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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Dynamic model-based sensor network design algorithm for system efficiency maximization

Here, a dynamic model-based sensor network design (DMSND) algorithm has been developed for maximizing system efficiency for an estimator-based control system. The algorithm synthesizes the optimal sensor network in the face of disturbances or set point changes. Computational expense of the large-scale combinatorial optimization problem is significantly reduced by parallel computing and by using combination of three novel strategies: multi-rate sampling frequency, model order reduction, and use of an incumbent solution that enables early termination of evaluation of infeasible sensor sets. The developed algorithm is applied to an acid gas removal unit as part of an integrated gasification combined cycle power plant with carbon capture. Even though there are more than thousand process states and more than hundred candidate sensor locations, the optimal sensor network design problem for maximizing process efficiency could be solved within couple of hours for a given budget.

47 OTHER INSTRUMENTATION↗
NASA NTRS2014

Novel Catalysts and Processing Technologies for Production of Aerospace Fuels from Non-Petroleum Raw Materials

Transportation fuels production (including aerospace propellants) from non-traditional sources (gases, waste materials, and biomass) has been an active area of research and development for decades. Reducing terrestrial waste streams simultaneous with energy conversion, plentiful biomass, new low-cost methane sources, and/or extra-terrestrial resource harvesting and utilization present significant technological and business opportunities being realized by a new generation of visionary entrepreneurs. We examine several new approaches to catalyst fabrication and new processing technologies to enable utilization of these nontraditional raw materials. Two basic processing architectures are considered: a single-stage pyrolysis approach that seeks to basically re-cycle hydrocarbons with minimal net chemistry or a two-step paradigm that involves production of supply or synthesis gas (mainly carbon oxides and H2) followed by production of fuel(s) via Sabatier or methanation reactions and/or Fischer-Tröpsch synthesis. Optimizing the fraction of product stream relevant to targeted aerospace (and other transportation) fuels via modeling, catalyst fabrication and novel reactor design are described. Energy utilization is a concern for production of fuels for either terrestrial or space operations; renewable sources based on solar energy and/or energy efficient processes may be mission enabling. Another important issue is minimizing impurities in the product stream(s), especially those potentially posing risks to personnel or operations through (catalyst) poisoning or (equipment) damage. Technologies being developed to remove (and/or recycle) heteroatom impurities are briefly discussed as well as the development of chemically robust catalysts whose activities are not diminished during operation. The potential impacts on future missions by such new approaches as well as balance of system issues are addressed.

space processing↗
NASA NTRS2014

Novel Catalysts and Processing Technologies for Production of Aerospace Fuels from Non-Petroleum Raw Materials

Transportation fuels production (including aerospace propellants) from non-traditional sources (gases, waste materials, and biomass) has been an active area of research and development for decades. Reducing terrestrial waste streams simultaneous with energy conversion, plentiful biomass, new low-cost methane sources, and/or extra-terrestrial resource harvesting and utilization present significant technological and business opportunities being realized by a new generation of visionary entrepreneurs. We examine several new approaches to catalyst fabrication and new processing technologies to enable utilization of these non-traditional raw materials. Two basic processing architectures are considered: a single-stage pyrolysis approach that seeks to basically re-cycle hydrocarbons with minimal net chemistry or a two-step paradigm that involves production of supply or synthesis gas (mainly carbon oxides and hydrogen) followed by production of fuel(s) via Sabatier or methanation reactions and/or Fischer-Tropsch synthesis. Optimizing the fraction of product stream relevant to targeted aerospace (and other transportation) fuels via modeling, catalyst fabrication and novel reactor design are described. Energy utilization is a concern for production of fuels for either terrestrial or space operations; renewable sources based on solar energy and/or energy efficient processes may be mission enabling. Another important issue is minimizing impurities in the product stream(s), especially those potentially posing risks to personnel or operations through (catalyst) poisoning or (equipment) damage. Technologies being developed to remove (and/or recycle) heteroatom impurities are briefly discussed as well as the development of chemically robust catalysts whose activity are not diminished during operation. The potential impacts on future missions by such new approaches as well as balance of system issues are addressed.

