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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 1,657 records · Page 92

Fluorocarbon based atomic layer etching of Si{sub 3}N{sub 4} and etching selectivity of SiO{sub 2} over Si{sub 3}N{sub 4}

Angstrom-level plasma etching precision is required for semiconductor manufacturing of sub-10 nm critical dimension features. Atomic layer etching (ALE), achieved by a series of self-limited cycles, can precisely control etching depths by limiting the amount of chemical reactant available at the surface. Recently, SiO{sub 2} ALE has been achieved by deposition of a thin (several Angstroms) reactive fluorocarbon (FC) layer on the material surface using controlled FC precursor flow and subsequent low energy Ar{sup +} ion bombardment in a cyclic fashion. Low energy ion bombardment is used to remove the FC layer along with a limited amount of SiO{sub 2} from the surface. In the present article, the authors describe controlled etching of Si{sub 3}N{sub 4} and SiO{sub 2} layers of one to several Angstroms using this cyclic ALE approach. Si{sub 3}N{sub 4} etching and etching selectivity of SiO{sub 2} over Si{sub 3}N{sub 4} were studied and evaluated with regard to the dependence on maximum ion energy, etching step length (ESL), FC surface coverage, and precursor selection. Surface chemistries of Si{sub 3}N{sub 4} were investigated by x-ray photoelectron spectroscopy (XPS) after vacuum transfer at each stage of the ALE process. Since Si{sub 3}N{sub 4} has a lower physical sputtering energy threshold than SiO{sub 2}, Si{sub 3}N{sub 4} physical sputtering can take place after removal of chemical etchant at the end of each cycle for relatively high ion energies. Si{sub 3}N{sub 4} to SiO{sub 2} ALE etching selectivity was observed for these FC depleted conditions. By optimization of the ALE process parameters, e.g., low ion energies, short ESLs, and/or high FC film deposition per cycle, highly selective SiO{sub 2} to Si{sub 3}N{sub 4} etching can be achieved for FC accumulation conditions, where FC can be selectively accumulated on Si{sub 3}N{sub 4} surfaces. This highly selective etching is explained by a lower carbon consumption of Si{sub 3}N{sub 4} as compared to SiO{sub 2}. The comparison of C{sub 4}F{sub 8} and CHF{sub 3} only showed a difference in etching selectivity for FC depleted conditions. For FC accumulation conditions, precursor chemistry has a weak impact on etching selectivity. Surface chemistry analysis shows that surface fluorination and FC reduction take place during a single ALE cycle for FC depleted conditions. A fluorine rich carbon layer was observed on the Si{sub 3}N{sub 4} surface after ALE processes for which FC accumulation takes place. The angle resolved-XPS thickness calculations confirmed the results of the ellipsometry measurements in all cases.

36 MATERIALS SCIENCE↗

ELISA: A Tool for Optimization of Rotor Hover Performance at Low Reynolds Number in the Mars Atmosphere

The Evolutionary aLgorithm for Iterative Studies of Aeromechanics (ELISA) was developed in support of the Rotorcraft Optimization for the Advancement of Mars eXploration (ROAMX) project. ELISA was developed to enable aerodynamic rotor hover optimization for low Reynolds number flows in the Mars atmosphere. The first objective of the algorithm allows for unconventional airfoil parameterization and multi-objective airfoil geometry optimization using OVERFLOW. The Pareto-optimal airfoil sets are converted to a set of Pareto-optimal airfoil decks, providing the lowest drag air foil geometry for each angle of attack, removing the need to arbitrarily select the airfoils to be used in the rotor optimization. The second objective allows for rotor geometry optimization with simultaneous maximization of blade loading and minimization of rotor power using the comprehensive analysis CAMRADII. The result is a Pareto-optimal rotor set, providing the lowest power rotor for each attainable blade loading, and one of the first tools for hover-optimized rotors for high-subsonic low Reynolds number conditions. The airfoil thickness can be modified after the airfoil optimization is complete, allowing for a post-airfoil-optimization adjustment of blade thickness to facilitate conforming to external structural analyses requirements. The relevance of the code is demonstrated with case studies for the ROAMX rotor optimization for Ingenuity-sized single rotors in the Mars atmosphere, a performance study optimizing the chord and twist of Ingenuity’s coaxial rotor resulting in the Sample Recovery Helicopters candidate rotor, and high-subsonic low Reynolds number airfoil optimization providing novel insights for higher-efficiency low Reynolds number airfoil geometries and flow physics.

