A behavioral micro simulation case study: Distribution center location
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Reconstructing high-resolution flow fields from sparse measurements is a major challenge in fluid dynamics. Existing methods often vectorize the flow by stacking different spatial directions on top of each other, hence confounding the information encoded in different dimensions. Here, we introduce a tensor-based sensor placement and flow reconstruction method which retains and exploits the inherent multidimensionality of the flow. We derive estimates for the flow reconstruction error, storage requirements and computational cost of our method. We show, with examples, that our tensor-based method is significantly more accurate than similar vectorized methods. Furthermore, the variance of the error is smaller when using our tensor-based method. While the computational cost of our method is comparable to similar vectorized methods, it reduces the storage cost by several orders of magnitude. The reduced storage cost becomes even more pronounced as the dimension of the flow increases. We demonstrate the efficacy of our method on three examples: a chaotic Kolmogorov flow, in situ and satellite measurements of the global sea surface temperature and three-dimensional unsteady simulated flow around a marine research vessel.
The impact of cationic and Lewis acidic functional groups installed in the primary or secondary coordination sphere (PCS or SCS) of an (electro)catalyst is known to vary depending on the precise positioning of those groups. However, it is difficult to systematically probe the effect of that position. In this report we probe the effect of the functional group position and identity on the observed reduction potentials (E p,c ) using substituted iron clusters, [Fe 4 N(CO) 11 R] n , where R = NO + , PPh 2 -CH 2 CH 2–9 BBN, ( Me PTA + ) 2 , ( Me PTA + ) 4 , and H + , where n = 0, -1, +1, or +3 (9-BBN is 9-borabicyclo(3.3.1)nonane and Me PTA + is 1-methyl-1 azonia-3,5-diaza-7-phosphaadamantane). The cationic NO + and H + ligands cause anodic shifts of 700 and 320 mV, respectively, in E p,c relative to unsubstituted [Fe 4 N(CO) 12 ] – . Infra-red absorption band data, νCO, suggests that some of the 700 mV shift by NO + results from electronic changes to the cluster core. Furthermore, this contrasts with the effects of cationic MePTA + and H + which cause primarily electrostatic effects on E p,c . Lewis acidic 9-BBN in the SCS had almost no effect on E p,c .
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Brønsted (BAS), Lewis (LAS), and surface Brønsted (SBAS) acid sites have been investigated for polyethylene (PE) upcycling by zeolite catalysts, but there is no clear consensus regarding their catalytic roles, partly due to the complexity of the catalysts used and varying reaction conditions across studies. This work systematically determined how these sites impact PE conversion rates and product distributions by utilizing a suite of microporous MFI catalysts with varying Si/Al ratios, acid site densities, and inherent mesoporosities. PE conversion rates did not trend with total BAS or LAS densities due to a combination of internal mass transfer limitation and the apparent inability of LAS alone to cleave C–C bonds, but a strong, statistically significant correlation was present with respect to SBAS density and mesopore surface area, jointly, owing to accelerated polymer activation on external surfaces to smaller diffusion-limited chains. However, ingress of these SBAS-derived fragments ultimately remained rate limiting, as demonstrated by solid conversion rates that increased with mesopore surface area at similar SBAS density and likewise increased with SBAS density at similar mesopore surface area. In batch PE cracking reactions, light gaseous product selectivities were most sensitive to total BAS, with higher densities generally exhibiting higher selectivity to C 3 and linear C 4 –C 7 products and higher alkane/alkene product ratios, consistent with increased β-scission turnovers. Insights from this work help systematically clarify the roles of BAS, LAS, SBAS, and mesopores in PE cracking reactions and inform the development of tailored zeolite catalysts for efficient polyolefin upcycling.
