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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

A matrix-inversion method for gamma-source mapping from gamma-count data

In a previous paper it was proposed that a simple matrix inversion method could be used to extract source distributions from gamma-count maps, using simple models to calculate the response matrix. The method was tested using numerically generated count maps. In the present work a 100 kBq Co{sup 60} source has been placed on a gridded surface and the count rate measured using a NaI scintillation detector. The resulting map of gamma counts was used as input to the matrix inversion procedure and the source position recovered. A multi-source array was simulated by superposition of several single-source count maps and the source distribution was again recovered using matrix inversion. The measurements were performed for several detector heights. The effects of uncertainties in source-detector distances on the matrix inversion method are also examined. The results from this work give confidence in the application of the method to practical applications, such as the segregation of highly active objects amongst fuel-element debris. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Direct Laser Writing of Multimetal Bifunctional Catalysts for Overall Water Splitting

Water electrolysis is of interest as a sustainable way to produce clean hydrogen and oxygen fuel and help mitigate the rising problems of climate change while meeting global energy demands. High-efficiency, stable, and earth-abundant bifunctional catalysts are needed to enable more effective electrochemical cells for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Here, we investigate the synthesis, composition, performance, and mechanism of multimetal catalysts serving dual functionality in both OER and HER of water electrolysis. Through a laser synthesis method, we synthesized heterogeneous catalysts of nanocrystalline multimetallic alloy pockets embedded within an amorphous oxide matrix. We evaluated the performance and composition of a range of mixed transition-metal oxide materials for both OER and HER, ultimately synthesizing a Cr 0.01 Fe 0.27 Co 0.34 Ni 0.38 O x /C y catalyst that has a stable, high-rate, and competitive overall water splitting performance of 1.76 V at 100 mA cm –2 in an alkaline medium. Using density functional theory to gain insight as the active site and mechanism, we propose that the inclusion of a minor amount of Cr increases the degeneracy of energetic states that lowers the cost of forming the O 2 p–d bond and H 1 s–d bond due to the hybridization of s, p, and d orbitals from Cr. Using a two-electrode water electrolysis cell with a constant potential of 1.636 V to mimic the setup for fuel production, we found the catalyst to be stable at 14–15 mA cm –2 for 40 h. Furthermore, this laser synthesis method allowing for facile and rapid synthesis of complex multimetal systems demonstrates how doping a Fe, Co, and Ni heterogeneous amorphous/nanocrystalline structure with small amounts of Cr is important for bifunctional catalytic behavior, particularly for increasing HER functionality in advancing our understanding for future electrocatalytic design.

08 HYDROGEN↗
DOE OSTI2021

Synthesis of Core@Shell Cu-Ni@Pt-Cu Nano-Octahedra and Their Improved MOR Activity

Fabrication of 3d metal-based core@shell nanocatalysts with engineered Pt-surfaces provides an effective approach for improving the catalytic performance. The challenges in such preparation include shape control of the 3d metallic cores and thickness control of the Pt-based shells. Herein, we report a colloidal seed-mediated method to prepare octahedral CuNi@Pt-Cu core@shell nanocrystals using CuNi octahedral cores as the template. By precisely controlling the synthesis conditions including the deposition rate and diffusion rate of the shell-formation through tuning the capping ligand, reaction temperature, and heating rate, uniform Pt-based shells can be achieved with a thickness of < 1 nm. Furthermore, the resultant carbon-supported CuNi@Pt-Cu core@shell nano-octahedra showed superior activity in electrochemical methanol oxidation reaction (MOR) compared with the commercial Pt/C catalysts and carbon-supported CuNi@Pt-Cu nano-polyhedron counterparts, demonstrating that both the lattice strain and shape effects arising from the as-prepared CuNi@Pt-Cu octahedral nanocatalysts play a crucial role in MOR performance.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Poster — Thur Eve — 43: Monte Carlo Modeling of Flattening Filter Free Beams and Studies of Relative Output Factors