propellants↗
DOE OSTI2017

Vitrification of Sellafield Wastes with High Metallic Magnesium Alloy Content - 17495

The Sellafield nuclear complex, located in northwest England, is the largest such site in the United Kingdom. Sellafield Limited, which is the operating contractor for the Nuclear Decommissioning Authority, is evaluating thermal treatment technologies for a potential future facility to process a variety of Intermediate Level Waste sludges and slurries accumulated from historical site operations. In support of that effort, Atkins and the Vitreous State Laboratory (VSL) of The Catholic University of America conducted studies to evaluate the feasibility and implications of installing a joule-heated ceramic melter (JHCM) vitrification system to process a variety of sludge and slurry radioactive wastes at the Sellafield site. These sludges have the potential to contain a significant proportion of reactive metals in localized regions. The metallic fraction derives from unreacted Magnox spent fuel cladding. Thus, an important objective of this work was to investigate the performance of JHCM technology for the treatment of streams with localized regions of high reactive metal contents. The present work was focused on Site Ion Exchange Effluent Plant (SIXEP) Magnox sludges, investigated previously. Suitable waste simulants were developed for the SIXEP Magnox sludge waste stream, which included surrogates for all important radionuclides. High waste-loading, fully compliant glass formulations were designed using a combination of previous experience, extensive waste glass data bases, and small-scale crucible melts. Glasses from the test melts were characterized for properties that are important for processability and product quality. The most viable compositions were then selected for small-scale melter trials to collect information on processing rates and behavior, off-gas and secondary waste compositions, and overall system mass balance. These data were used to support the technology evaluation, which considered such factors as minimization of inactive additions, waste volume reduction, retention of radionuclides, minimization of secondary wastes, and overall process efficiency and effectiveness. The data were also used to develop sizing estimates for the full-scale facility and to estimate treatment durations under various treatment scenarios. A series of tests was then performed with partial replacement of the magnesium hydroxide with a metallic magnesium alloy that is close in composition to Magnox alloy. A commercially available magnesium alloy, Elecktron AZ31B, which has a nominal magnesium content of 95.7%, was used for this purpose. The testing was performed on a DuraMelter 10 (DM10) JHCM system to characterize the melter off-gas, glass product, and the effects of magnesium alloy particle size on feed processing. Data on processing rate and any processing issues, product glass composition, off-gas composition including hydrogen, and system operating parameters, including flows, temperatures, pressures, etc., were collected and analyzed to evaluate the effects of magnesium alloy on the vitrification process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Affinity propagation clustering of full-field, high-spatial-dimensional measurements for robust output-only modal identification: A proof-of-concept study

Determination of the model order is a challenging problem in system identification, especially in output-only or operational modal identification where some modes are weakly excited. While existing methods such as the stabilization diagram method (spectral information) are effective, they do not scale to high-dimensional data, which is usually needed for high-fidelity characterization of structural dynamics and has been made available in the emerging full-field measurement techniques using optical methods such as photogrammetry and laser vibrometers. In this proof-of-concept study we present a new non-parametric, data-driven approach for robust output-only identification of high-spatial-dimensional modal parameters of basic structures by efficiently processing and interactively exploiting the full-field measurement (i.e., very dense spatial measurement points). Specifically, we first over-estimate the system model once, producing a pool of candidate modes associated with their modal frequencies and full-field, high-spatial-dimensional mode shapes. This is accomplished by a data-driven method termed affinity propagation clustering (APC), where the active clusters, which are the active modes in our formulations, emerge from the "message-passing" procedure and does not require a pre-determination of the cluster number (mode or model order). Next, rather than using the spectral information to distinguish the physical and spurious modes in the stabilization diagram method, we exploit and visualize the spatial, full-field mode shape associated with each candidate mode to do so. We conduct extensive experiments on basic structural models with comparisons to a few existing methods. The results indicate that the new method is computationally efficient for identifying high-spatial-dimensional modal parameters, and robust to identify weak modes by exploiting the full-field measurement. We also discuss its applicability and limitations for structures with complex geometry (shapes).

