2000
DOI: 10.1557/proc-612-d2.7.1
|View full text |Cite
|
Sign up to set email alerts
|

A Percolative Approach to Electromigration Modelling

Abstract: We present a stochastic model which simulates electromigration damage in metallic interconnects by biased percolation of a random resistor network. The main features of experiments including Black's law and the log-normal distribution of the times to failure are well reproduced together with compositional effects showing up in early stage measurements made on Al-0.5%Cu and Al-1%Si lines.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

1
5
0

Year Published

2000
2000
2014
2014

Publication Types

Select...
5
1

Relationship

3
3

Authors

Journals

citations
Cited by 6 publications
(6 citation statements)
references
References 12 publications
1
5
0
Order By: Relevance
“…The stepwise variations in Figure 5 c on top of the overall current decay could be explained by the stochastic change in the conduction path due to persistent trapping and detrapping of electrons leading to the rearrangement of the network composed of occupied traps. [ 47,48 ] Such behaviors have been successfully modeled for percolation networks with competing defect generation and defect recovery mechanisms, [ 48,49 ] again supporting electron trapping as the mechanism of the observed switching effect in oxidized graphene electrodes. The difference in retention time between the functionalized graphene electrodes in the MLG/Ta 2 O 5-x /TaO y /MLG devices and the annealed graphene samples may be explained by the different interfaces in the two types of devices, as the TaO y layer passivating the graphene fi lm could change the energy profi le of the electron traps and make it easier for the trapped electrons to escape in the MLG/Ta 2 O 5-x /TaO y /MLG devices.…”
Section: Communicationmentioning
confidence: 72%
“…The stepwise variations in Figure 5 c on top of the overall current decay could be explained by the stochastic change in the conduction path due to persistent trapping and detrapping of electrons leading to the rearrangement of the network composed of occupied traps. [ 47,48 ] Such behaviors have been successfully modeled for percolation networks with competing defect generation and defect recovery mechanisms, [ 48,49 ] again supporting electron trapping as the mechanism of the observed switching effect in oxidized graphene electrodes. The difference in retention time between the functionalized graphene electrodes in the MLG/Ta 2 O 5-x /TaO y /MLG devices and the annealed graphene samples may be explained by the different interfaces in the two types of devices, as the TaO y layer passivating the graphene fi lm could change the energy profi le of the electron traps and make it easier for the trapped electrons to escape in the MLG/Ta 2 O 5-x /TaO y /MLG devices.…”
Section: Communicationmentioning
confidence: 72%
“…From Monte Carlo simulations we found that also for biased percolation the resistance evolution follows a scaling relation R͑t͒ ϳ jt 2 tj 2m B , with m B 0.22 6 0.02 [18]. We note that the value of m B depends in general on current and temperature and thus on the importance of Joule heating effects, which control the correlations present in the degradation process [18]. Since in this case the process of defect creation is driven by the external current, the selective breaking of the crucial resistors suppresses the saturation region of the breakdown resistance typical of standard percolation.…”
mentioning
confidence: 93%
“…Again the curve marked by circles represents the evolution of the network resistance R͑t͒, while the squares represent that of R͑t 2 t͒. From Monte Carlo simulations we found that also for biased percolation the resistance evolution follows a scaling relation R͑t͒ ϳ jt 2 tj 2m B , with m B 0.22 6 0.02 [18]. We note that the value of m B depends in general on current and temperature and thus on the importance of Joule heating effects, which control the correlations present in the degradation process [18].…”
mentioning
confidence: 96%
“…The aim of this paper is to address this issue by presenting a stochastic approach which simulates EM damages in metallic interconnects in terms of percolation in a random resistor network [18]. By extending a previously proposed model [19], here we present a complete study whose preliminar results have been reported in [20][21][22]. In our appproach, even if there is no direct motion of matter, the effects of mass transport are implicitely accounted for by our percolative and stochastic approach.…”
Section: Introductionmentioning
confidence: 99%