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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

MCM-41 support for ultrasmall γ-Fe 2 O 3 nanoparticles for H 2 S removal

In this paper, MCM-41 is proposed to build mesostructured Fe 2 O 3 -based sorbents as an alternative to other silica or alumina supports for mid-temperature H 2 S removal. MCM-41 was synthesized as micrometric (MCM41_M) and nanometric (MCM41_N) particles and impregnated through an efficient two-solvent (hexane–water) procedure to obtain the corresponding γ-Fe 2 O 3 @MCM-41 composites. The active phase is homogeneously dispersed within the 2 nm channels in the form of ultrasmall maghemite nanoparticles assuring a high active phase reactivity. The final micrometric (Fe_MCM41_M) and nanometric (Fe_MCM41_N) composites were tested as sorbents for hydrogen sulphide removal at 300 °C and the results were compared with a reference sorbent (commercial unsupported ZnO) and an analogous silica-based sorbent (Fe_SBA15). MCM-41 based sorbents, having the highest surface areas, showed superior performances that were retained after the first sulphidation cycle. Specifically, the micrometric sorbent (Fe_MCM41_M) showed a higher SRC value than the nanometric one (Fe_MCM41_N), due to the low stability of the nanosized particles over time caused by their high reactivity. Finally and furthermore, the low regeneration temperature (300–350 °C), besides the high removal capacity, renders MCM41-based systems an alternative class of regenerable sorbents for thermally efficient cleaning up processes in Integrated Gasification Combined Cycles (IGCC) systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Advanced fuels from ethanol – a superstructure optimization approach

We develop a superstructure framework for the design of biorefineries for ethanol upgrading into advanced biofuels to replace gasoline, jet fuel or diesel. The framework integrates catalysis, process synthesis, and fuel property modelling towards the design of biorefineries producing fuels with specified properties. The proposed framework is applied to identify strategies for the upgrading of ethanol into one or more fuels with specific properties. We discuss the trade-off between profit and biorefinery complexity, as well as the relation among fuel property constraints, the optimal upgrading strategy selected, and process economics. Lastly, we show how to find the optimal biorefinery associated with a particular chemistry or catalyst. The results presented constitute the first systematic study of ethanol upgrading considering, simultaneously, fuel and process design.

09 BIOMASS FUELS↗
DOE OSTI2016

Optical arc sensor using energy harvesting power source

Wireless sensors without external power supply gained considerable attention due to convenience both in installation and operation. Optical arc detecting sensor equipping with self sustaining power supply using energy harvesting method was investigated. Continuous energy harvesting method was attempted using thermoelectric generator to supply standby power in micro ampere scale and operating power in mA scale. Peltier module with heat-sink was used for high efficiency electricity generator. Optical arc detecting sensor with hybrid filter showed insensitivity to fluorescent and incandescent lamps under simulated distribution panel condition. Signal processing using integrating function showed selective arc discharge detection capability to different arc energy levels, with a resolution below 17 J energy difference, unaffected by bursting arc waveform. The sensor showed possibility for application to arc discharge detecting sensor in power distribution panel. Also experiment with proposed continuous energy harvesting method using thermoelectric power showed possibility as a self sustainable power source of remote sensor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Hole mobility modulation of solution-processed nickel oxide thin-film transistor based on high-k dielectric

Solution-processed p-type oxide semiconductors have recently attracted increasing interests for the applications in low-cost optoelectronic devices and low-power consumption complementary metal-oxide-semiconductor circuits. In this work, p-type nickel oxide (NiO{sub x}) thin films were prepared using low-temperature solution process and integrated as the channel layer in thin-film transistors (TFTs). The electrical properties of NiO{sub x} TFTs, together with the characteristics of NiO{sub x} thin films, were systematically investigated as a function of annealing temperature. By introducing aqueous high-k aluminum oxide (Al{sub 2}O{sub 3}) gate dielectric, the electrical performance of NiO{sub x} TFT was improved significantly compared with those based on SiO{sub 2} dielectric. Particularly, the hole mobility was found to be 60 times enhancement, quantitatively from 0.07 to 4.4 cm{sup 2}/V s, which is mainly beneficial from the high areal capacitance of the Al{sub 2}O{sub 3} dielectric and high-quality NiO{sub x}/Al{sub 2}O{sub 3} interface. This simple solution-based method for producing p-type oxide TFTs is promising for next-generation oxide-based electronic applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

An x-ray penumbral imager for measurements of electron–temperature profiles in inertial confinement fusion implosions at OMEGA

