Search NASA⌕ Search

SEARCH · Search NASA

Results for “Performance Rating Method”

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.

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

At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine learning models for estimating contamination across different curbside collection strategies

Contaminated recyclables, which are frequently discarded as waste, pose a significant challenge to the implementation of a circular economy. These contaminated recyclables impede the circulation of resources, resulting in higher processing costs at material recovery facilities (MRFs). Over the past few decades, machine learning (ML) models such as linear regression (LR), support vector machine (SVM), and random forest (RF) have evolved to provide new methods for predicting inbound contamination rates in addition to traditional statistical models. In this study, we applied ML models to predict inbound contamination rates using demographic features from 15 counties in the U.S. with different curbside collection strategies. In general, we found that ML models outperformed linear mixed models. Specifically, SVM models had the highest performance (R 2 = 0.75; mean absolute error (MAE) = 0.06), which may be due to their ability to model nonlinear relationships between features and inbound contamination rates. Further, the key predictor was population, with poverty rate being positively correlated and median age negatively correlated with inbound contamination rates. To improve the management of contamination and enhance the implementation of a circular economy, better models are needed to understand and estimate inbound contamination rates as well as identify critical factors in the present and future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Entropy modeling on serrated flows in carburized steels

Samples comprised of carburized steel alloys, 4615, 4720, and 10B22, were tension tested at room temperature and at a strain rate of 2 × 10 -4 s -1 . The serrated-flow behavior was modeled and analyzed, using the refined composite multiscale entropy (RCMSE) method. High energy X-ray diffraction revealed the body-centered-cubic (BCC) structure of the three alloys in the as-received condition. Moreover, Vickers-hardness experiments were performed, which showed an increase in the hardness of the alloy that corresponded to increasing impurity concentrations. Here the diffusion coefficient of carbon in the three alloys were estimated, respectively, to be 2.5 × 10 -11 m 2 /s, 5.1 × 10 -11 m 2 /s, and 2.8 × 10 -11 m 2 /s for alloys, 10B22, 4615, and 4720, respectively, which agree with the values found in the literature for α-iron. Moreover, the sample entropy, on average, increased with respect to the heating time, and, consequently, the amount of carbon that had diffused into the alloy. Finally, the above results show that the complexity of the serration behavior in the alloys studied increases with respect to the amount of carbon that has diffused into the material.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Methodology and performance comparison of statistical learning pulse shape classifiers as demonstrated with organic liquid scintillator [Performance comparison of statistical learning pulse shape classifiers]

In this study, we present novel methods for automated pulse shape discrimination. The classifiers are trained using simple radionuclide sources and do not require ground truth labeling. We test their performance using labels derived from time of flight experiments and present the results in terms of energy-dependent Receiver Operating Characteristic (ROC) curves. In addition, we also train and test standard pulse shape discrimination methods on the same data for comparison. We find multiple methods that can yield similar false neutron and true neutron rates at 24 keVee as tail-to-total or Gatti’s optimal linear filter yield at 54 keVee.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

All-solid-state supercapacitors on silicon using graphene from silicon carbide

Carbon-based supercapacitors are lightweight devices with high energy storage performance, allowing for faster charge-discharge rates than batteries. Here, we present an example of all-solid-state supercapacitors on silicon for on-chip applications, paving the way towards energy supply systems embedded in miniaturized electronics with fast access and high safety of operation. We present a nickel-assisted graphitization method from epitaxial silicon carbide on a silicon substrate to demonstrate graphene as a binder-free electrode material for all-solid-state supercapacitors. We obtain graphene electrodes with a strongly enhanced surface area, assisted by the irregular intrusion of nickel into the carbide layer, delivering a typical double-layer capacitance behavior with a specific area capacitance of up to 174 μF cm{sup −2} with about 88% capacitance retention over 10 000 cycles. The fabrication technique illustrated in this work provides a strategic approach to fabricate micro-scale energy storage devices compatible with silicon electronics and offering ultimate miniaturization capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simultaneous imaging and diffraction in the dynamic diamond anvil cell

