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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Effect of High-K Dielectric Layer on 1/f Noise Behavior in Graphene Field-Effect Transistors

We report the 1/f noise characteristics at low-frequency in graphene field-effect transistors that utilized a high- dielectric tantalum oxide encapsulated layer (a few nanometers thick) placed by atomic layer deposition on Si3N4. A low-noise level of ~ 2.2  10-10 Hz-1 has been obtained at f = 10 Hz. The origin and physical mechanism of the noise can be interpreted by the McWhorter context, where fluctuations in the carrier number contribute dominantly to the low-frequency noise. Optimizing fabrication processes reduced the number of charged impurities in the graphene field-effect transistors. The study has provided insights into the underlying physical mechanisms of the noise at low-frequency for reducing the noise in graphene-based devices.

Yifei Wang↗
NASA NTRS2020

ICESat 2/ATLAS Onboard Flight Science Receiver Algorithms: Purpose, Process, and Performance

The Advanced Topographic Laser Altimetry System (ATLAS) is the sole instrument on the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2). Without some method of reducing the transmitted data, the volume of ATLAS telemetry would far exceed the normal X-band downlink capability or require many more ground station contacts. The ATLAS Onboard Flight Science Receiver Algorithms (hereinafter Receiver Algorithms or Algorithms) control the amount of science data that is telemetered from the instrument, limiting the data volume by distinguishing surface echoes from background noise, and allowing the instrument to telemeter data from only a small vertical region about the signal. This is accomplished through the transfer of the spacecraft's location and attitude to the instrument every second, use of an onboard Digital Elevation Model, implementation of signal processing techniques, and use of onboard relief and surface type reference maps. Extensive ground testing verified the performance of the Algorithms. On-orbit analysis shows that the Algorithms are working as expected from the ground testing; they are performing well and meeting the mission requirements.

Algoritms, Signal Processing, Optimization, Flight↗
NASA NTRS2020

Bonding to Bulk Metallic Glass using Aerospace-Grade Structural Adhesive

Bulk metallic glasses (BMGs) are non-crystalline metals with growing applications in aerospace. Due to their amorphous nature, BMGs generally exhibit stronger mechanical properties than most crystalline alloys and are more corrosion resistant. The limited reactivity of a corrosion resistant surface may explain the difficulty in establishing robust bonds to certain adhesives, especially commonly used structural adhesives for aerospace applications. Here, an amine cured aerospace adhesive was used for bonding an iron-nickel based BMG satellite component. Various types of processes were explored to avoid adhesive failure and increase bond strength. It was found that the BMG required specific chemical derivatization of the metal surface in order to achieve cohesive failure. Surface analysis was used to determine the mechanisms of adhesion enhancement. The process was optimized to maximize bond strength. This work helps explain the difficulties in bonding BMG materials and provides strategies for design of future bonded BMG components.

Roberts, Rose↗
NASA NTRSDate not supplied

Ultrashort Pulsed Laser Treatment: A Novel Sterilization Method for Planetary Protection

Introduction: On missions seeking signs of potential life elsewhere in the solar system, we have an obligation not to bring our own Earthly life with us. Reducing the bioburden (number of living microbes) on spacecraft is therefore required by the COSPAR Policy on Planetary Protection to target bodies that are of interest for understanding the origins of life (such as Mars). The method of spacecraft sterilization predominantly used by NASA is Heat Microbial Reduction, which is typically incompatible with heat-sensitive components such as optics and electronics, and is expensive and time-consuming. Here, we present preliminary results on a novel method for spacecraft hardware sterilization: high-intensity ultrashort (femtosecond) pulsed laser illumination. Femtosecond lasers use extremely high photon fluxes (10^29 photons/sec*cm^2, ~0.03 J/cm^2) in extremely short pulses, which can inactivate even stress-tolerant microbial spores with minimal damage to the spacecraft surface. This rapid sterilization technique could be carried out in situ in a spacecraft assembly clean room using high-speed surface scanning, saving critical time and resources. It also can potentially remove or reduce debris from inactivated cells and spores. Methods: To develop optimal laser processing parameters for inactivating planetary protection-relevant organisms on metal surfaces, we inoculated 1-cm^2 mirror-polished aluminum coupons with Bacillus subtilis spores (2x10^5 spores/coupon) and tested the effect of several parameters, including pulse count and fluence. Sterilization effectiveness was measured by recovering spores using a PVA (polyvinyl acetate) peel and conducting serial dilution and plating for colony-forming units (CFUs). Results: Our results show that pulse count and fluence both affect sterilization effectiveness and that within a certain pulse count range, increasing fluence increases effectiveness. We have demonstrated the ability to reduce viable microbial counts by at least 10^-4. Future work will include testing higher abundances and different species of microorganisms, effectiveness on complex surfaces, compatibility with sensitive surfaces, and quantification of cell debris removal. Femtosecond pulsed laser illumination has the potential to provide dramatic savings in both cost and schedule over current methods of bioburden reduction to prevent forward contamination. It may also have the potential for use in surface sterilization of returned samples to prevent back contamination.

