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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A novel priority selection system for nuclear power plant - 287

The priority selection system is an important component of security level instrument control platform for nuclear power plant, the main function of which is priority processing the manual or automatic command with various security levels and driving engineering safety features and field devices, such as pump and valve. Its stability and safety plays a crucial role in the operation of the power plant. The main objective of the present paper is to describe the new nuclear power plant-oriented priority selection system, which is developed independently by China Nuclear Control System Engineering Company. In this system, the control commands from 1E DCS, ECP and DAS systems are transmitted via hardwire, while those from NC DCS are transmitted by field-bus. The control commands experience priority output to control the field actuators. Meanwhile, in order to control key field devices when failure of the instrument control systems occurs, the issuing interface for native instructions with permissions setting is also offered. The whole system provides collection-feedback functions for field devices, high coverage self-diagnostic functions and periodic test functions for safety systems. Moreover, the feedback information of field devices, the results of self-diagnosis and periodic test will be submitted to DCS of nuclear power plant. In addition, the core part of priority selection system, namely priority selection module, is obtained by pure FPGA technology, which is different from DCS systems and could avoid common cause failure of software effectively. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

ROM-based Subset Selection Algorithm for Efficient Surrogate Modeling

This summary discusses a new methodology to support the construction of surrogate models for computationally expensive models with many input parameters and output responses. In realistic engineering calculations, such as thermal-hydraulics simulation, the cost of the simulation is typically expensive, especially when detailed models are employed to describe system behavior, thereby justifying the need for surrogate models. The cost of surrogate model construction is typically a function of the number of model parameters and the degree of model nonlinearity. For sufficiently complex models, the cost of constructing the surrogate model could be by itself overwhelmingly expensive, thereby diminishing its value. One key requirement of surrogate model construction is the ability to preselect the best parametric form to describe the model behavior over the expected range of parameter variations. This summary presents a new algorithm to help select the best approximation out of a template of functions using recent advances in reduced order modeling (ROM) techniques. The idea of selecting functions out of a template is typically referred to as subset selection in the statistical and applied mathematics community. Different from existing subset selection algorithms, we rely on ROM to help identify the most influential functions for the surrogate model. Previous work has shown that ROM can help reduce the effective dimensionality of the parameter space, which can help reduce the cost of surrogate model construction. In this summary, we adopt a different philosophy, where the fitting functions are treated as pseudo parameters and ROM is applied on the pseudo parameter space, with the result now being a ranked list of the pseudo parameters along with their contribution to the quality of the surrogate model fit. This approach allows the analyst to discard all terms that have negligible impact on the quantity of interest. A relap5 model is employed to demonstrate the application of the proposed methodology. (authors)

42 ENGINEERING↗
DOE OSTI2024

Tube-in-tube ionic liquid heat exchanger employing a selectively permeable tube

A tube-in-tube heat exchanger utilizes a selectively permeable tube having a selective permeable layer to allow the refrigerant to transfer into an ionic liquid to generate heating or cooling. The ionic liquid then provides heating or cooling to a heat transfer fluid through a non-permeable layer or tube. The system may be configured as a shell and tube design, with the third fluid free to flow on the outside of the shell, or as a shell and tube-in-tube, with a central tube containing a first liquid, a second tube containing a second liquid, and an outer shell containing the third liquid. The selectively permeable tube may include an anion or cation selectively permeable layer and this layer may be supported by a support layer or tube.

Bahar, Bamdad↗
DOE OSTI2016

Data mining and statistical inference in selective laser melting

Selective laser melting (SLM) is an additive manufacturing process that builds a complex three-dimensional part, layer-by-layer, using a laser beam to fuse fine metal powder together. The design freedom afforded by SLM comes associated with complexity. As the physical phenomena occur over a broad range of length and time scales, the computational cost of modeling the process is high. At the same time, the large number of parameters that control the quality of a part make experiments expensive. In this paper, we describe ways in which we can use data mining and statistical inference techniques to intelligently combine simulations and experiments to build parts with desired properties. We start with a brief summary of prior work in finding process parameters for high-density parts. We then expand on this work to show how we can improve the approach by using feature selection techniques to identify important variables, data-driven surrogate models to reduce computational costs, improved sampling techniques to cover the design space adequately, and uncertainty analysis for statistical inference. Here, our results indicate that techniques from data mining and statistics can complement those from physical modeling to provide greater insight into complex processes such as selective laser melting.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Selective and Chemical-Free Removal of Toxic Heavy Metal Cations from Water Using Shock Ion Extraction

