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Results for “Process Efficiency”

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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Development of a high efficiency thin silicon solar cell

Significant improvements in open-circuit voltage and conversion efficiency, even on relatively high bulk resistivity silicon, were achieved by using a screen-printed aluminum paste back surface field. A 4 sq cm 50 micron m thick cell was fabricated from textured 10 omega-cm silicon which had an open-circuit voltage of 595 mV and AMO conversion efficiency at 25 C of 14.3%. The best 4 sq cm 50 micron thick cell (2 omega-cm silicon) produced had an open-circuit voltage of 607 mV and an AMO conversion efficiency of 15%. Processing modifications are described which resulted in better front contact integrity and reduced breakage. These modifications were utilized in the thin cell pilot line to fabricate 4 sq cm cells with an average AMO conversion efficiency at 25 C of better than 12.5% and with lot yields as great as 51% of starts; a production rate of 10,000 cells per month was demonstrated. A pilot line was operated which produced large area (25 cm) ultra-thin cells with an average AMO conversion efficiency at 25 deg of better than 11.5% and a lot yield as high as 17%.

Storti, G.↗
DOE OSTI2015

Expression of the Aspergillus niger InuA gene in Saccharomyces cerevisiae permits growth on the plant storage carbohydrate inulin at low enzymatic concentrations

The plant storage carbohydrate inulin represents an attractive biomass feedstock for fueling industrial scale bioconversion processes due to its low cost, ability for cultivation on arid and semi-arid lands, and amenability to consolidated bioprocessing applications. As a result, increasing efforts are emerging towards engineering industrially relevant microorganisms, such as yeast, to efficiently ferment inulin into high value fuels and chemicals. Although some strains of the industrially relevant yeast model Saccharomyces cerevisiae can naturally ferment inulin, the efficiency of this process is often supplemented through expression of exogenous inulinase enzymes that externally convert inulin into its more easily fermentable component monomeric sugars. Here, the effects of overexpressing the Aspergillus niger InuA inulinase enzyme in an S. cerevisiae strain incapable of endogenously fermenting inulin were evaluated to determine their impact on growth. Expression of the A. niger InuA inulinase enzyme permitted growth on otherwise intractable inulin substrates from both Dahlia tubers and Chicory root. Despite being in the top 10 secreted proteins, growth on inulin was not observed until 120 h post-inoculation and required the addition of 0.1 g fructose/l to initiate enzyme production in the absence of endogenous inulinase activity. High temperature/pressure pre-treatment of inulin prior to fermentation decreased this time to 24 h and removed the need for fructose addition. The pre-growth lag time on untreated inulin was attributed primarily to low enzymatic efficiency, with a maximum value of 0.13 0.02 U InuA/ml observed prior to the peak culture density of 2.65 0.03 g/l. Nevertheless, a minimum excreted enzymatic activity level of only 0.03 U InuA/ml was found to be required for sustained growth under laboratory conditions, suggesting that future metabolic engineering strategies can likely redirect carbon flow away from inulinase production and reorient it towards product production or cellular growth in order to optimize strain development.

09 BIOMASS FUELS↗
DOE OSTI2022

Efficient light harvesting and photon sensing via engineered cooperative effects

Abstract Efficient devices for light harvesting and photon sensing are fundamental building blocks of basic energy science and many essential technologies. Recent efforts have turned to biomimicry to design the next generation of light-capturing devices, partially fueled by an appreciation of the fantastic efficiency of the initial stages of natural photosynthetic systems at capturing photons. In such systems extended excitonic states are thought to play a fundamental functional role, inducing cooperative coherent effects, such as superabsorption of light and supertransfer of photoexcitations. Inspired by this observation, we design an artificial light-harvesting and photodetection device that maximally harnesses cooperative effects to enhance efficiency. The design relies on separating absorption and transfer processes (energetically and spatially) in order to overcome the fundamental obstacle to exploiting cooperative effects to enhance light capture: the enhanced emission processes that accompany superabsorption. This engineered separation of processes greatly improves the efficiency and the scalability of the system.

