Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Reducing agent”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Bioreduction of Solid Rocket Motors for Planetary Protection

Solid rocket propulsion systems have been used for in-space applications including planetary exploration missions for many years. Current NASA science lander projects require solid rocket propulsion systems to touchdown on the surface of potentially life-supporting planets and moons. A critical requirement of these missions is the prevention of accidental transportation of Earth's microbes to these environments. This mission requirement places an increased importance on the ability to reduce the biological burden that may be on board the solid propulsion systems and potentially deposited in a habitable environment. Some traditional interplanetary spacecraft decontamination operations could reduce the reliability of the solid propulsion system, indicating a need for new decontamination procedures. New techniques for biological burden reduction are being studied and may become the method of choice to ensure adequate reduction has been achieved. These techniques include biocidal elimination through chemical agents already present within the motor and cellular disruption due to assembly and operational environments induced in the motor. Recent investigations into the effectiveness of these techniques have generated promising experimental results. These techniques and current experimental results will be presented.

Boyle, Sadie M.↗
DOE OSTI2026

Surrogate Neural Architecture Codesign Package (SNAC-Pack)

Neural architecture search (NAS) is a powerful approach for automating model design, but existing methods often optimize for accuracy alone or rely on proxy metrics such as bit operations (BOPs) that correlate poorly with hardware cost. This gap is particularly large for FPGA deployment, where cost is dominated by a multi-dimensional budget of lookup tables, DSPs, flip-flops, BRAM, and latency. We present the Surrogate Neural Architecture Codesign Package (SNAC-Pack), an open-source AutoML framework for hardware-aware neural architecture codesign and end-to-end FPGA deployment. SNAC-Pack runs a multi-objective global search with Optuna and NSGA-II, loading trials to a shared SQLite store that enables parallel workers across compute nodes. A hardware surrogate model outputs per-trial resource and latency estimates, avoiding the synthesis cost that would otherwise dominate the search loop. A local search stage then applies quantization-aware training (QAT) together with iterative magnitude pruning in a combined compression loop, after which the final model is synthesized to FPGA firmware via the hls4ml Python library. A YAML configuration and an optional agentic frontend let users run the pipeline on new datasets without modifying the framework. We demonstrate SNAC-Pack on jet classification at the Large Hadron Collider and superconducting qubit readout, discovering compact architectures that match or exceed strong baselines on the task metric while reducing FPGA resource utilization and, in the qubit readout case, reducing the design space exploration process from months of manual fine-tuning to hours of automated search.

Weitz, Jason [UC, San Diego]↗
DOE OSTI2020

A scalable approach of using biomass derived glycerol to synthesize cathode materials for lithium-ion batteries

Glycerol, a main byproduct of biodiesel, was used as the fuel agent in a scalable flame-assisted spray pyrolysis approach to synthesize micron-size cathode materials. Single droplet combustion, particle morphology, and electrochemical performance were examined considering the effects of salt concentration, water addition, and post-annealing time on synthesizing Li(Ni 1/3 Co 1/3 Mn 1/3 )O 2 (NCM111) cathode materials. Single droplet tests showed that a sufficient amount of water in the glycerol-based precursor could delay droplet inflation and ignition. Moreover, using a two-fluid atomization nozzle, spray tests demonstrated that adding water would result in less wrinkled and more uniform particles. Nevertheless, increasing water proportion in the precursor could reduce the reaction heat, resulting in that samples prepared with water addition needed longer post-annealing time to improve their electrochemical performance. Using the precursor without water, the best performed NCM111 cathode material was synthesized with only 2 h of post-annealing. It has a discharge capacity of 163.3 mAh/g at 0.1C and 85.5% capacity retention at 1C after 100 cycles. Furthermore, the current work confirmed the capability of using glycerol as a sustainable fuel agent to synthesize NCM111 cathode materials, and also provided basic conditions for the development of large-scale production in the future.

