOPEX/Poseidon in 1992 (beginning of the satellite altimetry era) to the near present. The production of long-term, consistent, and calibrated records of surface water cycle variables such as in the data set presented here is of fundamental importance to baseline future SWOT products

Riccardo Tortini↗
NASA NTRS1981

On the internal target model in a tracking task

An optimal control model for predicting operator's dynamic responses and errors in target tracking ability is summarized. The model, which predicts asymmetry in the tracking data, is dependent on target maneuvers and trajectories. Gunners perception, decision making, control, and estimate of target positions and velocity related to crossover intervals are discussed. The model provides estimates for means, standard deviations, and variances for variables investigated and for operator estimates of future target positions and velocities.

Caglayan, A. K.↗
DOE OSTI2015

WE-EF-BRA-03: Catheter- Free Ablation with External Photon Radiation: Treatment Planning, Delivery Considerations, and Correlation of Effects with Delivered Dose

Purpose: To plan, target, and calculate delivered dose in atrioventricular node (AVN) ablation with volume-modulated arc therapy (VMAT) in an intact porcine model. Methods: Seven pigs underwent AVN irradiation, with prescription doses ranging between 25 and 55Gy in a single fraction. Cardiac CT scans were acquired at expiration. Two physicians contoured AVN targets on 10 phases, providing estimates of target motion and inter-physician variability. Treatment planning was conducted on a static phase-averaged CT. The volume designated to receive prescription dose covered the full extent of AVN cardiac motion, expanded by 4mm for setup uncertainty. Optimization limited doses to risk structures according to single-fraction tumor treatment protocols. Orthogonal kV images were used to align bony anatomy at time of treatment. Localization was further refined with respiratory-gated cone-beam CT, and range of cardiac motion was verified under fluoroscopy. Beam delivery was respiratory-gated for expiration with a mean efficiency of 60%. Deformable registration of the 10 cardiac CT phases was used to calculate actual delivered dose for comparison to electro-anatomical and visually evident lesions. Results: The mean [minimum,maximum] amplitude of AVN cardiac motion was LR 2.9 [1.7,3.9]mm, AP 6.6 [4.4,10.4]mm, and SI 5.6 [2.0,9.9]mm. Incorporating cardiac motion into the dose calculation showed the volume receiving full dose was 40–80% of the volume indicated on the static planning image, although the contoured AVN target received full dose in all animals. Initial results suggest the dimensions of the electro-anatomical lesion are correlated with the 40Gy isodose volume. Conclusion: Image-guidance techniques allow for accurate and precise delivery of VMAT for catheter-free arrhythmia ablation. An arsenal of advanced radiation planning, dose optimization, and image-guided delivery techniques was employed to assess and mitigate effects of cardiac and respiratory motion. Feasibility of delivery to the pulmonary veins and left ventricular myocardium will be investigated in future studies. D. Packer Disclosures: Abiomed, Biosense Webster, Inc., Boston Scientific Corp., CardioFocus, Inc., Johnson and Johnson, Excerpta Medica, Ortho-McNeil-Jannsen, Sanofi Aventis, CardioInsight Technologies, InfoBionic, SIEMENS, Medtronic, Inc., CardioDx, Inc., CardioInsight Technologies, FoxP2 Medica, Mediasphere Medical, Wiley-Blackwell, St. Jude Medical, Endosense, Thermedical, EP Advocate LLC, Hansen Medical, American Heart Association, EpiEP, NIH.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Climate variation explains a third of global crop yield variability

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for B13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, 460% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (B32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

SU-E-J-96: Multi-Axis Dose Accumulation of Noninvasive Image-Guided Breast Brachytherapy Through Biomechanical Modeling of Tissue Deformation Using the Finite Element Method