42 ENGINEERING↗
DOE OSTI2018

Development of Intelligent Monitoring System (IMS) Modules for the Aquistore CO 2 Storage Project

The monitoring data generated at a CO 2 storage site can quickly result in large amounts of data, often requiring significant labor- and time-intensive efforts to process and analyze before being able to make operational decisions. Implementing an intelligent monitoring system (IMS) can reduce the associated data-processing and analysis costs, which can thereby improve the efficiency of the monitoring process and enable real-time operational decision-making. The Energy & Environmental Research Center (EERC) has completed a 3-year project focused on developing an IMS comprising new workflows, algorithms, and a user interface for the automation and integration of geologic carbon dioxide (CO 2 ) storage site-monitoring and simulation data. The design for the IMS was based on using injection and monitoring data acquired from Aquistore, an operating CO 2 storage project. Managed by the Petroleum Technology Research Centre, the Aquistore Project is injecting CO 2 captured from SaskPower’s coal-fired Boundary Dam Power Station into a deep saline formation for geologic storage. Using data from the Aquistore Project provided a real-world basis to develop an IMS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A Perspective on Solar-Driven Electrochemical Routes for Sustainable Methanol Production

The transition towards sustainable and renewable energy sources is imperative in mitigating the environmental impacts of escalating global energy consumption. Methanol, with its versatile applications and potential as a clean energy carrier, a precursor chemical, and a valuable commodity, emerges as a promising solution within the realm of renewable energy technologies. This work explores the integration of electrochemistry with solar power to drive efficient methanol production processes, focusing on electrochemical reduction (ECR) of CO 2 and methane oxidation reaction (MOR) as pathways for methanol synthesis. Through detailed analysis and calculations, we evaluate the thermodynamic limits and realistic solar-to-fuel (STF) efficiencies of ECR and MOR. Our investigation encompasses the characterization of multijunction light absorbers, determination of thermoneutral potentials, and assessment of STF efficiencies under varying conditions. We identify the challenges and opportunities inherent in both ECR and MOR pathways, shedding light on catalyst stability, reaction kinetics, and system optimization, thereby providing insights into the prospects and challenges of solar-driven methanol synthesis, offering a pathway towards a cleaner and more sustainable energy future.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS1988

Thermoplastic coated carbon fibers for textile preforms

A continuous process for producing prepreg from carbon fiber and thermoplastic matrix is described. After the tow has been spread using a pneumatic device, the process utilizes a fluidized bed to apply thermoplastic powder to the bundle. Finally, direct electrical heating of the coated fiber tow melts the polymer on the individual fibers, creating a uniform and extremely flexible prepreg. The efficiency of the process was evaluated during initial trials in which a thermoplastic polyimide, LaRC-TPI, was applied to T-300, 3K (3000 filament) carbon fiber tow. The physical properties of unidirectional composite specimens fabricated from this prepreg were measured, and the matrix uniformity and void content of the samples was determined. The results of these evaluations are detailed and discussed.

Allen, L. E.↗
NASA NTRS2012

Nanotube Production Devices Expand Research Capabilities

In order for the Hubble Space Telescope to take incredible, never-seen-before shots of celestial bodies and then send them back to Earth, the spacecraft needs power. While in orbit, Hubble cannot plug into an electrical outlet or stop at a store for some batteries. One of the ways NASA supplies power aboard a spacecraft is by harnessing energy from the most powerful entity in the solar system: the Sun. Since the 1960s, photovoltaic technology, or technology that converts sunlight into electricity, has been instrumental in the exploration of space. To build upon existing photovoltaic technology, NASA s Glenn Research Center has worked on a variety of innovative designs and materials to incorporate into photovoltaic cells, the building blocks of solar power systems. One of these materials is the carbon nanotube - a tiny structure about 50,000 times finer than the average human hair, with notably high electrical and thermal conductivity and an extreme amount of mechanical strength. Such properties give carbon nanotubes great potential to enhance the reliability of power generation and storage devices in space and on Earth. Dennis J. Flood, the branch chief of the photovoltaic division at Glenn in the 1990s, was looking into using carbon nanotubes to improve the efficiency of solar cells when he ran into a major roadblock - high-quality carbon nanotubes were not readily available. To address this problem, one of the chemists in Flood s group came up with a process and system for growing them. A senior chemist at Glenn, Aloysius F. Hepp, devised an injection chemical vapor deposition process using a specific organometallic catalyst in a two-zone furnace. Hepp's group found the unique process produced high-quality carbon nanotubes with less than 5 percent metal impurity. In addition, the process was more efficient than existing techniques, as it eliminated pre-patterning of the substrate used for growing the nanotubes, a timely and cost-prohibitive step.

