Case Studies of the Use of Image Processing in Metrology and Failure Analysis

2005 ◽  
Author(s):  
Kartik Ramanujachar
Keyword(s):  
Image Processing ◽  
Failure Analysis ◽  
Case Studies ◽  
Nearest Neighbor ◽  
Image Data ◽  
Cumulative Distribution ◽  
Information Theoretic ◽  
Atomic Force ◽  
Processing Techniques

Abstract This paper describes the use of image processing techniques in metrology and failure analysis with the help of three case studies. The first study concerns a technique that significantly automates the process and hence enables both a rapid and accurate extraction of cumulative distribution function for transistor CD through the use of edge detection and quantification of image intensities. The second study is about utilizing a cross correlation algorithm and an appropriately chosen sample and image to estimate the "on image" spatial resolution of an scanning electron microscope. The last case study uses image data acquired with an atomic force microscope. The paper describes how information theoretic concepts like entropy and mutual information combined with image segmentation and nearest neighbor extraction can be used to isolate those regions of the AFM scan that can potentially benefit from further analysis.

The Electrical Characterization and Physical Failure Analysis for Transistor Gate Leakage

2006 ◽  
Author(s):  
Tsung-Te Li ◽  
Chao-Chi Wu ◽  
Jung-Hsiang Chuang ◽  
Jon C. Lee
Keyword(s):  
Failure Analysis ◽  
Electrical Characterization ◽  
Physical Analysis ◽  
Gate Leakage ◽  
Force Microscopy ◽  
Atomic Force ◽  
Transmission Electron ◽  
Voltage Stress ◽  
Leakage Site

Abstract This article describes the electrical and physical analysis of gate leakage in nanometer transistors using conducting atomic force microscopy (C-AFM), nano-probing, transmission electron microscopy (TEM), and chemical decoration on simulated overstressed devices. A failure analysis case study involving a soft single bit failure is detailed. Following the nano-probing analysis, TEM cross sectioning of this failing device was performed. A voltage bias was applied to exaggerate the gate leakage site. Following this deliberate voltage overstress, a solution of boiling 10%wt KOH was used to etch decorate the gate leakage site followed by SEM inspection. Different transistor leakage behaviors can be identified with nano-probing measurements and then compared with simulation data for increased confidence in the failure analysis result. Nano-probing can be used to apply voltage stress on a transistor or a leakage path to worsen the weak point and then observe the leakage site easier.

Case Studies in Atomic Force Probe Analysis

2006 ◽  
Author(s):  
Randal Mulder ◽  
Sam Subramanian ◽  
Tony Chrastecky
Keyword(s):  
Failure Analysis ◽  
Case Studies ◽  
Light Emission ◽  
Electrical Characterization ◽  
Logic Circuits ◽  
Contrast Imaging ◽  
Atomic Force ◽  
Measuring Surface ◽  
Analysis Environment

Abstract The use of atomic force probe (AFP) analysis in the analysis of semiconductor devices is expanding from its initial purpose of solely characterizing CMOS transistors at the contact level with a parametric analyzer. Other uses found for the AFP include the full electrical characterization of failing SRAM bit cells, current contrast imaging of SOI transistors, measuring surface roughness, the probing of metallization layers to measure leakages, and use with other tools, such as light emission, to quickly localize and identify defects in logic circuits. This paper presents several case studies in regards to these activities and their results. These case studies demonstrate the versatility of the AFP. The needs and demands of the failure analysis environment have quickly expanded its use. These expanded capabilities make the AFP more valuable for the failure analysis community.

Die-Level Scanning Capacitance Microscopy Fault Isolation on SOI Fin-FET Devices for Advanced Semiconductor Nodes

2018 ◽  
Author(s):  
Lucile C. Teague Sheridan ◽  
Tanya Schaeffer ◽  
Yuting Wei ◽  
Satish Kodali ◽  
Chong Khiam Oh
Keyword(s):  
Atomic Force Microscopy ◽  
Failure Analysis ◽  
Fault Isolation ◽  
Scanning Capacitance Microscopy ◽  
Force Microscopy ◽  
Atomic Force

Abstract It is widely acknowledged that Atomic force microscopy (AFM) methods such as conductive probe AFM (CAFM) and Scanning Capacitance Microscopy (SCM) are valuable tools for semiconductor failure analysis. One of the main advantages of these techniques is the ability to provide localized, die-level fault isolation over an area of several microns much faster than conventional nanoprobing methods. SCM, has advantages over CAFM in that it is not limited to bulk technologies and can be utilized for fault isolation on SOI-based technologies. Herein, we present a case-study of SCM die-level fault isolation on SOI-based FinFET technology at the 14nm node.