ELISA↗

Estimation of LOCA break size using cascaded support vector regression - 334

A failure of emergency core cooling system (ECCS) during a certain small break loss of coolant accident (SBLOCA) can cause a severe core uncovery and fuel failure. The safety injection systems (SISs) might not function properly in case of a SBLOCA, due to the slight change of pressure in the pipes. Early trend of the major parameters has to be observed and the accurate information has to be given to the nuclear power plant (NPP) operators by precisely identifying the break size to effectively manage accidents. In this study, the objective is to provide to operators the information on the break size in a short time by considering the accident situations such as hot-leg LOCA, cold-leg LOCA, steam generator tube rupture (SGTR). A cascaded support vector regression (CSVR) is used in order to estimate the break size. The simulation data set was obtained from the optimized power plant reactor 1000 (OPR1000) using modular accident analysis program (MAAP) code. And genetic algorithm (GA) was used to select the input variables of the CSVR model and optimize its parameters. As a result of this study, the CSVR model estimate very well the break size of LOCAs. If the operators can predict the break size in the LOCA, they can response quickly and properly to LOCA circumstances to prevent the core uncovery and fuel failure. Also, it will be possible to more efficiently manage beyond design basis accidents. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of optimized drug-like small molecule inhibitors of the SARS-CoV-2 3CL protease for treatment of COVID-19

The SARS-CoV-2 3CL protease is a critical drug target for small molecule COVID-19 therapy, given its likely druggability and essentiality in the viral maturation and replication cycle. Based on the conservation of 3CL protease substrate binding pockets across coronaviruses and using screening, we identified four structurally distinct lead compounds that inhibit SARS-CoV-2 3CL protease. After evaluation of their binding specificity, cellular antiviral potency, metabolic stability, and water solubility, we prioritized the GC376 scaffold as being optimal for optimization. We identified multiple drug-like compounds with <10nM potency for inhibiting SARS-CoV-2 3CL and the ability to block SARS-CoV-2 replication in human cells, obtained co-crystal structures of the 3CL protease in complex with these compounds, and determined that they have pan-coronavirus activity. We selected one compound, termed coronastat, as an optimized lead and characterized it in pharmacokinetic and safety studies in vivo. Coronastat represents a new candidate for a small molecule protease inhibitor for the treatment of SARS-CoV-2 infection for eliminating pandemics involving coronaviruses.

60 APPLIED LIFE SCIENCES↗

Frequency domain synthesis of optimal inputs for adaptive identification and control

The input design problem of selecting appropriate inputs for use in SISO adaptive identification and model reference adaptive control algorithms is considered. Averaging theory is used to characterize the optimal inputs in the frequency domain. The design problem is formulated as an optimization problem which maximizes the smallest eigenvalue of the average information matrix over power constrained signals, and the global optimal solution is obtained using a convergent numerical algorithm. A bound on the frequency search range required in the design algorithm has been determined in terms of the desired performance.

Fu, Li-Chen↗

General shape optimization capability

A method is described for calculating shape sensitivities, within MSC/NASTRAN, in a simple manner without resort to external programs. The method uses natural design variables to define the shape changes in a given structure. Once the shape sensitivities are obtained, the shape optimization process is carried out in a manner similar to property optimization processes. The capability of this method is illustrated by two examples: the shape optimization of a cantilever beam with holes, loaded by a point load at the free end (with the shape of the holes and the thickness of the beam selected as the design variables), and the shape optimization of a connecting rod subjected to several different loading and boundary conditions.

Chargin, Mladen K.↗

Mid-Infrared Optimized Resolution Spacecraft (MIRORS)

A concept study was performed in 1994 to develop a mission design for a telescope to achieve the highest possible spatial resolution in the 10-30 micron range within a $200 million mission cost cap. The selected approach for the resulting Mid-Infrared Optimized Resolution Spacecraft (MIRORS) concept design utilizes a partially filled five meter aperture.

infrared↗

Image registration via optimization over disjoint image regions

Technologies pertaining to registering a target image with a base image are described. In a general embodiment, the base image is selected from a set of images, and the target image is an image in the set of images that is to be registered to the base image. A set of disjoint regions of the target image is selected, and a transform to be applied to the target image is computed based on the optimization of a metric over the selected set of disjoint regions. The transform is applied to the target image so as to register the target image with the base image.