Source record↗
DOE OSTI2023

Strengthening Cybersecurity for Industrial Control Systems: Innovations in Protecting PLC-Based Infrastructure

In this paper, we propose two new approaches aimed at enhancing the security of industrial control systems (ICS) that utilize programmable logic controllers (PLCs) for the control of critical processes. The first approach involves the addition of a unique digital watermark to the PWM control that adjusts the motor speed to control the critical process. This enables efficient detection and identification of any unauthorized modifications to the sensor signals responsible for controlling the plant. The second approach focuses on monitoring the input current (i.e power) drawn by the PLC during the execution of critical process control tasks. Malicious intrusions to change the PLC parameters and/or unauthorized firmware updates can be rapidly detected. Both approaches demonstrate a substantial improvement in the security of ICS, effectively safeguarding against potential cyber-attacks. Experimental results from a laboratory scale water tank level controlled via PLC showcases rapid intrusion detection capabilities.

Huang, Peng-Hao↗
DOE OSTI2025

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗
DOE OSTI2018

A quantitative and spatially resolved analysis of the performance-bottleneck in high efficiency, planar hybrid perovskite solar cells

Hybrid perovskites represent a potential paradigm shift for the creation of low-cost solar cells. Current power conversion efficiencies (PCEs) exceed 22%. However, despite this, record PCEs are still far from their theoretical Shockley–Queisser limit of 31%. To increase these PCE values, there is a pressing need to understand, quantify and microscopically model charge recombination processes in full working devices. Here, we present a complete microscopic account of charge recombination processes in high efficiency (18–19% PCE) hybrid perovskite (mixed cation and methylammonium lead iodide) solar cells. We employ diffraction-limited optical measurements along with relevant kinetic modeling to establish, for the first time, local photoluminescence quantum yields, trap densities, trapping efficiencies, charge extraction efficiencies, quasi-Fermi-level splitting, and effective PCE estimates. Correlations between these spatially resolved parameters, in turn, allow us to conclude that intrinsic electron traps in the perovskite active layers limit the performance of these state-of-the-art hybrid perovskite solar cells.

14 SOLAR ENERGY↗
DOE OSTI2017

The carbon nanotube formation parameter space: data mining and mechanistic understanding for efficient resource use

Carbon nanotube (CNT) synthesis via catalytic chemical vapor deposition is relatively energy consumptive and among the least efficient reactions with respect to carbon conversion efficiency. Interestingly, these processes can be fed using a diverse set of hydrocarbon starting materials, including methane, ethylene, and acetylene, over a wide range of operating temperatures and carbon-to-hydrogen feedstock ratios. Mapping the parameter space for successful CNT growth through data extraction from published literature illuminated the most energy- and material- efficient synthetic pathways in practice to date and provided insights on thermodynamic limitation of CNT growth (i.e., the fundamental mechanisms of CNT formation). Further experimental investigations confirmed that emergent trends in the literature were the result of physicochemical constraints on the process rather than behavioral inertia in the community. The initiation temperatures for CNT growth from acetylene, ethylene, and methane feedstocks via direct experimentation were 550, 700, and 950 °C, respectively, consistent with the trend in literature-extracted mean optima (642 ± 128, 739 ± 82, and 858 ± 125 °C, respectively). These relative temperatures are consistent with a universal CNT growth mechanism, wherein all carbon feedstocks are converted to alkyne-containing species that serve as direct precursors for CNT growth. Mitigating this step with rational carbon precursor delivery, rather than relying on heat to generate the most reactive precursors in situ, could largely reduce the environmental burdens in CNT manufacturing. Indeed, manipulating the starting gas-phase composition and minimizing the thermal treatment through the use of C 2 H 2 increased carbon conversion yield by a factor of more than 10 compared to C 2 H 4 , and, consequently, should minimize hazardous volatile organic compound and polycyclic aromatic hydrocarbon emissions. Finally, the methodology utilized in this study is transferrable to guide the green synthesis of other materials and should be automated in the future for high-throughput screening of the vast process chemistry literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Interfacial Chemistry Involved in Selective Separation of NMC/LMO and LCO/LMO Binary Cathode Materials by Froth Flotation Using Oleic Acid