Flattening filter free (FFF) beams have been adopted by many clinics and used for patient treatment. However, compared to the traditional flattened beams, we have limited knowledge of FFF beams. In this study, we successfully modeled the 6 MV FFF beam for Varian TrueBeam accelerator with the Monte Carlo (MC) method. Both the percentage depth dose and profiles match well to the Golden Beam Data (GBD) from Varian. MC simulations were then performed to predict the relative output factors. The in-water output ratio, Scp, was simulated in water phantom and data obtained agrees well with GBD. The in-air output ratio, Sc, was obtained by analyzing the phase space placed at isocenter, in air, and computing the ratio of water Kerma rates for different field sizes. The phantom scattering factor, Sp, can then be obtained from the traditional way of taking the ratio of Scp and Sc. We also simulated Sp using a recently proposed method based on only the primary beam dose delivery in water phantom. Because there is no concern of lateral electronic disequilibrium, this method is more suitable for small fields. The results from both methods agree well with each other. The flattened 6 MV beam was simulated and compared to 6 MV FFF. The comparison confirms that 6 MV FFF has less scattering from the Linac head and less phantom scattering contribution to the central axis dose, which will be helpful for improving accuracy in beam modeling and dose calculation in treatment planning systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

A robust prognostic signature for hormone-positive node-negative breast cancer

Background: Systemic chemotherapy in the adjuvant setting can cure breast cancer in some patients that would otherwise recur with incurable, metastatic disease. However, since only a fraction of patients would have recurrence after surgery alone, the challenge is to stratify high-risk patients (who stand to benefit from systemic chemotherapy) from low-risk patients (who can safely be spared treatment related toxicities and costs). Methods: We focus here on risk stratification in node-negative, ER-positive, HER2-negative breast cancer. We use a large database of publicly available microarray datasets to build a random forests classifier and develop a robust multi-gene mRNA transcription-based predictor of relapse free survival at 10 years, which we call the Random Forests Relapse Score (RFRS). Performance was assessed by internal cross-validation, multiple independent data sets, and comparison to existing algorithms using receiver-operating characteristic and Kaplan-Meier survival analysis. Internal redundancy of features was determined using k-means clustering to define optimal signatures with smaller numbers of primary genes, each with multiple alternates. Results: Internal OOB cross-validation for the initial (full-gene-set) model on training data reported an ROC AUC of 0.704, which was comparable to or better than those reported previously or obtained by applying existing methods to our dataset. Three risk groups with probability cutoffs for low, intermediate, and high-risk were defined. Survival analysis determined a highly significant difference in relapse rate between these risk groups. Validation of the models against independent test datasets showed highly similar results. Smaller 17-gene and 8-gene optimized models were also developed with minimal reduction in performance. Furthermore, the signature was shown to be almost equally effective on both hormone-treated and untreated patients. Conclusions: RFRS allows flexibility in both the number and identity of genes utilized from thousands to as few as 17 or eight genes, each with multiple alternatives. The RFRS reports a probability score strongly correlated with risk of relapse. This score could therefore be used to assign systemic chemotherapy specifically to those high-risk patients most likely to benefit from further treatment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Delivery validation of an automated modulated electron radiotherapy plan

Purpose: Modulated electron radiation therapy (MERT) represents an active area of interest that offers the potential to improve healthy tissue sparing in treatment of certain cancer cases. Challenges remain however in accurate beamlet dose calculation, plan optimization, collimation method, and delivery accuracy. In this work, the authors investigate the accuracy and efficiency of an end-to-end MERT plan and automated delivery method. Methods: Treatment planning was initiated on a previously treated whole breast irradiation case including an electron boost. All dose calculations were performed using Monte Carlo methods and beam weights were determined using a research-based treatment planning system capable of inverse optimization. The plan was delivered to radiochromic film placed in a water equivalent phantom for verification, using an automated motorized tertiary collimator. Results: The automated delivery, which covered four electron energies, 196 subfields, and 6183 total MU was completed in 25.8 min, including 6.2 min of beam-on time. The remainder of the delivery time was spent on collimator leaf motion and the automated interfacing with the accelerator in service mode. Comparison of the planned and delivered film dose gave 3%/3mm gamma pass rates of 62.1%, 99.8%, 97.8%, 98.3%, and 98.7% for the 9, 12, 16, and 20 MeV, and combined energy deliveries, respectively. Delivery was also performed with a MapCHECK device and resulted in 3%/3 mm gamma pass rates of 88.8%, 86.1%, 89.4%, and 94.8% for the 9, 12, 16, and 20 MeV energies, respectively. Conclusions: Results of the authors’ study showed that an accurate delivery utilizing an add-on tertiary electron collimator is possible using Monte Carlo calculated plans and inverse optimization, which brings MERT closer to becoming a viable option for physicians in treating superficial malignancies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