97 MATHEMATICS AND COMPUTING↗

The modeling of risk perception in the use of structural health monitoring information for optimal maintenance decisions

This paper proposes an approach to select a maintenance strategy from a predefined set of choices considering the decision maker’s behavioral risk profile. It is assumed that the damage state is characterized by a continuous state parameter probabilistically inferred from observable sensor data. This work applies an engineering application of consequence-based decision-making incorporating the acceptable risk intensity of the decision-maker, i.e., the decision-maker’s (individual or an organization) valuation of the outcome of a decision, using a risk profile model. The utility of a decision-maker is subjective, and this paper considers the fact that different decision-makers mentally assign a different importance factor (the utility) to the seriousness or urgency to take necessary actions with the increasing intensity of structural damage. The approach herein incorporates a layer of human psychology on selecting appropriate maintenance strategies that not only depend on the posterior distribution of unmeasurable damage state but also consider the behavioral risk profile of the decision-maker. Further, the collective decision-making of an organization consisting of many individuals is also investigated. The approach is exemplified in a case study involving life cycle monitoring of a miter gate, part of a lock system enabling navigation of inland waterways.

42 ENGINEERING↗

WE-AB-BRA-05: PET-Guided Delivery Quality Evaluation of Yttrium-90 Microsphere Radioembolizaton for Hepatocellular Carcinoma Patients: The Optimal Sequence of Radioembolizaton and Chemoembolization Treatments

Purpose: Selective-internal-radiation-therapy (SIRT) and transarterial-chemoembolization (TACE) are commonly used for treatment of liver tumors. The use of TACE, which is macroembolic, prior to SIRT may cause hemodynamic changes in tumor vasculature that impair yttrium-90 (90Y) microsphere delivery to the targeted lesions. This work aims to quantify dosimetric tumor coverage using 90Y positron emission tomography (PET) dosimetry after SIRT alone compared to TACE followed by SIRT. Methods: A total of 40 consecutive hepatocellular carcinoma (HCC) SIRT patients who had a post-SIRT 90Y PET/CT scan were evaluated. The patient-specific-3D-dose was reconstructed from the PET images. Patients were categorized into two groups: patients received TACE prior SIRT procedure (n=18) and patient received SIRT alone (n=22). The lesions and liver were delineated by a senior radiologist. We evaluated both the lesion-specific dose-volume-histogram (DVH) and the selectivity index (SI) defined as the ratio of the average dose inside the total lesion(s) and the average dose of the normal liver. The SI values of patients were compared based on whether TACE was previously used. Results: A wide spectrum was observed in the lesion-specific DVH-evaluation and SI appeared to be suitable of evaluating the quality of each SIRT infusion. The average SI of the entire patient group was 3.0, i.e. targeted lesion receiving three times higher dose than normal liver. The average SI was 1.8 for patients who had prior TACE and 3.9 for patients who did not have prior TACE (p=0.008). 85% of the patients with prior TACE demonstrated poor 90Y-microsphere delivery (SI <2) while none demonstrated excellent delivery (SI >4). On the other hand, the incidence SI >4 among patients with no prior TACE was 37%. Conclusion: 3D dose evaluation using post-SIRT PET suggests that 90Y microsphere delivery to liver tumors is impaired among patients who received prior TACE compared to those who receive SIRT alone.

60 APPLIED LIFE SCIENCES↗

Optimal environmental and economic performance trade-offs for fifth generation district heating and cooling network topologies with waste heat recovery

Network topology greatly influences both the economic and environmental performance of fifth generation district heating and cooling (5GDHC) systems. In this study the optimal trade-offs between the environmental and economic performance of 5GDHC network topologies for a five-building district with waste heat recovery were explored. A life cycle assessment method was used to calculate the total life cycle CO 2 emissions (LCCO2) associated with the installation and operation of various network topologies. Twelve months of empirical data from a data center cooling system were analyzed to assess its suitability for integration into a 5GDHC system. The most suitable method for utilizing this waste heat was selected based on the ambient loop warm pipe setpoint, waste heat temperature, and district energy system configuration. A multi-objective optimization algorithm was used to select the 5GDHC network topology that provided the optimal trade-off between LCCO2 and life cycle cost (LCC). A trade-off parameter was employed to weigh the importance of each objective in the selection process. The results showed waste heat from the data center was suitable for integration into the 5GDHC system due to its availability and consistent temperature profile. When return temperatures of 25 °C or higher were available from the liquid-cooled system, direct pre-heating of the ambient loop warm pipe was found to be the most effective waste heat integration method. The selection of the network topology that provided the optimal trade-off between LCCO2 and LCC (optimal trade-off topology) was highly dependent on factors such as fuel prices, CO 2 prices, electricity CO 2 emissions factors, availability of waste heat, embodied CO 2 emissions associated with network installation and network infrastructure costs. Optimal trade-off topologies produced substantial LCCO2 reductions relative to corresponding LCC increases. LCCO2 reduction to LCC increase ratios from 5.78 to 117.79 were identified with CO 2 offset costs ranging from 4.77 to 60.08 ($/tCO 2 e).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Time-Dependent Electric Bus and Charging Station Deployment Problem

