The Study of ESD Destructive Mechanism for PN-Junction

1996 ◽  
Author(s):  
N. Wakai ◽  
M. TsuTsumi ◽  
T. Setoya
Keyword(s):  
Energy Density ◽  
Thermal Diffusion ◽  
Electric Discharge ◽  
Intermediate Region ◽  
Human Body Model ◽  
Machine Model ◽  
Pn Junction ◽  
Special Cases ◽  
Equilibrium Region

Abstract Mechanism of destruction caused by electrostatic discharge of PN junction was examined from two viewpoints; classification of destruction mode with consideration to destructive energy density, and comparison of destruction shape. Destructive energy density of PN junction was calculated based on Speakman model, and destruction mode was classified by Wunsch-Bell plot. As a result of Wunsch-Bell plot, electric discharge which occur at low resistance, for example machine model (MM: C∙R = 200pF ∙ 0Ω), resulted in adiabatic destruction that does not involve thermal diffusion. With electric discharge at high resistance, for example human body model (HBM: C∙R = 100pF ∙ 1500Ω), excessive destruction in intermediate region that involves thermal diffusion, and depending on the device, destruction at equilibrium region were proven to be reproducible. In case of MM, (adiabatic region destruction) destruction was confirmed in a wide extent of the joint part, but in case of HBM (intermediate region destruction) destruction was confirmed near the center of the joint part. From this fact, it was found that by verifying the places of destruction and their shapes, although in special cases, it is possible to know the destruction mode when destruction occurs.

On the Dynamic Isotropy of Mechanisms With Two Degrees of Freedom

2005 ◽  
Author(s):  
Raffaele Di Gregorio ◽  
Alessandro Cammarata ◽  
Rosario Sinatra
Keyword(s):  
Finite Number ◽  
Degrees Of Freedom ◽  
Point Of View ◽  
Closed Curves ◽  
Special Cases ◽  
Dynamic Performances ◽  
Definition Of ◽  
Geometric Locus

The comparison of mechanisms with different topology or with different geometry, but with the same topology, is a necessary operation during the design of a machine sized for a given task. Therefore, tools that evaluate the dynamic performances of a mechanism are welcomed. This paper deals with the dynamic isotropy of 2-dof mechanisms starting from the definition introduced in a previous paper. In particular, starting from the condition that identifies the dynamically isotropic configurations, it shows that, provided some special cases are not considered, 2-dof mechanisms have at most a finite number of isotropic configurations. Moreover, it shows that, provided the dynamically isotropic configurations are excluded, the geometric locus of the configuration space that collects the points associated to configurations with the same dynamic isotropy is constituted by closed curves. This results will allow the classification of 2-dof mechanisms from the dynamic-isotropy point of view, and the definition of some methodologies for the characterization of the dynamic isotropy of these mechanisms. Finally, examples of applications of the obtained results will be given.

scholarly journals The characteristics of thermal diffusion

1940 ◽  
Vol 177 (968) ◽  
pp. 38-62 ◽  
Keyword(s):  
Thermal Diffusion ◽  
Successive Approximations ◽  
General Nature ◽  
Mixture Ratio ◽  
Inverse Power Law ◽  
Special Cases ◽  
Molecular Masses ◽  
Set Up ◽  
Coefficient Of Viscosity ◽  
Factor Α

When a gas mixture is contained in a vessel in which a steady temperature gradient is maintained, a concentration gradient is in general set up, whose amount is determined by the logarithm of the temperature ratio, and by k T , the thermal diffusion ratio; the general theory of non-uniform gases gives successive approximations to k T , and the first of these, [k T ]1, is accurate within a few per cent. The paper discusses the dependence of [k T ]1 on ( a ) the ratio of the molecular masses; ( b ) their concentration ratio ( c 1 or c 2 ); ( c ) the two ratios of the molecular diameters, inferred from the coefficient of viscosity, to their joint diameter, inferred from the coefficient of diffusion; and ( d ) three parameters depending on the mode of interaction between the unlike molecules. When this interaction is according to the inverse-power law, the three parameters ( d ) are all expressible in terms of the mutual force index, and [k T ]1, is a function of five independent variables. The general nature of its dependence on these variables is discussed, with particular reference to the end values (for c 1 or c 2 zero) of the thermal diffusion factor α, given by k T / c 1 c 2 ;these end values involve fewer variables (less by two) than the general values, and their functional character can be represented graphically. It is shown that k T may be zero not only when c 1 or c 2 is zero, but also for at most one intermediate mixture ratio. Formulae for [k T ]1 appropriate to various special cases are also given.

scholarly journals Application of Scikit and Keras Libraries for the Classification of Iron Ore Data Acquired by Laser-Induced Breakdown Spectroscopy (LIBS)

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1393 ◽  
Author(s):  
Yanwei Yang ◽  
Xiaojian Hao ◽  
Lili Zhang ◽  
Long Ren
Keyword(s):  
Machine Learning ◽  
Iron Ore ◽  
Laser Induced Breakdown Spectroscopy ◽  
Support Vector ◽  
Iron Ores ◽  
K Nearest Neighbor ◽  
Machine Model ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

Due to the complexity of, and low accuracy in, iron ore classification, a method of Laser-Induced Breakdown Spectroscopy (LIBS) combined with machine learning is proposed. In the research, we collected LIBS spectra of 10 iron ore samples. At the beginning, principal component analysis algorithm was employed to reduce the dimensionality of spectral data, then we applied k-nearest neighbor model, neural network model, and support vector machine model to the classification. The results showed that the accuracy of three models were 82.96%, 93.33%, and 94.07% respectively. The results also demonstrated that LIBS with machine learning model exhibits an excellent classification performance. Therefore, LIBS technique combined with machine learning can achieve a rapid, precise classification of iron ores, and can provide a completely new method for iron ores’ selection in the metallurgical industry.

