Everything seemed poised against any proposed physical and experimental stability of a structure like graphene. “Thermodynamically impossible”– a not uncommon shutdown to proposed novel physical or chemical concepts– was once used to describe the entire field of proposed two-dimensional crystals functioning separately from a three-dimensional base or crystalline structure. Rudolf Peierls and Lev Davoidovich Landau, both very accomplished physicists respectively known for the Manhattan Project and for developing a mathematical theory of helium superfluidity, rejected the possibility of isolated monolayer to few-layered crystal lattices. Their reasoning was that diverging thermodynamic-based crystal lattice fluctuations would render the material unstable regardless of controlled temperature. This logic is flawed, but not necessarily inaccurate– diamond, for instance, is thermodynamically metastable at room temperature and pressure in that there exists a slow (i.e. slow on the scale of millions of years) but continuous transformation to graphite. However, this logic was used to support an explanation of thermodynamic impossibility that was provided for graphene’s lack of isolation as late as 1979 by Cornell solid-state physicist Nathaniel David Mermin. These physicists’ claims had clear and consistent grounding in experimental data: as thin films become thinner, there exists a trend of a decreasing melting temperature and increasing instability that renders the films into islands at somewhere around ten to twenty atomic layers. This is driven by the thermodynamically-favorable minimization of surface energy.
Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.
Protein and gene circuit level synthetic bioengineering can require years to develop a single target. Phage assisted continuous evolution (PACE) is a powerful new tool for rapidly engineering new genes and proteins, but the method requires an automated cell culture system, making it inaccessible to non industrial research programs. Complex protein functions, like specific binding, require similarly dynamic PACE selection that can be alternatively induced or suppressed, with heat labile chemicals like tetracycline. Selection conditions must be controlled continuously over days, with adjustments made every few minutes. To make PACE experiments accessible to the broader community, we designed dedicated cell culture hardware and integrated optogenetically controlled plasmids. The low cost and open source platform allows a user to conduct PACE with continuous monitoring and precise control of evolution using light.