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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Low-temperature fabrication of efficient wide-bandgap organolead trihalide perovskite solar cells

A mixed halide perovskite solar cell with a 1.72 eV bandgap is developed by incorporating Br into perovskite through a low-temperature solution process. A high efficiency of 13.1% is achieved by carefully tuning the thickness, morphology, and surface passivation of the perovskite layers. Furthermore, the fabrication techniques and conditions are compatible with future perovskite/Si tandem cell studies.

14 SOLAR ENERGY↗
DOE OSTI2024

Determination of Vibrational Motions Driving Photoinduced Electron Transfer Reactions in Molecular Crystals and Organic Thin Films

The objective of this research is to develop an understanding of how nuclear motions can be used to drive and control photo-induced charge transfer and singlet fission reactions in molecular crystals and thin films. By following the structural evolution of reacting molecules and nanostructures on the timescale of their nuclear motion, we will determine what interplay of nuclear coordinates is most efficient in driving electron transfers, a necessary first step in most photovoltaic and photocatalytic processes. We will identify which nuclear coordinates effectively promote desirable electron transfer processes, or ineffectively dissipate photon energy into unwanted thermal energy, thus guiding the design and implementation of molecular systems tailored for high efficiency processes. Specifically, we aim to identify which nuclear coordinates are responsible for driving electron transfer and singlet fission reactions at different points along the reaction coordinate, particularly in regimes which deviate from Marcus theory predictions. We will do so by investigating systems with electron transfer and singlet fission occurring from non-thermalized states due to strong donor-acceptor electronic coupling. First, we will prove that specific vibrational modes are responsible for charge transfer processes in molecular crystals. Secondly, we will investigate how vibrational coherences and specific nuclear motions can be used to drive high yield singlet fission processes. Finally, we will determine how complex film morphology affects long-range charge transport, a key limiting factor in our ability to make gains in efficiency.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

Developing Guidelines for Assessing Visual Analytics Environments

Visual analytic systems can be evaluated from a user perspective with quantitative metrics (i.e., time to complete the analysis or the accuracy of the solution found). However, qualitative measures are also useful in a user assessment. These include such measures as the utility of the interactive visualizations in the analysis process and the user's assessment of the efficiency of the analytic process. Quantitative measures can be found if data sets with embedded ground truth are used for analysis. Qualitative measures are more elusive. In this paper we report on an experiment with professional analysts who ranked five of submissions to the VAST 2009 Challenge and provided the rationale for their rankings. Their comments were used in conjunction with a meta-analysis of the 2009 VAST Challenge reviews to produce a set of guidelines for visual analytic systems. As visual analytic software is expected to eventually help in all aspects of analysis, we expect to see future systems provide more help with generating the final report. Hence, researchers also need to have an understanding of what makes a good analytic product. Therefore we asked the analysts to rank the situational assessments of four grand challenge entries and to provide comments on those assessments. We used these comments to produce guidelines for researchers to use in evaluating their analytic reports.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Nanowire Array Structures for Photocatalytic Energy Conversion and Utilization: A Review of Design Concepts, Assembly and Integration, and Function Enabling

The increasing human demand for clean and renewable energy and a cleaner environment has stimulated various materials related research and development for efficient solar energy conversion and utilization, photocatalytic environmental remediation, and photoassisted selective conversion of organic compounds. Among the various candidate solutions to improving the efficiency of these processes, semiconductor nanowire (NW) and nanorod (NR) array structures have been offering a unique tool box combining desirable characteristics in structure, function, and applicability. Efficient photocatalytic energy conversion requires excellent light absorption, readily charge separation, transport, and collection, as well as fast kinetics of interfacial reactions and mass transport of reactants. The long axis of the NW enables adequate light absorption, while the radical axis provides short electron–hole separation distance. Additionally, the NW arrays have relatively high surface area to facilitate interfacial kinetics while their open pore structure allows good mass transport properties. This study reviews the current status of research on NW and NR array structures of some most popular semiconducting materials for photocatalytic energy conversion and utilization including photocatalytic water splitting and CO 2 reduction/fixation, dye/quantum dot sensitized solar cells, and other photoassisted reactive applications such as pollutant degradation, selective conversion of organic compounds, and biological disinfection.