The ability to visualize a sample undergoing a pressure-induced phase transition allows for the determination of kinetic parameters, such as the nucleation and growth rates of the high-pressure phase. For samples that are opaque to visible light (such as metallic systems), it is necessary to rely on x-ray imaging methods for sample visualization. Here, we present an experimental platform developed at beamline P02.2 at the PETRA III synchrotron radiation source, which is capable of performing simultaneous x-ray imaging and diffraction of samples that are dynamically compressed in piezo-driven diamond anvil cells. This setup utilizes a partially coherent monochromatic x-ray beam to perform lensless phase contrast imaging, which can be carried out using either a parallel- or focused-beam configuration. The capabilities of this platform are illustrated by experiments on dynamically compressed Ga and Ar. Melting and solidification were identified based on the observation of solid/liquid phase boundaries in the x-ray images and corresponding changes in the x-ray diffraction patterns collected during the transition, with significant edge enhancement observed in the x-ray images collected using the focused-beam. These results highlight the suitability of this technique for a variety of purposes, including melt curve determination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

A high-resolution large-eddy simulation framework for wildland fire predictions using TensorFlow

Background: Wildfires are becoming more severe, so we need improved tools to predict them over a wide range of conditions and scales. One approach towards this goal entails the use of coupled fire/atmosphere modelling tools. Although significant progress has been made in advancing their physical fidelity, existing tools have not taken full advantage of emerging programming paradigms and computing architectures to enable high-resolution wildfire simulations. Aims: The aim of this study was to present a new framework that enables landscape-scale wildfire simulations with physical representation of combustion at an affordable cost. Methods: We developed a coupled fire/atmosphere simulation framework using TensorFlow, which enables efficient and scalable computations on Tensor Processing Units. Key Results: Simulation results for a prescribed fire were compared with experimental data. Predicted fire behavior and statistical analysis for fire spread rate, scar area, and intermittency showed overall reasonable agreement. Scalability analysis was performed, showing close to linear scaling. Conclusions: While mesh refinement was shown to have less impact on global quantities, such as fire scar area and spread rate, it benefits predictions of intermittent fire behavior, buoyancy-driven dynamics, and small-scale turbulent motion. Implications: This new simulation framework is efficient in capturing both global quantities and unsteady dynamics of wildfires at high spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

MDLoader: A Hybrid Model-Driven Data Loader for Distributed Graph Neural Network Training

Scalable data management is essential for processing large scientific dataset on HPC platforms for distributed deep learning. In-memory distributed storage is preferred for its speed, enabling rapid, random, and frequent data access required by stochastic optimizers. Processes use one-sided or collective communication to fetch remote data, with optimal performance depending on (i) dataset characteristics, (ii) training scale, and (iii) interconnection network. Empirical analysis shows collective communication excels with larger mini-batch sizes and/or fewer processes, whereas one-sided communication outperforms at larger scales. We propose MDLoader, a hybrid in-memory data loader for distributed graph neural network training. MDLoader features a model-driven performance estimator that dynamically selects between one-sided and collective communication at the beginning of training using Tree of Parzen Estimators (TPE). Evaluations on NERSC Perlmutter and OLCF Summit show MDLoader outperforms single-backend loaders by up to 2.83 × and predicts the suitable communication method with 96.3% (Perlmutter) and 94.3% (Summit) success rate.

Bae, Jonghyun↗
DOE OSTI2020

The Value of Information From Horizontal Distributed Acoustic Sensing Compared to Multicomponent Geophones Via Machine Learning

Abstract Faults play an important role in recharging many geothermal reservoirs, and seismic information can image the locations of these faults. The value of information (VOI) metric is used to objectively quantify and compare the value of two types of seismic receiver data via a machine learning approach. The demonstrated VOI methodology is novel by including spatial models from seismic data and obtaining the information statistics from machine learning. Our two-dimensional numerical experiments compare images created from sparsely spaced (80 m), two-component geophone sampling to high spatial resolution (1 m), single-component DAS. We used a three-fold cross validation of a U-Net convolutional neural networks to achieve average classification statistics. The results suggest that when horizontal sources are utilized, geophones and DAS identify reflectors and non-reflectors at roughly the same rate. The average F1 score for horizontal DAS is 0.939 and 0.931 for geophones. For images created from a vertical source, DAS performed marginally better (F1 = 0.919) than geophones (F1 = 0.877). Our transferrable methodology can provide guidance on which acquisition scenarios can improve images of important structures in the subsurface and present an efficient method for obtaining reliability statistics from high-dimensional, spatial data.

