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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

MnBi-based magnets prepared from melt-spun alloys: Effect of $α → β$ phase transformation during field annealing

The temperature of the annealing treatment applied to the MnBi alloys with the intention to stabilize the α -MnBi “low-temperature” phase – a promising material for the rare-earth-free permanent magnets – is usually kept below the range of the β -Mn 1.08 Bi “high-temperature” phase. This work is focused on the investigation of the effects of partial and complete α → β phase transformation in bulk magnetic-field-annealed magnets on their structure and magnetic properties. MnBi alloys modified with In, Mg and Sb were melt-spun, compacted to their full density and then heated in a magnetic field of 30 kOe to temperatures sufficiently high for the beginning of the α → β transformation. A heating of 15 °C/min was used which was immediately followed by cooling at the rate of 7.5 °C/min; the degree of the phase transformation was measured by in situ monitoring of changes in the sample magnetization. In all the studied alloys, the α → β transformation was found to improve the [0 0 1] fiber texture induced by the applied magnetic field, although it simultaneously decreased the coercivity. A partial transformation has resulted in a 11% increase of the maximum energy product for the Mn 50 Bi 49 Sb 0.5 In 0.5 magnet, to 8.3 MGOe, and a 3% increase for the Mn 50 Bi 46 Mg 3 Sb 0.5 In 0.5 magnet, to 12.8 MGOe. In the latter alloy, the α → β and reverse transformations were found to initially occur in well-defined pockets leading to clusters of large, highly textured α crystallites. In the Mn 50 Bi 48.5 Sb 1.5 magnet, only part of the α phase could be recovered after the transformation, which instead promoted the paramagnetic MnBi 0.9 Sb 0.1 phase.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effect of temperature on abrasion erosion in particle based concentrating solar powerplants

The use of solid particles as a heat transfer medium is being explored for concentrated solar power plants (CSP) to increase their efficiency by achieving operating temperature >700 °C. During operation, these hot particles are expected to move along the various components within the collector system, resulting in material degradation from a combination of high-temperature oxidation and erosion. In the present study, the performance of candidate materials was evaluated through a series of abrasion erosion experiments at room temperature as well as at 800 °C. Wear in metallic and refractory type materials was investigated using CarboBead® HSP 40/70 particles inside a resistance heated kiln. Furthermore, cross-sectional scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDS) analysis on the specimens tested at 800 °C determined that the specific wear rate in Inconel 740H and stainless steel 316 metallic specimens was influenced by the thermally grown oxide morphology. High chromium Inconel 740H specimens exhibited greater resistance to wear with a steady state specific wear rate of 1.92E-4 mm 3 N -1 m –1 compared to 5.7E-3 mm 3 N -1 m –1 for Stainless Steel 316.

14 SOLAR ENERGY↗
DOE OSTI2021

Effect of cathode on crosstalk in Si-based lithium-ion cells

Crosstalk between the cathode and the anode in Li-ion batteries has a great impact on performance, safety and cycle lifetime. However, a systematic investigation of crosstalk behavior in silicon (Si)-based cells with various cathode materials has not been reported. We investigated the crosstalk behavior of a Si anode coupled with one of the following cathodes—LiCoO 2 (LCO), LiNi 0.5 Mn 0.3 Co 0.2 (NMC532), and LiFePO 4 (LFP)—in a full cell. For each electrochemical couple, we compared electrolyte decomposition products, solid electrolyte interphase (SEI) chemistry, and degradation mechanisms during cycling. From a very early stage of cycling, each couple showed different crosstalk behavior; different electrolyte decomposition products and SEI chemistry on the Si anodes were seen. Specifically, the formation and growth mechanism of Si SEI differ depending on cathode materials. For the LFP system, the Si SEI rich in LiF and inorganic species, which is stable and robust. It forms at an early stage of cycle. As a result, the SEI of Si from the LFP system well tolerates SEI breakage due to mechanical changes of Si and suppresses Li loss, resulting in stable cycle life.

