scholarly journals Optimization models for semiconductor dopant profiling

2007 ◽  
pp. 91-115 ◽  
Author(s):  
Martin Burger ◽  
Michael Hinze ◽  
Rene Pinnau
Keyword(s):  
Optimization Models ◽  
Dopant Profiling

Modeling And Optimization Of The Construction Organization's Production Program

2020 ◽  
pp. 49-56
Keyword(s):  
Software Package ◽  
Target Function ◽  
Optimization Models ◽  
Labor Resource ◽  
Production Program ◽  
Construction Organizations ◽  
Source Data ◽  
Labor Resources ◽  
Construction Organization ◽  
Planning Production

In the article, the author considers the problems of complex algorithmization and systematization of approaches to optimizing the work plans of construction organizations (calendar plans) using various modern tools, including, for example, evolutionary algorithms for "conscious" enumeration of options for solving a target function from an array of possible constraints for a given nomenclature. Various typical schemes for modeling the processes of distribution of labor resources between objects of the production program are given, taking into account the array of source data. This data includes the possibility of using the material and technical supply base (delivery, storage, packaging) as a temporary container for placing the labor resource in case of released capacity, quantitative and qualification composition of the initial labor resource, the properties of the construction organization as a counterparty in the contract system with the customer of construction and installation works etc. A conceptual algorithm is formed that is the basis of the software package for operational harmonization of the production program ( work plans) in accordance with the loading of production units, the released capacities of labor resources and other conditions stipulated by the model. The application of the proposed algorithm is most convenient for a set of objects, which determines the relevance of its implementation in optimization models when planning production programs of building organizations that contain several objects distributed over a time scale.

2D carrier Density Mapping Using SNDM-dC/dV and dC/dz of SiC Power MOSFET

2019 ◽  
Author(s):  
Jing-jiang Yu ◽  
T. Yamaoka ◽  
T. Aiso ◽  
K. Watanabe ◽  
Y. Shikakura ◽  
...  
Keyword(s):  
Carrier Density ◽  
Environmental Control ◽  
Boundary Region ◽  
Power Mosfet ◽  
Dopant Profiling ◽  
Density Mapping ◽  
Resolution Observation ◽  
Develop Software ◽  
20 Nm ◽  
High Resolution Observation

Abstract Scanning nonlinear dielectric microscopy is continuously developed as an AFM-derived method for 2D dopant profiling of semiconductor devices. In this paper, the authors apply 2D carrier density mapping to Si and SiC and succeed a high resolution observation of the SiC planar power MOSFET. Furthermore, they develop software that combines dC/dV and dC/dz images and expresses both density and polarity in a single distribution image. The discussion provides the details of AFM experiments that were conducted using a Hitachi environmental control AFM5300E system. The results indicated that the carrier density decreases in the boundary region between n plus source and p body. The authors conclude that although the resolutions of dC/dV and dC/dz are estimated to be 20 nm or less and 30 nm or less, respectively, there is a possibility that the resolution can be further improved by using a sharpened probe.

Extending Electrical Scanning Probe Microscopy Measurements of Semiconductor Devices Using Microwave Impedance Microscopy

2015 ◽  
Author(s):  
Benedict Drevniok ◽  
St. John Dixon-Warren ◽  
Oskar Amster ◽  
Stuart L Friedman ◽  
Yongliang Yang
Keyword(s):  
Scanning Probe Microscopy ◽  
Semiconductor Devices ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Scanning Probe ◽  
Cross Sectional ◽  
Probe Microscopy ◽  
Dopant Profiling ◽  
Capacitance Voltage

Abstract Scanning microwave impedance microscopy was used to analyze a CMOS image sensor sample to reveal details of the dopant profiling in planar and cross-sectional samples. Sitespecific capacitance-voltage spectroscopy was performed on different regions of the samples.

COMPARISON OF TWO OPTIMIZATION MODELS FOR CONSTRUCTING PATTERNS IN THE METHOD OF LOGICAL ANALYSIS OF DATA

2020 ◽  
pp. 10-13
Author(s):  
Р.И. Кузьмич ◽  
А.А. Ступина ◽  
С.Н. Ежеманская ◽  
А.П. Шугалей
Keyword(s):  
Objective Function ◽  
Optimization Model ◽  
Logical Analysis ◽  
Optimization Models ◽  
Logical Analysis Of Data

Предлагаются две оптимизационные модели для построения информативных закономерностей. Приводится эмпирическое подтверждение целесообразности использования критерия бустинга в качестве целевой функции оптимизационной модели для получения информативных закономерностей. Информативность, закономерность, критерий бустинга, оптимизационная модель Comparison of two optimization models for constructing patterns in the method of logical analysis of data Two optimization models for constructing informative patterns are proposed. An empirical confirmation of the expediency of using the boosting criterion as an objective function of the optimization model for obtaining informative patterns is given.

scholarly journals A comparison of optimization models for lumber production planning

2015 ◽  
Vol 36 (2) ◽  
pp. 239-246 ◽  
Author(s):  
Francisco P Vergara ◽  
Cristian D Palma ◽  
Héctor Sepúlveda
Keyword(s):  
Production Planning ◽  
Optimization Models

Relaxed optimization models for spectrum auctions

2020 ◽  
Author(s):  
Carlos Agualimpia-Arriaga ◽  
Carlos Adrian Correa-Florez ◽  
Carlos Ivan Paez Rueda
Keyword(s):  
Optimization Models ◽  
Spectrum Auctions

Dual hesitant fuzzy decision making in optimization models

2021 ◽  
Vol 154 ◽  
pp. 107103
Author(s):  
Fanyong Meng ◽  
Jie Tang ◽  
Witold Pedrycz
Keyword(s):  
Decision Making ◽  
Optimization Models ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision

scholarly journals Optimization models for computer data storage design: An application

1994 ◽  
Vol 26 (4) ◽  
pp. 743-756
Author(s):  
Marco Gagliardi ◽  
Cosimo Spera
Keyword(s):  
Data Storage ◽  
Optimization Models ◽  
Computer Data
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