Decarburization of steel parts during heat treating results in a lower surface hardness, undesirable residual stress profiles, and poor part performance. Significant effort has been made towards preventing decarburization and determining the impact of annealing time and temperature on decarburization rate. Much of the published research has focused on medium carbon steels, ranging from 0.3wt% C to the eutectoid composition. The goal of the current research is to determine decarburization rates for steels with carbon concentrations above the eutectoid concentration. AISI 52100 steel was heated in air for 12, 24, and 36 hours at three temperature ranges (below A 1 , above A cm , and between A 1 and A cm ). Optical microscopy was used to determine the carbon concentration as a function of depth from the surface. The diffusion coefficients of carbon in austenite and ferrite plus cementite phase assemblages were calculated. These diffusion coefficients can be used in a finite difference simulation to predict decarburization at different temperatures and times.

A physics-based software model is being developed to predict the nitriding and ferritic nitrocarburizing (FNC) performance of quenched and tempered steels with tempered martensitic microstructure. The microstructure of the nitrided and FNC steels is comprised of a white compound layer of nitrides (ε and γ’) and carbides below the surface with a hardened diffusion zone (i.e., case) that is rich in nitrogen and carbon. The composition of the compound layer is predicted using computational thermodynamics to develop alloy specific nitriding potential KN and carburizing potential KC phase diagrams. The thickness of the compound layer is predicted using parabolic kinetics. The diffusion in the tempered martensite case is modeled using diffusion with a reaction. Diffusion paths are also developed on these potential diagrams. These model predictions are compared with experimental results.

The objective of this work is to develop the material and numerical models needed to simulate the carburizing process of an automotive gear. The paper discusses the factors that influence calculation time and accuracy and presents important equations and material property data. It describes how the simulation predicts local carbon content based on diffusion and how quenching computation provides information on stress states and residual stresses. It also explains how to account for the effects of grain growth, volume variation due to phase changes, and transformation plasticity.

Thermochemical surface engineering by nitriding/carburizing of stainless steel causes a surface zone of expanded austenite, which improves the wear resistance of the stainless steel while preserving the stainless behavior. As a consequence of the thermochemical surface engineering, huge residual stresses are introduced in the developing case, arising from the volume expansion that accompanies the dissolution of high interstitial contents in expanded austenite. Modelling of the composition and stress profiles developing during low temperature surface engineering from the processing parameters temperature, time and gas composition is a prerequisite for targeted process optimization. A realistic model to simulate the developing case has to take the following influences on composition and stress into account: - a concentration dependent diffusion coefficient - trapping of nitrogen by chromium atoms - the effect of residual stress on diffusive flux - the effect of residual stress on solubility of interstitials - plastic accommodation of residual stress. The effect of all these contributions on composition and stress profiles will be addressed.

Boriding thermochemical treatment produces layers with high hardness which improves the tribological performance of ductile cast iron while the austempering treatment improves the mechanical performance of the substrate. In this work, samples of the ductile cast iron alloyed with copper, copper-nickel and copper-nickel-molybdenum were borided in a salt bath (borax + aluminum) at temperatures of 850, 900 and 950°C during 2 and 4 hours. The data for the layers obtained were used to determine the diffusion coefficients and activation energies of this process. The results of the calculated diffusion coefficients were similar to those obtained by the direct measurements of the layer thicknesses. For the sample alloyed with Cu or Cu-Ni the activation energy obtained was 141.27 kJ/mol, and for the sample alloyed with Cu-Ni-Mo the value was 212.98 kJ/mol. The statistical parameters and the correlation coefficients (R) showed satisfactory agreement.