25 ENERGY STORAGE↗
DOE OSTI2021

Metformin attenuates expression of angiogenic and inflammatory genes in human endometriotic stromal cells

Highlights: • Metformin reduced cell migration, and proliferation of endometriotic stromal cells. • Metformin attenuated the expression of angiogenic and inflammatory genes in human endometriotic stromal cells. • Metformin could be used as an effective adjuvant in endometriosis treatment. Endometriosis is a benign gynecological disease that is manifested by the presence and growth of endometrial cells and glands outside the uterine. Active angiogenesis, migration, and invasion of endometrial tissue outside the uterine are critical for the development of endometriosis and lead to the survival and growth of endometriotic lesions. Metformin, as an anti-diabetic agent, represents anti-angiogenic property. Here, we performed a study using human normal endometrial stromal cells (N-ESCs) from healthy endometrial tissue and human eutopic endometrial stromal cells (EU-ESCs) and ectopic endometrial stromal cells (ECT-ESCs) from endometriosis patients. ESCs were cultured and treated with different concentrations of Metformin (0–20 mmol/l) for 72 h to evaluate Metformin effect on cell viability, proliferation, migration was measured by methyl thiazolyl tetrazolium (MTT) assay and scratch test respectively as well as expression of angiogenesis and migration markers. The Metformin reduced cell migration, and proliferation of endometriotic stromal cells in a time and concentration dependently manner. Furthermore, Metformin attenuated the expression of angiogenic and inflammatory genes in human endometriotic stromal cells. The direct anti-proliferative effect on ECT-ESCs combined with the effects of Metformin on inflammatory and angiogenesis-related genes expression supports its therapeutic potential for endometriosis. Metformin could be used as an effective adjuvant in endometriosis treatment.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1977

Microbe Detector

The AutoMicrobic System (AMS) represents years of intensive research and development by McDonnell Douglas Corp. that originated with a NASA study aimed at development of a fully automated microbial detection and identification system for spacecraft use. A urine specimen is placed into the system, where it is subjected to different freeze-dried microbe nutrients for the nine most common pathogens. An electro-optical scanner studies each specimen once an hour through a 4-to-13 hour cycle, operating automatically. Changes in cell growths on each culture are monitored by computer. The presence of pathogens is indicated when growth reaches a predetermined level. The system also enumerates the pathogens and specifies the type. Developed initially to handle urine testing, AMS soon is expected to allow analyses of blood, spinal fluid, and other body fluids. An additional capability under development is "susceptibility testing," or the determination of which microbe-killing agents-such as penicillin or other antibiotics-would be most effective in eliminating the pathogens. The whole process of detecting, identifying, and enumerating the pathogens and determining susceptibility is accomplished in less half the time required for the manual procedure. The AMS minimizes human error, reduces technician time , and increases laboratory output.

Source record↗
NASA NTRS2009

Advanced Signal Processing Techniques Applied to Terahertz Inspections on Aerospace Foams

The space shuttle's external fuel tank is thermally insulated by the closed cell foams. However, natural voids composed of air and trapped gas are found as by-products when the foams are cured. Detection of foam voids and foam de-bonding is a formidable task owing to the small index of refraction contrast between foam and air (1.04:1). In the presence of a denser binding matrix agent that bonds two different foam materials, time-differentiation of filtered terahertz signals can be employed to magnify information prior to the main substrate reflections. In the absence of a matrix binder, de-convolution of the filtered time differential terahertz signals is performed to reduce the masking effects of antenna ringing. The goal is simply to increase probability of void detection through image enhancement and to determine the depth of the void.