Electrochemical methods are known to have attractive features and capabilities when used for ion separations and water purification. In this study, we developed a new process called shock ion extraction (shock IX) for selective and chemical-free removal of toxic heavy metals from water. Shock IX is a hybrid process that combines shock electrodialysis (shock ED) and ion exchange using an ion exchange resin wafer (IERW), and this method can be thought of functionally as an electrochemically assisted variation of traditional ion exchange. In particular, shock IX exhibits greater ion removal and selectivity for longer periods of time, compared to the use of ion exchange alone. Here, the use of an IERW in shock ED also increases multivalent ion selectivity, reduces energy consumption, and improves the hydrodynamics and scalability of the system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Transient Kinetic Selectivity in Nanotubes Growth on Solid Co–W Catalyst

Solid Co–W catalysts have been shown to yield single-walled carbon nanotubes (CNT) with high selectivity, simplistically attributed to CNT-catalyst symmetry match for certain chiral indices (n,m). Here, based on large-scale first-principles calculations combined with kinetic Monte Carlo simulations, we show instead that such selectivity arises from a complex kinetics of growth. The solid Co7W6 catalyst strongly favors a restructured, asymmetric CNT edge which entails preferential nucleation of tubes with 2m < n but much faster growth of chiral tubes with n ≤ 2m. We uncover a tendency of interface defects formation that, although rare, drive CNT type change from smaller to larger chiral angles (zigzag to armchair). Furthermore, being both least prone to defects and fast growing, the (12,6) CNT appears as a transient, kinetics-selected type reaching highest abundance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Preventing Loss of Selectivity during the Oxidative Dehydrogenation of Propane over Supported Vanadium Catalysts

Supported vanadium materials are promising catalysts for the oxidative dehydrogenation of propane to propylene (ODHP), but a lack of mechanistic understanding limits the rational design of catalysts with improved propylene selectivity. Adding Ta to V/SiO 2 increases the propylene selectivity, as well as the activity, leading to superior performance compared to state-of-the-art boron-based systems. In this contribution, we utilize this surprising promotional effect of Ta to elucidate key elements of the mechanistic cycle. Through a combination of characterization techniques, computational modeling, and kinetic experiments, we show that the catalytic cycle over V/SiO 2 likely involves the formation of an isopropyl alcohol intermediate, the fate of which is in kinetic competition between subsequent dehydration to propylene or further oxidation. Furthermore, we show that the relatively facile propylene overoxidation observed for these materials occurs via the epoxidation of propylene by a proposed peroxovanadium intermediate, rather than the abstraction of propylene’s allylic C–H bond as previously assumed. Using these key mechanistic features, we rationalize the enhanced selectivity and activity of Ta promotion. In conclusion, our mechanistic framework offers avenues for future catalyst development to improve supported vanadium materials for ODHP.

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

Plasmon-Enhanced Greenhouse Selectivity for High-Temperature Solar Thermal Energy Conversion

The greenhouse effect arises when thermal radiation is forced to undergo absorption and re-emission many times before escaping, while sunlight transmits largely unimpeded. Although this effect is responsible for global warming, it is generally weak in solid-state materials because radiation can be easily overpowered by other modes of heat transfer. Here, we report on the use of infrared plasmonic nanoparticles to enhance the greenhouse effect in transparent mesoporous materials. Local surface plasmon resonances in transparent conducting oxide nanoparticles (TCO NPs) selectively shorten the mean free path of thermal photons while maintaining high solar transmittance. The addition of a small amount of TCO NPs (<0.1% by volume) nearly halves the heat losses at 700 °C. This leads to an experimentally demonstrated effective thermal emittance of ~0.17 at 700 °C, which is the lowest reported value to date, among all selective surfaces and transparent insulating materials measured at 650 °C or above. Furthermore, our results show that plasmon-enhanced greenhouse selectivity (PEGS) is a promising mechanism for spectral control of radiative heat transfer, and more specifically, for conversion of minimally concentrated sunlight into high-temperature heat.

