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DTSTART:20380119T001407
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DTSTAMP:20210325T181507Z
UID:E759464A-3768-4D3A-B19E-EDC2DCE28A37
DTSTART;TZID=Brazil/East:20210325T140000
DTEND;TZID=Brazil/East:20210325T150000
DESCRIPTION:Aggressively scaled transistor technologies with metal gate/hig
 h-k stacks encounter additional\nreliability challenges beside bias temper
 ature instability (BTI) in PMOS and NMOS devices\,\ntime dependent dielect
 ric breakdown and hot carrier degradation. Time-zero variability and\nvari
 ability induced by device aging is a growing concern which needs to be mod
 eled using\nstochastic processes. The physical nature of the stochastic pr
 ocess remains under debate and to\nsupport model development efforts large
  statistical data sets are essential. In addition\,\nself-heating during r
 eliability testing can be observed in novel device structures like bulk\nF
 inFET\, SOI FinFETs\, FDSOI and gate-all-around devices and needs proper a
 ttention.\nFurthermore\, to increase the confidence in the discrete device
  reliability models\,\ndevice-to-circuit correlations need to be establish
 ed. In this presentation we discuss how to\nobtain stochastic BTI data for
  discrete SRAM and logic device beyond 3​σ​\, address\ndevice-to-circ
 uit correlations using ring-oscillators and explore self-heating effects i
 n FinFET\nand SOI devices.\n\nSpeaker(s): Andreas Kerber\, PhD\, \n\nVirtu
 al: https://events.vtools.ieee.org/m/264341
LOCATION:Virtual: https://events.vtools.ieee.org/m/264341
ORGANIZER:unicampedschapter@gmail.com
SEQUENCE:6
SUMMARY:Distinguished Lecture - Andreas Kerber on Reliability of Metal Gate
  / High-K CMOS devices
URL;VALUE=URI:https://events.vtools.ieee.org/m/264341
X-ALT-DESC:Description: <br /><p><span class="fontstyle0">Aggressively scal
 ed transistor technologies with metal gate/high-k stacks encounter additio
 nal<br />reliability challenges beside bias temperature instability (BTI) 
 in PMOS and NMOS devices\,<br />time dependent dielectric breakdown and ho
 t carrier degradation. Time-zero variability and<br />variability induced 
 by device aging is a growing concern which needs to be modeled using<br />
 stochastic processes. The physical nature of the stochastic process remain
 s under debate and to<br />support model development efforts large statist
 ical data sets are essential. In addition\,<br />self-heating during relia
 bility testing can be observed in novel device structures like bulk<br />F
 inFET\, SOI FinFETs\, FDSOI and gate-all-around devices and needs proper a
 ttention.<br />Furthermore\, to increase the confidence in the discrete de
 vice reliability models\,<br />device-to-circuit correlations need to be e
 stablished. In this presentation we discuss how to<br />obtain stochastic 
 BTI data for discrete SRAM and logic device beyond 3</span><span class="fo
 ntstyle2">​</span><span class="fontstyle3">&sigma\;</span><span class="f
 ontstyle2">​</span><span class="fontstyle0">\, address<br />device-to-ci
 rcuit correlations using ring-oscillators and explore self-heating effects
  in FinFET<br />and SOI devices.</span></p>
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