25 Search Results

Thermal energy storage (TES) enables concentrating solar power to remain competitive in the renewable energy mix by firming up intermittent solar resource and providing grid services such as load shifting. Free from siting constraints, stand-alone TES systems show promise as a low-cost alternative to traditional pumped-storage hydropower or compressed air energy storage. At the core of all TES technologies is a storage medium, the selection of which governs many aspects of system design and operation. Although the majority of commercial installations utilize molten salts, solid particles can demonstrate stability over wider temperature ranges. This amounts to increased energy storage densitiesmore » and corresponding reductions in system cost which is essential in achieving low-cost energy storage. In this work, eight solid particle candidates are systematically identified and screened for application in a specific particle-TES system. The five most promising candidates (CARBO CP and HSP, calcined flint clay (CFC), brown fused alumina (BFA), and silica sand) are further characterized by size and morphology for fluidization suitability, flowability for particle transport, and thermal stability. Calcined flint clay and brown fused alumina are eventually down-selected due to thermal instability at the target operational temperature of 1200 °C. Although the physical characteristics of CARBO outperform silica sand in all categories examined, the marginal performance gains are considered insufficient to justify the additional media cost so silica sand is selected as the leading candidate. Within the silica sand (α-quartz) space, the high end of Geldart Group B particles is identified to satisfy the target fluidization regime for the application of interest without compromising particle flowability. Here, in focused testing, Silica 460 is shown to exhibit sufficient stability through long-duration (500-hour) thermal and cyclic testing (1200 °C), 10-hour testing at 1400 °C, and in contact with candidate refractory containment materials. Finally, an average heat capacity of 1.1 J/g∙ °C is measured over 300-1200 °C with a quartz inversion enthalpy (ΔH_α-β) of 10.7J/g.« less

Using what has become a celebrated catchphrase, Philip W. Anderson once wrote that “more is different” (Science, Vol. 177, Issue 4047, pp. 393–396, 1972). First formulated in the context of condensed matter, this statement carries far beyond the sole limits of solid-state physics. It emphasizes that collective behavior can be more than the mere sum of what happens for elementary constituents or the mere collation of the evolution of each degree of freedom. Said otherwise, complex phenomena can arise out of the interplay between multiple sub-phenomena each of which can be relatively simple. The process of particle resuspension, in whichmore » discrete particles adhering on a surface are pulled off and carried away by a fluid flow, is another example involving a web of phenomena pertaining to fluid mechanics, particle dynamics and interface chemistry whose cross-effects create an intricate topic. The purpose of this review is to analyze the physics at play in particle resuspension in order to bring insights into the rich complexity of this common but challenging concern. Following the more-is-different vision, this is performed by starting from a range of practical observations and experimental data. We then work our way through the investigation of the key mechanisms which play a role in the overall process. In turn, these mechanisms reveal an array of fundamental interactions, such as particle–fluid, particle–particle and particle–surface, whose combined effects create the tapestry of current applications. At the core of this analysis are descriptions of these physical phenomena and the different ways through which they are intertwined to build up various models used to provide quantitative assessment of particle resuspension. The physics of particle resuspension implies to hold together processes occurring at extremely different space and time scales and models are key in providing a single vehicle to lead us through such multiscale journeys. This raises questions on what makes up a model and one objective of the present work is to clarify the essence of a modeling approach. In spite of its ubiquitous nature, particle resuspension is still at the early stages of developments. Many extensions need to be worked out and revisiting the art of modeling is not a moot point. The need to consider more complex objects than small and spherical particles and, moreover, to come up with unified descriptions of mono- and multilayer resuspension put the emphasis on solid model foundations if we are to go beyond current limits. Further, this is very much modeling in the making and new ideas are proposed to stimulate interest into this everyday but challenging issue in physics.« less

When immersed in a plasma environment, small nano-to micrometer sized solid particles undergo electrical charging by collecting charged species from the plasma. Once charged, these particles interact in peculiar ways with the surrounding plasma, triggering a widespread of interesting physical phenomena. Such systems, also known as complex or dusty plasmas, have been investigated for a few decades already.

