Automated method for overlay sample plan optimization based on spatial variation modeling

2001 ◽  
Author(s):  
Xuemei Chen ◽  
Moshe E. Preil ◽  
Mathilde Le Goff-Dussable ◽  
Mireille Maenhoudt
Keyword(s):  
Spatial Variation ◽  
Automated Method ◽  
Plan Optimization ◽  
Sample Plan

Overlay excursion management through sample plan optimization and cycle time reduction

2003 ◽  
Author(s):  
Xuemei Chen ◽  
Ming-Yeon Hung ◽  
Kelly Kuo ◽  
Steven Fu ◽  
Geoge Shanthikumar ◽  
...  
Keyword(s):  
Cycle Time ◽  
Plan Optimization ◽  
Cycle Time Reduction ◽  
Time Reduction ◽  
Sample Plan

Computer Indexing of Electron Diffraction Patterns Including the Effects of Lattice Symmetry

1977 ◽  
Vol 35 ◽  
pp. 22-23
Author(s):  
J. S. Lally ◽  
R. J. Lee
Keyword(s):  
Electron Diffraction ◽  
Zone Axis ◽  
Crystal Thickness ◽  
Double Diffraction ◽  
Automated Method ◽  
Lattice Symmetry ◽  
Intensity Calculations ◽  
Unknown Structure ◽  
Diffraction Patterns ◽  
Orientation Parameters

In the 50 year period since the discovery of electron diffraction from crystals there has been much theoretical effort devoted to the calculation of diffracted intensities as a function of crystal thickness, orientation, and structure. However, in many applications of electron diffraction what is required is a simple identification of an unknown structure when some of the shape and orientation parameters required for intensity calculations are not known. In these circumstances an automated method is needed to solve diffraction patterns obtained near crystal zone axis directions that includes the effects of systematic absences of reflections due to lattice symmetry effects and additional reflections due to double diffraction processes.Two programs have been developed to enable relatively inexperienced microscopists to identify unknown crystals from diffraction patterns. Before indexing any given electron diffraction pattern, a set of possible crystal structures must be selected for comparison against the unknown.

Digital representation of spatial variation of multivariate landscape data

2006 ◽  
Vol 7 (2) ◽  
pp. 181-188 ◽  
Author(s):  
A. Altobelli ◽  
E. Bressan ◽  
E. Feoli ◽  
P. Ganis ◽  
F. Martini
Keyword(s):  
Spatial Variation ◽  
Digital Representation

Automated method for isolation of human pancreatic islets

Diabetes ◽  
1988 ◽  
Vol 37 (4) ◽  
pp. 413-420 ◽  
Author(s):  
C. Ricordi ◽  
P. E. Lacy ◽  
E. H. Finke ◽  
B. J. Olack ◽  
D. W. Scharp
Keyword(s):  
Pancreatic Islets ◽  
Human Pancreatic Islets ◽  
Automated Method

Function of coprophagous beetles (Coleoptera: Scarabaeidae, Geotrupidae, Hydrophilidae) in cattle pastures inferred from pitfall trapping data

2010 ◽  
Vol 27 (2) ◽  
pp. 85-91 ◽  
Author(s):  
Martin Šlachta ◽  
Jan Frelich ◽  
Tomáš Tonka
Keyword(s):  
Seasonal Variation ◽  
Spatial Variation ◽  
Dry Weight ◽  
Seasonal Distribution ◽  
The Other ◽  
Pitfall Trapping ◽  
Other Hand ◽  
Nested Anova ◽  
Species Groups ◽  
Dung Decomposition

Function of coprophagous beetles (Coleoptera: Scarabaeidae, Geotrupidae, Hydrophilidae) in cattle pastures inferred from pitfall trapping dataAn analysis of data on the dry weight biomass of coprophagous beetles in standardized dung (4.5 l) was conducted in order to characterize the spatial and the seasonal distribution of the beetles' biomass in cattle pastures and to elucidate their function in dung decomposition. Nested Anova with factors of farm, site (nested in farm), seasonal period and year was used to evaluate the effect of these factors on the biomass of four functional species groups: the dung dwellers ofScarabaeidae(subfamilyAphodiinae), the dung dwellers ofHydrophilidae, the small tunnellers ofScarabaeidae(subfamilyCoprinae) and the large tunnellers ofGeotrupidae. The spatial variation of biomass (between the sites and the farms) was insignificant (P>0.05) in the two dung-dweller groups and in the large-tunnellers group. On the other hand, a significant (P<0.05) seasonal variation of biomass was found in all but the large tunneller group. In dung dwellers, the spring biomass was formed mainly by two species,Aphodius prodromusandA. sphacelatus. In summer, most of the biomass was accounted for bySphaeridium lunatum, S. scarabaeoidesandA. rufipes. In the two tunneller groups,Onthophagus fracticornis, Geotrupes stercorariusandG. spinigerformed a majority of the biomass in dung.

Elucidating the Weakly Reversible Cs-Pb-Br Perovskite Nanocrystal Reaction Network with High-Throughput Maps and Transformations

2020 ◽  
Author(s):  
Jakob Dahl ◽  
Xingzhi Wang ◽  
Xiao Huang ◽  
Emory Chan ◽  
Paul Alivisatos
Keyword(s):  
High Throughput ◽  
Dynamic Equilibrium ◽  
Reaction Network ◽  
Substantial Impact ◽  
Equilibrium Behavior ◽  
Automated Method ◽  
Lead Bromide ◽  
Different Shapes ◽  
Complex Chemistry ◽  
Lead Halide

<p>Advances in automation and data analytics can aid exploration of the complex chemistry of nanoparticles. Lead halide perovskite colloidal nanocrystals provide an interesting proving ground: there are reports of many different phases and transformations, which has made it hard to form a coherent conceptual framework for their controlled formation through traditional methods. In this work, we systematically explore the portion of Cs-Pb-Br synthesis space in which many optically distinguishable species are formed using high-throughput robotic synthesis to understand their formation reactions. We deploy an automated method that allows us to determine the relative amount of absorbance that can be attributed to each species in order to create maps of the synthetic space. These in turn facilitate improved understanding of the interplay between kinetic and thermodynamic factors that underlie which combination of species are likely to be prevalent under a given set of conditions. Based on these maps, we test potential transformation routes between perovskite nanocrystals of different shapes and phases. We find that shape is determined kinetically, but many reactions between different phases show equilibrium behavior. We demonstrate a dynamic equilibrium between complexes, monolayers and nanocrystals of lead bromide, with substantial impact on the reaction outcomes. This allows us to construct a chemical reaction network that qualitatively explains our results as well as previous reports and can serve as a guide for those seeking to prepare a particular composition and shape. </p>

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