42 ENGINEERING↗
DOE OSTI2026

Absorption Correction for Reliable Pair Distribution Functions from Low Energy X-ray Sources

This paper explores the development and testing of a simple absorption correction model for processing powder X-ray diffraction data from Debye−Scherrer geometry laboratory X-ray experiments. This may be used as a preprocessing step before using PDFGETX3 to obtain reliable pair distribution functions (PDFs). Various experimental and theoretical methods for estimating μR were explored, and the most appropriate μR values for correction were identified for different capillary diameters and X-ray beam sizes. We identify operational ranges of μR where a reasonable signal-to-noise ratio is possible after correction. A user-friendly software package, DIFFPY.LABPDFPROC, is presented that can help estimate μR and perform absorption corrections with a rapid calculation for efficient processing.

Absorption↗
DOE OSTI2021

Harnessing Photoelectrochemistry for Wastewater Nitrate Treatment Coupled with Resource Recovery

Wastewater is a misplaced resource well suited to recover nutrients, value-added chemicals, energy, and clean water. A photoelectrochemical device is proposed to transform wastewater nitrates to ammonia and nitrous oxide, coupled with water oxidation. Numerical models were developed to quantify the dependence of process efficiencies and nitrogen-removal rates on light absorber band gaps, electrocatalytic kinetic parameters, competing oxygen reduction and hydrogen evolution reactions, and the reacting nitrate species concentrations that affect the mass-transfer limited current densities. With a single light-absorber and state-of-the-art catalysts, optimal solar-to-chemical efficiencies of 7% and 10% and nitrogen-removal rates of 260 and 395 gN m -2 day -1 are predicted for nitrate reduction to ammonia and nitrous oxide, respectively. The influence of competing reactions on the performance depends on the nitrate concentration and band gap of the light absorber modeled. Oxygen reduction is more dominant than hydrogen evolution to compete with the nitrate reduction reaction, but it is mass-transfer limited. Even with kinetic parameters that enhanced the driving forces for the competing reactions, the performance is only minimally affected by these reactions for optimally selected band gaps and nitrate concentrations larger than 100 mM. Here, theoretically predicted peak nitrogen removal rates and specific energy intensities are competitive with reported estimates for electrochemical and Sharon-Anammox processes for ammonia recovery and nitrogen removal, respectively. This result, together with the added benefit of harnessing sunlight to produce value-added products, indicates promise in the photoelectrochemical approach as a tertiary pathway to recover nutrients and energy from wastewater nitrates.

25 ENERGY STORAGE↗
DOE OSTI2021

An Intelligent Garbage Sorting System Based on Edge Computing and Visual Understanding of Social Internet of Vehicles

In order to enable Social Internet of Vehicles devices to achieve the purpose of intelligent and autonomous garbage classification in a public environment, while avoiding network congestion caused by a large amount of data accessing the cloud at the same time, it is therefore considered to combine mobile edge computing with Social Internet of Vehicles to give full play to mobile edge computing features of high bandwidth and low latency. At the same time, based on cutting-edge technologies such as deep learning, knowledge graph, and 5G transmission, the paper builds an intelligent garbage sorting system based on edge computing and visual understanding of Social Internet of Vehicles. First of all, for the massive multisource heterogeneous Social Internet of Vehicles big data in the public environment, different item modal data adopts different processing methods, aiming to obtain a visual understanding model. Secondly, using the 5G network, the model is deployed on the edge device and the cloud for cloud-side collaborative management, aiming to avoid the waste of edge node resources, while ensuring the data privacy of the edge node. Finally, the Social Internet of Vehicles devices is used to make intelligent decision-making on the big data of the items. First, the items are judged as garbage, and then the category is judged, and finally the task of grabbing and sorting is realized. The experimental results show that the system proposed in this paper can efficiently process the big data of Social Internet of Vehicles and make valuable intelligent decisions. At the same time, it also has a certain role in promoting the promotion of Social Internet of Vehicles devices.