Hot-spot shape and electron temperature (T e ) are key performance metrics used to assess the efficiency of converting shell kinetic energy into hot-spot thermal energy in inertial confinement fusion implosions. X-ray penumbral imaging offers a means to diagnose hot-spot shape and T e , where the latter can be used as a surrogate measure of the ion temperature (T i ) in sufficiently equilibrated hot spots. We have implemented a new x-ray penumbral imager on OMEGA. We demonstrate minimal line-of-sight variations in the inferred T e for a set of implosions. Furthermore, we demonstrate spatially resolved T e measurements with an average uncertainty of 10% with 6 μm spatial resolution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Land use strategies to mitigate climate change in carbon dense temperate forests

Strategies to mitigate carbon dioxide emissions through forestry activities have been proposed, but ecosystem process-based integration of climate change, enhanced CO 2 , disturbance from fire, and management actions at regional scales are extremely limited. In this work, we examine the relative merits of afforestation, reforestation, management changes, and harvest residue bioenergy use in the Pacific Northwest. This region represents some of the highest carbon density forests in the world, which can store carbon in trees for 800 y or more. Oregon’s net ecosystem carbon balance (NECB) was equivalent to 72% of total emissions in 2011–2015. By 2100, simulations show increased net carbon uptake with little change in wildfires. Reforestation, afforestation, lengthened harvest cycles on private lands, and restricting harvest on public lands increase NECB 56% by 2100, with the latter two actions contributing the most. Resultant cobenefits included water availability and biodiversity, primarily from increased forest area, age, and species diversity. Converting 127,000 ha of irrigated grass crops to native forests could decrease irrigation demand by 233 billion m 3 ∙y –1 . Utilizing harvest residues for bioenergy production instead of leaving them in forests to decompose increased emissions in the short-term (50 y), reducing mitigation effectiveness. Increasing forest carbon on public lands reduced emissions compared with storage in wood products because the residence time is more than twice that of wood products. Thus, temperate forests with high carbon densities and lower vulnerability to mortality have substantial potential for reducing forest sector emissions. Our analysis framework provides a template for assessments in other temperate regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Summary report of the 4th IAEA Technical Meeting on Fusion Data Processing, Validation and Analysis (FDPVA)

The objective of the Fourth Technical Meeting on Fusion Data Processing, Validation and Analysis was to provide a platform during which a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolating needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge-based understanding of the physical processes governing the dynamics of these plasmas. This paper presents the recent progress and achievements in the domain of plasma diagnostics and synthetic diagnostics data analysis (including image processing, regression analysis, inverse problems, deep learning, machine learning, big data and physics-based models for control) reported at the meeting. The progress in these areas highlight trends observed in current major fusion confinement devices. A special focus is dedicated on data analysis requirements for ITER and DEMO with a particular attention paid to artificial intelligence for automatization and improving reliability of control processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Development of FELIX based readout system for HV-CMOS sensor testbeam

The High Voltage CMOS (HV-CMOS) sensors are extensively investigated by the ATLAS collaboration for the High-Luminosity LHC (HL-LHC) upgrade of the Inner Tracker (ITk) detector. The HV-CMOS technology is a commercial integrated circuit process with the advantages of monolithic readout and fast charge collection. A front-end test platform of CaRIBOu (Control and Readout Itk BOard) and a testbeam Telescope based on the ATLAS IBL (Insertable B-Layer) silicon pixel modules, have been developed for the HV-CMOS sensor study and characterization in testbeam experiments. The Front-End LInk eXchange (FELIX) system is a newapproach to function as the gateway between detector front-end electronics and the commodity switched network in the ATLAS upgrade. A FELIX based readout system has been developed for both the CaRIBOu and the testbeam Telescope. It has been deployed successfully in the testbeam at theCERNSPS H8 beamline in August 2017. The test results show that the readout system is capable of sensor calibration and readout of a high-density pixel detector with high trigger rate in testbeam experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Electronics integration for the GE2/1 and ME0 GEM detector systems for the CMS phase-2 muon system upgrade

Abstract The Large Hadron Collider is currently undergoing its High Luminosity upgrade, which is set to increase the instantaneous luminosity by about a factor of five. Consequently, the Compact Muon Solenoid experiment is upgrading its muon spectrometer to cope with the increased muon flux in the forward region. The GE2/1 triple-gas electron multiplier detector, which has recently entered the mass production phase, and the ME0 triple-GEM detector system, which is in the late prototyping phase, are undergoing electronics integration. These proceedings briefly discuss the frontend electronics for the GE2/1 and ME0 detector systems, the electronics integration testing process, and the future plans for the frontend electronics of these two detector systems by the CMS GEM collaboration.