Energy & Fuels↗
DOE OSTI2016

TH-CD-201-02: A Monte Carlo Investigation of a Novel Detector Arrangement for the Energy Spectrum Measurement of a 6MV Linear Accelerator

Purpose: Direct measurement of the energy spectrum of a 6MV linear accelerator has not been successful due to the high fluence rate, high energy nature of these photon beams. Previous work used a Compton Scattering (CS) spectrometry setup with a shielded spectrometer for spectrum measurements. Despite substantial lead shielding, excessive pulse pile-up was seen. MCNP6 transport code was used to investigate the feasibility and effectiveness of performing measurements using a novel detector setup. Methods: Simulations were performed with a shielded high-purity germanium (HPGe) semiconductor detector placed in the accelerator vault’s maze, with a 2 cm diameter collimator through a 92 cm thick concrete wall. The detector was positioned 660 cm from a scattering rod (placed at isocenter) at an angle of 45° relative to the central axis. This setup was compared with the shielded detector positioned in the room, 200 cm from the scattering rod at the same CS angle. Simulations were used to determine fluence contributions from three sources: (1) CS photons traveling through the collimator aperture, the intended signal, (2) CS scatter photons penetrating the detector shield, and (3) room-scattered photons penetrating the detector shield. Variance reduction techniques including weight windows, DXTRAN spheres, forced collisions, and energy cutoffs were used. Results: Simulations showed that the number of pulses per starting particle from an F8 detector tally for the intended signal decreased by a factor of 10{sup 2} when moving the detector out of the vault. This reduction in signal was amplified for the unwanted scatter signal which decreased by up to a factor of 10{sup 9}. Conclusion: This work used MCNP6 to show that using a vault wall to shield unwanted scatter and increasing isocenter-to-detector distance reduces unwanted fluence to the detector. This study aimed to provide motivation for future experimental work using the proposed setup.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

Simulations and Data analysis for the 35 ton Liquid Argon detector as a prototype for the DUNE experiment

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment which will be built at the Sanford Underground Research Facility (SURF), and will receive a wide-band neutrino beam from Fermilab, 1300~km away. At this baseline DUNE will be able to study many of the properties of neutrino mixing, including the neutrino mass hierarchy and the value of the CP-violating complex phase ($\delta_{CP}$). DUNE will utilise Liquid Argon (LAr) Time Projection Chamber (TPC) (LArTPC) technology, and the Far Detector (FD) will consist of four modules, each containing 17.1~kt of LAr with a fiducial mass of around 10~kt. Each of these FD modules represents around an order of magnitude increase in size, when compared to existing LArTPC experiments. \\ The 35 ton detector is the first DUNE prototype for the single (LAr) phase design of the FD. There were two running periods, one from November 2013 to February 2014, and a second from November 2015 to March 2016. During t he second running period, a system of TPCs was installed, and cosmic-ray data were collected. A method of particle identification was developed using simulations, though this was not applied to the data due to the higher than expected noise level. A new method of determining the interaction time of a track, using the effects of longitudinal diffusion, was developed using the cosmic-ray data. A camera system was also installed in the detector for monitoring purposes, and to look for high voltage breakdowns. \\ Simulations concerning the muon-induced background rate to nucleon decay are performed, following the incorporation of the MUon Simulations UNderground (MUSUN) generator into the DUNE software framework. A series of cuts which are based on Monte Carlo truth information is developed, designed to reject simulated background events, whilst preserving simulated signal events in the $n \rightarrow K^{+} + e^{-}$ decay channel. No background events are seen to survive the app lication of these cuts in a sample of 2~$\times$~10$^9$ muon! s, representing 401.6~years of detector live time. This corresponds to an annual background rate of <~0.44~events$\cdot$Mt$^{-1}\cdot$year$^{-1}$ at 90\% confidence, using a fiducial mass of 13.8~kt.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Graphite Oxidation Rate Study on ET-10 and ETU-10 Grades - Task 4: QA Support and Testing for Structural Graphite Oxidation

INL performed targeted oxidation tests to measure oxidation rates for samples of ET-10 and ETU-10 graphite under CRADA No. 21CRA22 Mod. 3, Annex A, “Tritium Testing to Support Kairos Power Advanced Reactor Demonstration” (04/02/2024). All testing was conducted within INL’s Carbon Characterization Laboratory (CCL) using test standard ASTM D7542-21 "Standard Test Method for Air Oxidation of Carbon and Graphite in the Kinetic Regime" [ASTM International, 2021]. Kairos Power provided all test specimens through its graphite vendor Ibiden, Inc. to INL and ASTM specimen specified dimensions. Information within this report only provides the Arrhenius oxidation rate plots as a function of temperature for each graphite grade tested. The raw mass loss per time data will be provided on the Nuclear Data Management and Analysis System (NDMAS) portal located on the INL information system.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Pulse Shaping and Matched Filters for EMAT Communication System

