Tesfaye Tadesse Molla

Development of High Temperature Mechanical Rig for Characterizing the Viscoplastic Properties of Alloys Used in Solid Oxide Cells

Analyzing the thermomechanical reliability of the solid oxide cell (SOC) stack requires precise measurement of the mechanical properties of the different components in the stack at operating conditions of the SOC. It is challenging to precisely characterize the time-dependent deformational properties of metallic components in the SOC stacks at the required level of stress and operational conditions (high temperature and controlled atmosphere). This work presents an improved methodology for characterizing the time-dependent, or viscoplastic, properties of metallic alloys used in the SOC stacks at a high temperature and in a controlled atmosphere. The methodology uses a mechanical loading rig designed to apply variable and constant loads on samples within a gas-tight high temperature furnace. In addition, a unique, remotely installed length measuring setup involving a laser micrometer is used to monitor deformations in the sample. Application of the methodology is exemplified by measurement of stress relaxation, creep, and constant strain rate behaviors of a high-temperature alloy used in the construction of SOC metallic interconnects at different temperatures. Furthermore, measurements using the proposed methodology are also verified by the literature and experiments conducted using other machines.

An ICME Framework for Design of Stainless Steel for Sintering

Recent progress in the development of integrated computational materials engineering (ICME) models offers new capabilities to deal with the challenge of designing multi-component alloys. In this study, a new type of computational method for efficient design of sintered stainless steel alloys, optimized for manufacturability (sintering) as well for performance, is presented. Development of the design method follows the materials systems approach that integrates processing, structure, and property relations during metal injection molding (MIM). It includes a multi-objective genetic algorithm (GA) to optimize alloy composition with the aim of improving the sintering as well as performance-related properties. To achieve this, the GA is coupled with computational thermodynamics and predictive analytical models. Thermodynamic simulations, based on the calculation of phase diagram CALPHAD method, are used to establish constraints through phase stability at equilibrium and calculate the diffusivity that determines the sintering behavior of the alloy. In addition, an advanced predictive model is used to determine solution strengthening. To demonstrate the capability of our method, a design exercise for austenitic stainless steel is presented. New alloys which are optimized for improved sinterability, yield strength, corrosion resistance, and cost are compared to 316L, a commercially available austenitic steel that is widely produced by MIM.