The use of carbon supports for late transition-metal nanoparticle catalysts has grown substantially in recent years due to efforts to develop electrocatalysts for clean energy applications and catalysts for new aqueous-phase biomass-related conversions and due to the evolution of new carbon materials with unique properties (e.g., graphene, carbon nanotubes, and so forth). However, much less is known about the bonding energetics of catalytic metal nanoparticles on carbon supports in comparison with oxide supports, which are more common for thermal catalysis. Here, we report the growth morphology and heats of adsorption of Ni vapor deposited onto graphene/Ni(111) at 300 K andmore » 100 K using metal vapor single-crystal adsorption calorimetry and He⁺ low-energy ion scattering (LEIS). These results provide the Ni chemical potential versus particle size, and the Ni/graphene adhesion energy. LEIS intensities suggest that Ni grows as flat-topped face-centered cubic islands with a nearly constant thickness of ~1.5 nm when deposited at 300 K. At 100 K, Ni grows as smaller nanoparticles, well modeled as hemispherical hexagonal close-packed nanoparticles with a density of ~2 × 10¹⁶ particles/m². The Ni chemical potential as a function of average particle diameter in the 0.5 to 4 nm range at 100 K was determined from the heats of Ni gas adsorption. Further, by fitting the measured chemical potential as a function of diameter, we determined an adhesion energy of 3.6 J/m² for large Ni particles on graphene/Ni(111). This adhesion energy is in good agreement with previous scanning tunneling microscopy and density functional theory investigations of Ni/graphene/Ni(111).« less

Abstract. Measurement of light absorption of solar radiation by aerosols is vital for assessing direct aerosol radiative forcing, which affects local and global climate. Low-cost and easy-to-operate filter-based instruments, such as the Particle Soot Absorption Photometer (PSAP), that collect aerosols on a filter and measure light attenuation through the filter are widely used to infer aerosol light absorption. However, filter-based absorption measurements are subject to artifacts that are difficult to quantify. These artifacts are associated with the presence of the filter medium and the complex interactions between the filter fibers and accumulated aerosols. Various correction algorithms have been introduced tomore » correct for the filter-based absorption coefficient measurements toward predicting the particle-phase absorption coefficient (Babs). However, the inability of these algorithms to incorporate into their formulations the complex matrix of influencing parameters such as particle asymmetry parameter, particle size, and particle penetration depth results in prediction of particle-phase absorption coefficients with relatively low accuracy. The analytical forms of corrections also suffer from a lack of universal applicability: different corrections are required for rural and urban sites across the world. In this study, we analyzed and compared 3 months of high-time-resolution ambient aerosol absorption data collected synchronously using a three-wavelength photoacoustic absorption spectrometer (PASS) and PSAP. Both instruments were operated on the same sampling inlet at the Department of Energy's Atmospheric Radiation Measurement program's Southern Great Plains (SGP) user facility in Oklahoma. We implemented the two most commonly used analytical correction algorithms, namely, Virkkula (2010) and the average of Virkkula (2010) and Ogren (2010)–Bond et al. (1999) as well as a random forest regression (RFR) machine learning algorithm to predict Babs values from the PSAP's filter-based measurements. The predicted Babs was compared against the reference Babs measured by the PASS. The RFR algorithm performed the best by yielding the lowest root mean square error of prediction. The algorithm was trained using input datasets from the PSAP (transmission and uncorrected absorption coefficient), a co-located nephelometer (scattering coefficients), and the Aerosol Chemical Speciation Monitor (mass concentration of non-refractory aerosol particles). A revised form of the Virkkula (2010) algorithm suitable for the SGP site has been proposed; however, its performance yields approximately 2-fold errors when compared to the RFR algorithm. To generalize the accuracy and applicability of our proposed RFR algorithm, we trained and tested it on a dataset of laboratory measurements of combustion aerosols. Input variables to the algorithm included the aerosol number size distribution from the Scanning Mobility Particle Sizer, absorption coefficients from the filter-based Tricolor Absorption Photometer, and scattering coefficients from a multiwavelength nephelometer. The RFR algorithm predicted Babs values within 5 % of the reference Babs measured by the multiwavelength PASS during the laboratory experiments. Thus, we show that machine learning approaches offer a promising path to correct for biases in long-term filter-based absorption datasets and accurately quantify their variability and trends needed for robust radiative forcing determination.« less

