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Tire debris is produced by the normal wear of vehicle tire treads. Preliminary results are presented, which aim at characterizing the shape of debris particles by means of fractal analysis. Materials and Methods. Silica and carbon black filled styrene - butadiene rubber debris coming from controlled laboratory wear tests is being analyzed. The binarized images of individual debris particles obtained from a white light microscope are processed by an algorithm [1], which determines the perimeter (P) as a function of the chosen unit of length (yardstick, L). The fractal dimension (D) of the contour is deduced from the Log[P] vs. Log[L] plot [2]. Results. Some sets of wearing conditions (abrader type, pressure, velocity) yield particles in a homogeneous class, described by one value of $D$ in the explored yardstick range. Example: coarse particles similar to those of [3] have $D=1.3$. Particles produced under different conditions need not be homogeneous: Log-Log plots either yield one value of $D$ or exhibit a corner point at a characteristic yardstick length $L_c$. . In this case particles have both a textural and a structural fractal dimension. Interpretation. Particle morphology is the response to wearing conditions mediated by material inhomogeneities at the micrometer scale of length [3, 4, 5]. These results may provide information about crack initiation and tear dynamics [6] in filled elastomers. Applications. Beyond being relevant to the diagnostics of rubber wear processes and to product quality assessment, fractal shape analysis provides a non destructive means, other than analytical electron microscopy [7], of characterizing and identifying tire debris particles in heterogeneous, environmental specimens. With reference to this last application, morphological analysis has to be cross validated by a different method: indeed, the elastomer contents is determined by a purposedly developed, high sensitivity technique, which relies on IR absorption spectroscopy. Res

Some results about the mathematical morphology of tire debris particles are presented and related to other experimental data about the material degradation processes. Fractal analysis has been applied to three types of debris particles originated from the abrasion of silica filled tread rubber under different severity conditions. The structural fractal dimension, D_S , of the particle contour has served as a morphological descriptor (without being regarded as an intrinsic property of the fractured material !). D_S was estimated by processing optical images. A value of the morphological threshold which separates the textural from the structural domain in the RICHARDSON plot was determined in order to maximize discrimination betwen the three particle types and rank them by increasing values of D_S. The FOURIER transform followed by nonlinear filtering was applied to scanning electron microscope (SEM) images of tire debris particles undergoing leaching processes. Some morphological descriptors have been extracted, which quantify the effects of leaching on particle surfaces.

Work outlined herewith aims at identifying rubber particles from treadwear among airborne particulate matter and in soil samples. To this purpose, morphological, microanalytical and chemical characterisation techniques are applied, which include fractal analysis of particle contours, X-ray elemental maps, and infrared absorption spectroscopy. The first results are presented. In detail: 1) the fractal dimension of a rubber particle contour seems to depend on abrasion conditions; 2) airborne rubber particles from samples collected during skid-braking tests of a passenger car are detected and sized; 3) elemental microanalysis detects tread rubber debris in soil samples. As a by-product of characterisation, the representative elementary volume of a compounded elastomer is estimated.

Particles of tread robber debris produced by laboratory wear tests are imaged by light microscopy. The fractal dimension, D F, of the image perimeter is estimated. The sensitivity of D F with respect to the image acquisition and processing parameters is determined. Particles belonging to two types of undifferentiated debris, low severity (LS) and rasping (R), respectively, are analyzed. The values of D Fhave distributions, which, if suitably interpreted, allow the identification of either debris type with the following conditional probabilities: p LS/LS = 0.71 and p R/R = 0.81. The procedure can be eventually applied to environmental impact studies.

Tire debris is produced by the normal wear of tires. Two problems are addressed herewith: characterization of debris particles and their identification in heterogeneous specimens, which come from laboratory wear tests and from the environment. Both problems are solved by analytical electron microscopy (EM). The scanning electron microscope (SEM) shows that tire debris has a typical, warped surface and pores, and that its characteristic elements, detected by energy dispersive X-ray spectroscopy (EDXS), are S and Zn. As a consequence, the identification of tire debris particles in heterogeneous laboratory specimens is straightforward. In those environmental specimens (road dust), where Zn cannot be detected, identification is possible in some cases, provided morphology, microanalysis, and X-ray mapping are combined. The analytical transmission electron microscope characterizes tire debris on the sub-micrometer scale by imaging, EDXS, and electron diffraction patterns. The microstructure exhibits typical elastomer-filler clusters. The representative elementary volume is found to be approximately 8×10 -23 m 3. © 2001 Elsevier Science Inc. All rights reserved.

Tire debris particles from low severity laboratory wear tests have been investigated by the TAOS optical scattering facility at Yale University. The incident wavelength is 532 nm. After the TAOS event some particle samples have been imaged by a scanning electron microscope and microanalyzed. The TAOS intensity patterns recorded within a solid angle in the backward sector have been processed by cluster analysis and compared with the patterns computed by a T-matrix code. Preliminary agreement has been found between TAOS data and the particle models (size, shape, refractive index). The purpose of the investigation is to obtain signatures of the material, based on its TAOS pattern. © 2001 Optical Society of America.

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