BYU Materials Innovation Lab

Here's a new article from our former grad student, Braxton Owens, on feature engineering and machine learning on grain boundaries that was published in npj Computational Materials:

rdcu.be

Here is a new article from our former postdoc, Akarsh Verma, on the tensile loading of an incoherent twin that exhibits non-Arrhenius grain boundary migration. The work also involved Professors Eric Homer and several co-authors.

Deformation and boundary motion analysis of a faceted twin grain boundary In this article, molecular dynamics simulations are used to understand how a nickel bicrystal with faceted incoherent Σ3 grain boundaries responds to …

Here is a new article from our former postdoc, Akarsh Verma, on the effect of solute atoms on non-Arrhenius grain boundary migration. The work also involved Professors Eric Homer, Oliver Johnson and several co-authors.

Solute influence in transitions from non-Arrhenius to stick-slip Arrhenius grain boundary migration Synthetic driving force based molecular dynamics simulations are used to evaluate the grain boundary velocities for an incoherent Σ3 [111] 60° {11 8 5…

Here is a new article from our former postdoc, Akarsh Verma, on factors that impact observations of non-Arrhenius grain boundary migration. The work also involved Professors Eric Homer, Oliver Johnson and several co-authors.

Insights into factors that affect non-Arrhenius migration of a simulated incoherent Σ3 grain boundary Non-Arrhenius grain boundary migration, sometimes referred to as antithermal migration where temperature and GB velocity values are inversely related …

Here's a new article published in collaboration with a Jarod Robinson and Greg Thompson at the University of Alabama. Akarsh Verma and Eric Homer collaborated on the simulations in the work.

Nanotwin stability in alloyed copper under ambient and cryo-temperature dependent deformation states Nanometer size grains, solid solution strengthening, low temperatures, and a high density of nanotwins can provide significant strengthening to a mate…

Here's a new article from our group where we've found a model that describes why some grain boundaries would be able to migrate at cryogenic temperatures and why their velocities would then decrease as higher temperatures. It turns out that non-Arrhenius migration can emerge from competing thermally activated processes.

A classical equation that accounts for observations of non-Arrhenius and cryogenic grain boundary migration - npj Computational Materials Observations of microstructural coarsening at cryogenic temperatures, as well as numerous simulations of grain boundary motion that show faster migration at low temperature than at high temperature, have been troubling because they do not follow the expected Arrhenius behavior. This work demonstrate...

Here's a collaborative project with Prof Homer at BYU and Prof Olivetti at MIT that extracts Aluminum Alloy compositions and properties form thousands of published scientific manuscripts.

Aluminum alloy compositions and properties extracted from a corpus of scientific manuscripts and US patents - Scientific Data Measurement(s) chemical composition of aluminum alloys • mechanical properties of aluminum alloys Technology Type(s) natural language processing

Here's a publication out of Clemson that includes Dr. Homer as a collaborator.

The grain boundary stiffness and its impact on equilibrium shapes and boundary migration: Analysis of the Σ5, 7, 9, and 11 boundaries in Ni Grain boundaries (GBs) play a critical role in the formation of microstructure during materials processing and its subsequent evolution under service …

New article from Dr Johnson and others in our lab.
https://authors.elsevier.com/c/1dRa~4r9SULkBJ

New article written by our recently graduated PhD student Stephen Cluff

Coupling kinetic Monte Carlo and finite element methods to model the strain path sensitivity of the isothermal stress-assisted martensite nucleation in TRIP-assisted steels The properties of TRIP-assisted steels are influenced by the transformation of retained austenite into martensite during deformation via the mechanica…

Our lab is looking to hire a postdoc to work on machine learning and atomistic modeling of metallic interfaces. The opportunity comes with full funding and conference travel.

Candidates must have a Ph.D. in materials science, mechanical engineering, computer science, or a related field with a solid background in general materials science. While experience in particular computational techniques or materials systems is not necessary, a strong background in computational materials science and/or computer programming is required. Excellent written and oral communication skills are essential.
Experience with machine learning methods and the LAMMPS molecular dynamics software is desired. Fluency in Python and MATLAB programming is a plus.

Only candidates with any/all the above-mentioned experience will be considered.