Shen, Xuehao↗
NASA NTRS2007

WGM-Based Photonic Local Oscillators and Modulators

Photonic local oscillators and modulators that include whispering-gallery mode (WGM) optical resonators have been proposed as power-efficient devices for generating and detecting radiation at frequencies of the order of a terahertz. These devices are intended especially to satisfy anticipated needs for receivers capable of detecting lowpower, narrow-band terahertz signals to be used for sensing substances of interest in scientific and military applications. At present, available terahertz-signal detectors are power-inefficient and do not afford the spectral and amplitude resolution needed for detecting such signals. The proposed devices would not be designed according to the conventional approach of direct detection of terahertz radiation. Instead, terahertz radiation would first be up-converted into the optical domain, wherein signals could be processed efficiently by photonic means and detected by optical photodetectors, which are more efficient than are photodetectors used in conventional direct detection of terahertz radiation. The photonic devices used to effect the up-conversion would include a tunable optical local oscillator and a novel electro-optical modulator. A local oscillator according to the proposal would be a WGM-based modelocked laser operating at a desired pulserepetition rate of the order of a terahertz. The oscillator would include a terahertz optical filter based on a WGM microresonator, a fiber-optic delay line, an optical amplifier (which could be either a semiconductor optical amplifier or an erbium-doped optical fiberamplifier), and a WGM Ka-band modulator. The terahertz repetition rate would be obtained through harmonic mode locking: for example, by modulating the light at a frequency of 33 GHz and locking each 33d optical mode, one would create a 1.089-THz pulse train. The high resonance quality factors (Q values) of WGM optical resonators should make it possible to decrease signal-generation threshold power levels significantly below those of other optical-signal-generation devices.

Matsko, Andrey↗
DOE OSTI2015

Sol–gel method as a way of carbonyl iron powder surface modification for interaction improvement

This article presents a method for modification of carbonyl iron particles’ surface (CIP), (d{sub 50}=4–9 µm) by silica coatings obtained using the sol–gel method. Reaction parameters were determined to obtain dry magnetic powder with homogeneous silica coatings without further processing and without any by-product in the solid or liquid phase. This approach is new among the commonly used methods of silica coating of iron particles. No attempt has been made to cover a carbonyl iron surface by silica in a waste-free method, up to date. In the current work two different silica core/shell structures were made by the sol–gel process, based on different silica precursors: tetraethoxy-silane (TEOS) and tetramethoxy-silane (TMOS). The dependence between the synthesis procedure and thickness of silica shell covering carbonyl iron particles has been described. Surface morphology of the modified magnetic particles and the coating thickness were characterized with the use of scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Determination of the physicochemical structure of the obtained materials was performed by the energy-dispersive X-ray spectroscope (EDS), and the infrared technique (IR). The surface composition was analyzed using X-ray photoelectron spectroscopy (XPS). Additionally, distribution of particle size was measured using light microscopy. The new, efficient process of covering micro-size CIP with a nanometric silica layer was shown. Results of a performed analysis confirm the effectiveness of the presented method. - Highlights: • Proper covering CIP by sol–gel silica layer avoids agglomeration. • A new solid waste-free method of CIP coating is proposed. • Examination of the properties of modified CIP in depends on washing process. • Coatings on CIP particles doesn’t change the magnetic properties of particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Low-Cost Bio-Based Carbon Fibers for High Temperature Processing

