Thermal Activated Grain Boundary Creep In Polycolycrystalline Copper
Creep deformation in metals and alloys at intermediate temperatures and low stresses are attributed to power-law and diffusion mechanisms. Thermal activation parameters of steady state creep correlate with the macroscopic and microscopic variables, leading to inter-relationships between the apparent and true parameters. The observations are confirmed by tensile creep data of high purity polycrystalline copper, obtained by stress incremental and temperature differential methods at intermediate temperatures of 573, 673 and 773 K and low stresses of 7.08, 14.16, and 21.24 MPa, for creep rates ranging from 10-7 to 10-5 s-1. The mean apparent (experimental) stress exponent, activation energy and activation volume of 2, 60 kJ/mol and 1.5 x 10-27 m-3, are lower than the true (model) values, suggesting that grain boundary phenomenon is rate controlling, and the difference in values can be associated with the limitations imposed by the internal stress to creep. The decrease of stress exponent with temperature increase indicates transition from power-law creep to Newtonian flow, or progressive weakening of the grain boundaries with enhanced relative movement of the grains. To a first approximation, independent deformation mechanisms or individual strain rates can be coupled to obtain the net strain rate. By superposition of the rate equations, the net strain rate is determined as the sum of three independent creep mechanisms of Cobble diffusion creep, grain boundary sliding and power-law creep. The stress exponent 2 relates to grain boundary sliding, while the lower activation energy with respect to the lattice self-diffusion energy signifies grain boundary movement. Therefore, the most plausible mechanism for the grain boundary diffusion coefficient being higher than the lattice diffusion coefficient in the creep test regime is grain boundary movement. LINEST multiple regression analysis of the creep data establishes excellent correlations between the strain rate, applied stress and temperature; and the best fit creep equation gives values of the regression parameters which are consistent with the empirical values.