Instruments & Instrumentation↗
DOE OSTI2024

Spatial-Temporal PV Hosting Capacity Estimation and Evaluation

Evaluating Photovoltaic Hosting Capacity (PVHC) is an essential step in the process of integrating solar energy into power grids, particularly when focusing on the distribution network (DN) as the primary integration target. PVHC needs to be investigated, especially in cases where the grids are unbalanced, and their operational conditions vary spatially and temporally. This motivation prompted us to propose a scalable model tailored to this application. In this paper, we applied linearization to the alternating current optimal power flow (AC-OPF) and solar inverters, transforming the original problem into a mixed-integer linear programming (MILP) problem. Additionally, we accounted for the battery energy storage system (BESS) as a time-coupling factor for calculating PVHC. We then compared the PVHC results between the IEEE-13 bus and SMART-DS San Francisco (SFO) cases and discussed the extent to which BESS can enhance the PVHC of a DN. Furthermore, we designed a web-based graphical visualization for the SFO case, enabling user interaction with raw data and simulation results on a map through a graphical user interface (GUI). In summary, our results and findings provide valuable insights for future three-phase unbalanced AC-OPF PVHC practices and their visualization.

AC-optimal power flow↗
DOE OSTI2021

Intelliquench: An Adaptive Machine Learning System for Detection of Superconducting Magnet Quenches

In superconducting magnets, the irreversible transition of a portion of the conductor to resistive state is called a “quench.” Having large stored energy, magnets can be damaged by quenches due to localized heating, high voltage, or large force transients. Unfortunately, current quench protection systems can only detect a quench after it happens, and mitigating risks in Low Temperature Superconducting (LTS) accelerator magnets often requires fast response (down to ms). Additionally, protection of High Temperature Superconducting (HTS) magnets is still suffering from prohibitively slow quench detection. In this study, we lay the groundwork for a quench prediction system using an auto-encoder fully-connected deep neural network. After dynamically trained with data features extracted from acoustic sensors around the magnet, the system detects anomalous events seconds before the quench in most of our data. While the exact nature of the events is under investigation, we show that the system can “forecast” a quench before it happens under magnet training conditions through a randomized experiment. This opens up the way of integrated data processing, potentially leading to faster and better diagnostics and detection of magnet quenches

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Integration of plant and microbial oil processing at oilcane biorefineries for more sustainable biofuel production

Oilcane—an oil-accumulating crop engineered from sugarcane—and microbial oil have the potential to improve renewable oil production and help meet the expected demand for bioderived oleochemicals and fuels. To assess the potential synergies of processing both plant and microbial oils, the economic and environmental implications of integrating microbial oil production at oilcane and sugarcane biorefineries were characterized. Due to decreased crop yields that lead to higher simulated feedstock prices and lower biorefinery capacities, current oilcane prototypes result in higher costs and carbon intensities than microbial oil from sugarcane. To inform oilcane feedstock development, we calculated the required biomass yields (as a function of oil content) for oilcane to achieve financial parity with sugarcane. At 10 dw% oil, oilcane can sustain up to 30% less yield than sugarcane and still be more profitable in all simulated scenarios. Assuming continued improvements in microbial oil production from cane juice, achieving this target results in a minimum biodiesel selling price of 1.34 [0.90, 1.85] USD∙L –1 (presented as median [5th, 95th] percentiles), a carbon intensity of 0.51 [0.47, 0.55] kg CO 2 e L –1 , and a total biodiesel yield of 2140 [1870, 2410] L ha –1 year –1 . Compared to biofuel production from soybean, this outcome is equivalent to 3.0–3.9 as much biofuel per hectare of land and a 57%–63% reduction in carbon intensity. While only 20% of simulated scenarios fell within the market price range of biodiesel (0.45–1.11 USD∙L –1 ), if the oilcane biomass yield would improve to 25.6 DMT∙ha –1 ∙y –1 (an equivalent yield to sugarcane) 87% of evaluated scenarios would have a minimum biodiesel selling price within or below the market price range.

09 BIOMASS FUELS↗
DOE OSTI2021

Quantitative order-parameter measurement in lattice-mismatched AlInP using precession electron diffraction

Precession electron diffraction (PED) was used to measure the long-range order parameter in lattice-mismatched AlInP epitaxial films under investigation for solid-state-lighting applications. Both double- and single-variant films grown at 620, 650, and 680°C were analyzed in TEM cross-section. PED patterns were acquired in selected-area-diffraction mode through external microscope control using serial acquisition, which allows inline image processing. The integrated peak intensities from experimental patterns were fit using dynamical simulations of diffraction from the ordered domain structures. Included in the structure-factor calculations were mean atomic displacements of the anions (P) due to ordering, which were found by valence-force-field calculations to have a nearly linear dependence on order parameter. A maximum order parameter of S = 0.36 was measured for a double-variant specimen grown at 650°C.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Fiber-optic sensor packaging assessment and benchmarking for embedded sensing applications