Application of AFP in Resolving Systematic Issue in Wafer Fabrication

2013 ◽  
Author(s):  
Hui Peng Ng ◽  
Ghim Boon Ang ◽  
Chang Qing Chen ◽  
Alfred Quah ◽  
Angela Teo ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Case Studies ◽  
Failure Mechanisms ◽  
Critical Role ◽  
Electrical Characterization ◽  
Process Technology ◽  
Atomic Force ◽  
Defect Localization ◽  
Non Volatile Memory ◽  
Visual Failure

Abstract With the evolution of advanced process technology, failure analysis is becoming much more challenging and difficult particularly with an increase in more erratic defect types arising from non-visual failure mechanisms. Conventional FA techniques work well in failure analysis on defectively related issue. However, for soft defect localization such as S/D leakage or short due to design related, it may not be simple to identify it. AFP and its applications have been successfully engaged to overcome such shortcoming, In this paper, two case studies on systematic issues due to soft failures were discussed to illustrate the AFP critical role in current failure analysis field on these areas. In other words, these two case studies will demonstrate how Atomic Force Probing combined with Scanning Capacitance Microscopy were used to characterize failing transistors in non-volatile memory, identify possible failure mechanisms and enable device/ process engineers to make adjustment on process based on the electrical characterization result. [1]

Impacts of Sample Preparation Methodology on TEM Failure Analysis of Advanced Semiconductor Devices

2011 ◽  
Author(s):  
Yongkai Zhou ◽  
Jie Zhu ◽  
Han Wei Teo ◽  
ACT Quah ◽  
Lei Zhu ◽  
...  
Keyword(s):  
Sample Preparation ◽  
Failure Analysis ◽  
Case Studies ◽  
Thickness Measurement ◽  
Interface Roughness ◽  
Silicide Formation ◽  
Cross Sectional ◽  
Inspection Method ◽  
Low Mass

Abstract In this paper, two failure analysis case studies are presented to demonstrate the importance of sample preparation procedures to successful failure analyses. Case study 1 establishes that Palladium (Pd) cannot be used as pre-FIB coating for SiO2 thickness measurement due to the spontaneously Pd silicide formation at the SiO2/Si interface. Platinum (Pt) is thus recommended, in spite of the Pt/SiO2 interface roughness, as the pre-FIB coating in this application. In the second case study, the dual-directional TEM inspection method is applied to characterize the profile of the “invisible” tungsten residue defect. The tungsten residue appears invisible in the planeview specimen due to the low mass-thickness contrast. It is then revealed in the cross-sectional TEM inspection.

PDE-Based Image Processing

2012 ◽  
pp. 49-89
Author(s):  
Rajeev Srivastava
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Shape From Shading ◽  
Surface Geometry ◽  
Partial Differential ◽  
Basic Concepts ◽  
Processing Techniques ◽  
Image Modelling

This chapter describes the basic concepts of partial differential equations (PDEs) based image modelling and their applications to image restoration. The general basic concepts of partial differential equation (PDE)-based image modelling and processing techniques are discussed for image restoration problems. These techniques can also be used in the design and development of efficient tools for various image processing and vision related tasks such as restoration, enhancement, segmentation, registration, inpainting, shape from shading, 3D reconstruction of objects from multiple views, and many more. As a case study, the topic in consideration is oriented towards image restoration using PDEs formalism since image restoration is considered to be an important pre-processing task for 3D surface geometry, reconstruction, and many other applications. An image may be subjected to various types of noises during its acquisition leading to degraded quality of the image, and hence, the noise must be reduced. The noise may be additive or multiplicative in nature. Here, the PDE-based models for removal of both types of noises are discussed. As examples, some PDE-based schemes have been implemented and their comparative study with other existing techniques has also been presented.

