Plasma immersion ion implantation (Pm) is a novel implantation technique for high-dose/high-current implants. Using the SPICE circuit simulator to model the PIII process, the sheath voltage and ion energy distribution...
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Plasma immersion ion implantation (Pm) is a novel implantation technique for high-dose/high-current implants. Using the SPICE circuit simulator to model the PIII process, the sheath voltage and ion energy distribution are examined. Implanting into a dielectric substrate results in a significant voltage buildup in the wafer, reducing the effective implant energy. Increasing the pulse voltage raises the dose/pulse, but at the cost of an expanded implant energy spread. Increasing the plasma ion density also raises the dose/pulse, but at the cost of a wider implant energy spread and a lower coupling efficiency. Increasing the substrate thickness reduces both the coupling efficiency and dose/pulse while broadening the energy spread. The large voltage generated across the dielectric substrate decreases the charge neutralization time significantly, reducing the possibility of gate oxide damage.
A new experimental method for determining the secondary electron yield for plasma exposed surfaces is described. From the measurement of the plasma condition and the total current generated when a voltage pulse is app...
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A new experimental method for determining the secondary electron yield for plasma exposed surfaces is described. From the measurement of the plasma condition and the total current generated when a voltage pulse is applied to a target material exposed to a plasma, the dependence of the secondary electron yield of that target on ion energy can be extracted. The secondary electron yield Is determined by an analytical model of the plasma ion, electron, and displacement currents. Experimental results for an aluminum target correlate well with previous secondary electron measurements which used a traditional technique, Secondary electrons yield data of other materials: single crystal silicon, aluminum, titanium nitride, and silicon dioxide are also extracted.
Plasma immersion ion implantation (PIII) is a technique which promises high dose rate implantation and compatibility with large-area processing. When a large negative bias is applied to the substrate which is immersed...
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Plasma immersion ion implantation (PIII) is a technique which promises high dose rate implantation and compatibility with large-area processing. When a large negative bias is applied to the substrate which is immersed inside a high ion-density plasma, all ion species present will be implanted without ion mass selection, Innovations of this techniques include: implantation time independent of implantation area, capability to perform concomitant deposition and implantation, and simplicity of machine design and maintenance. This paper reports the modeling of PIII plasma dynamics and several demonstrated semiconductor processing applications such as plasma doping, subsurface material synthesis, ion beam mixing, microcavity engineering, and surface modifications. Several processing issues such as substrate charging and dosimetry will also be discussed.
The effects of wafer bias and plasma parameters on thin oxide charging during plasma immersion ion implantation (PIII) are simulated. The simulator has been shown to determine accurately the charging currents generate...
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The effects of wafer bias and plasma parameters on thin oxide charging during plasma immersion ion implantation (PIII) are simulated. The simulator has been shown to determine accurately the charging currents generated during PIII. The dependence of the plasma electron temperature, ion density and plasma uniformity on charging damage in metal oxide semiconductor capacitor structures is investigated. A lower plasma electron temperature is shown to reduce charging damage. Simulation and experimental results show that for a given voltage pulse waveform there is a range of bias repetition rates allowed by limiting the charging damage below a threshold value. Within this range there exists a switch-over repetition rate that minimizes the charging damage.
An analytical model of oxide charging in plasma processing is presented. The model simulates the interactions of the plasma with semiconductor device structures on the wafer and the substrate bias to determine the cha...
An analytical model of oxide charging in plasma processing is presented. The model simulates the interactions of the plasma with semiconductor device structures on the wafer and the substrate bias to determine the charging induced in thin gate oxides. This model agrees well with experimental data for pulsed substrate bias. The simulation shows that a lower plasma electron temperature can reduce the charging damage. Well structures modulate the charging damage, with p wells charging more negatively and n wells charging more positively than an identical case without a well structure. Two‐dimensional charging effects such as plasma nonuniformities and antenna structures have also been successfully modeled. Antenna‐type device structures are shown to enhance the charging damage in both capacitor and well structures.
Chair and Varshney have derived an optimal rule for fusing decisions based on the Bayesian criterion. To implement the rule, the probability of detection P-D and the probability of false alarm P-F for each detector mu...
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Chair and Varshney have derived an optimal rule for fusing decisions based on the Bayesian criterion. To implement the rule, the probability of detection P-D and the probability of false alarm P-F for each detector must be known, but this information is not always available in practice. An adaptive fusion model which estimates the P-D and P-F adaptively by a simple counting process is presented, Since reference signals are not given, the decision of a local detector is arbitrated by the fused decision of all the other local detectors, Furthermore, the fused results of the other local decisions are classified as ''reliable'' and ''unreliable.'' Only reliable decisions are used to develop the rule, Analysis on classifying the fused decisions in term of reducing the estimation error is given and simulation results which conform to our analysis are presented.
Symmetric, alpha-stable random variables and processes have, recently, been receiving increasing attention from the signalprocessing and communication communities as statistical models for signals and noises that con...
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Symmetric, alpha-stable random variables and processes have, recently, been receiving increasing attention from the signalprocessing and communication communities as statistical models for signals and noises that contain impulsive components. This paper is intended as a comprehensive review of the fundamental concepts and results of signalprocessing with alpha-stable processes with emphasis placed on acquainting engineers with this emerging discipline in signalprocessing and revealing its potential applications. In particular, we start with deriving alpha-stable models for impulsive noise. This derivation serves as an illustration of the Generalized Central Limit Theorem, which states that the first-order distributions in all observed time series follow, to a higher or lesser degree, a stable law. We proceed to present new, fast algorithms for estimation of the parameters of alpha-stable interference and address two signal detection problems. These problems also build intuition on the differences between Gaussian and non-Gaussian, alpha-stable signalprocessing, as well as indicate the performance gains that are to be expected if the signalprocessing algorithms are designed on the basis of a non-Gaussian, alpha-stable assumption rather than on a Gaussianity assumption. In the paper, we follow a presentation style that emphasizes only the highlights of the field and omit the fine mathematical details. However, we have included a large number of references to the literature for the interested reader to study further. Copyright (C) 1996 Published by Elsevier Science Ltd
Statistical geometric features (SGF) have recently been proposed for the classification of image textures. The SGF method is easily extended to use other geometric properties of connected regions. Following a brief re...
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In this paper a combination of lossless and lossy compression techniques is presented for the storage and transmission of 3-D medical images. The lossy version of the data is used for fast preview when browsing throug...
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In this paper a combination of lossless and lossy compression techniques is presented for the storage and transmission of 3-D medical images. The lossy version of the data is used for fast preview when browsing through large databases. When only a small region is of interest then the lossless corrections for this region are transmitted. A special structuring of the bit-stream is also adopted to allow visualization directly from the compressed bit-stream.
All digital signalprocessing (DSP) circuits use analog front-end anti-aliasing filters to process sensor inputs. These analog filters have a number of disadvantages with respect to cost, power, stability, and ease of...
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All digital signalprocessing (DSP) circuits use analog front-end anti-aliasing filters to process sensor inputs. These analog filters have a number of disadvantages with respect to cost, power, stability, and ease of integration in VLSI. This paper proposes the use of all-digital oversampling front-end sensors, resulting in a performance/cost-effective DSP application. Simulations for modem and speech applications illustrate the design tradeoffs.
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