Date of Award

8-2018

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Materials Engineering

Committee Chair

Alejandro Strachan

Committee Member 1

Marisol Koslowski

Committee Member 2

Eric Kvam

Committee Member 3

Michael Titus

Abstract

Novel properties in martensitic alloys are predicted using molecular dynamics (MD) simulations, the uncertainty from input models in MD is explored and quantified, and new data infrastructure for MD is developed.

The possible regimes of material properties are extended through free energy landscape engineering (FELE), where coherent, epitaxial integration of two materials at the nanoscale can result in metamaterials with fundamentally different behavior. Free energy as a function of strain is calculated using MD simulations and analytically combined to predict potential new properties for a Ni 63% - Al 37% martensitic alloy combined with B2 NiAl, shown to be an ideal candidate for modifying the martensitic landscape. Direct MD simulations show the landscape predictions hold, producing large reduction in thermal hysteresis while retaining transformation strain, second order martensitic transformations, and both tunable and ultra-low stiffness. These properties are shown for structures including nanolaminates, nanowires, and nanoprecipitates; the final case provides an example of a more easily accessible structure through standard metallurgical processing routes. The uncertainty in these results is described, including atomic level variability, cycle variability, and the interatomic model; the model uncertainty is most significant, but only generally approximated through similar results with a second, independent interatomic potential.

Beginning from simpler models, functional uncertainty quantification (FunUQ) is developed to directly address the errors between multiple interatomic models. Functional derivatives describe the sensitivity to local changes to the input function and a computationally feasible calculation method for MD simulations is derived. Together with the discrepancy between two models, the functional error between models can be calculated. These capabilities are shown for relatively simple MD models, structures, and properties, with possible extension to more complex systems and properties. Challenges are addressed, with primary attention to cases where the discrepancy between input functions is large.

Improvements for community use of MD simulations is finally presented through use of the nanoHUB online collaboration and cloud computing platform to improve a growing materials data infrastructure (MDI). Tools which introduce unfamiliar users to MD simulations are shown first, without coding, downloads, or installation. Next, connections with existing atomistic MDI are described including databases for interatomic models, structures, tests, and properties. Tools to document and improve MD workflows with Jupyter notebooks are then demonstrated, further connecting these tools and resources.

To conclude, future possibilities and challenges with FELE are considered within martensitic materials and beyond, extension of FunUQ to complex interatomic models and applicability to other materials modeling is examined, and new directions in atomistic MDI are discussed

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