Purpose: Noninvasive image-guided breast brachytherapy delivers conformal HDR Ir-192 brachytherapy treatments with the breast compressed, and treated in the cranial-caudal and medial-lateral directions. This technique subjects breast tissue to extreme deformations not observed for other disease sites. Given that, commercially-available software for deformable image registration cannot accurately co-register image sets obtained in these two states, a finite element analysis based on a biomechanical model was developed to deform dose distributions for each compression circumstance for dose summation. Methods: The model assumed the breast was under planar stress with values of 30 kPa for Young’s modulus and 0.3 for Poisson’s ratio. Dose distributions from round and skin-dose optimized applicators in cranial-caudal and medial-lateral compressions were deformed using 0.1 cm planar resolution. Dose distributions, skin doses, and dose-volume histograms were generated. Results were examined as a function of breast thickness, applicator size, target size, and offset distance from the center. Results: Over the range of examined thicknesses, target size increased several millimeters as compression thickness decreased. This trend increased with increasing offset distances. Applicator size minimally affected target coverage, until applicator size was less than the compressed target size. In all cases, with an applicator larger or equal to the compressed target size, > 90% of the target covered by > 90% of the prescription dose. In all cases, dose coverage became less uniform as offset distance increased and average dose increased. This effect was more pronounced for smaller target-applicator combinations. Conclusions: The model exhibited skin dose trends that matched MC-generated benchmarking results and clinical measurements within 2% over a similar range of breast thicknesses and target sizes. The model provided quantitative insight on dosimetric treatment variables over a range of clinical circumstances. These findings highlight the need for careful target localization and accurate identification of compression thickness and target offset. Prof. Rivard is a shareholder of Advanced Radiation Therapy, LLC, the manufacturer of the AccuBoost noninvasive image-guided breast brachytherapy system examined herein. None of the other authors have any conflicts-of-interest for this work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV -2 spike receptor binding domain ( RBD )

The continued emergence of new SARS-CoV-2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high-affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent-exposed hACE2-binding residues of the SARS-CoV-2 spike receptor binding domain (RBD) protein using the software tool OptMAVEn-2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9-mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade-off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced by OptMAVEn-2.0 using a Rosetta-based approach. We used Rosetta SnugDock for local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” with DeepAb to assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS-CoV-2 variants or other antigenic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Synthesis and Characterization of Magnesium Vanadates as Potential Magnesium‐Ion Cathode Materials through an Ab Initio Guided Carbothermal Reduction Approach**

Abstract Many technologically relevant materials for advanced energy storage and catalysis feature reduced transition‐metal (TM) oxides that are often nontrivial to prepare because of the need to control the reducing nature of the atmosphere in which they are synthesized. Herein, we show that an ab initio predictive synthesis strategy can be used to produce multi‐gram‐scale products of various MgV x O y ‐type phases (δ‐MgV 2 O 5 , spinel MgV 2 O 4 , and MgVO 3 ) containing V 3+ or V 4+ relevant for Mg‐ion battery cathodes. Characterization of these phases using 25 Mg solid‐state NMR spectroscopy illustrates the potential of 25 Mg NMR for studying reversible magnesiation and local charge distributions. Rotor‐assisted population transfer (RAPT) is used as a much‐needed signal‐to‐noise enhancement technique. The ab initio guided synthesis method is seen as a step forward towards a predictive synthesis strategy for targeting specific complex TM oxides with variable oxidation states of technological importance.

Lee, Jeongjae↗
DOE OSTI2021

Synthesis and Characterization of Magnesium Vanadates as Potential Magnesium-Ion Cathode Materials through an Ab Initio Guided Carbothermal Reduction Approach**

Many technologically relevant materials for advanced energy storage and catalysis feature reduced transition-metal (TM) oxides that are often nontrivial to prepare because of the need to control the reducing nature of the atmosphere in which they are synthesized. In this report, we show that an ab initio predictive synthesis strategy can be used to produce multi-gram-scale products of various MgV x O y -type phases (δ-MgV 2 O 5 , spinel MgV 2 O 4 , and MgVO 3 ) containing V 3+ or V 4+ relevant for Mg-ion battery cathodes. Characterization of these phases using 25 Mg solid-state NMR spectroscopy illustrates the potential of 25 Mg NMR for studying reversible magnesiation and local charge distributions. Rotor-assisted population transfer (RAPT) is used as a much-needed signal-to-noise enhancement technique. The ab initio guided synthesis method is seen as a step forward towards a predictive synthesis strategy for targeting specific complex TM oxides with variable oxidation states of technological importance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A workflow to assess the efficacy of brine extraction for managing injection-induced seismicity potential using data from a CO 2 injection site near Decatur, Illinois