25 ENERGY STORAGE↗
DOE OSTI2023

Sensitivity Analysis of Effectiveness of FLEX Strategies Using a CDF-Based Importance Measure Under Accident Conditions

One of the lessons learned from the Fukushima Daiichi nuclear power plant (NPP) accident is strengthening the station blackout (SBO) mitigation capabilities by enhancing defense in depth for all existing and new NPPs. One of the possible remedies is diverse and flexible coping strategies (FLEX). The objective of this study is to address the benefits of FLEX in various accident scenarios in terms of both risk and cost. FLEX was originally devised against SBO accidents. In this research, we investigate the fundamental plant responses against accidents considering two fundamentally different cases: accidents that lead to high pressure on the primary side and accidents that lead to low pressure on the primary side. Several uncertainties are associated with the characteristics of the FLEX portable equipment. Specifically, the time for FLEX deployment may depend on several factors such as type of accident, point of injection, availability of safety systems, battery backup timings, and human actions. This study utilizes a dynamic risk assessment framework to analyze accident scenarios and suggests a novel importance measure, which is a cumulative distribution function– based importance metric that characterizes the influence of input distribution on complete output distribution. The importance of the existing and newly developed FLEX strategy based on risk significance is illustrated with examples. The suggested measure provides clear insight into how FLEX affects risk of the whole system and additional risk margins thanks to new safety systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Applying a science‐based systems perspective to dispel misconceptions about climate effects of forest bioenergy

Abstract The scientific literature contains contrasting findings about the climate effects of forest bioenergy, partly due to the wide diversity of bioenergy systems and associated contexts, but also due to differences in assessment methods. The climate effects of bioenergy must be accurately assessed to inform policy‐making, but the complexity of bioenergy systems and associated land, industry and energy systems raises challenges for assessment. We examine misconceptions about climate effects of forest bioenergy and discuss important considerations in assessing these effects and devising measures to incentivize sustainable bioenergy as a component of climate policy. The temporal and spatial system boundary and the reference (counterfactual) scenarios are key methodology choices that strongly influence results. Focussing on carbon balances of individual forest stands and comparing emissions at the point of combustion neglect system‐level interactions that influence the climate effects of forest bioenergy. We highlight the need for a systems approach, in assessing options and developing policy for forest bioenergy that: (1) considers the whole life cycle of bioenergy systems, including effects of the associated forest management and harvesting on landscape carbon balances; (2) identifies how forest bioenergy can best be deployed to support energy system transformation required to achieve climate goals; and (3) incentivizes those forest bioenergy systems that augment the mitigation value of the forest sector as a whole. Emphasis on short‐term emissions reduction targets can lead to decisions that make medium‐ to long‐term climate goals more difficult to achieve. The most important climate change mitigation measure is the transformation of energy, industry and transport systems so that fossil carbon remains underground. Narrow perspectives obscure the significant role that bioenergy can play by displacing fossil fuels now, and supporting energy system transition. Greater transparency and consistency is needed in greenhouse gas reporting and accounting related to bioenergy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Transiently Transfected Mammalian Cell Cultures: An Adaptable and Effective Platform for Virus-like Particle-Based Vaccines against Foot-and-Mouth Disease Virus

RNA viruses, such as foot-and-mouth disease virus (FMDV), have error-prone replication resulting in the continuous emergence of new viral strains capable of evading current vaccine coverage. Vaccine formulations must be regularly updated, which is both costly and technically challenging for many vaccine platforms. In this report, we describe a plasmid-based virus-like particle (VLP) production platform utilizing transiently transfected mammalian cell cultures that combines both the rapid response adaptability of nucleic-acid-based vaccines with the ability to produce intact capsid epitopes required for immunity. Formulated vaccines which employed this platform conferred complete protection from clinical foot-and-mouth disease in both swine and cattle. This novel platform can be quickly adapted to new viral strains and serotypes through targeted exchanges of only the FMDV capsid polypeptide nucleic acid sequences, from which processed structural capsid proteins are derived. This platform obviates the need for high biocontainment manufacturing facilities to produce inactivated whole-virus vaccines from infected mammalian cell cultures, which requires upstream expansion and downstream concentration of large quantities of live virulent viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Enhancing the Carbon Monoxide Oxidation Performance through Surface Defect Enrichment of Ceria-Based Supports for Platinum Catalyst

Effective synthesis and application of single-atom catalysts on supports lacking enough defects remain a significant challenge in environmental catalysis. Herein, we present a universal defect-enrichment strategy to increase the surface defects of CeO 2 -based supports through H 2 reduction pretreatment. The Pt catalysts supported by defective CeO 2 -based supports, including CeO 2 , CeZrO x , and CeO 2 /Al 2 O 3 (CA), exhibit much higher Pt dispersion and CO oxidation activity upon reduction activation compared to their counterpart catalysts without defect enrichment. Specifically, Pt is present as embedded single atoms on the CA support with enriched surface defects (CA-HD) based on which the highly active catalyst showing embedded Pt clusters (Pt C ) with the bottom layer of Pt atoms substituting the Ce cations in the CeO 2 surface lattice can be obtained through reduction activation. Embedded PtC can better facilitate CO adsorption and promote O 2 activation at Pt C –CeO 2 interfaces, thereby contributing to the superior low-temperature CO oxidation activity of the Pt/CA-HD catalyst after activation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Hybrid Quantum-Classical Eigensolver without Variation or Parametric Gates