Concentrating Solar Power (CSP) with thermal energy storage has the potential to be a renewable energy technology with long duration, inexpensive energy storage. Higher temperature operation increases the conversion efficiency and reduces the cost of energy storage. Several emerging CSP designs utilize particles as the solar receiver due to their high temperature stability and low cost. In some designs, the particles are also used as the thermal energy storage (TES) media. In either configuration, an energy transfer is required between the hot particles and the working fluid in the power cycle in a Particle-to-Fluid Heat Exchanger (PtFHX). Understanding the heatmore » transfer between a moving packed bed and a stationary surface is critical to the successful design of a PtFHX. In this paper, a test facility is described in which a moving packed bed of silica sand with particle size 100–600 μm is introduced into the channel formed by two parallel plates, one of which is heated. The effective static thermal conductivity of the particles used for the test are separately measured over the entire range of test temperatures. The inlet and outlet bulk temperatures of the particle flow are measured as are the surface temperatures at several axial locations along the centerline of the plate. The result is the measurement of heat transfer coefficient as a function of temperature for several velocities. The uncertainty of the measurements is presented and the results are compared to model results found in the literature.« less

Feedstock attributes of lignocellulosic biomass, such as particle size, compositional makeup, and moisture content, can vary substantially even within pre-processed materials and have a significant effect on conversion in fast pyrolysis-based processes. However, the economic impacts of these attributes are not well understood. To address this, biomass deconstruction phenomena captured with a versatile particle-scale simulation were linked to techno-economic impacts via reduced-order models. Parametric analysis of the particle-scale model, which was validated using literature data, was used in combination with multiple linear regression models to develop correlations between feedstock attributes and yields of pyrolysis oil, gas, and char. Yields weremore » then correlated with the minimum fuel selling price (MFSP) using a techno-economic model, bridging the gap between physics-based biomass conversion simulations and predictions of MFSP for a catalytic fast-pyrolysis process. Empirical correlations derived from the literature regarding the impact of mineral matter (ash) on oil yield were also considered. The model correlations deployed in the integrated framework capture the impacts of variation in feedstock attributes on the MFSP. Variations in ash were shown to have the biggest impact, varying MFSP by -13%/+22% due to catalytic effects and lower relative amounts of convertible lignocellulosic material. It was also found that, if ash can be controlled to low levels, the increased extractives in forest residues can help compensate for some yield losses associated with increased ash. As a result, other inputs considered (particle size, moisture content, and reactor temperature) had relatively negligible effects on process economics within the ranges analyzed considering particle-scale effects alone.« less

Here, the shape method, a novel approach to obtain the functional form of the γ-ray strength function (γSF), is introduced. In connection with the Oslo method the slope of the nuclear level density (NLD) and γSF can be obtained simultaneously even in the absence of neutron resonance spacing data. The foundation of the shape method lies in the primary γ-ray transitions which preserve information on the functional form of the γSF. The shape method has been applied to ⁵⁶Fe, ⁹²Zr, and ¹⁶⁴Dy, which are representative cases for the variety of situations encountered in typical NLD and γSF studies. The comparisonsmore » of results from the shape method to those from the Oslo method demonstrate that the functional form of the γSF is retained regardless of nuclear structure details or J^π values of the states fed by the primary transitions.« less