14 SOLAR ENERGY↗
DOE OSTI2022

Prescreening-Based Subset Selection for Improving Predictions of Earth System Models With Application to Regional Prediction of Red Tide

We present the ensemble method of prescreening-based subset selection to improve ensemble predictions of Earth system models (ESMs). In the prescreening step, the independent ensemble members are categorized based on their ability to reproduce physically-interpretable features of interest that are regional and problem-specific. The ensemble size is then updated by selecting the subsets that improve the performance of the ensemble prediction using decision relevant metrics. We apply the method to improve the prediction of red tide along the West Florida Shelf in the Gulf of Mexico, which affects coastal water quality and has substantial environmental and socioeconomic impacts on the State of Florida. Red tide is a common name for harmful algal blooms that occur worldwide, which result from large concentrations of aquatic microorganisms, such as dinoflagellate Karenia brevis, a toxic single celled protist. We present ensemble method for improving red tide prediction using the high resolution ESMs of the Coupled Model Intercomparison Project Phase 6 (CMIP6) and reanalysis data. The study results highlight the importance of prescreening-based subset selection with decision relevant metrics in identifying non-representative models, understanding their impact on ensemble prediction, and improving the ensemble prediction. These findings are pertinent to other regional environmental management applications and climate services. Additionally, our analysis follows the FAIR Guiding Principles for scientific data management and stewardship such that data and analysis tools are findable, accessible, interoperable, and reusable. As such, the interactive Colab notebooks developed for data analysis are annotated in the paper. This allows for efficient and transparent testing of the results’ sensitivity to different modeling assumptions. Moreover, this research serves as a starting point to build upon for red tide management, using the publicly available CMIP, Coordinated Regional Downscaling Experiment (CORDEX), and reanalysis data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Understanding the structural basis of species selective, stereospecific inhibition for Cryptosporidium and human thymidylate synthase

Thymidylate synthase (TS), found in all organisms, is an essential enzyme responsible for the de novo synthesis of deoxythymidine monophosphate. The TS active sites of the protozoal parasite Cryptosporidium hominis and human are relatively conserved. Evaluation of antifolate compound 1 and its R-enantiomer 2 against both enzymes reveals divergent inhibitor selectivity and enzyme stereospecificity. To establish how C. hominis and human TS (ChTS and hTS) selectively discriminate 1 and 2, respectively, we determined crystal structures of ChTS complexed with 2 and hTS complexed with 1 or 2. Coupled with the previously determined structure of ChTS complexed with 1, we finally discuss a possible mechanism for enzyme stereospecificity and inhibitor selectivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Carbon Free and Noble Metal Free Ni 2 Mo 6 S 8 Electrocatalyst for Selective Electrosynthesis of H 2 O 2

Electrocatalytic two-electron reduction of oxygen is a promising method for producing sustainable H 2 O 2 but lacks low-cost and selective electrocatalysts. Here, the Chevrel phase chalcogenide Ni 2 Mo 6 S 8 is presented as a novel active motif for reducing oxygen to H 2 O 2 in an aqueous electrolyte. Although it has a low surface area, the Ni 2 Mo 6 S 8 catalyst exhibits exceptional activity for H 2 O 2 synthesis with >90% H 2 O 2 molar selectivity across a wide potential range. Chemical titration verified successful generation of H 2 O 2 and confirmed rates as high as 90 mmol H 2 O 2 g cat –1 h –1 . The outstanding activities are attributed to the ligand and ensemble effects of Ni that promote H 2 O dissociation and proton-coupled reduction of O 2 to HOO*, and the spatial effect of the Chevrel phase structure that isolates Ni active sites to inhibit O—O cleavage. The synergy of these effects delivers fast and selective production of H 2 O 2 with high turn-over frequencies of ≈30 s –1 . Additionally, the Ni 2 Mo 6 S 8 catalyst has a stable crystal structure that is resistive for oxidation and delivers good catalyst stability for continuous H 2 O 2 production. The described Ni-Mo6S8 active motif can unlock new opportunities for designing Earth-abundant electrocatalysts to tune oxygen reduction for practical H 2 O 2 production.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Site-Selective Catalysis of a Multifunctional Linear Molecule: The Steric Hindrance of Metal–Organic Framework Channels

