Phytochemical and chemotaxonomic study on the dried rhizome of Menispermum dauricum DC
Not Available
Ren, Wenjing↗
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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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An investigation of the multi-mode Richtmyer-Meshkov instability at a gas/HE interface using Pagosa
Here, in this work, we present a hydrocode Pagosa and explore the Richtmyer-Meshkov Instability (RMI) at an air/high explosive (HE) interface for the first time that is important but has not received much attention yet in the high explosive safety field. Thus, the presented Pagosa can be expected to predict the whole deflagration-to-detonation transition (DDT) process in future. In Pagosa, spatial discretization is implemented on cubic staggered grids by computing different variables at the vertex and the cell center, respectively, a special operator-splitting technique is employed to reduce the computational cost, and an artificial viscosity is added to handle the discontinuous shock waves in our simulations. To quantitatively evaluate the capability of Pagosa to solve these kinds of instabilities, the single mode Rayleigh-Taylor instability (RTI) and the multimode RMI at an air/SF 6 interface are first performed, respectively. The Pagosa results are compared with the related numerical solutions in the existing references and the experimental result. Moreover, a theoretical derivation of growth of RTI is also provided based on our numerical method. Subsequently, we explore the multi-mode RMI at an air/HE interface as well as the effects of several factors using Pagosa. Numerical results show that Pagosa is a powerful toolset to generate the right structures and the amplitude of RTI and RMI at an air/SF 6 interface. The solid HE can be penetrated by a strong shock wave and forms RMI deformations. The RMI at an air/HE interface behaves very different than at an air/SF 6 interface, periodic, decreased oscillation is observed due to material character, and is very sensitive to the initial simulation settings, that is, a tiny change in physical quantities will lead to a remarkable RMI structure, which is also observed in a shock bubble interaction. The findings in this work are significant, and will present a new insight for the high explosive field.
97 MATHEMATICS AND COMPUTING↗
Nitrogen-doped graphene-wrapped Cu 2 S as a superior anode in sodium-ion batteries
Sodium-ion batteries (SIBs) have been attracting an ever-growing research interest, mainly ascribed to their cost-effectiveness. However, SIBs have been significantly hindered by lack of a suitable anode. Herein, an exceptional Cu 2 S-based composite anode is developed via a facile ball-milling method, in which Cu 2 S particles are wrapped by nitrogen-doped graphene sheets (Cu 2 S@NG). This Cu 2 S@NG composite anode enables extremely long cycling life, ultra-stable cyclability with high capacity, and excellent rate capability. The superior performance of the Cu 2 S@NG composite is owing to its intriguing core-shell structure and the exceptional properties of both the Cu 2 S and NG. In this study, it is found that the NG shell yields multiple merits in improving the performance of Cu 2 S: (i) mitigating the loss of active materials, (ii) constituting a stable interface, (iii) providing improved electrical conductivity and good ionic transfer, and (iv) enhancing mechanical integrity. Additionally, the vital effects of different voltage windows and a surface coating via atomic layer deposition on further enhancing performance are clarified. Significantly, the electrochemical mechanism of Cu 2 S during sodiation/desodiation is unveiled using advanced synchrotron-based in-situ X-ray diffraction and X-ray adsorption spectroscopy. This work represents a great advance in seeking high-performance anodes in SIBs.
25 ENERGY STORAGE↗
Inferring colloidal interaction from scattering by machine learning
A machine learning solution for the potential inversion problem in elastic scattering is outlined. The inversion scheme consists of two major components, a generative network featuring a variational autoencoder which extracts the targeted static two-point correlation functions from experimentally measured scattering cross sections, and a Gaussian process framework which probabilistically infers the relevant structural parameters from the inverted correlation functions. Via a case study of charged colloidal suspensions, the feasibility of this approach for quantitative study of molecular interaction is critically benchmarked and its merit over existing deterministic approaches, in terms of numerical accuracy and computationally efficiency, is demonstrated.
36 MATERIALS SCIENCE↗
Flame aerosol synthesis of hollow alumina nanoshells for application in thermal insulation
Commercial implementation of hollow nanoshell materials is often limited by difficult scale-up and high cost. Here we present a scalable, continuous, and potentially low-cost route to hollow nanostructured materials using a High Temperature Reducing Jet flame aerosol reactor. The key advantage of this process over traditional flame aerosol synthesis methods is separation of flame chemistry and particle formation, which allows production of hollow nanoshells from an aqueous salt solution without any template or surfactant. We produced amorphous hollow alumina with an average diameter of 181 nm and shell thickness below 10 nm, and demonstrated the generality of the method by also producing hollow SiO 2 , ZrO 2 , Ga 2 O 3 , and Co 2 O 3 . We characterized the morphology, phase transition, thermal stability, and thermal conductivity of the flame-made hollow alumina by electron microscopy, x-ray diffraction, and thermal analysis methods. As a prototypical application, we incorporated hollow alumina into thermal insulation, combining it with common fiberglass insulation to reduce the thermal conductivity by 30% relative to pure fiberglass, to 0.028 W m -1 K -1 while maintaining robust fire-resistance and elasticity.