BISON validation of FeCrAl cladding mechanical failure during simulated reactivity-initiated accident conditions*

Here, a reactivity-initiated accident (RIA) is a postulated design basis accident in light water reactors (LWRs) in which a rapid reactivity insertion induces a fission rate increase and a fuel pellet temperature rise. During RIA, the fuel pellet thermally expands and may cause pellet-cladding mechanical interaction (PCMI). Separate effects PCMI tests were performed on C26M FeCrAl cladding tube samples, introducing biaxial stress via a well understood modified burst test (MBT) system. A high-speed camera in the MBT system captured the projections, covering a 360° view of the cladding deformation and enabling a digital image correlation (DIC) method to quantify the surface strains with high fidelity. Representative hot zero-power RIA mechanical loading conditions were applied to the sample, and the test duration ranged from 20 to 500 ms at an average temperature of 573 K. BISON finite element–based fuel performance code modeling was performed against the high-fidelity DIC data produced from the MBTs. Validation calculations were conducted with 2D models and systematically compared with test data of the burst time, burst pressure, burst hoop strains, and hoop strain rates. Based on the behaviors from the separate effects test, BISON calculations satisfactorily predicted the cladding deformation behaviors. Sensitivity analysis was conducted to identify highly influential mechanical properties responsible for the cladding failure behavior during the MBT experiments. The results highlight the significance of the cladding's mechanical strength in governing cladding strain, followed by the significance of the mechanical interactions between the pellet and the cladding.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Budget Constrained Machine Learning for Early Prediction of Adverse Outcomes for COVID-19 Patients

Background: Machine learning (ML) based risk stratification models of Electronic Health records (EHR) data may help to optimize treatment of COVID-19 patients, but are often limited by their lack of clinical interpretability and cost of laboratory tests. We develop a ML based tool for predicting adverse outcomes based on EHR data to optimize clinical utility under a given cost structure. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Healthcare in northwest Ohio and southeastern Michigan. Methods: We tested performance of various ML approaches for predicting either increasing ventilatory support or mortality and the set of model features under a budget constraint was optimized via exhaustive search across all combinations of features. Results: The optimal sets of features for predicting ventilation under any budget constraint included demographics and comorbidities (DCM), basic metabolic panel (BMP), D-dimer, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), CRP, brain natriuretic peptide (BNP), and procalcitonin and for mortality included DCM, BMP, complete blood count, D-dimer, LDH, CRP, BNP, procalcitonin and ferritin. Conclusions: This study presents a quick, accurate and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.

Cadena Pico, JoseE.↗
DOE OSTI2015

Analysis of fluid fuel flow to the neutron kinetics on molten salt reactor FUJI-12

Molten Salt Reactor is a reactor are operating with molten salt fuel flowing. This condition interpret that the neutron kinetics of this reactor is affected by the flow rate of the fuel. This research analyze effect by the alteration velocity of the fuel by MSR type Fuji-12, with fuel composition LiF-BeF{sub 2}-ThF{sub 4}-{sup 233}UF{sub 4} respectively 71.78%-16%-11.86%-0.36%. Calculation process in this study is performed numerically by SOR and finite difference method use C programming language. Data of reactivity, neutron flux, and the macroscopic fission cross section for calculation process obtain from SRAC-CITATION (Standard thermal Reactor Analysis Code) and JENDL-4.0 data library. SRAC system designed and developed by JAEA (Japan Atomic Energy Agency). This study aims to observe the effect of the velocity of fuel salt to the power generated from neutron precursors at fourth year of reactor operate (last critical condition) with number of multiplication effective; 1.0155.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Impact of Irradiation on Corrosion Performance of Hybrid Organic/Inorganic Coatings on Austenitic Stainless Steel