The variability in cathode compositions within recycled lithium-ion battery (LIB) feedstocks poses a significant challenge to efficient downstream refining processes. This study demonstrates the feasibility of using froth flotation with oleic acid as a collector to selectively separate lithium nickel-manganese-cobalt oxide (NMC) and lithium cobalt oxide (LCO) from lithium manganese oxide (LMO) materials. Laboratory-scale flotation tests achieved an 80% separation efficiency in a single stage, producing a froth product with >90% purity of NMC/LCO at approximately 90% yield. Concurrently, the LMO materials were enriched in the sink product with ∼90% purity and ∼90% yield. This approach was further validated using recycled cathode materials, confirming its applicability to realistic feedstocks. The underlying mechanism governing the selective separation of NMC/LCO from LMO was investigated using ζ-potential measurements, contact angle measurements, bubble-particle attachment experiments, and X-ray photoelectron spectroscopy (XPS) analysis. Both contact angle and bubble-particle attachment results confirmed that oleic acid adsorption rendered NMC and LCO surfaces hydrophobic, thereby enhancing flotation recovery. At pH 5, oleic acid adsorbed preferentially onto NMC and LCO surfaces via electrostatic interactions, while exhibiting minimal adsorption on LMO surfaces. However, separation efficiency deteriorated at higher pH, which was attributed to the co-flotation of LMO materials caused by oleate chemisorption on MnOH + species. This work establishes froth flotation as a viable cathode/cathode separation strategy, providing a low-cost, scalable pathway to preconcentrate and enrich nickel-rich and cobalt-rich cathode active materials from incompatible cathode chemistries for direct recycling or hydrometallurgical processing. Furthermore, this study reveals, for the first time, the mechanism of oleate adsorption on the surface of different cathode materials.

PH↗
DOE OSTI2017

The Catalytic Effect of Electronegative Additives on Removal of Perchloroethylene Vapor from Air by Pulsed Corona Discharge

It is established that electronegative additives (CCl{sub 4}, freon-113) produce a catalytic effect on the conversion of volatile organic compounds (VOCs) under the action of atmospheric-pressure nonequilibrium plasma generated in pulsed corona discharge. At concentrations below 0.1%, these additives significantly decrease the discharge current, but the energy efficiency of the process of VOC removal from air increases. The catalytic effect of electronegative additives on the VOC conversion in air and nitrogen is quantitatively demonstrated in the case of perchloroethylene C{sub 2}Cl{sub 4} (PCE) vapor removal. The addition of 0.085% CCl{sub 4} to air reduces the energy consumption for PCE removal at initial concentration of 0.09% by half (from 12 to 6 eV per molecule) at a 63% degree of cleaning. Mechanisms explaining the active inf luence of electronegative additives on the discharge current and the process of impurity removal are suggested.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