Electromagnetic acoustic transducer (EMAT) is used as a noncontact sensor for acoustic communication in a stainless-steel plate channel. The acoustic wave multipath propagations within the channel cause intersymbol interference (ISI). ISI highly degrades the signal-to-noise ratio (SNR). The poor SNR will result in a low bitrate and a high bit error rate (BER). In this study, a test platform is designed to estimate the performance of the EMAT communication system. Two periodic-permanent-magnet (PPM) EMATs are designed to be used as a transmitter and a receiver. EMAT generates shear-horizontal (SH) wave propagating through the stainless-steel plate channel. We present methods to minimize the ISI effect and recover the message embedded in the received signals hampered by interference, reverberation and multipath effects. The root raised cosine (RRC) filters are introduced as a pulse-shaping filter for transmission and a matched filter for receiving messages. Amplitude Shift Keying (ASK) method is used for modulating the transmitted binary message. The pulse shaping and matched filters reduced the ISI caused by the undesirable multipath effect significantly to the extent that a 5-kbps bitrate can be achieved without any error (zero BER).

Huang, Xin↗
DOE OSTI2022

Modelling and Experimental Validation of Improved Performance of Lithium-Ion Batteries Having Thick Electrodes with Laser-Ablated Micro-Structures

For widespread adoption of electric vehicles, lithium-ion batteries (LiBs) need to achieve energy densities of >275 Wh/kg, cost less than $100/Wh, and charge to more than 80% capacity within 15 minutes. Increasing the battery electrode thicknesses is one way to increase cell energy densities while also saving on cell manufacturing cost by increasing the ratio of electrode active material to inactive material within each cell. However, increased electrode loading is often accompanied by decreased Li+-ion diffusion across the full thick electrodes. This leads to significant cell polarization that prevents full capacity utilization and accelerates cell degradation, especially at fast charging/discharging rates. The introduction of secondary pore networks in thick battery electrodes alleviates some of the trade-offs between energy and power performance. These microstructures provide low tortuosity pathways for facile Li+-ion diffusion deep into the thick electrodes, diminishing detrimental concentration gradients within the cell. Ultrafast-pulsed laser ablation is a promising method to introduce micro pores or channels in thick battery electrodes as it allows for precise control of pattern geometries, results in minimal damage to the electrode and can be introduced into existing roll-to-roll electrode manufacturing lines. Herein, the limitations of thick planer electrodes and the advanced predictive models to identify optimal electrode patterns for improved cycling performance will be presented. The impact of electrode laser patterning to create secondary pore networks also will be discussed. Materials characterization techniques (SEM-EDS, XRD) were used to explore the affect ultrafast laser ablation had on the electrode materials’ morphology and structure. The improvements in the patterned electrodes’ electrochemical cycling performances and degrees of wetting will be compared to a pristine baseline case. Finally, the discrepancies between experimentally obtained data and model predictions will be explained.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗
DOE OSTI2017

Determination of a Generic Human Error Probability Distribution, Part 2: A Dynamic SPAR-H Example Application

Humans are an integral part of a nuclear power plant (NPP) from its construction, to its everyday maintenance and operation. In the nuclear industry there are many approaches to quantifying component reliability, which is called probability risk assessment (PRA). In PRA there are two considerations given to the quantification, static and dynamic. Static is quantified before or after an operation; and dynamic is time dependent, in that the probability changes as real time data are provided. In PRA, the importance of the components is calculated, but what of the importance of the human component? There are several methods for human reliability analysis (HRA), which include but are not limited to: THERP, ATHEANA, CREAM, SPAR-H, ASEP, and SLIM. Each of these methods aims to provide a more accurate and objective human error probability (HEP) quantification. Of the methods listed above, ASEP, THERP, and SPAR-H are all inextricably linked. The Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method was generated to better generalize the Technique for Human Error Rate Prediction (THERP) and Accident Sequence Precursor (ASEP). THERP is mapped to specific scenario templates, and ASEP is a simplified screening method, while SPAR-H employs generalizations to describe the spectrum of human behavior while maintaining the same theoretical underpinnings. SPAR-H is a well-known and accepted HRA method that uses performance shaping factors (PSFs) to classify inputs to the human component. PSFs capture a wide variety of input data, including plant status, crew dynamics, task description, and psychological aspects of the human operator. Current efforts have been focused to further generalize SPAR-H in to a dynamic framework. These methods can fit into dynamic NPP simulations such as RAVEN / RELAP-7. In order to do this, a dynamic methodology is applied to model the human as would be applied to the components. This method is applied in part one in the accompanying paper.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Effects of scan rate on the corrosion behavior SS 304 stainless steel in the nanofluid measured by Tafel polarization methods