Trinh, Long Buu↗
NASA NTRSDate not supplied

Summary of Technical Interchange Meetings (TIMs) Designed to Enable Earth Independent Medical Operations (EIMO)

The Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program hosted a series of TIMs in 2023-2024 designed to stimulate discussion around specific topics with the goal of enabling EIMO. In context of the thematic constituent elements of EIMO, namely pre-mission planning, acute/emergent/prolonged medical decision making, supply/resource management and task load management, subject matter experts from industry, academia and government (NASA and other Agencies) provided valuable and actionable guidance and recommendations. Earth-based medical experts will remain indispensable for pre-mission planning, however, management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets to enable support of astronaut health and performance and reduce overall mission risk. Key to achieving these enhancements is providing an integrated data system platform capable of utilizing multiple data streams in concert with a variety of on-board databases and passive monitoring of video and wearable sensors to enable a multi-modal, agentic AI-based clinical decision support system (CDSS) to support crew medical officer (CMO) medical decision-making. The EIMO series of TIMs (I-V) have proven to be instructive and portend a significant paradigm shift will be necessary to maintain crew health and performance on exploration class missions. Importantly, since the expected paradigm shift will be significantly different from the methods of operation that have been employed for the majority of missions from the inception of human spaceflight to date, any proposed methods must be deployed in the setting of ongoing operations early and be “tested, reviewed and practiced” while reliable back-up is available to facilitate an Enterprise-wide level of comfort and acceptance. Serious constraints on data transmission coupled with a large and expanding universe of on-board medical informatics data streams will necessitate implementation of a CDSS to supplant the current reliance on support provided by ground-based SMEs. Establishment of trust in the system by CMO/crew and the ground-based medical support team will be essential. Co-development of a CDSS with industry partners will assure that state of the art tools can be employed, and industry efficiencies can be leveraged. Training regimens, materials and tools must evolve to be responsive (just-in-time training) and facilitate autonomous execution of procedures. Proficiency metrics should be established and be based on validated competencies or milestones as opposed to a prescribed number of training hours. Training should be prioritized for broad, translatable skills that have universal application across a variety of medical conditions. Repetition was deemed to be the key to achieving proficiency and emphasis should lie in procedural training which is known to extinguish more rapidly than diagnostic skills. Advanced tools, e.g., extended reality, can provide more realistic and effective training. Use of advanced probabilistic risk assessment tools will be essential to optimize the medical system capability while carefully balancing risk relative to mass/power/volume limitations. Importance of factoring use-life of medical supplies and maintaining awareness of redundancy and opportunity to re-purpose under off nominal situations was emphasized. Consideration of adopting optimized performance standards vs. “good-enough” performance thresholds is warranted. The use of legacy systems as opposed to creating new systems may be preferable. Managing task load and associated cognitive load will be essential to maintain operational safety and behavioral health. ExMC aspires to create a shared EIMO paradigm and strategic vision for advancing medical system design through novel technologies, training, protocols, and support capabilities, built upon the spirit of successful strategies and innovations over the past six decades of space medicine operations.

Jay Lemery↗
DOE OSTI2024

Quantifying leaf symptoms of sorghum charcoal rot in images of field‐grown plants using deep neural networks

Abstract Charcoal rot of sorghum (CRS) is a significant disease affecting sorghum crops, with limited genetic resistance available. The causative agent, Macrophomina phaseolina (Tassi) Goid, is a highly destructive fungal pathogen that targets over 500 plant species globally, including essential staple crops. Utilizing field image data for precise detection and quantification of CRS could greatly assist in the prompt identification and management of affected fields and thereby reduce yield losses. The objective of this work was to implement various machine learning algorithms to evaluate their ability to accurately detect and quantify CRS in red‐green‐blue images of sorghum plants exhibiting symptoms of infection. EfficientNet‐B3 and a fully convolutional network emerged as the top‐performing models for image classification and segmentation tasks, respectively. Among the classification models evaluated, EfficientNet‐B3 demonstrated superior performance, achieving an accuracy of 86.97%, a recall rate of 0.71, and an F1 score of 0.73. Of the segmentation models tested, FCN proved to be the most effective, exhibiting a validation accuracy of 97.76%, a recall rate of 0.68, and an F1 score of 0.66. As the size of the image patches increased, both models’ validation scores increased linearly, and their inference time decreased exponentially. This trend could be attributed to larger patches containing more information, improving model performance, and fewer patches reducing the computational load, thus decreasing inference time. The models, in addition to being immediately useful for breeders and growers of sorghum, advance the domain of automated plant phenotyping and may serve as a foundation for drone‐based or other automated field phenotyping efforts. Additionally, the models presented herein can be accessed through a web‐based application where users can easily analyze their own images.