The site-selective reaction of a multifunctional linear molecule requires a suitable catalyst possessing both uniform narrow channel to limit the molecule rotation and a designed active site in the channel. Recently, nanoparticles (NPs) were incorporated in metal–organic frameworks (MOFs) with the tailorable porosity and ordered nanochannel, which makes these materials (NPs/MOFs) highly promising candidates as catalytic nanoreactors in the field of heterogeneous catalysis. Inspired by a “Gondola” sailing in narrow “Venetian Canal” without sufficient space for a U-turn, a simple heterogeneous catalyst based on NPs/MOFs is developed here that exhibits site-selectivity for the oxidation of diols by restricting the random rotation of the molecule (the “Gondola”) in the limited space of the MOF channel (the narrow “Venetian Canal”), thereby protecting the middle functional group via steric hindrance. This strategy is not limited to the oxidation of diols, but can be extended to the site-selective reaction of many similar multifunctional linear molecules, such as the reduction of alkadienes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Enhanced Laplace Pressures for Functional Surfaces: Wicking, Switchability, and Selectivity

Abstract Wetting functionalities of rough surfaces are largely determined by the Laplace pressure generated across liquid–gas interfaces formed within surface structures. Typically, rough wetting surfaces create negative Laplace pressures, enabling capillary wicking, while rough non‐wetting surfaces create positive Laplace pressures, exhibiting fluid repellency. Here, with microfabricated reentrant structures, it is shown that the same surface can exhibit either a negative or positive Laplace pressure, regardless of its intrinsic wettability. This material‐independent Laplace pressure duality enables or enhances a range of wetting functionalities including wicking, switchability, and selectivity. On the same surface, capillary rise, capillary dip, and the combination of the two which leads to further enhancement of the total sustainable capillary height and Laplace pressure, the driving force for wicking is demonstrated. Further, active switching of wetting states between the hemiwicking and the repellent Cassie state on reentrant structures is shown. Moreover, with a water‐hexane mixture system, selective wetting of reentrant structures are demonstrated, that is, water can be selectively wicked or repelled in the presence of hexane, and vice versa. These functionalities are achieved, which would typically require complex chemical coatings, solely using surface structures, thus largely expanding the design space for a wide range of thermofluidic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Time‐Dependent Cation Selectivity of Titanium Carbide MXene in Aqueous Solution

Abstract Electrochemical ion separation is a promising technology to recover valuable ionic species from water. Pseudocapacitive materials, especially 2D materials, are up‐and‐coming electrodes for electrochemical ion separation. For implementation, it is essential to understand the interplay of the intrinsic preference of a specific ion (by charge/size), kinetic ion preference (by mobility), and crystal structure changes. Ti 3 C 2 T z MXene is chosen here to investigate its selective behavior toward alkali and alkaline earth cations. Utilizing an online inductively coupled plasma system, it is found that Ti 3 C 2 T z shows a time‐dependent selectivity feature. In the early stage of charging (up to about 50 min), K + is preferred, while ultimately Ca 2+ and Mg 2+ uptake dominate; this unique phenomenon is related to dehydration energy barriers and the ion exchange effect between divalent and monovalent cations. Given the wide variety of MXenes, this work opens the door to a new avenue where selective ion‐separation with MXene can be further engineered and optimized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Modulating Iron Crystals with Lattice Chalcophile‐Siderophile Elements for Selective Dechlorinations Over Hydrogen Evolution

Selective dechlorination of organic chlorides over hydrogen evolution reaction (HER) remains a challenge because of their coincidence. Nanoscale zerovalent iron (nFe 0 ) draws a promising picture of in situ groundwater dechlorination, but its indiscriminate reactivity limits the application. Here, nFe 0 crystals are designed with electron shuttles and improved hydrophobic nature based on elemental chalcophile-siderophile characteristics, where chalcophile-siderophile S served as a bridge to allow impregnating nFe 0 crystals with weakly siderophile and strongly chalcophile Cu. Even impregnations of lattice chalcophile-siderophile elements into the nFe 0 crystals are evidenced at both intraparticle and individual-particle levels. The modulated Fe microenvironment and physicochemical properties broke the reactivity-selectivity-longevity-stability trade-off. Compared to nFe 0 , superhydrophobic Cu─S─nFe 0 with lattice expansion promoted dechlorination by 20-fold but inhibited HER by 150-fold, utilizing ≈80–100% electrons from the Fe 0 reservoir. This work demonstrates the concept of engineering nFe 0 lattice with tunable structure-property relationships, mimicking reductive dehalogenases by selectively interacting with halocarbon functional groups for efficient dehalogenation and sustainable groundwater remediation.

