Converged Thoughts Tenby Jay Cuthrell
Sometimes I read published research from Google. Admittedly, it’s often (usually?) way over my head. Sometimes I’ll find a familiar area and learn a bit more about an area that I have brushed up against in my past.
When I went to college in the early 1990s it was for materials science and engineering. Back in those days, you could buy tennis shoes that would last longer than the fashion statements they made.
One area of materials science and engineering is the study of polymeric systems. Plastic? Yep. But there’s more to polymers than just plastic. You contain polymers, such as, DNA.
I remember grad students that studied polymers. Everyone on campus had access to DECstations (and uhm… QBATCH) , Mac SE’s, and sometimes Windows 3.1 towers that would have IEEE or other cards to interface with LabView and the like. Some of those grad students even used computers as part of their research for the purposes of simulation.
One common approach to computational physics is the Monte Carlo method. Back in those days, what you would think of as high performance computing (HPC) was probably a trip up the road to see the Cray… unless you had a SLIP account… but I digress.
Simulation tools have come a long way since the mid 1990s. In fact, there are even open source options when it comes to getting your feet wet or committed to hard edged research.
Fun reading material.
Google Research has done interesting work and published quite a bit of material on how they use various algorithms (like Monte Carlo, et al) and combinations of techniques to extend the body of knowledge in everything from networks to so-called deep learning. Reading their published materials is a real treat and a testament to how Google gives back to the wider scientific computation community as well.
So, how would one see the convergence in shoes and computational simulations of polymeric systems? Well, block copolymers are very interesting. You can think of them like customized polymers that open various design options due to their unique properties.
If you’ve bought a pair of sneakers recently then you know the prices are approaching levels of… well… they are getting spendy! Those sneakers are also highly collectible and valuable as well.
Unfortunately, our material world does not last forever. As such, the fashion that does not last may be reflected in the pricey sneakers that also do not last. But it doesn’t have to be this way. So, it stands to reason that this market is going to get really really feisty as well.
I don’t usually link to Wired but when I do there is probably a good reason.
First, imagine having access to top notch block copolymer researchers with deep understanding of how to leverage computational modeling and simulation to make the PERFECT set of kicks. Oh, and these reserachers know where to go for their high performance computing (HPC) needs.
Yes. I’m biased. 🤓
Next, imagine that you can create a collectible and highly sought after pair of sneakers for a market that seeks a guaranteed set of unique properties and you have the means to control production and set price. And what if they lasted a long time too and your investment was protected from premature degradation? Pretty cool, right?
Here’s where the convergence comes into focus on the consumer experience once again. Imagine going from your wish of perfect kick to your actually shipped overnight perfect set of kicks. Convergence in this instance will be an example of “it just works”.
Finally, imagine that you get to pick specific attributes from the block copolymer that will form your shoes – and you aren’t just picking from A, B, C, or D options… you get full sliders to control the just in time allocation of the copolymerization itself! You will truly have custom made long life shoes in every sense of the process.
We’re not that far away from that possibility and the first steps towards this converged path are only a few clicks away. ALl the remains is the will to satisfy the growing demands of sneakerheads around the world.
✍️ 🤓 Edit on Github 🐙 ✍️
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