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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 631 records · Page 35

Investigation of the Effect of Gate Oxide Screening with Adjustment Pulse on Commercial SiC Power MOSFETs

This paper presents a method to recover the negative threshold voltage shift during high field gate oxide screening of 1.2 kV 4H-SiC MOSFETs with an additional adjustment gate voltage pulse. To reduce field failure rates of the MOSFETs in operation, manufacturers perform a screening treatment to remove devices with extrinsic defects in the oxide. Current gate oxide screening procedures are limited to oxide fields at or below ~9 MV/cm for short durations (<1 s), which is not enough to remove all the devices with extrinsic defects. The results show that by implementing a lower field gate pulse, the threshold voltage shift can be partially recovered, and therefore the maximum screening field and time can be increased. However, both the initial screening pulse and the adjustment pulse require careful calibration to prevent significant degradation of the device threshold voltage, on-resistance, interface state density, or intrinsic lifetime. With a well calibrated set of pulses, higher screening fields can be utilized without significantly damaging the devices. This leads to an improvement in the overall screening efficiency of the process, reducing the number of devices with extrinsic oxide defects entering the field, and improving the reliability of the SiC MOSFETs in operation.

42 ENGINEERING↗

Engineering-Scale Integrated Energy System Data Projection Demonstration via the Dynamic Energy Transport and Integration Laboratory

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified.

08 HYDROGEN↗

A Design Method for Low-Pressure Venturi Nozzles

The purpose of this work is to provide empirical design models for low-pressure, subsonic Venturi nozzles. Experimentally validated simulations were used to determine the effect of nozzle geometry and operating conditions on the suction ratio (ratio of suction mass flow rate to motive mass flow rate) of low-pressure, subsonic Venturi nozzles, over a wide range of geometries and operating conditions, through a parametric study. The results of the parametric study were used to develop seven empirical models, each with a different range of applicability or calculating a different indicator of nozzle performance (i.e., suction ratio, momentum ratio, or dynamic pressure ratio), of the Venturi nozzles using a constrained multi-variable global optimization method. Of the seven empirical models, the best models were found to be those for low- (less than one) and high-suction ratios (greater than one), with mean absolute percentage errors of 5% and 18%, respectively. These empirical models provide a design tool for subsonic, low-pressure Venturi nozzles that is more than an order of magnitude more accurate than a governing equation approach or conventional flow head calculations. These newly-developed empirical models can be applied for initial nozzle design when precise suction ratios are required.

O’Hern, Hannah↗

High-throughput fabrication and semi-automated characterization of oxide thin film transistors

High throughput experimental methods are known to accelerate the rate of research, development, and deployment of electronic materials. For example, thin films with lateral gradients in composition, thickness, or other parameters have been used alongside spatiallyresolved characterization to assess how various physical factors affect material properties under varying measurement conditions. Similarly, multi-layer electronic devices that contain such graded thin films as one or more of their layers can also be characterized spatially in order to optimize the performance. In this work, we apply these high throughput experimental methods to thin film transistors (TFTs), demonstrating combinatorial device fabrication and semiautomated characterization using sputtered oxide TFTs as a case study. Here, we show that both extrinsic and intrinsic types of device gradients can be generated in a TFT library, such as channel thickness and length, channel cation compositions, and oxygen atmosphere during deposition. We also present a semi-automated method to measure the 44 devices fabricated on a 50x50mm substrate that can help to identify properly functioning TFTs in the library and finish the measurement in a short time. Finally, we propose a fully automated characterization system for similar TFT libraries, which can be coupled with high throughput data analysis. These results demonstrate that high throughput methods can accelerate the investigation of TFTs and other electronic devices.

