Christopher DiMarco

Alumni (Ph.D. 2019)
Education:
Arcadia University, B.S. in Mathematics
Columbia University, B.S. and M.S. in Mechanical Engineering
 
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Research Bio:
 
I am a final-year PhD student co-advised by Professors Jeffrey Kysar and James Hone. My research interests pertain to exploring the mechanics of materials of small scale systems through both experiments and computations. My PhD research has focused on the mechanical properties of two-dimensional materials. In particular, we are interested in understanding and measuring the mechanical properties of grain boundaries in polycrystalline graphene synthesized via Chemical Vapor Deposition (CVD). My research can be broken into three interrelated projects: (1) the optimization of graphene synthesis through CVD , (2) the measurement of the critical failure load of suspended circular graphene membranes through nanoindentation, and (3) the construction of a multiscale model to analyze and predict the failure modes of polycrystalline graphene, as well as the statistics of failure.  
 
We designed and constructed an Ultra-High Purity (UHP) automated CVD system in order to minimize uncertainty and oxidizing impurities. This yields (1) repeatability, (2) well-stitched grain boundaries, and (3) the ability to grow graphene at lower temperatures. Combined with electropolishing, we produce very flat, clean, and mechanically robust large-area monolayer polycrystalline graphene films. The monolayer films are in turn transferred through electrochemical delamination to a holey silicon nitride substrate for mechanical testing. Lastly, we subject the suspended circular membranes to a near-point load through nanoindentation and measure the statistical distribution of the mechanical stiffness, the pre-stress, and the critical failure load based on the local distribution of grain boundaries.  
 
In parallel, we constructed a multiscale model using the Finite Element Method (FEM) to explore the failure modes of polycrystalline graphene within the context of the nanoindentation experiments. We model the grain boundary with a Cohesive Zone Model (CZM) whose properties are determined from Molecular Dynamics (MD) simulations. To connect to experiments, we formulated a Probability Density Function (PDF) that is informed by the multiscale model to provide a statistical distribution of the breaking load based on an idealized two-dimensional grain structure. This PDF provides the means to (1) experimentally validate our CZM properties of the grain boundary and (2) perform an inverse analysis to back-out the grain boundary strength from experimental data. 
 
Hobbies:
Rock climbing, Skiing

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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