Gonzalez, Emmanuel M.↗
DOE OSTI2020

Graphite Intercalation Compounds Derived by Green Chemistry as Oxygen Reduction Reaction Catalysts

Precious group metal (PGM) catalysts such as Pt supported on carbon supports are expensive catalysts utilized for the oxygen reduction reaction (ORR) due to their unmatched catalytic activity and durability. As an alternative, PGM-free ORR electrocatalysts that offer respectable catalytic activity are being pursued. Most of the notable PGM-free catalysts are obtained either from a bottom-up approach synthesis utilizing nitrogen-rich polymers as building blocks, or from a top down approach, where nitrogen and metal moieties are incorporated to carbonaceous matrixes. The systematic understanding of the origin of catalytic activity for either case is speculative and currently employed synthesis techniques typically generate large amounts of hazardous waste such as acids, oxidizing agents, and solvents. Herein, for the first time, we investigate the catalytic activity of graphite-based materials obtained via intercalation strategies that minimally perturb the graphitic backbone. Here, our outlined approaches demonstrate initial efforts to not only elucidate the role of each element but also significantly reduce the use of hazardous chemicals, which remains a pressing challenge. Graphite intercalation compounds (GIC) were obtained using fewer steps and solvent-free processes. X-ray diffraction and Raman results confirm the successful intercalation of FeCl 3 between graphite layers. Electrochemical data shows that the ORR performance of FeCl 3 -intercalated GIC displays slight improvement where the onset potential reaches 0.77 V vs RHE in alkaline environments. However, expansion of the graphite and solvent-free incorporation of iron and nitrogen moieties resulted in a significant increase in ORR activity with onset potential to 0.89 V vs RHE, a maximum half-wave of 0.72 V vs RHE, and a limiting current of about 2.5 mA cm –2 . We anticipate that the use of near solvent-free processes that result in a high yield of catalysts along with the fundamental insight into the origin of electrochemical activity will tremendously impact the methodologies for developing next-generation ORR catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An intelligent energy router for managing behind-the-meter resources and assets

With increase in distributed energy resources (DERs) and smart loads, each energy resource and load need a separate power conversion system leading to complex coordination and interaction, reduced energy conversion efficiency, coordinating compliance to grid standards (IEEE 1547) from multiple sources, reduced security. Also, multiple vendors with legacy system designs and proprietary communications interfaces result in redundancy and increase in cost of power electronics systems. This paper presents an energy router concept for buildings applications which provides autonomous power flow between sources and loads with a novel agent-based software interface.

Chinthavali, Madhu Sudhan↗
NASA NTRS2019

Bioreduction of Solid Rocket Motors for Planetary Protection

Solid rocket propulsion systems have been used for in-space applications including planetary exploration missions for many years. Current NASA science lander projects require solid rocket propulsion systems to touchdown on the surface of potentially life-supporting planets and moons. A critical requirement of these missions is the prevention of accidental transportation of Earth's microbes to these environments. This mission requirement places an increased importance on the ability to reduce the biological burden that may be on board the solid propulsion systems and potentially deposited in a habitable environment. Some traditional interplanetary spacecraft decontamination operations could reduce the reliability of the solid propulsion system, indicating a need for new decontamination procedures. New techniques for biological burden reduction are being studied and may become the method of choice to ensure adequate reduction has been achieved. These techniques include using innate antimicrobial capacity of chemical agents already present within the motor and cellular disruption due to assembly and operational environments induced in the mated case. Recent investigations into the effectiveness of some of these techniques have generated promising experimental results.