GrafTech International Holdings Inc. (GTI), under Award No. DE-EE0005779, worked with Oak Ridge National Laboratory (ORNL) under CRADA No. NFE-15-05807 to develop lignin-based carbon fiber (LBCF) technology and to demonstrate LBCF performance in high-temperature products and applications. This work was unique and different from other reported LBCF work in that this study was application-focused and scalability-focused. Accordingly, the executed work was based on meeting criteria based on technology development, cost, and application suitability. High-temperature carbon fiber based insulation is used in energy intensive industries, such as metal heat treating and ceramic and semiconductor material production. Insulation plays a critical role in achieving high thermal and process efficiency, which is directly related to energy usage, cost, and product competitiveness. Current high temperature insulation is made with petroleum based carbon fibers, and one goal of this protect was to develop and demonstrate an alternative lignin (biomass) based carbon fiber that would achieve lower cost, CO2 emissions, and energy consumption and result in insulation that met or exceeded the thermal efficiency of current commercial insulation. In addition, other products were targeted to be evaluated with LBCF. As the project was designed to proceed in stages, the initial focus of this work was to demonstrate lab-scale LBCF from at least 4 different lignin precursor feedstock sources that could meet the estimated production cost of $5.00/pound and have ash level of less than 500 ppm in the carbonized insulation-grade fiber. Accordingly, a preliminary cost model was developed based on publicly available information. The team demonstrated that 4 lignin samples met the cost criteria. In addition, the ash level for the 4 carbonized lignin samples was below 500 ppm. Processing as-received lignin to produce a high purity lignin fiber was a significant accomplishment in that most industrial lignin, prior to purification, had greater than 4X the ash level needed for this project, and prior to this work there was not a clear path of how to achieve the purity target. The lab scale development of LBCF was performed with a specific functional application in mind, specifically for high temperature rigid insulation. GTI is a consumer of foreign-sourced pitch and rayon based carbon fibers for use in its high temperature insulation products, and the motivation was that LBCF had potential to decrease costs and increase product competitiveness in the marketplace through lowered raw material costs, lowered energy costs, and decreased environmental footprint. At the end of this project, the Technology Readiness Level (TRL) remained at 5 for LBCF in high temperature insulation.

09 BIOMASS FUELS↗
DOE OSTI2019

Photocatalytic pure water splitting with high efficiency and value by Pt/porous brookite TiO 2 nanoflutes

We report the remarkable production of H 2 and H 2 O 2 from pure water using porous brookite TiO 2 nanoflutes decorated with Pt nanoparticles through two-electron photocatalytic intermediate water splitting (PIWS). The H 2 production rate from deionized water (pH similar to 7.0) was 9.8 +/- 0.6 $\mu$mol mg -1 h -1 , more than 12-fold and 230-fold higher than the reported TiO 2 -based photocatalytic overall water splitting (POWS) and H 2 /H 2 O 2 production systems, respectively. The apparent quantum yields (AQY) value can achieve 43.4%, which is the highest value compared with the reported TiO 2 -based POWS systems and the commercial value for PIWS is similar to 9-fold higher than that for POWS even ignoring the separation cost. The mechanism of the distinct performance was confirmed by DFT and experimental measurements. The present work provides a feasible strategy to significantly improve the process efficiency and value of photocatalytic water splitting in both pure water and seawater using natural sunlight.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Ultrafast processing of pixel detector data with machine learning frameworks

