Back (no, really)

It’s been a while since I last posted, and I’ve been up to quite a bit since then. For starters, I’m officially done with undergrad - apparently now I’m a bachelor of arts and a master of science.

In other news, I finally (!) decided on a grad school - this fall, I will be moving on from Penn and starting my Ph.D. in physics at Harvard. I actually packed up and moved to Cambridge a week ago, and have been getting settled and starting work in my new lab - I’m doing biophysics work in Dave Weitz’s group, which is really exciting. (More details later…)

Physics bloggers have actually been shuffling around quite a bit: for example, fliptomato has come back to the U.S. from the U.K., while in a happy coincidence Mark Trodden will be leaving Syracuse for… Penn!

A nice little sidenote is that one of my main papers stemming from some of the work I did while at Penn was accepted not too long ago - watch out for it in Nano Letters sometime soon…

And lastly, moving has given me a chance to organize some of the clutter in my life. In that spirit, I’ve decided to give my new personal webpage and this blog a quick makeover.

Meme

So, it looks like I’m part of a blog-meme. I normally wouldn’t do this, but I have some time to kill what with all this flying I’m doing (visiting grad schools). So, here goes, slightly modified…

1. Link to the person who tagged you. Done.

2. List 7 a few random things currently on your mind.

• Where should I go for grad school? I have it narrowed down to a few institutions, each of which has its own particular strengths and weaknesses - in terms of the projects I’m very excited about, equipment/facilities, funding, location, the size of the groups, the intellectual culture, etc. The spreadsheet has them dead even to within uncertainty, which means that I’ll have to keep taking data…

• Some of the research groups I’m interested in joining are quite large. This is often cited as a disadvantage, since it could translate into less “face-time” with the advisor, although to be fair - isn’t the more relevant parameter the (postdoc + senior grad student)/new student ratio rather than the faculty/new student ratio?

• Research - just thinking through the details of a number of experiments and simulations that I’m working on. The annoying thing with all this traveling is that it really punches a hole in my productivity (as well as means I’ll be missing the first half of the APS March Meeting!); but then again, talking to all these fascinating people and finding out about all the cool work going on at these different places is invaluable.

• Another thing that traveling makes difficult is staying on top of the literature. I have several tens of papers waiting to be read, and while long flights are great for plowing through them, the rate at which the to-read list grows is impressive.

• I came across this interesting NYT book review on a recent book, Intern by Sandeep Jauhar. The gist is Scrubs-ian in nature - it’s the story of a medical intern trying to deal with the imperfections of day-to-day hospital culture, the meaning of life, etc. - but what really got me was his physics background (he has a Ph.D. from Berkeley) and the analogies he makes: “Life on the wards was like the plasmons I had studied in condensed matter physics… where individual electrons, moving randomly, coalesced into something greater than the sum of their parts. There was a sort of synchronized buzz. … In the midst of this collective excitation, I kept thinking, Why am I so lonely?” Alright, so it’s kind of a stretch, but still - it’s physics.

3. Tag more people at the end of your blog and link to theirs. I’ll suggest Rod, Sam and Travis.

4. Let the tagged people know by leaving a note on their site. Done.

Graduate School

It’s graduate admissions season, apparently. So far I’ve heard back from six institutions: four acceptances (including a number of my top choices) with fellowships at two of them, one we’ll-fly-you-out ‘interview’, and one phone interview that went rather well… so at the end of the day, figuring out where I want to end up may be nontrivial.

As I noted in a previous comment, my algorithm for deciding where to apply to was pretty simple: I spent a good deal of time soul-searching and deciding (roughly) what I want to do for the next five-ish years, made a list of all the people I thought would make good research advisors to that end, and applied to the n departments that contained the maximal number of the people on my list (where n was determined by how many applications I was willing to fill out; turned out to be thirteen in total - I’m not superstitious).

My algorithm for deciding where to go for grad school will probably be a variant of the algorithm I used to pick my undergrad institution, and again is not too complicated (Sean Carroll has a very nice post on this subject, btw, as does okham as I just discovered):

1. Make a list of all the factors that I care about: for example, number/quality of advisors who I’m interested in (based on various factors like personal interactions, reputation, publication record, how they place people…), how excited I am by current research efforts, intellectual environment, potential for interesting collaborations, other students, location, quality of the department/school/life, bureaucratic requirements, funding, etc.

2. Weight individual factors accordingly: pretty self-explanatory, although this requires a lot of thought.

3. Visit all the places I’m seriously considering/find out as much about them as possible: this is the data collection stage, so that I have a good idea of how various places shape up in terms of the factors I listed. I’m pretty much traveling every weekend from next Friday to the end of March, with a few days in between for the APS March meeting. That’ll be fun.

4. Assign data values corresponding to each factor for each department: i.e. the results of step #3. These data values will obviously have error bars to reflect the subjectivity inherent to the data collection process, but the inverse relationship between error bar size and time spent on step #3 should enable a single-valued result.