36 MATERIALS SCIENCE↗

Porous graphitic carbon nitride nanosheets by pre-polymerization for enhanced photocatalysis

Highlights: • A porous g-C{sub 3}N{sub 4} nanosheet is synthesized by a simple pre-polymerization method. • A large surface area and pore volume are obtained. • Formation mechanism of the porous structure is discussed. • Photocatalytic hydrogen evolution and degradation performances are both enhanced. - Abstract: A facile and green method was developed to fabricate porous graphitic carbon nitride (g-C{sub 3}N{sub 4}) nanosheets by simply pre-polymerizing melamine at 350 °C for 2 h. A porous structure was formed in the resulted g-C{sub 3}N{sub 4} (CN-350). Consequently, the specific surface area and pore volume of CN-350 was greatly enhanced, resulting in superior performance in photocatalytic hydrogen evolution and dye degradation. The hydrogen evolution rate and degradation constant of CN-350 were 11.2 and 8.8 times higher than that of bulk g-C{sub 3}N{sub 4} under visible light irradiation. The porous structure not only provided CN-350 with abundant active catalytic sites and cross-plane diffusion channels to facilitate the charge and mass transportation, but also promoted the charge separation in the photocatalytic reaction. This work provided a promising method for mass-production of highly active and stable g-C{sub 3}N{sub 4}-based photocatalysts for environmental and energetic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Enhancing the connection between computation and experiments in electrocatalysis

Combining computational and experimental methods is a powerful approach to understand the variables that govern catalyst performance and ultimately design improved materials. However, the effectiveness of this approach rests on the strength of the relationships between calculated parameters and experimental measurements. These relationships are complicated by the intricacy and dynamic behaviour of catalytic active sites, and by the non-trivial relationship between calculated reaction energetics and observed rates. In this Perspective, we highlight opportunities to enhance the connection between computation and experiment in electrocatalysis. These include measuring the intrinsic kinetic behaviour of catalysts, creating precise models for the active site and its environment, and forming clear relationships between calculated reaction energetics and observed rates. As experimental and computational methods continue to become more powerful, clear connections between the two will maximize their utility to guide the design of efficient and selective electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Two-Step Load Disaggregation Algorithm for Quasi-static Time-series Analysis on Actual Distribution Feeders

This paper focuses on developing a two-step load disaggregation method for conducting quasi-static time-series analysis using actual distribution feeder data. This can help utilities conduct power flow studies using smart meter measurements to assess the impact of high penetration of distributed energy resources. In the first step, load profiles of residential and commercial buildings obtained from smart meter data are used to match the load profile at the feeder head. This step will determine the number of residential and commercial loads on the feeder. The second step is to allocate the selected load profiles to each load node based on its transformer rating. This allows each load node to have its own load profile and the aggregation of those nodal load profiles matches closely to the metered feeder load shape at the substation. This algorithm is validated using smart meter data and the SCADA data of a real feeder. We compared the performance of the proposed method with the traditional load allocation method (i.e. use the feeder load shape for all subsequent load nodes scaling by the transformer capacities) when conducting quasi-static power flow studies. Results show that the proposed algorithm matches the utility data well and the obtained voltage profiles reveal more voltage dynamics than using the conventional load allocation method. (PDF) A Two-Step Load Disaggregation Algorithm for Quasi-static Time-series Analysis on Actual Distribution Feeders.

load disaggregation, load shape, quasi-static, tim↗

Stereochemical Control of Water Transport Properties in Thiol‐yne Polymers

Barrier polymers underpin almost every commercial sector, yet the needs of several emerging areas remain unmet by commercially‐available materials, including temporary orthopedic implants, transient health monitors, neural implants, and other long‐term implants. The ability to tune polymer composition independently of polymer structure positions thiol‐yne click chemistry as a promising platform to serve these emerging technologies. Here, this work describes the differences in the hierarchical structure of stoichiometrically identical materials which differ only in the proportion of the cis versus trans backbone alkene stereochemistry. Varying the isomer content in this way directs different temperature and rate dependent crystallization behavior, which affords control over micron‐scale structure. This investigation focuses on how these stereochemical features affect the water vapor permeation process by several methods and develops an understanding of how this unique structural regularity improves barrier performance relative to a commercially available water barrier polymer, poly(ethylene terephthalate).