Modern photon science performed at high repetition rate free-electron laser (FEL) facilities and beyond relies on 2D pixel detectors operating at increasing frequencies (towards 100 kHz at LCLS-II) and producing rapidly increasing amounts of data (towards TB/s). This data must be rapidly stored for offline analysis and summarized in real time for online feedback to the scientists. While at LCLS all raw data has been stored, at LCLS-II this would lead to a prohibitive cost; instead, enabling real time processing of pixel detector data (dark, gain, common mode, background, charge summing, subpixel position, photon counting, data summarization) allows reducing the size and cost of online processing, offline processing and storage by orders of magnitude while preserving full photon information. This could be achieved by taking advantage of the compressibility of sparse data typical for LCLS-II applications. Faced with a similar big data challenge a decade ago, computer vision stimulated revolutionary advances in machine learning hardware and software. We investigated if these developments are useful in the field of data processing for high speed pixel detectors and found that typical deep learning models and autoencoder architectures failed to yield useful noise reduction while preserving full photon information, presumably because of the very different statistics and feature sets in computer vision and radiation imaging. However, the raw performance of modern frameworks like Tensorflow inspired us to redesign in Tensorflow mathematically equivalent versions of the state-of-the-art, “classical” algorithms used at LCLS. The novel Tensorflow models resulted in elegant, compact and hardware agnostic code, gaining 1 to 2 orders of magnitude faster processing on an inexpensive consumer GPU, reducing by 3 orders of magnitude the projected cost of online analysis and compression without photon loss at LCLS-II. The novel Tensorflow models also enabled ongoing development of a pipelined hardware system expected to yield an additional 3 to 4 orders of magnitude speedup, necessary for meeting the data acquisition and storage requirements at LCLS-II, potentially enabling acquiring every single FEL pulse at full speed. Computer vision a decade ago was dominated by hand-crafted filters; their structure inspired the deep learning revolution resulting in modern deep convolutional networks; similarly, our novel Tensorflow filters provide inspiration for designing future deep learning models for ultrafast and efficient processing and classification of pixel detector images at FEL facilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Process parameter translation strategies for variable directed energy deposition spot size using 316L, copper, and Inconel 625

Directed energy deposition (DED) is a form of additive manufacturing available across a variety of laser spot diameter values, often referred to as spot sizes. However, there is no method to easily transfer process parameters across discrete spot sizes, leading to DED process parameters that are equipment specific and not widely applicable. In this study, a strategy is proposed and investigated for five spot sizes that keep the areal energy density constant while varying power, feed rate, and powder flow during the deposition of 316L stainless steel. An assessment of trends in hardness and microstructure is possible due to the novel production of components of a single material across several spot sizes using a single nozzle on a single DED system. The proposed strategy was used to nullify the hardness drop during functional grading of Inconel 625 and pure copper, enabling fabrication of multi-material sample that does not compromise desirable properties. This application shows the value in establishing more efficient process parameter development and understanding spot size influences on geometric and material property flexibility, to enable a more diverse powder-based DED design space and to increase the industry adoption of DED systems.

316L↗
DOE OSTI2013

Measures of the environmental footprint of the front end of the nuclear fuel cycle

Previous estimates of environmental impacts associated with the front end of the nuclear fuel cycle (FEFC) have focused primarily on energy consumption and CO2 emissions. Results have varied widely. This work builds upon reports from operating facilities and other primary data sources to build a database of front end environmental impacts. This work also addresses land transformation and water withdrawals associated with the processes of the FEFC. These processes include uranium extraction, conversion, enrichment, fuel fabrication, depleted uranium disposition, and transportation. To allow summing the impacts across processes, all impacts were normalized per tonne of natural uranium mined as well as per MWh(e) of electricity produced, a more conventional unit for measuring environmental impacts that facilitates comparison with other studies. This conversion was based on mass balances and process efficiencies associated with the current once-through LWR fuel cycle. Total energy input is calculated at 8.7 x 10- 3 GJ(e)/MWh(e) of electricity and 5.9 x 10- 3 GJ(t)/MWh(e) of thermal energy. It is dominated by the energy required for uranium extraction, conversion to fluoride compound for subsequent enrichment, and enrichment. An estimate of the carbon footprint is made from the direct energy consumption at 1.7 kg CO2/MWh(e). Water use is likewise dominated by requirements of uranium extraction, totaling 154 L/MWh(e). Land use is calculated at 8 x 10- 3 m2/MWh(e), over 90% of which is due to uranium extraction. Quantified impacts are limited to those resulting from activities performed within the FEFC process facilities (i.e. within the plant gates). Energy embodied in material inputs such as process chemicals and fuel cladding is identified but not explicitly quantified in this study. Inclusion of indirect energy associated with embodied energy as well as construction and decommissioning of facilities could increase the FEFC energy intensity estimate by a factor of up to 2.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Water Sorption Study of Various Polymers and Polymeric Composites

