Our approach is divided into several technical approaches:

1) Precise particle shape specification based on observation, 2) calculation of particle properties and 3) the calculation of the effect of particle shape on the properties of the polymer materials.Our computational webtool ZENO focuses on the calculation of basic properties of advanced composites and the general problem of how these properties depend on filler shape and the intrinsic properties of the particles and the polymer matrix. Application of the model limited at present to the dilute particle limit where particle dispersion is not an important issue. It is essential to study this dilute limit to effectively characterize the particle characteristics. Property changes induced by the particles in the dilute limit provide a useful metrology for particle shape and the intrinsic properties of the particles themselves if the particle shape is known from independent imaging observations. We briefly describe the specific properties to be considered:

Basic composite properties P in the dilute can be written as a virial expansion ,P = P_{o} [1 + [P] c + O(c^{2})], in the particle concentration. Specifically, P is the shear viscosity, thermal and electrical conductivity and the shear and bulk moduli of the composite. The relevant virials are the intrinsic viscosity, the intrinsic conductivity, the intrinsic shear modulus, particle diffusion coefficient, intrinsic bulk modulus, intrinsic Poisson ratio, intrinsic dielectric constant, intrinsic refractive index, intrinsic magnetic permeability, intrinsic hydrodynamic effective mass, and others. These virial coefficients are functions of particle shape, the interface between particle and matrix, and the property contrast between the particle properties which is defined by the property ratio, P_{particle} / P_{matrix} .

Mathematically these property calculations are 'classical' in the sense that they involve the solution to well-known continuum mechanic equations (Laplace, Poisson, Navier-Stokes, Kelvin, Maxwell. etc. ), but the treatment of complex particle shape and boundary data is intractable analytically and provide a challenge for any existing computational resource.The basis of our method is a newly developed path-integral algorithm that solves these problems by averaging over random walk paths.

Since the path-integral approach underlying ZENO is non-standard in materials modelling, we briefly describe its basis and the method of implementation. ZENO first involves enclosing the arbitrarily-shaped object within a sphere from whose surface random walks are launched. The probing trajectories either hit or return to the launch surface ('loss') as shown in the figure for a model soot particle aggregate, whereupon the trajectory is either terminated or re-initiated.

**Figure 1**: Collection of spheres (green) represents a model soot particles (cluster-cluster aggregate) and the path (yellow) represents a probing random walk trajectory. The hydrodynamic radius of the soot particle is determined by fraction trajectories that hit the sphere.

ZENO permits great flexibility in defining particle geometry, e.g., beads, cylinders, ellipsoids, and surfaces with triangulated surfaces, so as to allow more physically realistic modeling of particle structure. ZENO is computationally faster than competing methods for complex geometries and is completely parallel. Most methods have computational times O(n^{3}) where n is the number of body elements, but ZENO computational times are O(n). This is a serious factor for complex bodies where n is large and for random objects where ensembles of objects must be generated and sampled.

The initial development for ZENO was funded by NIST through a collaborative effort with the Stevens Institute and this program is available to the public. Access to ZENO, along with a description of the computed properties, is available through its website:

**Figure 2**: Webpage for ZENO which explains principle and method of computation, downloadable programs for public use and references providing computational validation.