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Defect-specific strength factors and superposition model for predicting strengthening of ion irradiated Fe18Cr alloy

Here, a high-purity binary alloy Fe18Cr was subjected to heavy-ion irradiation in order to provide improved understanding of the irradiation effect on radiation hardening associated with dislocation loop and network formation, α’ precipitation. The specimens were irradiated with 8 MeV Fe ions (~2 μm ion range) to midrange doses of 0.37 and 3.7 dpa at 300, 350 and 450 °C using dose rates of ~10 –5 –10 –3 dpa/s. Nanoindentation testing was performed to extract the bulk equivalent hardness at low depth from these ion irradiated specimens. High-quality transmission electron microscopy (TEM) images were acquired by utilizing a flash electropolishing method on the Focused Ion Beam (FIB) prepared liftouts. An accurate calculation of the strength factor was provided based on detailed TEM characterization of the irradiated microstructures. A newly refined hardening superposition method was applied to combine the strengthening components from each microstructure. The good agreement between microstructure predicted strength and measured strength further demonstrated the fidelity to use hardening model to quantify the mechanical properties of ion irradiated materials.

36 MATERIALS SCIENCE↗

Computational studies of hydraulic stressors for biological performance assessment in a hydropower plant with Kaplan turbine

We report Hydropower is currently one of the preeminent sources of renewable energy in the United States and globally. Hydropower plants also have detrimental impacts on the environment and ecology, including direct impacts to anadromous fish populations. The computational fluid dynamics (CFD) – based Biological Performance Assessment (BioPA) toolset is used for biological evaluations of fish passage through hydropower plants. The hydraulic environment of a hydropower plant was evaluated using CFD coupled with discrete element method (DEM) simulations. The predicted flow field and particle collision rate were validated against the experimental data in a water flume that has an idealized hydroturbine distributor geometry. Flow simulations were conducted to evaluate the hydraulic stressors, such as nadir pressure, fluid shear, runner collision, in a physical scale in a hydropower plant with Kaplan turbine which are responsible for injury and mortality of fish in a downstream migration. The cumulative exposure probability for the nadir pressure and collision with turbine runner was found to decrease with increased discharge rate. The lowest discharge rate shows the higher value of cumulative shear exposure probability. The maximum value of collision velocity increases with increased discharge rate. We offer the conclusions that will help in understanding various hydraulic stressors for biological assessment for environmentally sustainable hydroturbine passage.

13 HYDRO ENERGY↗

Numerical Simulation and Experimental Study of the Gas–Solid Flow Behavior Inside a Full-Loop Circulating Fluidized Bed: Evaluation of Different Drag Models

Both experimental and computational studies of the fluidization of high-density polyethylene (HDPE) particles in a small-scale full-loop circulating fluidized bed (CFB) are conducted. Experimental measurements of pressure drop are taken at various locations along the bed. The solids circulation rate is measured with an advanced particle image velocimetry (PIV) technique. Bed height of the quasi-static region in the standpipe is also measured. Comparative numerical simulations are performed with a computational fluid dynamics solver utilizing a discrete element method (CFD-DEM). Here, this paper examines the effect of different drag laws used in the CFD simulations through a detailed and direct comparison with experimental data from a small-scale, full-loop circulating fluidized bed. The Hill–Koch–Ladd drag correlation was shown to have good agreement with respect to system component pressure drop and inventory height in the standpipe.