Injection of CO 2 for storage in a geologic formation increases pore pressure and alters in situ stresses. Depending on the orientation of any existing fault and fracture planes, such as critically stressed planes, this stress alteration will modify normal stresses acting on planes and could result in frictional sliding and release stored energy in the form of seismicity. Brine extraction (BE) is a technique that can be applied prior to, or during, CO 2 injection to reduce pore pressure for increasing storage capacity and, potentially, for reducing the likelihood of frictional sliding. Here a workflow is described to assess the efficacy of BE for mitigating frictional sliding (i.e., seismicity) during injection and entails: site characterization, stress calculations and failure assessment, static and dynamic modeling, and BE operational planning. Site characterization describes the stress field used to calculate the Coulomb Failure Function (CFF) that constrains allowable pore pressure changes and injection rates in the numerical simulation of CO 2 injection scenarios. The inclusion of BE in the workflow allows for determination of the potential need for pressure reduction, and evaluation of the effectiveness of this operation. Example application of the workflow using an injection field dataset near Decatur, IL, provides insight on fracture planes and stresses at the site, formation properties and the impact of variable CO 2 injection-rate targets on whether BE plans are required. The study workflow indicates that BE could enhance CO 2 injection rate by 39% and correspondingly reduce the potential for injection-induced seismicity as indicated by a reduction in CFF.

58 GEOSCIENCES↗
DOE OSTI2018

Deep Learning Algorithm for Auto-Delineation of High-Risk Oropharyngeal Clinical Target Volumes With Built-In Dice Similarity Coefficient Parameter Optimization Function

Automating and standardizing the contouring of clinical target volumes (CTVs) can reduce interphysician variability, which is one of the largest sources of uncertainty in head and neck radiation therapy. In addition to using uniform margin expansions to auto-delineate high-risk CTVs, very little work has been performed to provide patient- and disease-specific high-risk CTVs. The aim of the present study was to develop a deep neural network for the auto-delineation of high-risk CTVs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Protein markers for identification of Yersinia pestis and their variation related to culture

The detection of high consequence pathogens, such as Yersinia pestis, is well established in biodefense laboratories for bioterror situations. Laboratory protocols are well established using specified culture media and a growth temperature of 37 °C for expression of specific antigens. Direct detection of Y. pestis protein markers, without prior culture, depends on their expression. Unfortunately protein expression can be impacted by the culture medium which cannot be predicted ahead of time. Furthermore, higher biomass yields are obtained at the optimal growth temperature (i.e. 28 °C–30 °C) and therefore are more likely to be used for bulk production. Analysis of Y. pestis grown on several types of media at 30 °C showed that several protein markers were found to be differentially detected in different media. Analysis of the identified proteins against a comprehensive database provided an additional level of organism identification. Peptides corresponding to variable regions of some proteins could separate large groups of strains and aid in organism identification. This work illustrates the need to understand variability of protein expression for detection targets. The potential for relating expression changes of known proteins to specific media factors, even in nutrient rich and chemically complex culture medium, may provide the opportunity to draw forensic information from protein profiles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic-scale atmospheric dynamics, their performance across timescales and under out-of-distribution forcing, such as +3K or +4K uniform-warming forcings, and the sources of biases remain elusive, to establish the model's reliability for Earth science. Here, we design three sets of experiments targeting synoptic-scale phenomena, interannual variability, and out-of-distribution uniform-warming forcings. We evaluate the Neural General Circulation Model (NeuralGCM), a hybrid model integrating a dynamical core with ML-based component, against observations and physics-based Earth system models (ESMs). At the synoptic scale, NeuralGCM captures the evolution and propagation of extratropical cyclones with performance comparable to ESMs. At the interannual scale, when forced by El Niño-Southern Oscillation sea surface temperature (SST) anomalies, NeuralGCM successfully reproduces associated teleconnection patterns but exhibits deficiencies in capturing nonlinear response. Under out-of-distribution uniform-warming forcings, NeuralGCM simulates similar responses in global-average temperature and precipitation and reproduces large-scale tropospheric circulation features similar to those in ESMs. Notable weaknesses include overestimating the tracks and spatial extent of extratropical cyclones, biases in the teleconnected wave train triggered by tropical SST anomalies, and differences in upper-level warming and stratospheric circulation responses to SST warming compared to physics-based ESMs. The causes of these weaknesses were explored. Despite the noted weaknesses, NeuralGCM reproduces responses across experiments reasonably and performs comparably to ESMs. By integrating a dynamical core with ML, NeuralGCM shows potential for developing ML-based ESMs.