In the formulations of many composite materials, polymeric materials are often used as binder materials to enhance processability, functionality, and safety during manufacturing. For instance, poly(ester urethane), such as Estane® 5703, is used in the formulation of PBX 9501, and vinyl copolymer elastomer (VCE) is used in the formulation of VCE/filler compos ites. The stability of these binders directly impacts the overall stability and performance of their composites. Estane and VCE are prone to hydrolytic degradation, with water sorption behavior playing a significant role in their long-term stability and aging behavior. Hence, it is critical to study their water sorption behavior under various humidity and tempera ture conditions. To improve the accuracy and reduce labor-intensive work involved in water sorption experiments, an automated Dynamic Vapor Sorption (DVS) system was employed, which can generate large datasets. To efficiently process and analyze these datasets, Python scripts were developed. These scripts not only streamlined data processing, but also accu rately derived the Arrhenius parameters related to water diffusion and sorption properties for the tested materials. This approach offers a robust framework for evaluating water trans port and sorption processes in polymeric materials and adds valuable capabilities to future water sorption testing efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Potential of hybrid functionalized meso-porous materials for the separation and immobilization of radionuclides

Functionalized meso-porous materials are a class of hybrid organic-inorganic material in which a meso-porous metal oxide framework is functionalized with multifunctional organic molecules. These molecules may contain one or more anchor groups that form strong bonds to the pore surfaces of the metal oxide framework and free functional groups that can impart and or modify the functionality of the material such as for binding metal ions in solution. Such materials have been extensively studied over the past decade and are of particular interest in absorption applications because of the tremendous versatility in choosing the composition and architecture of the metal oxide framework and the nature of the functional organic molecule as well as the efficient mass transfer that can occur through a well-designed hierarchically porous network. A sorbent for nuclear applications would have to be highly selective for particular radio nuclides, it would need to be hydrolytically and radiolytically stable, and it would have to possess reasonable capacity and fast kinetics. The sorbent would also have to be available in a form suitable for use in a column. Finally, it would also be desirable if once saturated with radio nuclides, the sorbent could be recycled or converted directly into a ceramic or glass waste form suitable for direct repository disposal or even converted directly into a material that could be used as a transmutation target. Such a cradle-to- grave strategy could have many benefits in so far as process efficiency and the generation of secondary wastes are concerned.This paper will provide an overview of work done on all of the above mentioned aspects of the development of functionalized meso-porous adsorbent materials for the selective separation of lanthanides and actinides and discuss the prospects for future implementation of a cradle-to-grave strategy with such materials. (author)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Graph-Based Representations and Applications to Process Simulation

Rapid and robust convergence of a process flowsheet is critical to enable large-scale simulations that address core scientific questions related to process design, optimization, and sustainability. However, due to the highly coupled and nonlinear nature of chemical processes, efficiently solving a flowsheet remains a challenge. In this work, we show that graph representations of the underlying physical phenomena in unit operations may help identify potential avenues to systematically reformulate the network of equations and enable more robust topology-based convergence of flowsheets. To this end, we developed graph abstractions of the governing equations of vapor-liquid and liquid-liquid equilibrium separation equipment. These graph abstractions consist of a mesh of interconnected variable nodes and equation nodes that are systematically generated through PhenomeNode, a new open-source library in Python developed in this study. We show that partitioning the graph into separate mass, energy, and equilibrium subgraphs can help decouple nonlinearities and guide decomposition algorithms. By employing the graph abstraction on an industrial separation process for separating glacial acetic acid from water, we implemented a new block decomposition scheme in BioSTEAM and demonstrated that this can accelerate convergence over a traditional sequential modular approach.

Distillation↗