Boyle, Sadie↗
DOE OSTI2024

Reducing Sample Size While Improving Equity in Vaccine Clinical Trials: A Machine Learning-Based Recruitment Methodology with Application to Improving Trials of Hepatitis C Virus Vaccines in People Who Inject Drugs

Despite the availability of direct-acting antivirals that cure individuals infected with the hepatitis C virus (HCV), developing a vaccine is critically needed in achieving HCV elimination. HCV vaccine trials have been performed in populations with high incidence of new HCV infection such as people who inject drugs (PWID). Developing strategies of optimal recruitment of PWID for HCV vaccine trials could reduce sample size, follow-up costs and disparities in enrollment. We investigate trial recruitment informed by machine learning and evaluate a strategy for HCV vaccine trials termed PREDICTEE—Predictive Recruitment and Enrichment method balancing Demographics and Incidence for Clinical Trial Equity and Efficiency. PREDICTEE utilizes a survival analysis model applied to trial candidates, considering their demographic and injection characteristics to predict the candidate’s probability of HCV infection during the trial. The decision to recruit considers both the candidate’s predicted incidence and demographic characteristics such as age, sex, and race. We evaluated PREDICTEE using in silico methods, in which we first generated a synthetic candidate pool and their respective HCV infection events using HepCEP, a validated agent-based simulation model of HCV transmission among PWID in metropolitan Chicago. We then compared PREDICTEE to conventional recruitment of high-risk PWID who share drugs or injection equipment in terms of sample size and recruitment equity, with the latter measured by participation-to-prevalence ratio (PPR) across age, sex, and race. Comparing conventional recruitment to PREDICTEE found a reduction in sample size from 802 (95%: 642–1010) to 278 (95%: 264–294) with PREDICTEE, while also reducing screening requirements by 30%. Simultaneously, PPR increased from 0.475 (95%: 0.356–0.568) to 0.754 (95%: 0.685–0.834). Even when targeting a dissimilar maximally balanced population in which achieving recruitment equity would be more difficult, PREDICTEE is able to reduce sample size from 802 (95%: 642–1010) to 304 (95%: 288–322) while improving PPR to 0.807 (95%: 0.792–0.821). PREDICTEE presents a promising strategy for HCV clinical trial recruitment, achieving sample size reduction while improving recruitment equity.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2011

Software Productivity of Field Experiments Using the Mobile Agents Open Architecture with Workflow Interoperability

We analyzed a series of ten systematically developed surface exploration systems that integrated a variety of hardware and software components. Design, development, and testing data suggest that incremental buildup of an exploration system for long-duration capabilities is facilitated by an open architecture with appropriate-level APIs, specifically designed to facilitate integration of new components. This improves software productivity by reducing changes required for reconfiguring an existing system.

Clancey, William J.↗
DOE OSTI2021

FAK-targeting PROTAC demonstrates enhanced antitumor activity against KRAS mutant non-small cell lung cancer

Focal adhesion kinase (FAK) has been established as a promising therapeutic target for KRAS mutant non-small cell lung cancer (NSCLC). However, phase II clinical trials of a FAK inhibitor (Defactinib) have only shown modest antitumor activity. To address this challenge, here we report the use of a FAK-targeting proteolysis targeting chimera (D-PROTAC) to treat KRAS mutant NSCLC. We validated that D-PROTAC could efficiently eliminate FAK protein via the ubiquitin-proteasome pathway in KRAS mutant NSCLC A427 cells, causing over 90% degradation at 800 nM. After comparing both in vitro and in vivo therapeutic efficacies, we demonstrated that D-PRTOAC outperformed Defactinib in inhibiting tumor growth. Specifically, D-PROTAC at 800 nM reduced cell viability, migration, and invasion by ∼80%. Furthermore, a ∼85% suppression of tumor growth was elicited by D-PROTAC when intratumorally administrated at 10 mg/kg in subcutaneous A427-bearing mice. These results thus demonstrate for the first time that PROTACs may serve as promising therapeutic agents for the intractable NSCLC harboring KRAS mutations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Data-Driven Affinely Adjustable Robust Volt/VAr Control