Planetary Protection; Lasers; Sterilization; Bacil↗
NASA NTRS2024

3D Printing and Surface Engineering of Ti6Al4V Scaffolds for Enhanced Osseointegration in an In Vitro Study

Ti6Al4V superalloy is recognized as a good candidate for bone implants owing to its biocompatibility, corrosion resistance, and high strength-to-weight ratio. While dense metal implants are associated with stress shielding issues due to the difference in densities, stiffness, and modulus of elasticity compared to bone tissues, the surface of the implant/scaffold should mimic the properties of the bone of interest to assure a good integration with a strong interface. In this study, we investigated the additive manufacturing of porous Ti6Al4V scaffolds and coating modification for enhanced osteoconduction using osteoblast cells. The results showed the successful fabrication of porous Ti6Al4V scaffolds with adequate strength. Additionally, the surface treatment with NaOH and Dopamine Hydrochloride (DOPA) promoted the formation of Dopamine Hydrochloride (DOPA) coating with an optimized coating process, providing an environment that supports higher cell viability and growth compared to the uncoated Ti6Al4V scaffolds, as demonstrated by the higher proliferation ratios observed from day 1 to day 29. These findings bring valuable insights into the surface modification of 3D-printed scaffolds for improved osteoconduction through the coating process in solutions.

metal additive manufacturing↗
DOE OSTI2021

BETO 2021 Peer Review - Bench Scale Integration WBS 2.4.1.100

Bench Scale Integration develops and optimizes fermentation processes to produce bio-based fuels and chemicals from biomass sugars. The project uses fermentation science to achieve high titers and production rates by, for example, manipulating how the microorganisms are fed biomass sugars and nutrients, modifying fermentation conditions (pH, temperature, aeration) or developing online control strategies that increase production rates. For this period of performance, we conducted small scale fermentation research using strategies mentioned to produce 2,3-butanediol (BDO) from biomass utilizing NREL's proprietary Zymomonas mobilis microorganism. BDO is a versatile chemical which can be catalytically upgraded to a variety of hydrocarbon fuels and chemicals. The 3-yr project goal was to increase BDO titers from 50 g/L (FY17 level) to 125 g/L on biomass sugars by 2020. This is a 150% increase in titer showing the commercial potential of Z. mobilis while reducing the cost to downstream processing. We successfully achieved this target. The project also showed yearly progress improvements to the process design case by using a whole biomass slurry. Future work will focus on procedures for scaling to produce large quantities of BDO broth for separations and upgrading R&D and improve the titer and rates from biomass whole slurry. Our goal is to produce 100 g/L BDO titer from whole slurry at >1000L by 2023 which will meet the technical targets set by our techno-economic analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Feedstock Supply Chain Analysis

Addressing the challenge of biomass feedstock variability that affects the optimization of processing and conversion processes, the project's goal is to maximize biorefinery economics by improving the process quality control of feedstock, which will lead to greater plant availability and predictable yields of high value biofuels and co-products.

09 BIOMASS FUELS↗
DOE OSTI2022

Plasma Processing for In-Situ Field Emission Mitigation of Superconducting Radiofrequency (SRF) Cryomodules

Field emission (FE) is one of the main limiting factors of superconducting radio-frequency (SRF) cavities operating in accelerators and it occurs whenever contaminants, like dust, metal flakes or even absorbates, are present on the surface of the cavity high electric field region. Field emission reduces the maximum achievable accelerating field and generates free electrons that may interact with the beam, damage or activate the beamline. One practical method that can be used to mitigate this problem is in-situ plasma cleaning, or plasma processing. The development of a processing that can be applied in-situ is extremely advantageous, since it enables the recovery of the cryomodule performance without the need of disassembling the whole cryomodule, which is an extremely expensive and time-consuming process. On the other hand, plasma processing only requires the cryomodule warm-up to room-temperature and the subsequent processing of the contaminated cavities. The entire process is reasonably quick and involves a limited number of personnel. For these reasons we would like to advocate for continuing to invest in the R&D of plasma processing to optimize its applicability in cryomodules and for extending the technique to other frequency ranges and cavities geometries.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Data Analytics Methods to Measure Plant Outage Resilience