The effects of gamma radiation on the performance of two corrosion-resistant coatings applied to stainless-steel 304L (SS304L) surfaces are presented. Specifically, the ability of the coatings to mitigate corrosion of SS304L surfaces as a function of the dose received (0–1300 Mrad) and dose rate (176 compared to 1054 rad/s) is evaluated using electrochemical methods, spectroscopy, and microscopy. Coating A, an organic/inorganic hybrid coating consisting of a two-part silica ceramic component and a polymer linker was evaluated in comparison to Coating B, which utilized Coating A as a topcoat for a commercial, off-the-shelf, Zn-rich primer. Post irradiation, Coating A demonstrated some corrosion protection following exposure to low levels of gamma radiation, but coating degradation occurred with an increased exposure dose and resulted in isolated regions of corrosion initiation. For Coating B, greater corrosion resistance was observed compared to Coating A due to the sacrificial nature of the Zn at elevated doses of gamma radiation. No effect of the dose rate (for the single dose examined) was observed for either coating. It is proposed for Coating B that as the polymer coating thermally degrades above 250 °C (bond scission of the polymer occurs), the remaining Zinc layer adhered to the SS304L post-irradiation enables enhanced corrosion resistance as compared to Coating A, which displays solely polymer degradation. The results presented herein establish an understanding of coating behavior with radiation exposure, specifically the relationship between corrosion coating performance and radiation dose, and can inform ageing and lifetime management for various applications.

degradation↗
DOE OSTI2020

On the Performance of Detecting Injection of Fabricated Messages into the CAN Bus

There have been several public demonstrations of attacks on connected vehicles showing the ability of an attacker to take control of a targeted vehicle by injecting messages into their Controller Area Network (CAN) bus. In this article, using injected speed reading and Revolutions Per Minute (RPM) reading messages in in-motion vehicle, we examine the ability of the Pearson correlation and the unsupervised learning methods k-means clustering and Hidden Markov Model (HMM) to differentiate ’no-attack’ and ’under-attack’ states of the given vehicle. We found that the Pearson correlation distinguishes the two states, the k-means clustering method has an acceptable accuracy but high false positive rate and HMM detects attacks with acceptable detection rate but has a high false positive in detecting attacks from speed readings when there is no attack. The accuracy of these unsupervised learning methods are comparable to the ones of the supervised learning methods used by CAN bus Intrusion Detection System (IDS) suppliers. In addition, the article shows that studying CAN anomaly detection techniques using off-vehicle test facilities may not properly evaluate the performance of the detection techniques. Finally, the results suggest using other features besides the data content of the CAN messages and integrate knowledge about how the Electronic Control Units (ECUs) collaborate in building effective techniques for the detection of injection of fabricated message attacks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Anodic electrochemical performances of MgCo{sub 2}O{sub 4} synthesized by oxalate decomposition method and electrospinning technique for Li-ion battery application

Highlights: • MgCo{sub 2}O{sub 4} was prepared by oxalate decomposition method and electrospinning technique. • Electrospun MgCo{sub 2}O{sub 4} shows the reversible capacity of 795 and 227 mAh g{sup −1} oxalate decomposition MgCo{sub 2}O{sub 4} after 50 cycle. • Electrospun MgCo{sub 2}O{sub 4} show good cycling stability and electrochemical performance. - Abstract: Magnesium cobalt oxide, MgCo{sub 2}O{sub 4} was synthesized by oxalate decomposition method and electrospinning technique. The electrochemical performances, structures, phase formation and morphology of MgCo{sub 2}O{sub 4} synthesized by both the methods are compared. Scanning electron microscope (SEM) studies show spherical and fiber type morphology, respectively for the oxalate decomposition and electrospinning method. The electrospun nanofibers of MgCo{sub 2}O{sub 4} calcined at 650 °C, showed a very good reversible capacity of 795 mAh g{sup −1} after 50 cycles when compared to bulk material capacity of 227 mAh g{sup −1} at current rate of 60 mA g{sup −1}. MgCo{sub 2}O{sub 4} nanofiber showed a reversible capacity of 411 mAh g{sup −1} (at cycle) at current density of 240 mA g{sup −1}. Improved performance was due to improved conductivity of MgO, which may act as buffer layer leading to improved cycling stability. The cyclic voltammetry studies at scan rate of 0.058 mV/s show main cathodic at around 1.0 V and anodic peaks at 2.1 V vs. Li.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-P-44: The Characteristics and Clinical Application of the ArcCHECK for VMAT Verification

