Resistive bridge defect detection enhancement under parameter variations combining Low VDD and body bias in a delay based test

Resistive bridges are a major class of defects in nanometer technologies that can escape test, posing a serious reliability risk for CMOS IC circuits. The increase of process parameter variations represents a challenge for resistive bridge detection using traditional test methods, and requires more...

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Detalles Bibliográficos
Autores: Héctor Luis Villacorta Minaya, Víctor Hugo Champac Vilela
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2012
País:México
Institución:Instituto Nacional de Astrofísica, Óptica y Electrónica
Repositorio:Repositorio Institucional del INAOE
Idioma:inglés
OAI Identifier:oai:inaoe.repositorioinstitucional.mx:1009/2060
Acceso en línea:http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/2060
Access Level:acceso abierto
Palabra clave:info:eu-repo/classification/Inspec/Resistive bridges
info:eu-repo/classification/Inspec/Nanometer technologie
info:eu-repo/classification/Inspec/CMOS technology
info:eu-repo/classification/cti/1
info:eu-repo/classification/cti/22
info:eu-repo/classification/cti/2203
Descripción
Sumario:Resistive bridges are a major class of defects in nanometer technologies that can escape test, posing a serious reliability risk for CMOS IC circuits. The increase of process parameter variations represents a challenge for resistive bridge detection using traditional test methods, and requires more efficient test methods to be developed. In this work, we show that resistive bridge detection improves by correlating the defect-induced extra circuit delay with the power supply voltage value and the reverse body bias (RBB) applied. A Timing Critical Resistance (Rᵗcrit) is defined as a metric to quantify the resistive bridge detection enhancement in the presence of process variations under a delay based test. We show that the smaller the supply voltage, the higher the resistive bridge detection which further enhances by applying RBB. Results are presented for a 65 nm CMOS technology.