Battery electric buses (BEBs) have gained popularity due to their emission-free and energy-efficient features. Many transit authorities worldwide have set goals to gradually replace their bus fleets with BEBs. Considering the potential decline in BEB battery and charger prices, this study proposes a time-dependent bus fleet transition model to determine the optimal bus fleet transition plan, which includes selecting the bus lines to be electrified, determining the timing and type of BEBs to be purchased, and deploying on-route fast chargers and depot chargers. The model is a bi-objective integer linear program that considers the trade-off between electrified transit mileages and bus electrification costs. A normalized normal constraint method is applied to solve the bi-objective optimization model. The effectiveness of the proposed model is tested using a real-world bus network. Additionally, sensitivity analyses are conducted to better understand the impact of different parameter values on the optimal solutions. Our proposed model can provide transit authorities with a powerful tool to make informed decisions about their BEB fleet replacement plans.

ADVANCED PROPULSION SYSTEMS↗

Surface‐modified Ag@Ru‐P25 for photocatalytic CO 2 conversion with high selectivity over CH 4 formation at the solid–gas interface

Systematic optimization of the photocatalyst and investigation of the role of each component is important to maximizing catalytic activity and comprehending the photocatalytic conversion of CO 2 reduction to solar fuels. A surface-modified Ag@Ru-P25 photocatalyst with H 2 O 2 treatment was designed in this study to convert CO 2 and H 2 O vapor into highly selective CH 4 . Ru doping followed by Ag nanoparticles (NPs) cocatalyst deposition on P25 (TiO 2 ) enhances visible light absorption and charge separation, whereas H 2 O 2 treatment modifies the surface of the photocatalyst with hydroxyl (–OH) groups and promotes CO 2 adsorption. High-resonance transmission electron microscopy, X-ray photoelectron spectroscopy, X-ray absorption near-edge structure, and extended X-ray absorption fine structure techniques were used to analyze the surface and chemical composition of the photocatalyst, while thermogravimetric analysis, CO 2 adsorption isotherm, and temperature programmed desorption study were performed to examine the significance of H 2 O 2 treatment in increasing CO 2 reduction activity. The optimized Ag 1.0 @Ru 1.0 -P25 photocatalyst performed excellent CO 2 reduction activity into CO, CH 4 , and C 2 H 6 with a ~95% selectivity of CH 4 , where the activity was ~135 times higher than that of pristine TiO 2 (P25). For the first time, this work explored the effect of H 2 O 2 treatment on the photocatalyst that dramatically increases CO 2 reduction activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective and Efficient Production of Biomass-Derived Vinylfurans

We describe a two-step catalytic process for the selective and rapid conversion of biomass-derived acetylfurans into vinylfurans. This is accomplished by nearly quantitatively reducing acetylfurans into furyl alcohols using a copper chromite catalyst and exploiting the promoter-like properties of ethanol, the solvent. Subsequently, furyl alcohol is dehydrated using solid-acid catalysts. Catalyst deactivation due to oligomeric species is a major issue, but the activity can be partially recovered by calcination. Optimization of reaction conditions showed that the selectivity could be increased by using nitrobenzene, a polar aprotic solvent. Here, the high-boiling point solvent allows the formation of vinylfurans with a selectivity of up to 85%; the product can be isolated in high purity by distillation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

State Dependent Optimization with Quantum Circuit Cutting

Quantum circuits can be reduced through optimization to better fit the constraints of quantum hardware. One such method, initial-state dependent optimization (ISDO), reduces gate count by leveraging knowledge of the input quantum states. Surprisingly, we found that ISDO is broadly applicable to the downstream circuits produced by circuit cutting. Circuit cutting also requires measuring upstream qubits and has some flexibility of selection observables to do reconstruction. Therefore, we propose a state-dependent optimization (SDO) framework that incorporates ISDO, our newly proposed measure-state dependent optimization (MSDO), and a biased observable selection strategy. Building on the strengths of the SDO framework and recognizing the scalability challenges of circuit cutting, we propose nonseparate circuit cutting-a more flexible approach that enables optimizing gates without fully separating them. We validate our methods on noisy simulations of QAOA, QFT, and BV circuits. Results show that our approach consistently mitigates noise and improves overall circuit performance, demonstrating its promise for enhancing quantum algorithm execution on near-term hardware.

Li, Xinpeng↗

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