EAGER: An Innovative Modelling Approach to Predict Non-Equilibrium Phases Produced in Metal Additive Manufacture Processes

University Of Alabama In Huntsville, Huntsville AL

Investigators

Abstract

This EArly-concept Grant for Exploratory Research (EAGER) project will develop a new and untested approach toward modeling of the non-equilibrium behavior of complex metal alloys in terms of the evolution of their atomic arrangement. In additive manufacturing of metals, various process maps are used to guide the selection of time and temperature to produce the desired microstructure to meet the required mechanical properties or performance. Most metal fabrication processes occur at equilibrium, with known conditions of temperature and time. In contrast, the laser-engineered net shaping and related additive manufacturing processes builds a part by depositing the metal as small molten drops which are rapidly and repeatedly heated and solidified layer by layer. While this greatly reduces the time, cost, and weight in the direct build of a complex multi-part assembly, the rapid and repeated melting and re-solidification in additive manufacturing results in a variety of difficult-to-predict non-equilibrium phases that lead to uncertainty in the resulting microstructure and mechanical properties. At present, expensive trial-and-error experimental studies form the basis for such microstructural development. This work has the potential to realize non-equilibrium maps that will enable the full potential of additive manufacturing, thereby advancing the processing of industrially significant alloys to empower new applications in the biomedical, aerospace, chemical, and energy industries. As a result, this work will enhance the US economy, society, and global competitiveness in manufacturing. To realize the full potential for reducing fabrication costs through the use of additive manufacturing, viable thermodynamic and kinetic road maps need to be generated for predicting the microstructures to guide and optimize the processing parameters to optimize the material performance. The thermodynamics and kinetics of Inconel 718, a nickel based superalloy, will be modeled from first-principles calculations and data-intensive statistical mechanics approaches. The temporal evolution of atomic arrangements at given temperature and chemical potentials, will be modeled based on the diffusion through vacancy mechanism. The change of atomic configuration will be simulated under an adiabatic approximation, averaging out fast degrees of freedom such as electronic and lattice vibrations on the hopping time scale. Then, the temporal evolution of atomic arrangement will be modeled by a series of events: switching a vacancy with one of its nearest neighbor atoms, which is equivalent to the hopping of the switched atom to the vacant site. Integrating numerical predictions with experimentally observed microstructural responses will rapidly verify the proposed approach. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.