Recent years have seen the increasing proliferation of distributed energy resources with intermittent power outputs, posing new challenges to the voltage management in distribution networks. To this end, this paper proposes a data-driven affinely adjustable robust Volt/VAr control (AARVVC) scheme, which modulates the smart inverter’s reactive power in an affine function of its active power, based on the voltage sensitivities with respect to real/reactive power injections. To achieve a fast and accurate estimation of voltage sensitivities, we propose a data-driven method based on deep neural network (DNN), together with a rule-based bus-selection process using the bidirectional search method. Our method only uses the operating statuses of selected buses as inputs to DNN, thus significantly improving the training efficiency and reducing information redundancy. Finally, a distributed consensus-based solution, based on the alternating direction method of multipliers (ADMM), for the AARVVC is applied to decide the inverter’s reactive power adjustment rule with respect to its active power. Only limited information exchange is required between each local agent and the central agent to obtain the slope of the reactive power adjustment rule, and there is no need for the central agent to solve any (sub)optimization problems. Finally, numerical results on the modified IEEE-123 bus system validate the effectiveness and superiority of the proposed data-driven AARVVC method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Compatibilization Strategy and Mechanism for Co-stabilizing Commingled Plastics and Pyrolyzed Rubber in Asphalt

Hot mix asphalt mixture is considered the ideal approach to reuse waste plastics in high-value applications because of its very high amount of usage in highway construction. However, the differences in polarity and density between polymers and asphalt lead to polymer coalescence and therefore the poor storage stability of modified asphalt. These challenges are exalted when recycling commingled plastics. This study introduced an innovative compatibilization strategy and mechanism for co-stabilizing commingled plastics and pyrolyzed rubber in asphalt. Commingled plastics were first grafted with maleic anhydride for surface activation, followed by reactive kneading with pyrolyzed rubber and crosslinking agent to form an integrated thermoplastic elastomer (ITPE) for asphalt modification. The mechanical, thermal, and interfacial behaviors of the ITPE were evaluated through tensile testing, thermogravimetric analysis, and scanning electron microscopy. The storage stability and rheological properties of the modified binder blends were evaluated through the cigar tube test and dynamic shear rheometer testing. Results demonstrated a successful formation of imide bonds in the ITPE, which can improve the strength, ductility, and thermal stability of rubber–plastic composites. Appropriate utilization of crosslinking agents can improve both rutting and fatigue resistance of ITPE-modified asphalt with good storage stability because of the co-existence of rigid plastic and soft rubbery regimes and the formation of a crosslink network. Furthermore, excessive content of crosslinker led to severe phase separation and reduced storage stability of modified binder blends. Extra crosslinker tended to float in asphalt because of its low density and caused an excessive formation of the crosslink network in the top section of the asphalt.

asphalt binder modifiers↗
NASA NTRS1990

Effect of hindlimb suspension on cardiovascular responses to sympathomimetics and lower body negative pressure

To determine whether hindlimb suspension is associated with the development of cardiovascular deconditioning, male rats were studied before and after undergoing one of three treatment conditions for 9 days: (1) cage control (n = 15, CON), (2) horizontal suspension (n = 15, HOZ), and (3) head-down suspension (n = 18, HDS). Testing included lower body negative pressure administered during chloralose-urethan anesthesia and graded doses of sympathomimetic agents (norepinephrine, phenylephrine, and tyramine) administered to conscious unrestrained animals. Both HDS and HOZ were associated with a small decrease in the hypotensive response to lower body negative pressure. The HOZ group, but not the HDS group, exhibited augmented reflex tachycardia. Furthermore, both HDS and HOZ groups manifested reduced pressor responses to phenylephrine after treatment. These reductions were associated with significantly attenuated increases in mesenteric vascular resistance. However, baroreflex control of heart rate was not altered by the treatment conditions. Collectively, these results indicate that 9 days of HDS in rats does not elicit hemodynamic response patterns generally associated with cardiovascular deconditioning induced by hypogravic conditions.

Overton, J. Michael↗