global warming↗
DOE OSTI2014

Method for controlling energy density for reliable pulsed laser deposition of thin films

We have established a methodology to stabilize the laser energy density on a target surface in pulsed laser deposition of thin films. To control the focused laser spot on a target, we have imaged a defined aperture in the beamline (so called image-focus) instead of focusing the beam on a target based on a simple “lens-focus.” To control the laser energy density on a target, we have introduced a continuously variable attenuator between the output of the laser and the imaged aperture to manipulate the energy to a desired level by running the laser in a “constant voltage” mode to eliminate changes in the lasers’ beam dimensions. This methodology leads to much better controllability/reproducibility for reliable pulsed laser deposition of high performance electronic thin films.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Tree tensor network hierarchical equations of motion based on time-dependent variational principle for efficient open quantum dynamics in structured thermal environments

In this work, we introduce an efficient method, TTN-HEOM, for exactly calculating the open quantum dynamics for driven quantum systems interacting with highly structured bosonic baths by combining the tree tensor network (TTN) decomposition scheme with the bexcitonic generalization of the numerically exact hierarchical equations of motion (HEOM). The method yields a series of quantum master equations for all core tensors in the TTN that efficiently and accurately capture the open quantum dynamics for non-Markovian environments to all orders in the system–bath interaction. These master equations are constructed based on the time-dependent Dirac–Frenkel variational principle, which isolates the optimal dynamics for the core tensors given the TTN ansatz. The dynamics converges to the HEOM when increasing the rank of the core tensors, a limit in which the TTN ansatz becomes exact. We introduce TENSO, tensor equations for non-Markovian structured open systems, as a general-purpose Python code to propagate the TTN-HEOM dynamics. We implement three general propagators for the coupled master equations: two fixed-rank methods that require a constant memory footprint during the dynamics and one adaptive-rank method with a variable memory footprint controlled by the target level of computational error. We exemplify the utility of these methods by simulating a two-level system coupled to a structured bath containing one Drude–Lorentz component and eight Brownian oscillators, which is beyond what can presently be computed using the standard HEOM. Our results show that the TTN-HEOM is capable of simulating both dephasing and relaxation dynamics of driven quantum systems interacting with structured baths, even those of chemical complexity, with an affordable computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Material Characterization of Hierarchical Tunable Pore Size Polymer Foams Used in the MARBLE Mix Morphology Experiment

One of the great challenges of inertial confinement fusion and high energy density experiments is understanding the effects of mix on thermonuclear burn. The MARBLE campaign, conceived at Los Alamos National Laboratory, aims to gather new insights into this issue by utilizing unique target capsules containing polymer foams of variable pore sizes, tunable over an order of magnitude. Such capsules allow the degree of initial heterogeneity to be controlled experimentally for the first time. Here, we describe the various characterization efforts used to gain understanding of the chemical structure and behavior of the foam. Previous experiments were not sensitive to foam physical properties, and the MARBLE platform has aided in the development of techniques to measure foam properties such as deuterium content, density variation, hydrogen adsorption, and pore size and volume distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Evaluating IMRT and VMAT dose accuracy: Practical examples of failure to detect systematic errors when applying a commonly used metric and action levels