The Effects of scan rate on the Tafel polarization curve that is obtained to determine corrosion rate are conducted. The tafel polarization curves are obtained at different scan rates for Stainless Steel 304 in nanofluids contain 0.01 gpl nano particle ZrO{sub 2}. The corrosion stainless steel in nanofluid contains adm+0.01 gpl ZrO{sub 2} nanoparticles at different scan rate was performed by Tafel polarization. The results show that according corrosion potential examination of the stainless steel in nanofluid media 0.01gpl ZrO{sub 2} nanoparticle was actively corroded. The value of cathodic Tafel slope stainless steel in nanofluid at different scan rate relatively unchanged after polarization testing. Mean while the value of anodic Tafel slope stainless steel in nanofluid increase at different scan rate. The results of Tafel polarization technique show that corrosion rate of stainless steel in nanofluid increase with increasing scan rate. X ray diffraction examination of stainless steel after Tafel polarization depict that γ Fe phase is major phase in the surface of alloy.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Investigating ion recombination effects in a liquid-filled ionization chamber array used for IMRT QA measurements

Purpose: PTW’s Octavius 1000 SRS array performs IMRT quality assurance (QA) measurements with liquid-filled ionization chambers (LICs) to allow closer detector spacing and higher resolution, compared to air-filled QA devices. However, reduced ion mobility in LICs relative to air leads to increased ion recombination effects and reduced collection efficiencies that are dependent on Linac pulse frequency and pulse dose. These pulse parameters are variable during an IMRT delivery, which affects QA results. In this study, (1) 1000 SRS collection efficiencies were measured as a function of pulse frequency and pulse dose, (2) two methods were developed to correct changes in collection efficiencies during IMRT QA measurements, and the effects of these corrections on QA pass rates were compared. Methods: To obtain collection efficiencies, the OCTAVIUS 1000 SRS was used to measure open fields of varying pulse frequency, pulse dose, and beam energy with results normalized to air-filled chamber measurements. Changes in ratios of 1000 SRS to chamber measured dose were attributed to changing collection efficiencies, which were then correlated to pulse parameters using regression analysis. The usefulness of the derived corrections was then evaluated using 6 MV and 10FFF SBRT RapidArc plans delivered to the OCTAVIUS 4D system using a TrueBeam (Varian Medical Systems) linear accelerator equipped with a high definition multileaf collimator. For the first correction, MATLAB software was developed that calculates pulse frequency and pulse dose for each detector, using measurement and DICOM RT Plan files. Pulse information is converted to collection efficiency, and measurements are corrected by multiplying detector dose by ratios of calibration to measured collection efficiencies. For the second correction the MU/min in the daily 1000 SRS calibration was chosen to match the average MU/min of the volumetric modulated arc therapy plan. Effects of the two corrections on QA results were examined by performing 3D gamma analysis comparing predicted to measured dose, with and without corrections. Results: Collection efficiencies correlated linearly to pulse dose, while correlations with pulse frequency were less defined, generally increasing as pulse frequency decreased. After complex MATLAB corrections, average 3D gamma pass rates improved by [0.07%,0.40%,1.17%] for 6 MV and [0.29%,1.40%,4.57%] for 10FFF using [3%/3 mm,2%/2 mm,1%/1 mm] criteria. Maximum changes in gamma pass rates were [0.43%,1.63%,3.05%] for 6 MV and [1.00%,4.80%,11.2%] for 10FFF using [3%/3 mm,2%/2 mm,1%/1 mm] criteria. On average, pass rates of simple daily calibration corrections were within 1% of complex MATLAB corrections. Conclusions: OCTAVIUS 1000 SRS ion recombination effects have little effect on 6 MV measurements. However, the effect could potentially be clinically significant for higher pulse dose unflattened beams when using tighter gamma tolerances, especially when small aperture sizes are used, as is common for SRS/SBRT. In addition, ion recombination effects are strongly correlated to changing MU/min, therefore MU/min used in daily 1000 SRS calibrations should be matched to the expected average MU/min of the IMRT plan.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-F-CAMPUS-J-05: Fast Volumetric MRI On An MRI-Linac Enables On-Line QA On Dose Deposition in the Patient