36 MATERIALS SCIENCE↗
Na + -gated nanochannel membrane for highly selective ammonia (NH 3 ) separation in the Haber-Bosch process
Currently, cryogenic condensation is the predominant process for recovering ammonia (NH 3 ) in the Haber-Bosch (HB) process, which is highly energy intensive. To be more compatible with the reaction conditions in the HB process and thus minimize the pressure and temperature swing during reactant recycling, energy-efficient technologies for NH 3 extraction at elevated temperature and pressure are greatly needed. In this work, the Na + -gated nanochannel membrane, shown exclusively for water conduction in our previous work, also exhibited highly NH 3 -selective performance, with NH 3 /H 2 selectivity as high as 4,280 and NH 3 /N 2 selectivity > 10,000 at temperature up to 250 °C and pressure up to 35 bar. Excellent stability of the Na + -gated nanochannel membrane was demonstrated during a 100-h run in ternary NH 3 /H 2 /N 2 gas mixture at 200 °C and 35 bar, consistent with structural characterization by X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and Fourier transfer infrared (FTIR) spectroscopy. A techno-economic analysis (TEA) was conducted for the HB process using the Na + -gated nanochannel membrane and the traditional HB process with condenser. Finally, under the optimized separation conditions, > 80% energy savings and approximately 20% reduction of the net NH 3 production cost can be achieved, demonstrating the great potential of the Na + -gated nanochannel membrane for NH 3 separation in the HB process.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Creation of hollow silica-fiberglass soft ceramics for thermal insulation
Hollow-structured materials show promise in thermal insulation because the shells encapsulating gaseous voids can interrupt heat transport pathways. Here, in this study, we present two low-cost routes to fabricate hollow silica nanoshells, via gas-phase and liquid-phase methods. The gas-phase synthesis method generates hollow shells by a droplet surface precipitation mechanism in a flame aerosol reactor. The liquid-phase synthesis route forms hollow shells by removal of a carbon template, which is produced by hydrothermal reaction of glucose. Both approaches (gas- and liquid-phase) provide hollow silica with amorphous structure, low thermal conductivity (0.023 and 0.026 W m –1 K –1 ), small particle size (442 and 383 nm), thin shell (35 and 36 nm), and low density (0.015 and 0.033 g cm –3 ). We employed high shear mechanical mixing to fabricate hollow silica-fiberglass composite ceramics. The resulting three-dimensional network provides the ceramics with robust mechanical elasticity and fire-retardancy while maintaining low thermal conductivity, dramatically outperforming an analogous material using commercial silica gel in place of the hollow nanoshells. Our findings provide two practical routes to synthesize hollow silica, either of which can be used to manufacture a class of hollow shell-fiber nanocomposite soft ceramics for energy-saving applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Kinetic modeling of NH3-selective catalytic reduction (SCR) over a mildly hydrothermally aged commercial Cu-SSZ-13 catalyst
Not Available
Wei, Lai (ORCID:0000000330352851)↗
Kinetic model describing self-limiting CO 2 diffusion in supported amine adsorbents
A reaction–diffusion shrinking core model describing the decay in diffusivity of supported amine sorbents upon CO 2 sorption under both simulated direct air capture and point source capture conditions is described. The decay in CO 2 diffusivity is associated with crosslinking in the aminopolymer samples and general pore blockage in the amino-silane derived samples, which occurs as CO 2 is adsorbed. The model is used to extract four kinetic parameters that govern the CO 2 uptake kinetics and working capacity: an apparent reaction rate constant, an initial effective diffusivity, and two dimensionless decay parameters. Ideally, an initially reaction limited system would allow for direct determination of the intrinsic reaction rate constant; however, sorption experiments suggest mass transfer resistances related to gas mixing, external boundary layers and intraparticle diffusion are present. Reaction rate constants are determined and agree well with theoretical values predicted with the Eyring equation parameterized using density functional theory energies from literature sources. The kinetic performance is expressed as the average effective diffusivity as a function of average conversion, which can be correlated to the dispersion of sorption sites on the support and the morphology of the active sorbent phase. Four supports are impregnated or grafted with amines, SBA-15, single-walled zeolite nanotubes (ZNT), Syloid SiO 2 , and γ-Al 2 O 3 . Due to its pore structure, γ-Al 2 O 3 supported amines can be modeled at the μm scale or at the nm scale, where the shell balance is on the μm-sized macroporous particle aggregate or on the nm-sized amine film on the surface of the Al 2 O 3 nanoparticles, which comprise the spherical particle aggregates. Faster diffusion rates are maintained under 400 ppm rather than 10% CO 2 due to a slower reaction rate giving a slower decay in diffusivity. In conclusion, this work provides a first principles kinetic analysis of CO 2 sorption where previous models are semi-empirical and use arbitrary kinetic parameters.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Understanding polymer-porous solid interactions based on small gas molecule adsorption behavior
Not provided.