The use of near-term quantum devices that lack quantum error correction, for addressing quantum chemistry and physics problems, requires hybrid quantum-classical algorithms and techniques. Here, we present a process for obtaining the eigenenergy spectrum of electronic quantum systems. This is achieved by projecting the Hamiltonian of a quantum system onto a limited effective Hilbert space specified by a set of computational bases. From this projection, an effective Hamiltonian is obtained. Furthermore, a process for preparing short depth quantum circuits to measure the corresponding diagonal and off-diagonal terms of the effective Hamiltonian is given, whereby quantum entanglement and ancilla qubits are used. The effective Hamiltonian is then diagonalized on a classical computer using numerical algorithms to obtain the eigenvalues. The use case of this approach is demonstrated for ground state and excited states of BeH2 and LiH molecules, and the density of states, which agrees well with exact solutions. Additionally, hardware demonstration is presented using IBM quantum devices for H2 molecule.

Jouzdani, Pejman (ORCID:0000000256470381)↗
DOE OSTI2023

Effects of Substance Use and Antisocial Personality on Neuroimaging-Based Machine Learning Prediction of Schizophrenia

Abstract Background and hypothesis Neuroimaging-based machine learning (ML) algorithms have the potential to aid the clinical diagnosis of schizophrenia. However, literature on the effect of prevalent comorbidities such as substance use disorder (SUD) and antisocial personality (ASPD) on these models’ performance has remained unexplored. We investigated whether the presence of SUD or ASPD affects the performance of neuroimaging-based ML models trained to discern patients with schizophrenia (SCH) from controls. Study design We trained an ML model on structural MRI data from public datasets to distinguish between SCH and controls (SCH = 347, controls = 341). We then investigated the model’s performance in two independent samples of individuals undergoing forensic psychiatric examination: sample 1 was used for sensitivity analysis to discern ASPD (N = 52) from SCH (N = 66), and sample 2 was used for specificity analysis to discern ASPD (N = 26) from controls (N = 25). Both samples included individuals with SUD. Study results In sample 1, 94.4% of SCH with comorbid ASPD and SUD were classified as SCH, followed by patients with SCH + SUD (78.8% classified as SCH) and patients with SCH (60.0% classified as SCH). The model failed to discern SCH without comorbidities from ASPD + SUD (AUC = 0.562, 95%CI = 0.400–0.723). In sample 2, the model’s specificity to predict controls was 84.0%. In both samples, about half of the ASPD + SUD were misclassified as SCH. Data-driven functional characterization revealed associations between the classification as SCH and cognition-related brain regions. Conclusion Altogether, ASPD and SUD appear to have effects on ML prediction performance, which potentially results from converging cognition-related brain abnormalities between SCH, ASPD, and SUD.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Metal Oxide vs Organic Semiconductor Charge Extraction Layers for Halide Perovskite Indoor Photovoltaics

Halide perovskite indoor photovoltaics (PVs) are highly promising to autonomously power the billions of microelectronic sensors in the emerging and disruptive technology of the Internet of Things (IoT). However, how the wide range of different types of hole extraction layers (HELs) impacts the indoor light harvesting of perovskite solar cells is still elusive, which hinders the material selection and industrial–scale fabrication of indoor perovskite photovoltaics. In the present study, new insights are provided regarding the judicial selection of HELs at the buried interface of halide perovskite indoor photovoltaics. This study unravels the detrimental and severe light–soaking effect of metal oxide transport layer–based PV devices under the indoor lighting effect for the first time, which then necessitates the interface passivation/engineering for their reliant performance. This is not a stringent criterion under 1 sun illumination. By systematically investigating the charge carrier dynamics and sequence of measurements from dark, light–soaked, interlayer–passivated device, the bulk and interface defects are decoupled and reveal the gradual defect passivation from shallow to deep level traps. Thus, the present study puts forward a useful design strategy to overcome the deleterious effect of metal oxide HELs and employ them in halide perovskite indoor PVs.

14 SOLAR ENERGY↗