42 ENGINEERING↗

Self-Substitution and the Temperature Effects on the Electrochemical Performance in the High Voltage Cathode System LiMn 1.5+x Ni 0.5-x O 4 (x = 0.1)

The high voltage cathode material, LiMn 1.6 Ni 0.4 O 4 , was prepared by a polymer-assisted method. The novelty of this paper is the substitution of Ni with Mn, which already exists in the crystal structure instead of other isovalent metal ion dopants which would result in capacity loss. The electrochemical performance testing including stability and rate capability was evaluated. The temperature was found to impose a change on the valence and structure of the cathode materials. Specifically, manganese tends to be reduced at a high temperature of 800 °C and leads to structural changes. The manganese substituted LiMn 1.5 Ni 0.5 O 4 (LMN) has proved to be a good candidate material for Li-ion battery cathodes displaying good rate capability and capacity retention. Finally, the cathode materials processed at 550 °C showed a stable performance with negligible capacity loss for 400 cycles.

25 ENERGY STORAGE↗

Sensitivity Analysis of Occupant Preferences on Energy Usage in Residential Buildings: Preprint

Residential buildings, accounting for 37% of the total electricity consumption in the United States, are suitable for demand-side management (DSM) programs to support effective and economical operation of the power system. A home energy management system (HEMS) enables residential buildings to participate in such programs. It is important to account for occupant preferences in HEMS to ensure occupant satisfaction while participating in DSM programs. For example, people who prefer a higher thermal comfort level are likely to consume more energy. In this study, we used foresee™, a HEMS developed by the National Renewable Energy Lab (NREL), to perform a sensitivity analysis of occupant preferences with the following objectives: minimize utility cost, minimize carbon footprint, and maximize thermal comfort. To incorporate the preferences into the HEMS, the SMARTER method was used to derive a set of weighting factors for each objective. We performed week-long building energy simulations using a model of a home in Fort Collins, Colorado, where there is mandatory time-of-use electricity rate structure. The foreseeTM HEMS was used to control the home with six different sets of occupant preferences. The study shows that occupant preferences can have a significant impact and is important to consider when modeling residential buildings. Results show that the HEMS could achieve energy reduction ranging from 3% to 21%, cost savings ranging from 5% to 24%, and carbon emission reduction ranging from 3% to 21%, while maintaining a low thermal discomfort level ranging from 0.78 K-hour to 6.47 K-hour in a one-week period during winter. These outcomes quantify the impact of varying occupant preferences and will be useful for controlling the electrical grid and developing HEMS solutions.

carbon footprint↗

Performance of a Nonelectric Infant Warmer in Rwandan Health Centers

Background: Neonatal hypothermia remains a challenge in resource-limited settings. Methods. We conducted a prospective mixed-methods cohort study in rural Rwandan health centers to assess the performance of an infant warmer we designed for low-resource settings. All hypothermic infants were eligible for enrollment. Outcomes. Safety: incidence of adverse reactions. Effectiveness: attainment of euthermia, rate of temperature rise. Feasibility: correct use of warmer, signs of wear. Interviews of caregivers and nurses. Findings. Of 102 encounters, there were no adverse reactions. Of 80 encounters for hypothermia when infants on warmer for ≥1 hour, 79 achieved euthermia; 73 in ≤2 hours. Of the 80 encounters, 64 had temperature rise ≥0.5°C/h. Of the 102 encounters, there were no instances of the warmer being prepared, used, or cleaned incorrectly. Five out of the 12 warmers exhibited wear. Interview participants were predominantly positive; some found time for readiness of warmer challenging. Interpretation. The warmer performed well. It is appropriate to study in larger scale.

60 APPLIED LIFE SCIENCES↗

Risk of Positive Sentinel Lymph Node After Neoadjuvant Systemic Therapy in Clinically Node-Negative Breast Cancer: Implications for Postmastectomy Radiation Therapy and Immediate Breast Reconstruction