ON THE RADIO DETECTION OF MULTIPLE-EXOMOON SYSTEMS DUE TO PLASMA TORUS SHARING

The idea of single exomoon detection due to the radio emissions caused by its interaction with the host exoplanet is extended to multiple-exomoon systems. The characteristic radio emissions are made possible in part by plasma from the exomoon’s own ionosphere. In this work, it is demonstrated that neighboring exomoons and the exoplanetary magnetosphere could also provide enough plasma to generate a detectable signal. In particular, the plasma-torus-sharing phenomenon is found to be particularly well suited to facilitate the radio detection of plasma-deficient exomoons. The efficiency of this process is evaluated, and the predicted power and frequency of the resulting radio signals are presented.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

Sensor development in the Shuttle era

The use of the Space Shuttle in the development of earth observation sensors is examined. Two sensor classes are selected for case histories: infrared temperature sounders and microwave radiometers. The most significant finding in each of the developmental studies of these two sensor classes is considered to be the feasibility and value of using the Shuttle/Spacelab as a test vehicle for the operation in space of a versatile multimode experimental sensor. The Shuttle Electrically Scanned Microwave Radiometer and the Shuttle Infrared Interferometer are found to be the most effective instruments in this context. The Shuttle/Spacelab Sortie mission characteristics provide opportunities for new approaches to the development of sensors, using the Shuttle as a test vehicle to improve the efficiency of the process with respect to time, cost, and/or quality of the final product. As for crew functions, the short-term Spacelab mission requires some near real-time evaluation of data quality and sensor function in order to insure efficient data collection.

Gerding, R. B.↗
NASA NTRS1989

PRIME: A bottom-up approach to probabilistic rule development

PRIME is a system to be used by an intelligent machine to allow it to operate in an abstract but uncertain (or stochastic) environment. It maintains a model of the effects of the machine's actions in the form of a rule base, which is induced from experience. This bottom-up approach to rule development allows the model to adapt to changes in the environment. Each rule consists of a condition under which the rule is active, an action, the effect of the action on the environment, and an estimate of the probability of this effect occurring. The effect probabilities are used to model the uncertainty in the environment, permitting multiple possible effects for a single action under a particular set of conditions. The objective of the intelligent machine is to satisfy user-specified goals with maximum probability of success. PRIME fulfills this requirement in two ways: it continuously updates the rule base with the most recent information, to ensure the validity of the model; and it generates plans which have the maximum probability of achieving the goals, based on the probability estimates in the rule base. PRIME is composed of three main processes: exploration, generalization, and planning. In exploration, the machine executes various randomly chosen actions, observes the effects on the environment, and updates the rule base accordingly. This process is used to develop the rule base in simulation, as well as to supplement the current knowledge during normal operation. Generalization is the procedure used to induce general rules from experience, which is encoded in the form of specific rules. These general rules extend the machine's knowledge to situations which have not been encountered yet, thereby increasing the capability of the machine to plan effectively. Planning is the process of constructing an optimal sequence of actions to satisfy a goal, using the rule base to predict the effects of these actions and to determine the probability of success of the plan. The rule representation and many other data structures were specifically chosen to maximize the efficiency of these processes. A simulated environment was designed to test the performance of PRIME. The results of experimentation were largely negative. The main problem was that the domain coverage of the rules was inadequate for the number of rules stored in the rule base, due to redundancies in general rules and numerous rules covering ineffective actions. It was determined that a more efficient generalization, and some form of goal-directed exploration, are necessary in order to solve most of the current deficiencies in PRIME.

Miller, Scott A.↗
NASA NTRS1972

Computer enhancement through interpretive techniques

The improvement in the usage of the digital computer through the use of the technique of interpretation rather than the compilation of higher ordered languages was investigated by studying the efficiency of coding and execution of programs written in FORTRAN, ALGOL, PL/I and COBOL. FORTRAN was selected as the high level language for examining programs which were compiled, and A Programming Language (APL) was chosen for the interpretive language. It is concluded that APL is competitive, not because it and the algorithms being executed are well written, but rather because the batch processing is less efficient than has been admitted. There is not a broad base of experience founded on trying different implementation strategies which have been targeted at open competition with traditional processing methods.

Foster, G.↗