Hoang, Son↗
DOE OSTI2023

Gradient process parameter optimization in additive friction stir deposition of aluminum alloys

As one of the most novel additive manufacturing methods, currently selection and optimization of processing parameters in additive friction stir deposition (AFSD) have mainly relied on experiments and subsequent characterization of microstructural and mechanical properties. Such approaches are both time- and resource-consuming. Therefore, an ultrasound elastography enhanced gradient process parameter optimization method was applied in the present work to obtain a window of optimized processing parameters for AFSD processing of aluminum alloy by varying both rotational and linear deposition speeds. Further, the quality of AFSD processed layer was investigated for physical nature of surface, dynamic elastic modulus, and microstructural aspects in cross-sections of the deposited layer. The efficiency in exploring process parameters was significantly enhanced by implementing a high-throughput screening experimental design based on application of gradient process parameters and continuous ultrasound elastographs. In addition, the applied ultrasonic elastography technique assisted in evaluating the homogeneity in microstructure and mechanical properties of AFSD sample over the entire gradients of the process parameters. The techniques adopted in current work can be further extended to identify suitable parameters for AFSD fabrication of components with desired mechanical properties such as hardness, fatigue, etc.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Editorial: Biomass Modification, Characterization, and Process Monitoring Analytics to Support Biofuel and Biomaterial Production

This Frontiers Research Topic journeys through various challenges facing researchers seeking to develop fuels and products derived from lignocellulosic biomass. These challenges include: the rapid quantification of plant cell wall chemistry, enabling yields of potential monomeric sugars to be assessed, identification of plants possessing ideal trait that can be brought to the forefront of research efforts; once the native plant chemistry is known, how can yields be improved by chemically or genetically altering plant cell walls to reduce recalcitrance; does genetic modification of plants to increase accessibility to saccharification enzymes hinder the plant’s growth and/or function; are the innovative methods identified by researchers cost-effective and scalable to a commercial level? These topics are a sampling of the obstacles researchers combat when nominating a specific plant for downstream applications or implementing new deconstruction, genetic, or measurement strategies. How well can different plants can be broken down into useful, downstream precursor molecules? Efforts to develop a lucid picture of the chemical composition of abundant, diverse plants being explored as potential starting feedstocks has resulted in the evolution of high-throughput techniques that permit many more samples to be screened in much shorter periods of time. Advances in thermochemical and spectroscopic techniques have enabled the screening of thousands of plants for different phenotypes, such as cell-wall composition and monomeric sugar release. Some instrumental methods have been coupled with multivariate analysis, providing elegant chemometric predictive models enabling the accelerated identification of potential feedstocks. Rapid instrumental techniques have been developed for real-time monitoring of diverse processes, such as the efficacy of specific pretreatment strategies, or downstream products, such as biofuels and biomaterials. Real-time process monitoring techniques are needed for all stages of the feedstocks-to-biofuels conversion process to maximize efficiency and lower costs by monitoring and optimizing performance. These approaches allow researchers to adjust experimental conditions during, rather than at the conclusion, of processes, thereby decreasing overhead expenses.

09 BIOMASS FUELS↗
DOE OSTI2023

Metal hydride heat exchanger and method of use

A heat exchanger incorporates a metal hydride heat exchanger and mitigates the fluid mixing process, and thus greatly improves the heat transfer efficiency and heat recovery processes. The metal hydride heat exchanger has a container for the metal hydride that has a large aspect ratio. A plurality of high aspect container for the metal hydride may be coupled with a manifold.