Excess energy–volume and cohesive energy density coefficients for binary systems. Comparison with constant pressure functions

1976 ◽  
Vol 54 (22) ◽  
pp. 3559-3563 ◽  
Author(s):  
Digby D. Macdonald
Keyword(s):  
Energy Density ◽  
Cohesive Energy ◽  
Binary Systems ◽  
Constant Pressure ◽  
Liquid Mixtures ◽  
Excess Energy ◽  
Excess Functions ◽  
Cohesive Energy Density ◽  
Excess Functions Of Mixing

Excess energy–volume and cohesive energy density coefficients have been calculated for the hexane + perfluoro-hexane, water + DMSO, water + tert-butanol, water + methanol, water + acetonitrile, and methanol + DMSO Systems. These parameters are compared with other constant pressure excess functions of mixing for these binary systems, and it is proposed that they represent additional criteria for the classification of liquid mixtures.

The Psychopathology of Drug Addiction: A Review

1994 ◽  
Vol 24 (4) ◽  
pp. 597-622 ◽  
Author(s):  
Luigi Cancrini
Keyword(s):  
Drug Use ◽  
Drug Addiction ◽  
Drug Abusers ◽  
Acting Out ◽  
Public Health Services ◽  
Type D ◽  
Special Cases ◽  
Hiv Infection Prevention ◽  
Type C

The psychopathology of drug addiction is reviewed. Empirical research data on a time span of more than twelve years are presented. The data support a four-type-based classification of drug abusers, and the family structure underlining such personality types is analyzed. Clinical cases are presented. Type A addicts (adjustment disorders) present an evident relation between the external event, psychic trauma, and drug-abusing behavior. Type B (neurotic disorders) have a tendency to reduce internal anxiety by drug abuse, and their personal problems may be covered by drug use. Type C (psychosis and borderline) are an heterogeneous group, where often drug use can create a intense experience of inner freedom. Type D (sociopathic personality disorders) often express their psychic conflicts by means of serious acting-out, and come from families were “nonexistent” marriages were established. Intervention in public health services is examined, as well as the evolution of the addiction depending on the typology. The special cases of information on HIV infection prevention and overdose risk are also evaluated. It is concluded that the typology of drug addicts may shed light on prevention and therapy, whereas more specific therapeutic programs are needed.

Classification and Kinematic Equivalents of Contact Types for Fingertip-Based Robot Hand Manipulation

2016 ◽  
Vol 8 (4) ◽  
Author(s):  
Nicolas Rojas ◽  
Aaron M. Dollar
Keyword(s):  
Frictional Contact ◽  
Kinematic Chain ◽  
Robotic Manipulation ◽  
Robot Hand ◽  
Kinematic Chains ◽  
Special Cases ◽  
Contact Models ◽  
The Common ◽  
Standard Contact

In the context of robot manipulation, Salisbury's taxonomy is the common standard used to define the types of contact interactions that can occur between the robot and a contacted object; the basic concept behind such classification is the modeling of contacts as kinematic pairs. In this paper, we extend this notion by modeling the effects of a robot contacting a body as kinematic chains. The introduced kinematic-chain-based contact model is based on an extension of the Bruyninckx–Hunt approach of surface–surface contact. A general classification of nonfrictional and frictional contact types suitable for both manipulation analyses and robot hand design is then proposed, showing that all standard contact categories used in robotic manipulation are special cases of the suggested generalization. New contact models, such as ball, tubular, planar translation, and frictional adaptive finger contacts, are defined and characterized. An example of manipulation analysis that lays out the relevance and practicality of the proposed classification is detailed.

Infrared photoresponse from pn-junction Mg2Si diodes fabricated by thermal diffusion

2013 ◽  
Vol 74 (2) ◽  
pp. 311-314 ◽  
Author(s):  
Haruhiko Udono ◽  
Yusuke Yamanaka ◽  
Masahito Uchikoshi ◽  
Minoru Isshiki
Keyword(s):  
Thermal Diffusion ◽  
Pn Junction

scholarly journals COMPRESSIVE STRENGTH CLASSIFICATION OF LIGHTWEIGHT AGGREGATE CONCRETE USING A SUPPORT VECTOR MACHINE MODEL

2019 ◽  
Author(s):  
ANTONIO JOSÉ TENZA-ABRIL ◽  
ROSANA SATORRE-CUERDA ◽  
PATRICIA COMPAÑ-ROSIQUE ◽  
FRANCISCO JOSÉ NAVARRO-GONZÁLEZ ◽  
YOLANDA VILLACAMPA
Keyword(s):  
Support Vector Machine ◽  
Compressive Strength ◽  
Support Vector Machine Model ◽  
Lightweight Aggregate ◽  
Lightweight Aggregate Concrete ◽  
Support Vector ◽  
Machine Model ◽  
Aggregate Concrete
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