Engineering↗
Quantifying the anomalous water absorption behavior of cement mortar in view of its physical sensitivity to water
The one-dimensional water absorption into cement-based materials, possibly the simplest case of unsaturated water flow playing a fundamental role in predicting mass transport and durability, is still far from being completely understood due to several puzzling anomalies. Considering the water sensitivity of C-S-H gels (swell upon wetting and contract upon drying), a modified Richards equation (MRE) is proposed to quantify the anomalous water absorption into cement-based materials of changing porosity. Consistent experimental tests on a cement mortar and calculations indicate that the MRE with time-decaying water permeability can quantitatively capture the long-term absorption with two linear stages and a nonlinear transition stage between them. The water sensitivity is validated to be responsible for the anomalous deviation of water absorption from the classical square root of time law. It also partially contributes to the anomalous dependence of sorptivity on the temperature-dependent surface tension and viscosity of water and many organic liquids.
36 MATERIALS SCIENCE↗
On the moisture migration of concrete subject to high temperature with different heating rates
A better understanding of moisture migration in concrete at high temperature can play an important role to improve the fire-resistance and radiation-shielding capability of concrete structures. In this regard, within the numerical framework of Multi-physics Lattice Discrete Particle Model, the moisture clog in concrete during heating is defined as the moisture-saturated region between the so-called “water front” and “water back” (isosurfaces of saturation = 1). The moisture migration in concrete subject to slow and fast heating has been investigated by simulating experimental tests in which moisture has been monitored via different techniques, namely 3D Neutron Tomography and Ground-Penetrating Radar. An overall consistency between experimental and numerical results has been observed, indirectly proving the effectiveness of numerical modelling and experimental monitoring of moisture migration.
36 MATERIALS SCIENCE↗
Formation, structure, and thermal stability evolution of ternesite based on a single-stage sintering process
Highlights: • The synthesis of high-purity ternesite based on a single-stage sintering process was firstly studied. • The formation mechanism and crystallization behaviour of ternesite during sintering were investigated. • The structure perfection and symmetry of ternesite crystals were increased with its growth. • The growth and structural development of ternesite crystals during sintering resulted in a higher thermal stability of itself. Ternesite was prepared via a single-stage solid-state reaction from stoichiometric quantities of the CaCO{sub 3}, SiO{sub 2} and CaSO{sub 4}·2H{sub 2}O precursors. In this paper, the formation, structure, and thermal stability evolution of ternesite during sintering were investigated ex situ after quenching. The optimal sintering temperature for the formation of high-purity ternesite was approximately 1200 °C for 12 h, of which the purity level can reach as high as 96.3%. The results from scanning electron microscopy analysis suggest that the formation of ternesite benefited from the preformation of the intermediate silicate phase. Increasing the sintering temperature from 1100 °C to approximately 1250 °C was favourable for the growth of ternesite crystals, and a prolonged duration can also promote this behaviour. The structural perfection and symmetry of ternesite crystals increased with its growth, which was demonstrated by a multimethod approach. By means of thermal analysis, the growth and structural development of ternesite crystals during sintering eventually resulted in a higher thermal stability.
36 MATERIALS SCIENCE↗
Structural origin of size effect on piezoelectric performance of Pb(Zr,Ti)O 3
Grain size effect plays a vital role in piezoelectric performance from both scientific and technological view. However, the underlying structural mechanism related to grain size is still unclear. In the present study, the structural mechanism of grain size effect on piezoelectric performance has been revealed in the prototype Pb(Zr, Ti)O 3 system by using in-situ synchrotron X-ray diffraction. The miniaturization of grain size tends to favor the appearance of higher symmetric tetragonal phase, while a single monoclinic phase is determined in the coarse-grained ceramics. The direct structural evidence reveals that both tetragonal and monoclinic phases in the fine-grained ceramics are less sensitive to the electric field, corresponding to the inferior piezoelectric performance, while the single monoclinic phase in the coarse-grained ceramics is more active to be driven by the electric field, generating good piezoelectric behavior. Both domain switching ability and lattice strain are suppressed with decreasing grain size, which directly leads to the deterioration in piezoelectric performance. In conclusion, the current results will benefit the structural understanding of the size effect of piezoelectric and other related systems.
36 MATERIALS SCIENCE↗
Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor
With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .
42 ENGINEERING↗