Determination of constitutive properties of thin metallic films on substrates by spherical indentation using neural networks

The indentation test has been developed into a popular method for investiga ting mechanical properties of thin films. However, there exist only some em pirical or semi-analytical methods for determining the hardness and Young's modulus of a film from pyramidal indentation of the film on a substrate, w here the deformation of film and substrate is subjected to be elastic-plast ic. The aim of the present paper is to show how constitutive properties and material. parameters may be determined by using a depth-load trajectory wh ich is related to a fictitious bulk film material. This bulk film material is supposed to possess the same mechanical properties as the real film. It is assumed that the him and the substrate exhibit elastic-plastic material properties with nonlinear isotropic and kinematic hardening. The determinat ion of the depth-load trajectory of the bulk film is a so-called inverse pr oblem. This problem is solved in the present paper using both the depth-loa d trajectory of the pure substrate and the depth-load trajectory of the fil m deposited on this substrate. For this, use is made of the method of neura l networks. Having established the bulk film depth-load trajectory, the set of material parameters entering in the constitutive laws may be determined by using e.g. the method proposed by Huber and Tsakmakis (Huber, N., Tsakm akis, Ch., 1999. Determination of constitutive properties from spherical in dentation data using neural networks. Part II: plasticity with nonlinear is otropic and kinematic hardening. J. Mech. Phys. Solids 47, 1589-1607). (C) 2000 Elsevier Science Ltd. All rights reserved.