Fiber optic-based sensing for non-destructive evaluation (NDE) and structural health monitoring of various infrastructure and energy assets is an increasingly important sensing scheme. Because of their immunity to electromagnetic interferences, versatility in sensing mechanisms and designs as well as capability for distributed sensing, the fiber optic sensing is of great interest for embedding within infrastructures using advanced manufacturing methods. However, the protection of fiber optic sensors during advanced manufacturing-based embedding is an important aspect for infrastructure monitoring in practice. While successful installation of fiber optic sensors has been accomplished through application of epoxy or adhesives on infrastructure surfaces, there has been only limited investigation of fiber protection packaging schemes which are compatible with in-situ repair techniques such as the metallic cold-spray. With increasing interest and importance of cold spray-based repair processes, the integration of fiber optic sensors simultaneously during the repair is equally important. In this work, we focus our efforts on investigating various types of packaging schemes for their compatibility and integrability on the surfaces of metallic structures such as oil and gas pipelines during an in-situ repair coating. First, we consider sandblasting using silica sand particles of various size for optical fibers on the surface of a metallic coupon as a useful proxy test of sensor packaging stability. Structural damage of packaging is characterized by means of optical microscopy and the optical integrity of embedded fiber optic cables is examined using optical backscatter reflectometry (OBR). In addition, initial investigation of metallic cold-spray embedded fiber optic cables under various packaging on metallic substrates is also considered with early conclusions and future directions.

Fiber-optic sensors, Sensors packaging, Metallic C↗
DOE OSTI2025

Machine learning-driven design and self-sensing capabilities of automotive bumper lattices for adaptive impact response

We present a novel approach to design an automotive bumper energy absorber using carbon fiber reinforced polymer composites, optimized to meet conflicting performance requirements for two distinct impact scenarios. The design must satisfy both a low-speed (2.5 mph) pendulum intrusion test, simulating vehicle-to-vehicle collisions, and a high-speed (25 mph) leg flexion test, replicating pedestrian impacts. These tests demand opposing deformation characteristics: high flexibility (deformation < 85 mm) for the former and high stiffness (deformation < 22 mm) for the latter. To address these contradictory requirements, we developed a machine learning (ML) framework for inverse optimization of lattice designs and material selection. Unlike traditional iterative design processes, our ML model directly outputs optimal design parameters and material choices based on target performance inputs. The energy absorber was fabricated using advanced additive manufacturing techniques, including extrusion deposition and digital light processing. The integration of carbon fibers provides multifunctionality to the bumper structure, enabling self-sensing capabilities through changes in electrical resistivity under compression. This electrical response demonstrates high repeatability under multiple cycles at 2% compression and exhibits distinct signatures during crack formation under high deformation. This research offers adaptive performance through innovative design methodologies and smart material integration. The approach has potential applications in various fields requiring adaptive energy absorption and real-time structural health monitoring.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗
DOE OSTI2014

SU-E-T-474: IMRT Verification Using the On-Board EPID

Purpose: To verify IMRT and Rapid Arc (RA) plan's agreement with treatment delivery for radiation therapy using an on-board EPID compared to MapCHECK2 and ArcCHECK. Methods: On-board EPID (Exact arm) is commissioned using manufacturer's Preconfigured Data Input Package (PDIP). Portal dose calculation engine for comparison with measurement was commissioned with PDIP. The absolute dosimetric calibration of the EPID is performed using 10×10cm field size at 105cm source to image detector distance with 90.7 CU in the integrated mode. The dark and flood field of EPID were also calibrated in the integrated mode for all energies and dose rates. The output dose-response data from the manufacturer was verified. The improved gamma test method was used for EPID data analysis. Gamma test were used for MapCHECK2 (or ArcCHECK). The sensitivity of the method was tested using collimator rotation at 3 degree and 5 degree. Student T-test was used to distinguish the difference among the groups. Results: IMRT: The average of Gamma passing rate using EPID and MapCHECK2 is 98.9±1.6% and 98.7±2.0% (p = 0.342). There is no statistical difference between two groups.RA: The average of Gamma passing rate using EPID and ArcCHECK is 97.2±2.3% and 93.2±4.1%. (p = 0.002). EPID significantly improved the RapidARC plan passing rate compared to the ArcCHECK. 5% dose change typically causes between 3 – 55% change in Gamma. Conclusion: Using the EPID, we were able to perform QA verification on IMRT plans comparable to MapCHECK2 (p=0.342) and superior to that of ArcCHECK (p=0.002) using Gamma 3%, 3mm criteria. The sensitivity of EPID was found to be comparable to that of the MapCHECK2 and ArcCHECK. EPID dosimetry is faster (4.3 mins vs. 10 mins) due to easier setup and integrated data processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