Every 18 or 24 months nuclear power plants (depending on plant configuration, pressurized or boiling water reactor respectively) undergo a period of outage where the plant is taken offline and a large number of maintenance and surveillance activities (that cannot be performed while plant is running) are performed in typically 2–3 weeks. Planning of a plant outage is very challenging since all the activities are required to be performed in the shortest amount of time given available resources (typically contractor crews hired for the duration of the outage). Consequently, plant outages can be costly due the actual loss of power generation and crew costs and, because of it, there is a need to maximize resource usage in the outage planning phase and reduce the risk of outage delays. This paper is addressing these needs by providing a set of analytical methods designed to analyze plant outage schedule and identify critical elements based on available resources (time and crews). These methods are based on natural language processing and optimization algorithms. In this respect, two classes of methods have been developed: one that focuses on the time resource and how variability in the time to complete outage tasks may impact outage delays, and one that minimizes the risk of outage delays by integrating available resources to assess when daily activities should be performed.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark and Hadoop manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape.

Hou, Shiyue↗
DOE OSTI2025

Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida

Although synthetic biology can produce valuable chemicals in a renewable manner, its progress is still hindered by a lack of predictive capabilities. Media optimization is a critical, and often overlooked, process which is essential to obtain the titers, rates and yields needed for commercial viability. Here, we present a molecule- and host-agnostic active learning process for media optimization that is enabled by a fast and highly repeatable semi-automated pipeline. Its application yielded 60% and 70% increases in titer, and 350% increase in process yield in three different campaigns for flaviolin production in Pseudomonas putida KT2440. Explainable Artificial Intelligence techniques pinpointed that, surprisingly, common salt (NaCl) is the most important component influencing production. The optimal salt concentration is very high, comparable to seawater and close to the limits that P. putida can tolerate. The availability of fast Design-Build-Test-Learn (DBTL) cycles allowed us to show that performance improvements for active learning are rarely monotonous. This work illustrates how machine learning and automation can change the paradigm of current synthetic biology research to make it more effective and informative, and suggests a cost-effective and underexploited strategy to facilitate the high titers, rates and yields essential for commercial viability.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

An optimal repartitioning decision policy

A central problem to parallel processing is the determination of an effective partitioning of workload to processors. The effectiveness of any given partition is dependent on the stochastic nature of the workload. The problem of determining when and if the stochastic behavior of the workload has changed enough to warrant the calculation of a new partition is treated. The problem is modeled as a Markov decision process, and an optimal decision policy is derived. Quantification of this policy is usually intractable. A heuristic policy which performs nearly optimally is investigated empirically. The results suggest that the detection of change is the predominant issue in this problem.

Nicol, D. M.↗
DOE OSTI2023

Sparse regression for plasma physics

Many scientific problems can be formulated as sparse regression, i.e., regression onto a set of parameters when there is a desire or expectation that some of the parameters are exactly zero or do not substantially contribute. This includes many problems in signal and image processing, system identification, optimization, and parameter estimation methods such as Gaussian process regression. Sparsity facilitates exploring high-dimensional spaces while finding parsimonious and interpretable solutions. In the present work, we illustrate some of the important ways in which sparse regression appears in plasma physics and point out recent contributions and remaining challenges to solving these problems in this field. Further, a brief review is provided for the optimization problem and the state-of-the-art solvers, especially for constrained and high-dimensional sparse regression.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Development of Building Design Optimization Methodology: Residential Building Applications

Building design optimization is a highly complex problem, requiring long computational running processes because of the many options that exist when a building is being designed. This paper introduces an integrated approach through which to perform this optimization within an acceptable time frame. The approach includes the methods of variable selection, model simplification, and a sequential optimization process. Using singular value decomposition, a large number of design variables is reduced to a smaller subset that can be solved more quickly through the optimization algorithm. To expedite the variable selection process, a modeling approach that quickly simulates annual energy consumption was developed to replace full annual energy simulations. The developed methodology was applied to two residential buildings in the US, and the results are discussed herein. To assess the accuracy of the integrated optimization methodology, the optimized life cycle costs are compaa variables demonstrating the strongest contributions in the optimization study were identified. The proposed methodology significantly shortened the time requirements for the optimization processes of the two case studies by 74% and 84%; the optimized life cycle costs were within 0.05% and 0.06%, respectively, of the optimum point.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