Purpose: This study (1) examines a variety of real-world cases where systematic errors were not detected by widely accepted methods for IMRT/VMAT dosimetric accuracy evaluation, and (2) drills-down to identify failure modes and their corresponding means for detection, diagnosis, and mitigation. The primary goal of detailing these case studies is to explore different, more sensitive methods and metrics that could be used more effectively for evaluating accuracy of dose algorithms, delivery systems, and QA devices.Methods: The authors present seven real-world case studies representing a variety of combinations of the treatment planning system (TPS), linac, delivery modality, and systematic error type. These case studies are typical to what might be used as part of an IMRT or VMAT commissioning test suite, varying in complexity. Each case study is analyzed according to TG-119 instructions for gamma passing rates and action levels for per-beam and/or composite plan dosimetric QA. Then, each case study is analyzed in-depth with advanced diagnostic methods (dose profile examination, EPID-based measurements, dose difference pattern analysis, 3D measurement-guided dose reconstruction, and dose grid inspection) and more sensitive metrics (2% local normalization/2 mm DTA and estimated DVH comparisons).Results: For these case studies, the conventional 3%/3 mm gamma passing rates exceeded 99% for IMRT per-beam analyses and ranged from 93.9% to 100% for composite plan dose analysis, well above the TG-119 action levels of 90% and 88%, respectively. However, all cases had systematic errors that were detected only by using advanced diagnostic techniques and more sensitive metrics. The systematic errors caused variable but noteworthy impact, including estimated target dose coverage loss of up to 5.5% and local dose deviations up to 31.5%. Types of errors included TPS model settings, algorithm limitations, and modeling and alignment of QA phantoms in the TPS. Most of the errors were correctable after detection and diagnosis, and the uncorrectable errors provided useful information about system limitations, which is another key element of system commissioning.Conclusions: Many forms of relevant systematic errors can go undetected when the currently prevalent metrics for IMRT/VMAT commissioning are used. If alternative methods and metrics are used instead of (or in addition to) the conventional metrics, these errors are more likely to be detected, and only once they are detected can they be properly diagnosed and rooted out of the system. Removing systematic errors should be a goal not only of commissioning by the end users but also product validation by the manufacturers. For any systematic errors that cannot be removed, detecting and quantifying them is important as it will help the physicist understand the limits of the system and work with the manufacturer on improvements. In summary, IMRT and VMAT commissioning, along with product validation, would benefit from the retirement of the 3%/3 mm passing rates as a primary metric of performance, and the adoption instead of tighter tolerances, more diligent diagnostics, and more thorough analysis.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-F-I-57: Evaluate and Optimize PET Acquisition Overlap in 18F-FDG Oncology Wholebody PET/CT: Can We Scan PET Faster?

Purpose: The longer patient has to remain on the table during PET imaging, the higher the likelihood of motion artifacts due to patient discomfort. This study was to investigate and optimize PET acquisition overlap in 18F-FDG oncology wholebody PET/CT to speed up PET acquisition and improve patient comfort. Methods: Wholebody 18F-FDG PET/CT of phantoms, 8 pre-clinical patients (beagles) and 5 clinical oncology patients were performed in 90s/bed on a time-of-flight Gemini TF 64 system. Imaging of phantoms and beagles was acquired with reduced PET overlaps (40%, 33%, 27%, 20%, 13% and no overlap) in addition to the system default (53%). In human studies, 1 or 2 reduced overlaps from the listed options were used to acquire PET/CT sweeps right after the default standard of care imaging. Image quality was blindly reviewed using visual scoring criteria and quantitative SUV assessment. NEMA PET sensitivity was performed under different overlaps. Results: All PET exams demonstrated no significant impact on the visual grades for overlaps >20%. Blinded reviews assigned the best visual scores to PET using overlaps 53%–27%. Reducing overlap to 27% for oncology patients (12-bed) saved an average of ∼40% acquisition time (11min) compared to using the default overlap (18min). No significant SUV variances were found when reducing overlap to half of default for cerebellum, lung, heart, aorta, liver, fat, muscle, bone marrow, thighs and target lesions (p>0.05), except expected variability in urinary system. Conclusion: This study demonstrated by combined phantom, pre-clinical and clinical PET/CT scans that PET acquisition overlap in axial of today’s systems can be reduced and optimized. It showed that a reduction of PET acquisition overlap to 27% (half of system default) can be implemented to reduce table time by ∼40% to improve patient comfort and minimize potential motion artifacts, without prominently degrading image quality or compromising PET quantification.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Development of hierarchical, tunable pore size polymer foams for ICF targets

In this study, one of the great challenges of inertial confinement fusion experiments is poor understanding of the effects of reactant heterogeneity on fusion reactions. The Marble campaign, conceived at Los Alamos National Laboratory, aims to gather new insights into this issue by utilizing target capsules containing polymer foams of variable pore sizes, tunable over an order of magnitude. Here, we describe recent and ongoing progress in the development of CH and CH/CD polymer foams in support of Marble. Hierarchical and tunable pore sizes have been achieved by utilizing a sacrificial porogen template within an open-celled poly(divinylbenzene) or poly(divinylbenzene-co-styrene) aerogel matrix, resulting in low-density foams (~30 mg/ml) with continuous multimodal pore networks.

36 MATERIALS SCIENCE↗