5. Plug and chug: go wherever above algorithm says to go. Hey, it worked pretty well for my undergrad.

Speaking of which, I feel compelled to plug Penn. If anyone reading this happens to be a senior who got into Penn (terminology: I refer to UPenn, not Penn State) for something physics / materials science / nanoscience-related, I strongly urge you to think about coming here for grad school. There’s a lot of very exciting work going on here, and a lot of great people to work with - fantastic intellectual environment (I would say Penn does pretty highly on all the factors I mentioned above).

Wrapping up the summer

Crazily enough, the summer’s over. I’ve been bitten by the research bug, which means that I’m not as enthusiastic about taking classes as I once was, although they all look very interesting and useful. In particular, balancing nocturnal data-taking sessions with going to class/taking tests has never been my forte; and it’s tougher now, what with graduate school applications and pesky standardized tests.

Anyway, the past month’s pretty much consisted of finishing up taking/analyzing data for this paper I’ve been working on, as well as actually writing it. When I started out, I thought my data was somewhat interesting. Thanks to an excellent theorist collaborator, we have a good sense of what’s going, and it’s more interesting than I thought (which is always nice).

I did take a little vacation and went to the Princeton Center for Complex Materials (PCCM) summer school on condensed matter physics (unfortunately they don’t have their talks online yet). This is the second year that I’ve gone; hopefully there will be more. Two talks in particular resonated with me - Philip Kim’s talk on electronic transport in graphene, and Paul Chaikin’s talk on some aspects of colloidal physics. The graphene talk was of particular interest from a technical point of view. While it was very cool, given the nature of my work it dealt with things that I’m very familiar with and/or think about regularly, so I’m not going to describe it here.

On the other hand, Chaikin’s talk was interesting to me from a more conceptual point of view. I’ve encountered some notions of soft matter physics before, but his talk really drove home how exciting some of the things going on in that field are. He started off discussing his recent highly-publicized work on packing hard particles (interesting not only for studying granular materials or phase transitions, but also for designing three-dimensional colloidal photonic crystals) - the point being that random ellipsoid packings (like those formed using M&M’s) can pack denser than ‘conventional’ random jammed packings, even potentially approaching the FCC packing fraction of 0.74, because of their added rotational degrees of freedom. This, in turn, may help understand how glasses form. For me it wasn’t the story but how they fleshed it out (experimentally and using simulations) that was the exciting part.

Unfortunately I had an experiment to finish up and had to miss Chaikin’s second talk, on replication and self-assembly using colloids; his third talk on ‘random organization’ describing some work by David Pine (at NYU) and Jerry Gollub (at Haverford, but also affiliated with Penn) was equally good. He started out discussing reversibility in viscous liquids - that is, the fact that low Reynolds number shear flows are time reversible, a notion I first came across in an excellent article by Brewer and Hahn describing NMR spin echos. There’s a classic demonstration of this phenomenon by G. I. Taylor using a cylindrical Couette cell, although I couldn’t find a nice movie online. Anyway, similar experiments have been performed involving tracking small dyed spheres placed in the liquid while shearing them. Interestingly, while the system remains reversible for low enough strain amplitude, for whatever reason (e.g. collisions/chaos), hydrodynamic irreversibility sets in very quickly as the strain amplitude is increased. Really striking stuff. At the end of the day, colloids really are great systems to work with: they’re easy to make, specific and controllable (e.g. using DNA sticky ends or electric fields), and exhibit all kinds of interesting condensed matter phenomena.

Now that I think of it, the PCCM summer school was so enjoyable partly because it filled in the void left by the lack of regular talks and seminars over the summer. Thankfully, now that the new semester has started, that void has been filled again. Most recently, Jack Harris (from Yale) gave a talk on coupling light and MEMS using radiation pressure, something I don’t know much about. Part of the experimental challenge is in using the right structures; interestingly, a route his group is taking is to use silicon nitride membranes with holes drilled in them. I find this particularly amusing because our group has used (indeed, I made some my first year of research) similar porous membranes to image carbon nanotubes or nanotube-derived structures (like ‘peapods’) using TEM - it never occurred to me that they could be used for such a different purpose.

Anyway, writing this post has been very relaxing; now it’s time to get back to work…

To Read: NRC Report

I’m in the middle of taking some data, which can often be very tedious. Due to the nature of my research, once I’ve optimized the parameters to maximize the signal-to-noise ratio on this particular instrument as much as physically possible, taking this kind of data generally means sitting alone in a harshly-lit room for hours on end, staring at a computer screen and hoping desperately that nothing goes wrong. This often makes for a very Zen experience, particularly if I finish right as dawn is breaking and everything is dead silent.

And although this leaves a lot of time to think about other aspects of my research (which is always nice), after the n-th hour (for n very large) I generally find myself itching for something else to do or read. Which is why I started a new ‘things to read‘ list a while back, with my latest addition being the National Research Council’s 2007 Report on Condensed-Matter and Materials Physics (CMMP).

If the report is what I think it is, it’ll make for interesting reading. It’s centered around six key questions:

- How do complex phenomena emerge from simple ingredients?
- How will the energy demands of future generations be met?
- What is the physics of life?
- What happens far from equilibrium and why?
- What new discoveries await us in the nanoworld?
- How will the information technology revolution be extended?

Graduate school is a year away, and I most definitely plan on pursuing something in or related to CMMP - so it will be good to have this as a road map.