If you stumble across this page and have questions about what life as a physics grad student is like, feel free to hit me up at my name + the word "drive" at a very common email hosting service (obscuring my email address to prevent bots from finding it).
I'm in my final year of my PhD, and plan to graduate in spring 2027. What I have left to do is:
Graphene is like graphite, but it's a sheet only one atom thick. Laser-induced graphene (LIG) is a porous, 3D structure of graphene that's made by shooting a commercial CO2 laser at a polyimide film.
I have been making LIG and testing its resistance and robustness. The idea is that since it's so cheap to make and so configurable (you can change the laser settings when you're making it, or make it in different patterns, or make it from different substrates), it could be a good material to produce resistive sheets out of (which are like traditional electrical resistors, but shaped like sheets).
The application we were targeting was the field cages of time projection chambers (TPCs). TPCs are a common particle tracking technology. To operate, they need a strong, constant, uniform electric field. Normally the fields within TPCs are made uniform by connecting the anode and cathode (the two pieces of metal held at a potential difference) with a chain of resistors. Replacing that chain with a sheet resistor makes a more uniform field, and is safer if there's a discharge.
We found that we couldn't make LIG with our setup that was reproducible at a high enough resistance to limit the current from the high voltages a TPC operates at. But, we're looking to publish that result. I also tested how well our LIG can stand up to the cryogenic temperatures it would see in a TPC by dunking it in liquid nitrogen (it seems liquid nitrogen either totally destroys a resistor or barely affects it) and how well our LIG holds up under some smearing under my finger to get a sense of its physical robustness (smearing greatly increases the resistance, but not in a reproducible way).
I've also been working on a team in the IceCube collaboration, searching for τ neutrinos from space. The IceCube detector is a telescope that's made of around 5000 photomultiplier tubes (PMTs) buried in the ice at the South Pole, spanning a cubic kilometer. Data from the detector is used in a large number of projects. In ours, we look at the pattern of light that the PMTs pick up when a high-energy particle passes through the detector, and try to determine if that pattern came from a τ neutrino.
At high energies (above around 10 TeV), τ neutrinos look pretty different from other neutrinos, because the τ leptons they drop off leave cascades in the detector both when they're produced and when they decay (all other neutrinos leave either one cascade or a while line of cascades). But at lower energies, the τ leptons travel a shorter distance, and the two cascades from their production and decay overlap, so it's harder to tell that signature apart from those from other neutrinos. The approach we're taking is training a transformer (a kind of neural network) to distinguish simulated τ neutrinos and other particles, and then applying that transformer to real data. Another team did this same task with a convolutional neural network (CNN), but we hope to be able to identify more neutrinos with confidence with our newer neural network architecture, newer systematics models, and larger amount of data (since the detector has been running for a longer time).
It's unclear if we'll be finished with this project by the time I need to be working on my thesis (August), so I'm planning on just including the work I'll have done setting up the input for the transformer and training it on distinguishing τ neutrinos and electron neutrinos (our most confusible background).
I've worked on two projects that aren't going to make it into my thesis. The first was helping out an existing team during the unblinding of an analysis that measured neutrino oscillation properties, using info from a CNN trained to determine particles' energies and directions. The second was a search for anomalies in the direction and energy spectrum of neutrinos from the atmosphere that could point to new physics, which I also worked on as part of a team. That project is ongoing at the time of writing (March 2026), and I left because the timescale of the work left didn't fit my graduation timeline.