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

Selective CO 2 Reduction on 2D Mesoporous Bi Nanosheets

The conversion of CO 2 to value-added products using electrical or solar energy represents an attractive means for the capture and utilization of atmospheric CO 2 . Formate is a popular product from CO 2 reduction, but its reaction selectivity is usually unsatisfactory. Tin-based materials have attracted the most attention for formate production at present. Unfortunately, most of them only exhibit moderate selectivity in a narrow and highly cathodic potential window. In this study, it is demonstrated that traditionally under-explored bismuth has a much greater potential for formate production than tin or other materials. Mesoporous bismuth nanosheets are prepared here by the cathodic transformation of atomic-thick bismuth oxycarbonate nanosheets. They enable the selective CO 2 reduction to formate with large current density, excellent Faradaic efficiency (approximate to 100%) over a broad potential window and great operation stability. Moreover, Bi nanosheets are integrated with an oxygen evolution reaction electrocatalyst in full cells, and achieve efficient and robust solar conversion of CO 2 /H 2 O to formate/O 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Integrated Capture and Conversion of CO 2 to Methanol in a Post‐Combustion Capture Solvent: Heterogeneous Catalysts for Selective CN Bond Cleavage

Abstract An efficient and selective heterogeneous catalyst is identified for the condensed‐phase hydrogenation of captured CO 2 in the presence of an advanced water‐lean post‐combustion capture solvent, ( N ‐(2‐EthoxyEthyl)‐3‐MorpholinoPropan‐1‐Amine), 2‐EEMPA. The catalysts commonly used for gas‐phase CO 2 hydrogenation (e.g., Cu/Zn/Al 2 O 3 ) cause deactivation of amine promoters via N ‐methylation by CO cleavage of formamide intermediates. A heterogeneous catalyst system that suppresses N ‐methylation of amine solvents is identified, demonstrating how Pt, supported by reducible metal oxides CeO 2 or TiO 2 , can be selective for CN cleavage to produce methanol. This is the first known demonstration of integrated low‐temperature thermocatalytic capture and conversion of CO 2 to methanol in an economically viable CO 2 capture solvent. Technoeconomic analyses performed on the state‐of‐technology suggest that methanol can be produced with a minimum selling price of $4.4/gallon ($1,460/metric ton) when using CO 2 captured from a 650 MW natural gas combined cycle plant. Ultimately, a road map of how realistic and achievable improvements to space velocity and methanol selectivity of this integrated process can enable near cost parity to fossil‐derived methanol, with a selling price of ≈$1.4/gal ($470/metric ton), is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Mechanistic Insights into the Structure-Dependent Selectivity of Catalytic Furfural Conversion on Platinum Catalysts

The effects of structure and size on the selectivity of catalytic furfural conversion over supported Pt catalysts in the presence of hydrogen have been studied using first principles density functional theory (DFT) calculations and microkinetic modeling. Four Pt model systems, i.e., periodic Pt(111), Pt(211) surfaces, as well as small nanoclusters (Pt13 and Pt55) are chosen to represent the terrace, step, and corner sites of Pt nanoparticles. Our DFT results show that the reaction routes for furfural hydrogenation and decarbonylation are strongly dependent on the type of reactive sites, which lead to the different selectivity. On the basis of the size-dependent site distribution rule, we correlate the site distributions as a function of the Pt particle size. Our microkinetic results indicate the critical particle size that controls the furfural selectivity is about 1.0 nm, which is in good agreement with the reported experimental value under reaction conditions. This work was supported by National Basic Research Program of China (973 Program) (2013CB733501) and the National Natural Science Foundation of China (NSFC-21306169, 21176221, 21136001, 21101137 and 91334103). This work was also partially supported by the US Department of Energy (DOE), the Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.

biomass conversion↗