Shifting time waveform induced CMOS latch up in bootstrapping technique applications

Abstract Latch-up induced during High Temperature Operating Life (HTOL) test of a mixed signal device fabricated with 1.0 μm CMOS, double poly, double metal process caused failures due to an open in aluminum metal line. Metal lines revealed wedge voids of about 50% of the line width. Triggering of latch up mechanism during the HTOL test resulted in a several fold increase of current flowing through the ground metal line. This increase in current resulted in the growth of the wedge voids leading to failures due to open metal lines.

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A Silicon Debugging Methodology on Customer Prototype for Wafer Foundries

ISTFA 2012: Conference Proceedings from the 38th International Symposium for Testing and Failure Analysis ◽

10.31399/asm.cp.istfa2012p0411 ◽

2012 ◽

Author(s):

Mai Zhihong ◽

Ng Tsu Hau ◽

Dawood M. Khalid ◽

Tan Pik Kee ◽

Jeffrey Lam

Keyword(s):

Case Studies ◽

Semiconductor Industry ◽

Full Information ◽

Limited Information ◽

Ip Protection ◽

First Case ◽

Silicon Debugging ◽

Failure Location ◽

Device Chip ◽

Latch Up

Abstract IP protection is of major importance for a semiconductor company and only limited information is made available for device debugging for the product outsourced to a foundry. In order to position ourselves better in the ever competitive semiconductor industry, with the consideration of IP protection, we have to provide the customers with the Si debugging capability and device/chip verification services in foundry. This paper explores the Si debugging methodology and technique in a foundry. Two case studies are presented and discussed. The first case illustrates the isolation of the failure location by InGaAs microscopy, upon which the failure was identified to be caused by a latch-up issue. In the second case, due to confidentiality considerations from the customer, full information could not be provided to the foundry for silicon debugging. The paper illustrates the ability to effectively debug a failure despite being constrained by limited information from the customer.

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РАДИАЦИОННО СТОЙКОЕ КМОП СТАТИЧЕСКОЕ ОЗУ 16 МБИТ 1657РУ2У

Nanoindustry Russia ◽

10.22184/1993-8578.2020.13.3s.169.174 ◽

2020 ◽

Vol 96 (3s) ◽

pp. 169-174

Author(s):

Ю.М. Герасимов ◽

Н.Г. Григорьев ◽

А.В. Кобыляцкий ◽

Я.Я. Петричкович

Keyword(s):

Total Dose ◽

Heavy Particles ◽

Topological Features ◽

Radiation Hardened ◽

Latch Up

Рассматриваются архитектурные, схемотехнические и конструктивно-топологические особенности асинхронного радиационно стойкого ОЗУ 1657РУ2У емкостью 16 Мбит с организацией (1Мx16)/(2Mx8), изготавливаемого по коммерческой КМОП-технологии объемного кремния уровня 130 нм. СБИС ОЗУ нечувствительна к эффекту «защелкивания», имеет повышенные дозовую стойкость и сбоеустойчивость при воздействии отдельных ядерных частиц (ОЯЧ), протонов и нейтронов (ТЧ). The paper highlights architectural, schematic and topological features of the radiation hardened 16 Mbit CMOS SRAM with configurable organization 1Mx16/2Mx8, which is immune to latch-up and with improved total dose and heavy particles tolerance.

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Single Event Latch-up and Total Ionizing Dose Characterization of a Cobham Designed Smart Power Switch Controller

2020 IEEE Radiation Effects Data Workshop (in conjunction with 2020 NSREC) ◽

10.1109/redw51883.2020.9325838 ◽

2020 ◽

Author(s):

Matt Von Thun ◽

Younes Lotfi ◽

Tim Meade ◽

Aaron Turnbull

Keyword(s):

Single Event ◽

Total Ionizing Dose ◽

Smart Power ◽

Power Switch ◽

Latch Up

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Diamond Grinding Wheel Condition Monitoring Based on Acoustic Emission Signals

Sensors ◽

10.3390/s21041054 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1054

Author(s):

Guo Bi ◽

Shan Liu ◽

Shibo Su ◽

Zhongxue Wang

Keyword(s):

Neural Network ◽

Acoustic Emission ◽

Condition Monitoring ◽

Time Domain ◽

Diamond Wheel ◽

Feature Representation ◽

Grinding Wheel ◽

Time Waveform ◽

Original Time ◽

Whole Life Cycle

Acoustic emission (AE) phenomenon has a direct relationship with the interaction of tool and material which makes AE the most sensitive one among various process variables. However, its prominent sensitivity also means the characteristics of random and board band. Feature representation is a difficult problem for AE-based monitoring and determines the accuracy of monitoring system. It is knottier for the situation of using diamond wheel grinding optical components, not only because of the complexity of grinding process but also the high requirement on surface and subsurface quality. This paper is dedicated to AE-based condition monitoring of diamond wheel during grinding brittle materials and feature representation is paid more attention. AE signal of brittle-regime grinding is modeled as a superposition of a series of burst-type AE events. Theory analysis manifested that original time waveform and frequency spectrum are all suitable for feature representation. Considering the convolution form of b-AE in time domain, a convolutional neural network with original time waveform of AE signals as the input is built for multi-class classification of wheel state. Detailed state division in a wheel’s whole life cycle is realized and the accuracy is over 90%. Different from the overlapping in time domain, AE components of different crack mechanisms are probably separated in frequency domain. From this point of view, AE spectrums are more suitable for feature extraction than the original time waveform. In addition, the time sequence of AE samples is essential for the evaluation of wheel’s life elapse and making use of sequential information is just the idea behind recurrent neural network (RNN). Therefore, long short-term memory (LSTM), a special kind of RNN, is used to build a regression prediction model of wheel state with AE spectrums as the model input and satisfactory prediction accuracy is acquired on the test set.

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