scholarly journals RFI Artefacts Detection in Sentinel-1 Level-1 SLC Data Based On Image Processing Techniques

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2919 ◽  
Author(s):  
Agnieszka Chojka ◽  
Piotr Artiemjew ◽  
Jacek Rapiński
Keyword(s):  
Image Processing ◽  
Synthetic Aperture Radar ◽  
Nearest Neighbor ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Sar Images ◽  
Permanent Scatterers ◽  
Level 1 ◽  
Processing Techniques ◽  
Aperture Radar

Interferometric Synthetic Aperture Radar (InSAR) data are often contaminated by Radio-Frequency Interference (RFI) artefacts that make processing them more challenging. Therefore, easy to implement techniques for artefacts recognition have the potential to support the automatic Permanent Scatterers InSAR (PSInSAR) processing workflow during which faulty input data can lead to misinterpretation of the final outcomes. To address this issue, an efficient methodology was developed to mark images with RFI artefacts and as a consequence remove them from the stack of Synthetic Aperture Radar (SAR) images required in the PSInSAR processing workflow to calculate the ground displacements. Techniques presented in this paper for the purpose of RFI detection are based on image processing methods with the use of feature extraction involving pixel convolution, thresholding and nearest neighbor structure filtering. As the reference classifier, a convolutional neural network was used.

AIRCRAFT CLASSIFICATION USING IMAGE PROCESSING TECHNIQUES AND ARTIFICIAL NEURAL NETWORKS

2011 ◽  
Vol 25 (08) ◽  
pp. 1321-1335 ◽  
Author(s):  
ADIL GURSEL KARACOR ◽  
ERDAL TORUN ◽  
RASIT ABAY
Keyword(s):  
Image Processing ◽  
Image Data ◽  
Radar Data ◽  
Still Image ◽  
Image Processing Techniques ◽  
Black And White ◽  
Rf Signals ◽  
Different Types ◽  
Artificial Neural ◽  
Processing Techniques

Identifying the type of an approaching aircraft, should it be a helicopter, a fighter jet or a passenger plane, is an important task in both military and civilian practices. The task in question is normally done by using radar or RF signals. In this study, we suggest an alternative method that introduces the use of a still image instead of RF or radar data. The image was transformed to a binary black and white image, using a Matlab script which utilizes Image Processing Toolbox commands of Matlab, in order to extract the necessary features. The extracted image data of four different types of aircraft was fed into a three-layered feed forward artificial neural network for classification. Satisfactory results were achieved as the rate of successful classification turned out to be 97% on average.

scholarly journals Detection of Diabetic Retinopathy by Retinal Screening using Image Processing Techniques

2020 ◽  
pp. 447-457
Author(s):  
Shaziya Banu S ◽  
Ravindra S
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Nearest Neighbor ◽  
Extreme Condition ◽  
Diabetic Patients ◽  
K Nearest Neighbor ◽  
Image Processing Techniques ◽  
Primary Driver ◽  
Processing Techniques

<p>Diabetic Retinopathy (DR) is a related malady with diabetes and primary driver of sightlessness in diabetic patients. Epidemiological overview categorizes DR among four significant reasons for sight impedance. DR is a microvascular entanglement in which meager retinal veins may blast, bringing about vision misfortune. In this condition veins in retina swells and may blast in severe extreme condition. Operative medication is timely discovery by steady screenings that is by emphasizing the determination of retinal images using appropriate image processing techniques such as, Preprocessing of retinal image, image segmentation using sobel edge detector, local features extraction like mean, standard deviation, variance, Entropy, histogram values and so on. For classification of retina, system uses K-Nearest Neighbor (KNN) classifier. By adopting this approach, The classification of normal and abnormal images of retina is easy and will reduce the number of reviews for the ophthalmologists. Developing a method to automate functionality of retinal examination helps doctor to identify patient’s condition on disease. So that they can medicate the disease accordingly.</p>

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