Bahar, Bamdad↗
DOE OSTI2020

DEM and MELT: A Modular and Compact In-Can Melting Technology Dedicated to D and D and Remediation Waste - 20033

The DEM and MELT In-Can vitrification process is designed to process intermediate and high level waste coming for D and D and remediation operations. It is developed to treat liquid and solid waste, to produce a small amount of secondary waste and to minimize investment and operating costs. This In-Can vitrification process is also developed with a compact and modular design and can be adapted regarding nuclear operators' needs and requirements. Furthermore, this robust and simple process is flexible enough to accommodate most uncertainties on waste composition. The DEM and MELT process is developed through the French consortium coordinated by CEA which gathers Orano, ECM technologies and Andra. In the frame of this project, Orano has designed a compact and modular layout of the process allowing an efficient in situ implementation, close to the waste to be treated. This paper presents the compact and modular design of the DEM and MELT process and the way it can be used for a short duration, as a decommissioning tool aimed to be dismantled just after the treatment operation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

X-ray multi-probe data acquisition: A novel technique for laser pump x-ray transient absorption spectroscopy

We report the development and implementation of a novel data acquisition (DAQ) technique for synchrotron-based laser pump X-ray Transient Absorption (XTA) spectroscopy, called X-ray Multi-Probe DAQ (XMP DAQ). This technique utilizes high performance analog to digital converters and home-built software to efficiently measure and process the XTA signal from all x-ray pulses between laser excitations. XMP DAQ generates a set of time resolved x-ray absorption spectra at thousands of different pump–probe time delays simultaneously. Two distinct XMP DAQ schemes are deployed to accommodate different synchrotron storage ring filling patterns. Current Integration (CI) DAQ is a quasi-analog technique that implements a fitting procedure to extract the time resolved absorption intensity from the averaged fluorescence detector response. The fitting procedure eliminates issues associated with small drifts in the voltage baseline and greatly enhances the accuracy of the technique. Photon Counting (PC) DAQ is a binary technique that uses a time resolved histogram to calculate the XTA spectrum. While PC DAQ is suited to measure XTA data with closely spaced x-ray pulses (~10 ns) and a low count rate (<1 detected photon/pulse), CI DAQ works best for widely spaced pulses (tens of ns or greater) with a high count rate (>1 detected photon/pulse). XMP DAQ produces a two-dimensional XTA dataset, enabling efficient quantitative analysis of photophysical and photochemical processes from the sub-nanosecond timescale to 100 μs and longer.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

Differential Power Processing for DC Systems

This paper introduces an approach to dc power delivery that reduces power loss by minimizing redundant energy conversion. Existing power distribution techniques tend to increase the number of cascaded conversion stages, which limits overall efficiency. Differential power processing enables independent load regulation, while processing only a small portion of the total load power. Bulk power conversion occurs once. Load voltage domains are connected in series, and differential converters act as controllable current sources to regulate intermediate nodes. This enables independent, low supply voltages, which can reduce system energy consumption, especially in digital circuits and solid-state lighting. Since differential voltage regulators process a fraction of the load power, decreased size, cost, and conversion losses are attainable. Under balanced load conditions, secondary differential converters do not process any power. This paper analyzes several differential power delivery architectures that can be applied to homogenous and heterogeneous loads at various levels: chip, board, blade, etc. A variety of operating conditions for a test system with four series voltage domains are examined in simulation and verified with experimental hardware. Results in a reference application show a 7-8% decrease in input power and 6-7 percentage points increase in overall conversion efficiency as compared to a conventional cascaded approach.

Shenoy, PS↗
DOE OSTI2024

Approach for energy efficient building design during early phase of design process

Energy consumption in the building sector is about 40% of total energy consumed globally and is trending upwards, along with its contribution to greenhouse gas (GHG) emissions. Given the adverse impacts of GHG emissions, it is crucial to integrate energy efficiency into building designs. The most significant opportunities for enhancing energy performance are present during the initial phases of building design, when there is less impact of other design constraints. Various tools exist for simulating different design options and providing feedback in terms of energy consumption and comfort parameters. These simulation outputs must then be analyzed to derive design solutions. This paper presents an innovative approach that utilizes user input parameters, processes them through cloud computing, and outputs easily understandable strategies for energy-efficient building design. The methodology employs Asynchronous Distributed Task Queues (DTQ) - a more scalable and reliable alternative to conventional speedup techniques-for conducting parametric energy simulations in the cloud. The goal of this approach is to assist design teams in identifying, visualizing, and prioritizing energy-saving design strategies from a range of possible solutions for each project. Furthermore, a tool ‘eDOT’ has been developed utilizing the discussed methodology. Unlike existing tools, eDOT leverages artificial intelligence to dynamically generate and provide design strategies during the early phases of design process. By simplifying the simulation process, eDOT enables design teams to make informed, data-driven decisions without needing to interpret complex simulation outputs. A case study simulated for two locations is provided in this paper to demonstrate the effectiveness of eDOT, further underscoring its practical impact on energy-efficient building design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Design of Reduction Process of SnO 2 by CH 4 for Efficient Sn Recovery