A melting layer (ML) detection algorithm for cloud radar with polarimetric capability was developed and applied to the cloud radar data collected from five different sites around the world for several years. The retrieved melting layer top height (MLH) showed a very good correspondence with the ECMWF Reanalysis 5 zero degree level data for all five sites. The ML characteristics were distinctively different for different sites, revealing climatological characteristics of ML forming clouds in different regions. Generally, ML tended to occur more frequently in summer than in winter except for a maritime site, where low stratiform clouds formed frequently in summer, the top of which might be lower than the freezing level. In contrast, at two Arctic sites, ML occurred almost exclusively in summer because it was too cold to have an ML in the other seasons. The MLH also varied significantly from site to site but generally was higher during warmer seasons. Based on MLH, two new indices, bulk temperature lapse rate (BLR) and relative depth (RD) of liquid cloud below MLH (RD) were developed, which were useful to explain the environmental characteristics of the five sites. BLR generally increased with the surface temperature at all sites except at the marine site that showed an opposite trend, where a unique synoptic pattern in winter generated high BLR in this cold season. Finally, these findings confirm that studies on thermodynamic structures using cloud radars can be broadened, taking advantage of BLR and RD information, as these indices can represent environmental thermodynamic characteristics of the clouds that have ML.
Single-atom catalysts (SACs) have been applied in many fields due to their superior catalytic performance. Because of the unique properties of the single-atom-site, using the single atoms as catalysts to synthesize SACs is promising. In this work, we have successfully achieved Co 1 SAC using Pt 1 atoms as catalysts. More importantly, this synthesis strategy can be extended to achieve Fe and Ni SACs as well. X-ray absorption spectroscopy (XAS) results demonstrate that the achieved Fe, Co, and Ni SACs are in a M1-pyrrolic N 4 (M= Fe, Co, and Ni) structure. Density functional theory (DFT) studies show that the Co(Cp) 2 dissociation is enhanced by Pt 1 atoms, thus leading to the formation of Co 1 atoms instead of nanoparticles. These SACs are also evaluated under hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), and the nature of active sites under HER are unveiled by the operando XAS studies. These new findings extend the application fields of SACs to catalytic fabrication methodology, which is promising for the rational design of advanced SACs.
Surface structure affects the growth, shape and properties of nanoparticles. In wet chemical syntheses, metal additives and surfactants are used to modify surfaces and guide nanocrystal growth. To understand this process, it is critical to understand how the surface structure, and hence its energy, is modified. However, measuring the type and arrangement of atoms at hard-soft interfaces on nanoscale surfaces, especially in the presence of surfactants, is extremely challenging. Here, we determine the atomic structure of the hard-soft interface in a metallic nanoparticle by developing low-dose imaging conditions in four-dimensional scanning transmission electron microscopy that are preferentially sensitive to surface adatoms. By revealing experimentally the copper additives and bromide surfactant counterion at the surface of a gold nanocuboid and quantifying their interatomic distances, our direct, low-dose imaging method provides atomic-level understanding of chemically sophisticated nanomaterial surface structures. These measurements of the atomic structure of the hard-soft interface provide the information necessary to understand and quantify surface chemistries and energies and their pivotal role in nanocrystal growth.
Using satellite imagery we show that the installation footprint of grid-scale lithium-ion batteries is often comparable to much less energy-dense technologies such as aqueous battery systems.
An externally exposed V dopant imposes H-atom uptake at the polyoxotungstate surface and dictates the proton–coupled electron transfer mechanism.
The Advanced Test Reactor’s (ATR’s) distinctive ability to provide a wide range of irradiation conditions is attractive for programs pursuing fuel qualification experiments. These potentially high-fuel-load experiments are a relatively new development and produce unexplored effects on nearby experiments. Here, this paper explores how photon heating of such an experiment may affect other nearby experiment programs, ultimately serving to better inform decisions regarding experiment design and risks to programmatic goals. The MC21 (Monte Carlo for the 21st Century) code is used to model and study how gamma heat generation rates and axial effects impact different ATR positions. The results reveal that the proximity of a given experiment’s position to the high-fuel-load one can significantly alter that experiment’s expected axial profile.