C. Pennetta, E. Alfinito and L. Reggiani Dip. di Ingegneria dell’Innovazione,Universita’ di Lecce, Italy INFM – National Nanotechnology Laboratory, Lecce, Italy Motivations: To study the electrical conduction of disordered materials over the full range of the applied stress, by focusing on the role of the disorder. To investigate the stability of the electrical properties and electrical breakdown phenomena in conductor - insulator composites,in granular metals and in nanostructured materials. To establish the conditions under which we expect failure precursors and to identify these precursors. To study the properties of the resistance fluctuations,including their non-Gaussianity and to understand their link with other basic features of the system. The model Resistor Network Approach: THIN FILM OF RESISTANCE R R rn I T0 2D SQUARE LATTICE RESISTOR NETWORK = network resistance = resistance of the n-th resistor = stress current (d.c.), kept constant = thermal bath temperature two-species of resistors: rreg (Tn) = r0 [1 + (Tn -Tref) ] rn rOP = 109 rreg (broken resistor) Tn = local temperature = temperature coeff. of the resistance Biased and Stationary Resistor Network (BSRN) Model: Pennetta et al, UPON, Ed. D. Abbott & L. B. Kish, 1999 Pennetta et al. PRE, 2002 and Pennetta, FNL, 2002 rreg rOP defect generation probability WD=exp[-ED/kBTn] rOP rreg defect recovery probability WR =exp[-ER/kBTn] biased percolation: Tn =T0 + A[ rn in2 +(B/Nneig)m(rm,nim,n2 - rnin2)] Gingl et al, Semic. Sc. & Tech. 1996; Pennetta et al, PRL, 1999 The network evolution depends: a) on the external conditions (I, T0) b) on the material parameters (r0,,A,ED,ER) STEADY STATE <p> , <R> IRREVERSIBLE BREAKDOWN, pC p fraction of broken resistor, pC percolation threshold ED ER k BT0 sets the level of intrinsic disorder (<p>0 ) 0 max ( ED / kBT0 ) here =6.67 max Flow Chart of Computations I 0 change T Initial network t=0, R(T0) no Change T t = t +1 t>tmax? rreg rOP rreg(T) yes end Save R,p Solve Network rOP rreg rreg(T) Solve Network no R>Rmax ? yes end Results Network evolution for the irreversible breakdown case Observed electromigration damage pattern Granular structure of the material Atomic transport through grain boundaries dominates Transport within the grain bulk is negligeable Film: network of interconnected grain boundaries SEM image of electromigration damage in Al-Cu interconnects Experiments and Simulations Evolution and TTFs Experimental failure Simulated Failure Lognormal Distribution Tests under accelerated conditions Qualitative and quantitative agreement Steady State Regime Resistance evolution at increasing bias Average resistance <R>: I0 Steady state Distribution of resistance fluctuations, R = R-<R> at increasing bias probability density function (PDF) Ib Effect of the recovery energy: Effect of the initial film resistance: I R g R 0 I0 g ( I / I 0 ) 1 a( I / I 0 ) =2.0 0.1 In the pre-breakdown region: I=3.7 0.3 Effect on the average resistance of the bias conditions (constant voltage or constant current) and of the temperature coefficient of the resistance =0 =0 0 0 We have found that R b R 0 is: independent on the initial resistance of the film independent on the bias conditions dependent on the temperature coef. of the resistance dependent on the recovery activation energy = 1.85 ± 0.08 All these features are in good agreements with electrical measurements up to breakdown in carbon high-density polyethylene composites (K.K. Bardhan, PRL, 1999 and 2003) Relative variance of resistance fluctuations <R2>/<R>2 Effect on the resistance noise of the bias conditions and of the temperature coefficient of the resistance =0 =0 0 0 Non-Gaussianity of resistance fluctuations Bramwell, Holdsworth and Pinton (Nature, 396, 552, 1998): universal NG fluctuation distribution in systems near criticality BHP Denoting by: y m m Gaussian ( y ) ( y ) ( y) Ke a b ( y s ) e b ( y s ) a=/2, b=0.936, s=0.374, K=2.15 BHP distribution: generalization of Gumbel Bramwell et al. PRL, 84, 3744, 2000 a, b, s, K : fitting parameters Effects of the network size: networks NxN with: N=50, 75, 100, 125 Gaussian in the linear regime NG at the electrical breakdown: vanishes in the large size limit Role of the disorder: ED ER k BT0 p p 0 I p 0 I0 2 Pennetta et al., Physica A, in print 0 max At increasing levels of disorder (decreasing values) the PDF at the breakdown threshold approaches the BHP Power spectral density of resistance fluctuations Lorentzian: the corner frequency moves to lower values at increasing levels of disorder Conclusions : We have studied the distribution of the resistance fluctuations of conducting thin films with different levels of internal disorder. The study has been performed by describing the film as a resistor network in a steady state determined by the competition of two biased stochastic processes, according to the BSRN model. 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