We design a novel method for the CH 4 reduction of SnO 2 for the efficient recovery of Sn from SnO 2 through a study combining theory and experiment. The atomic-level process of CH 4 -SnO 2 interaction and temperature-dependent reduction behavior of SnO 2 were studied with a combination of a multi-scale computational method of thermodynamic simulations and density functional theory (DFT) calculations. We found that CH 4 was a highly efficient and a versatile reducing agent, as the total reducing power of CH 4 originates from the carbon and hydrogen of CH 4 , which sequentially reduce SnO 2 . Moreover, as a result of the CH 4 reduction of SnO 2 , a mixture of CO and H 2 was produced as a gas-phase product (syngas). The relative molar ratio of the produced gas-phase product was controllable by the reduction temperature and the amount of supplied CH 4 . The laboratory-scale experimental study confirmed that CH 4 actively reduces SnO 2 , producing 99.34% high-purity Sn and H 2 and CO. Our results present a novel method for an efficient, green, and economical recycling strategy for Sn with economic value added that is held by the co-produced clean energy source (syngas).

Science & Technology - Other Topics↗
DOE OSTI2024

A Dataset of CFD Simulated Industrial Furnace Images for Conditional Automatic Generation with GANs

The steel industry is constantly looking for ways to automate processes and improve efficiency. A standard practice in industry is to simulate how complex systems will operate before they are actually used. Some complex systems, including steel industry processes such as blast furnaces, require complex physics-based simulations utilizing computational fluid dynamics (CFD). These CFD physics-based simulations are very accurate but can take significant time and computational resources to process, resulting in challenges for the implementation of the models in real-world operational environments. In recent years, deep learning (DL) has been considered as a substitute for these CFD models. DL models can be trained on validated CFD simulation data and then used for industrial process inference. Previous DL-based solutions have made great contributions for industrial automation but are currently missing the additional visualization component that CFD simulations also provide. In this paper, we propose a dataset for simple DL generative approaches that can help to address this issue. The dataset and methodology under development to approach this prediction are discussed in this work.

Calix, Ricardo↗
DOE OSTI2018

Influence of Near-Surface Severe Plastic Deformation of Mild Steel on the Inhibition Performance of Sodium Molybdate and 1H-Benzotriazole in Artificial Sea Water

The effects of near-surface severe plastic deformation (NS-SPD) on the inhibition performance of sodium molybdate (SM) and 1H-benzotriazole (BTA) for mild steel were investigated using weight loss, polarization and electrochemical impedance spectroscopy measurements. The crystal grain size of NS-SPD-processed surface was analyzed by x-ray diffractometry and field emission scanning electron microscopy. A deformed layer with thickness of 20 ± 5 µm was produced on mild steel surface after NS-SPD process due to accumulated strains. The NS-SPD process caused more effective adsorption of corrosion inhibitors due to the fabrication of a surface with a high density of preferential adsorption sites. However, the stability of protective layer was predominantly influenced by the effect of NS-SPD process on inhibition efficiency. The fairly good persistence of protective layer formed on the surface by SM-containing solution and also positive effect of NS-SPD process on adsorption of molybdate ions caused higher inhibition performance for sodium molybdate. However, NS-SPD process encouraged deterioration of protective layer formed on steel surface in the presence of BTA inhibitor. It was ascribed to partial coverage of surface, low stability of adsorbed layer and thus more adsorption of aggressive ions on unprotected area which was uncovered during immersion time.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synthesizing and formulating metal oxide nanoparticle inks for perovskite solar cells