Background: Residual axillary lymph node involvement after neoadjuvant systemic therapy (NST) is the determining factor for postmastectomy radiation therapy (PMRT). Preoperative identification of patients needing PMRT is essential to enable shared decision-making when choosing the optimal timing of breast reconstruction. We determined the risk of positive sentinel lymph node (SLN) after NST in clinically node-negative (cN0) breast cancer. Methods: All cT1-3N0 patients treated with NST followed by mastectomy and SLNB between 2010 and 2016 were identified from the Netherlands Cancer Registry. Rate of positive SLN for different breast cancer subtypes was determined. Logistic regression analysis was performed to determine correlated clinicopathological variables with positive SLN. Results: In total 788 patients were included, of whom 25.0% (197/788) had positive SLN. cT1-3N0 ER+HER2+, cT1-3N0 ER−HER2+ , and cT1-2N0 triple-negative patients had the lowest rate of positive SLN: 7.2–11.5%, 0–6.3%, and 2.9–6.2%, respectively. cT1-3N0 ER+HER2− and cT3N0 triple-negative patients had the highest rate of positive SLN: 23.8–41.7% and 30.4%, respectively. Multivariable regression analysis showed that cT2 (odds ratio [OR] 1.93; 95% confidence interval [CI] 1.01–3.96), cT3 (OR 2.56; 95% CI 1.30–5.38), grade 3 (OR 0.44; 95% CI 0.21–0.91), and ER+HER2− subtype (OR 3.94; 95% CI 1.77–8.74) were correlated with positive SLN. Conclusions: In cT1-3N0 ER+HER2+, cT1-3N0 ER−HER2+, and cT1-2N0 triple-negative patients treated with NST, immediate reconstruction can be considered an acceptable option due to low risk of positive SLN. In cT1-3N0 ER+HER2− and cT3N0 triple-negative patients treated with NST, risks and benefits of immediate reconstruction should be discussed with patients due to the relatively high risk of positive SLN.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Performance and Reliability of Bonded Interfaces for High-temperature Packaging: Annual Progress Report

As maximum device temperatures approach 200 °Celsius, continuous operation, sintered silver materials promise to maintain bonds at these high temperatures without excessive degradation rates. A detailed characterization of the thermal performance and reliability of sintered silver materials and processes has been initiated for the next year. Future steps in crack modeling include efforts to simulate crack propagation directly using the extended finite element method (X-FEM), a numerical technique that uses the partition of unity method for modeling discontinuities such as cracks in a system.

30 DIRECT ENERGY CONVERSION↗

Iterative and Self-Consistent Estimation of Degradation and Soiling Loss in PV Systems - A Case Study

In many parts of the world, soiling is a significant loss mechanism for PV energy production. Methods for accurately quantifying historical and current soiling losses are needed. Furthermore, state-of-the-art methods to estimate degradation rates based on production data do not handle soiling in a satisfactory manner. In order to accurately estimate either of these quantities, it is in many cases helpful to consider their combined effect on PV system performance. In this work we make use of the Combined Degradation and Soiling (CODS) algorithm, which iteratively decomposes time series of daily normalized energy yield into four components: a soiling ratio, a degradation trend, seasonal variations, and noise. We demonstrate the use of the model on field performance data from a utility-scale power plant in a high-soiling environment in the Middle East. We apply the algorithm to the temperature-corrected performance index of the DC power on inverter level, quantifying how soiling varies over time and through the plant. The irradiation-weighted average soiling loss in this plant is 2.3 %, with a median soiling rate of -0.086 %/day. Between the inverters in the site in study, estimated degradation rates range between -0.86 %/year and -0.15 %/year, with a mean rate of -0.48 %/year.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Surrogate Model Based Optimization for Finding Robust Deep Learning Model Architectures

Deep Learning (DL) models are increasingly used throughout the sciences. However, their performance and usefulness depend greatly on their architecture which is defined by hyperparameters such as the number of nodes, layers, the learning rate, etc. Tuning these hyperparameters is time-consuming because evaluating their performance requires a lengthy training step. Stochastic optimizers used in training lead to performance variability and potentially prediction reliability issues. In this talk, we will describe an automated optimization method based on surrogate models and active learning strategies for tuning DL model architectures. We take into account the prediction variability with the goal to identify architectures that make reliable and robust predictions. We demonstrate our developments on an application arising in particle physics.

deep learning↗