Purpose: To evaluate the characteristics and clinical suitability of the ArcCHECK QA system for VMAT verification. Methods: The intrinsic sensitivity,short and long term reproducibility,dose and dose rate dependence,dose per pulsed dependence,field sizes dependence and directional response of the diodes were measured.The results of the diodes were compared with the measurement results of an ionization chamber and calculated results of TPS. Gamma index (3mm distance to agreement and 3% percentage difference ) was used to analyze the dose difference between the calculation and measurement for random selected 211 verified VMAT plans. Results: The ArcCHECK diodes performed well for all tests except directional dependence, which varies from a minimum of −3.9% (seen only when the beam is incident on the diode at 180°) to a maximum of 7.7% (approximately at 255°). Average gamma analysis passing rates with 3mm/3% for 113 NPC,48 cervical cancer and 50 rectal cancer VMAT plans are 93.5%,95.7% and 97.5%, statistical significance has been found between either two of the groups(t=−12.69∼−4.88,all P<0.01). Conclusion: With proposed calibration method,the ArcCHECK QA system is very suitable for VMAT pretreatment verification,the complexity of VMAT plan is the main factor affecting the passing rate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Biobased Poly(dodecylene Furanoate) with Inherent Advantages in Performance and Circularity

Biobased polymers are gaining traction toward more sustainable flexible-film packaging, yet overcoming trade-offs between their performance properties and end-of-life (EoL) options still remains a challenge. Here, it is shown that biobased poly(dodecylene 2,5-furanoate) (PDDF), synthesized via both step-growth polycondensation and chain-growth ring-opening polymerization methods, exhibits advantages not only in gas barrier properties but also in EoL options due to its biodegradability and closed-loop chemical circularity. Specifically, PDDF displays significantly lower oxygen and carbon dioxide permeability than commercial poly(butylene adipate-co-terephthalate) (PBAT) and linear low-density polyethylene , alongside a markedly higher modulus (by ≈3 ×) and reduced water vapor transmission rate compared to PBAT. This superior performance is attributed to the inherently rigid, polar, H-bonding furan rings that enhance chain interaction, packing and crystallinity and thus reduce free volume impeding gas diffusion, while the long hydrophobic dodecylene segments inhibit water permeation. Furthermore, PDDF can be recycled back to its cyclic monomer by base-catalyzed depolymerization or diester and diol monomers by simple methanolysis. These superior barrier properties, coupled with biodegradation and closed-loop circularity, highlight the potential of the biobased PDDF as a more sustainable alternative for packaging.

Poly(dodecylene 2,5-furanoate) (PDDF)↗
DOE OSTI2023

Enter Gaussian Mixture Modeling Extensions for Improved False Discovery Rate Estimation in GC-MS Metabolomics

Identifying small molecules (e.g., metabolites) is key towards driving scientific advancement in metabolomics, and gas chromatography–mass spectrometry (GC-MS) is an analytic method that may be applied to facilitate this process. The typical GC-MS identification workflow involves quantifying the similarity of an observed sample spectrum and other features (e.g. retention index) to that of several references, noting the compound of the best-matching reference spectrum as the identified metabolite. While a deluge of similarity metrics exists, none characterize the error rate of generated identifications, thereby presenting an unknown risk of false identification or discovery. To quantify this unknown risk, we propose a model-based framework for estimating the false discovery rate (FDR) among a set of identifications. Extending the traditional mixture modeling framework, our method incorporates both similarity score and experimental information in estimating the FDR. We apply these models to identification lists derived from across 548 samples of varying complexity and sample type (e.g., fungal species, standard mixtures, etc.), comparing their performance to that of the traditional Gaussian mixture model (GMM). Through simulation, we additionally assess the impact of reference library size on the accuracy of FDR estimates. In comparing the best performing model extensions to the GMM, our results indicate relative decreases in median absolute estimation error (MAE) ranging from 12% to 70%, based on comparisons of the median MAEs across all hit-lists. Results indicate that these relative performance improvements generally hold despite library size, however FDR estimation error typically worsens as the set of reference compounds diminishes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Machine learning framework for assessment of microbial factory performance

Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other hand, machine learning, complementary to metabolic modeling necessitates large amounts of data. Building such a database for metabolic engineering designs requires significant manpower and is prone to human errors and bias. We propose an approach to integrate data-driven methods with genome scale metabolic model for assessment of microbial bio-production (yield, titer and rate). Using engineered E. coli as an example, we manually extracted and curated a data set comprising about 1200 experimentally realized cell factories from ~100 papers. We furthermore augmented the key design features (e.g., genetic modifications and bioprocess variables) extracted from literature with additional features derived from running the genome-scale metabolic model iML1515 simulations with constraints that match the experimental data. Then, data augmentation and ensemble learning (e.g., support vector machines, gradient boosted trees, and neural networks in a stacked regressor model) are employed to alleviate the challenges of sparse, non-standardized, and incomplete data sets, while multiple correspondence analysis/principal component analysis are used to rank influential factors on bio-production. The hybrid framework demonstrates a reasonably high cross-validation accuracy for prediction of E.coli factory performance metrics under presumed bioprocess and pathway conditions (Pearson correlation coefficients between 0.8 and 0.93 on new data not seen by the model).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Subclinical Cardiac Dysfunction Detected by Strain Imaging During Breast Irradiation With Persistent Changes 6 Weeks After Treatment

Purpose: To evaluate 2-dimensional strain imaging (SI) for the detection of subclinical myocardial dysfunction during and after radiation therapy (RT). Methods and Materials: Forty women with left-sided breast cancer, undergoing only adjuvant RT to the left chest, were prospectively recruited. Standard echocardiography and SI were performed at baseline, during RT, and 6 weeks after RT. Strain (S) and strain rate (Sr) parameters were measured in the longitudinal, circumferential, and radial planes. Correlation of change in global longitudinal strain (GLS % and Δ change) and the volume of heart receiving 30 Gy (V30) and mean heart dose (MHD) were examined. Results: Left ventricular ejection fraction was unchanged; however, longitudinal systolic S and Sr and radial S were significantly reduced during RT and remained reduced at 6 weeks after treatment [longitudinal S (%) −20.44 ± 2.66 baseline vs −18.60 ± 2.70* during RT vs −18.34 ± 2.86* at 6 weeks after RT; longitudinal Sr (s{sup −1}) −1.19 ± 0.21 vs −1.06 ± 0.18* vs −1.06 ± 0.16*; radial S (%) 56.66 ± 18.57 vs 46.93 ± 14.56* vs 49.22 ± 15.81*; *P<.05 vs baseline]. Diastolic Sr were only reduced 6 weeks after RT [longitudinal E Sr (s{sup −1}) 1.47 ± 0.32 vs 1.29 ± 0.27*; longitudinal A Sr (s{sup −1}) 1.19 ± 0.31 vs 1.03 ± 0.24*; *P<.05 vs baseline], whereas circumferential strain was preserved throughout. A modest correlation between S and Sr and V30 and MHD was observed (GLS Δ change and V30 ρ = 0.314, P=.05; GLS % change and V30 ρ = 0.288, P=.076; GLS Δ change and MHD ρ = 0.348, P=.03; GLS % change and MHD ρ = 0.346, P=.031). Conclusions: Subclinical myocardial dysfunction was detected by 2-dimensional SI during RT, with changes persisting 6 weeks after treatment, though long-term effects remain unknown. Additionally, a modest correlation between strain reduction and radiation dose was observed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Sphere-Shaped Hierarchical Cathode with Enhanced Growth of Nanocrystal Planes for High-Rate and Cycling-Stable Li-Ion Batteries

High-energy and high-power Li-ion batteries have been intensively pursued as power sources in electronic vehicles and renewable energy storage systems in smart grids. With this purpose, developing high-performance cathode materials is urgently needed. Here we report an easy and versatile strategy to fabricate high-rate and cycling-stable hierarchical sphered cathode Li 1.2 Ni 0.13 Mn 0.54 Co 0.13 O 2 , by using an ionic interfusion method. The sphere-shaped hierarchical cathode is assembled with primary nanoplates with enhanced growth of nanocrystal planes in favor of Li+ intercalation/deintercalation, such as (010), (100), and (110) planes. This material with such unique structural features exhibits outstanding rate capability, cyclability, and high discharge capacities, achieving around 70% (175 mAh g–1 ) of the capacity at 0.1 C rate within about 2.1 min of ultrafast charging. Such cathode is feasible to construct high-energy and high-power Li-ion batteries.

25 ENERGY STORAGE↗