Purpose: The introduction of the MRI-linac in radiotherapy brings MRI-guided treatment with daily plan adaptions within reach. This paradigm demands on-line QA. With its ability to perform continuous volumetric imaging in an outstanding soft-tissue contrast, the MRI- linac promises to elucidate the dose deposition process during a treatment session. Here we study for a prostate case how dynamic MRI combined with linac machine parameters and a fast dose-engine can be used for on-line dose accumulation. Methods: Prostate imaging was performed in healthy volunteer on a 1.5T MR-scanner (Philips, Best, NL) according to a clinical MR-sim protocol, followed by 10min of dynamic imaging (FLASH, 4s/volume, FOV 40×40×12cm{sup 3}, voxels 3×3×3mm{sup 3}, TR/TE/α=3.5ms/1.7ms/5°). An experienced radiation oncologist made delineations, considering the prostate CTV. Planning was performed on a two-compartment pseudoCT (air/water density) according to clinical constraints (77Gy in PTV) using a Monte-Carlo (MC) based TPS that accounts for magnetic fields. Delivery of one fraction (2.2Gy) was simulated on an emulator for the Axesse linac (Elekta, Stockholm, SE). Machine parameters (MLC settings, gantry angle, dose rate, etc.) were recorded at 25Hz. These were re-grouped per dynamic volume and fed into the MC-engine to calculate a dose delivered for each of the dynamics. Deformations derived from non-rigid registration of each dynamic against the first allowed dose accumulation on a common reference grid. Results: The DVH parameters on the PTV compared to the optimized plan showed little changes. Local deformations however resulted in local deviations, primarily around the air/rectum interface. This clearly indicates the potential of intra-fraction adaptations based on the accumulated dose. Application in each fraction helps to track the influence of plan adaptations to the eventual dose distribution. Calculation times were about twice the delivery time. Conclusion: The current Result paves the way to perform on-line treatment delivery QA on the MRI-linac in the near future.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

High Energy, Long Cycle Life Lithium-ion Batteries for PHEV Application

High-loading and high quality PSU Si anode has been optimized and fabricated. The electrochemical performance has been utilized. The PSU Si-graphite anode exhibits the mass loading of 5.8 mg/cm2, charge capacity of 850 mAh/ g and good cycling performance. This optimized electrode has been used for full-cell fabrication. The performance enhancement of Ni-rich materials can be achieved by a diversity of strategies. Higher Mn content and a small amount of Al doping can improve the electrochemical performance by suppressing interfacial side reactions with electrolytes, thus greatly benefiting the cyclability of the samples. Also, surface coatings of Li-rich materials and AlF 3 are able to improve the performance stability of Ni-rich cathodes. One kilogram of optimized concentration-gradient LiNi 0.76 Co 0.10 Mn 0.14 O 2 (CG) with careful control of composition, morphology and electrochemical performance was delivered to our collaborators. The sample achieved an initial specific capacity close to 190 mA h g -1 at C/10 rate and 180 mA h g -1 at C/3 rate as well as good cyclability in pouch full cells with a 4.4 V upper cut-off voltage at room temperature. Electrolyte additive with Si-N skeleton forms a less resistant SEI on the surface of silicon anode (from PSU) as evidenced by the evolution of the impedance at various lithiation/de-lithiation stages and the cycling data The prelithiation result demonstrates a solution processing method to achieve large area, uniform SLMP coating on well-made anode surface for the prelithiation of lithium-ion batteries. The prelithiation effect with this method is applied both in graphite half cells, graphite/NMC full cells, SiO half cells, SiO/NMC full cells, Si-Graphite half cells and Si-Graphite/NMC full cells with improvements in cycle performance and higher first cycle coulombic efficiency than their corresponding cells without SLMP prelithiation. As to the full cell fabrication and test, full pouch cells with high capacity of 2.2 Ah and 1.2 Ah have been fabricated and delivered. The cells show great uniformity and good cycling performance. The prelithiation method effectively compensate the loss in the first cycle. The cell with high energy density and long-cycle life has been achieved.

25 ENERGY STORAGE↗