The perovskite solar cell has commercial potential due to the low-cost of materials and manufacturing processes with cell efficiencies on par with traditional technologies. Nanomaterials have many properties that make them attractive for the perovskite devices, including low-cost inks, low temperature processing, stable material properties and good charge transport. In this feature article, the use of nanomaterials in the hole transport and electron transport layers are reviewed. Specifically, SnO 2 and NiO x are the leading materials with the most promise for translation to large scale applications. Here, the review includes a discussion of the synthesis, formulation, and processing of these nanoparticles and provides insights for their further deployment towards commercially viable perovskite solar cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Scoping Study of Machine Learning Techniques for Visualization and Analysis of Multi-source Data in Nuclear Safeguards

In implementation of nuclear safeguards, many different techniques are being used to monitor operation of nuclear facilities and safeguard nuclear materials, ranging from radiation detectors, flow monitors, video surveillance, satellite imagers, digital seals to open source search and reports of onsite inspections/verifications. Each technique measures one or more unique properties related to nuclear materials or operation processes. Because these data sets have no or loose correlations, it could be beneficial to analyze the data sets together to improve the effectiveness and efficiency of safeguards processes. Advanced visualization techniques and machine-learning based multi-modality analysis could be effective tools in such integrated analysis. In this project, we will conduct a survey of existing visualization and analysis techniques for multi-source data and assess their potential values in nuclear safeguards.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Low-cost sensors and analytics for a digital factory

ORNL Manufacturing Demonstration Facility and Perisense worked on a low-cost solution for machining process monitoring to enable a digital factory. Enabling machine connectivity for digital factors is expensive for many small to medium manufacturers. The hypothesis for the research project is that a lowcost sensor suite, which can be retrofitted to a legacy machine tool or a new machine tool, can effectively provide real-time, in-situ sensing for manufacturing processes, which can enable improvements in process performance and efficiency. The Perisense sensor node was installed on the Haas TM1 machine with a current sensor and an accelerometer. Cutting tests were performed at different process parameters and sensor data was recorded. Results show a correlation of the current sensor to the spindle load. The accelerometer, mounted on the machine base, showed a correlation to the spindle speed as well as the spindle load. The sensor data can be used to monitor the machining process and provide insights on the machine spindle load utilization.

42 ENGINEERING↗
DOE OSTI2018

Relationship between lignocellulosic biomass dissolution and physicochemical properties of ionic liquids composed of 3-methylimidazolium cations and carboxylate anions

The ionic liquid (IL) 1-ethyl-3-methylimidazolium acetate ([EMIM]Acetate) has been widely used for biomass processing, i.e., to pretreat, activate, or fractionate lignocellulosic biomass to produce soluble sugars and lignin. However, this IL does not achieve high biomass solubility, therefore minimizing the efficiency of biomass processing. In this paper, [EMIM]Acetate and three other ILs composed of different 3-methylimidazolium cations and carboxylate anions ([EMIM]Formate, 1-allyl-3-methylimidazolium ([AMIM]) formate, and [AMIM]Acetate) were analyzed to relate their physicochemical properties to their biomass solubility performance. While all four ILs are able to dissolve hybrid poplar under fairly mild process conditions (80 °C and 100 RPM stirring), [AMIM]Formate and [AMIM]Acetate have particularly increased biomass solubility of 40 and 32%, respectively, relative to [EMIM]Acetate. Molecular dynamics simulations suggest that strong interactions between IL and specific plant biopolymers may contribute to this enhanced solubilization, as the calculated second virial coefficients between ILs and hemicellullose are most favorable for [AMIM]Formate, matching the trend of the experimental solubility measurements. The simulations also reveal that the interactions between the ILs and hemicellulose are an important factor in determining the overall biomass solubility, whereas lignin–IL interactions were not found to vary significantly, consistent with literature. Finally, the combined experimental and simulation studies identify [AMIM]Formate as an efficient biomass solvent and explain its efficacy, suggesting a new approach to rationally select ionic liquid solvents for lignocellulosic deconstruction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