During my dissertation, I was lookig for information on the emissiom of 172nm scintillation light in mixtures of gaseous Xe and CO2 (95:5% - 98:2%), with results being difficult to come by. I found a collaborator who had tested this at lower CO2 concentrations (0-0.5%), but nothing else, no predictions or generalizable applications. Not knowing the optimal search engine terms or what textbook to look in for rules governing gaseous light emission, I ended up looking in fluorescence chemistry papers (my previous field of study) which had something called the Stern-Volmer relation for different concentrations of quenchant in a fluorescent solution. I figured gas scintillation queching was probably similar to liquid fluorescence quenching, but the standard relation didn’t quite fit below 10% additive.
I dug around more and found a modification of this relation for diffusion-limited quenching of fluorescent solutions (the same limitation imposed in gas mixtures, quenching due to random Brownian collisions) that employed an exponential term, allowing for a smoother curve down to low additive concentrations. This perfectly matched the available data and allowed me to model the predicted behavior. I discussed this with the one member of my committee who was available, an organic chemist (my PI was on vacation, everyone else was sick, and my dissertation defense was in 2 weeks). He said my reasoning and math for using this formula made sense and gave me a thumbs up to include this analysis. When my PI came back from holiday, he asked me why I didn’t use some equation generally used in the field, or even just a generic exponential fit. I was ignorant of his suggestion, but it provided the same general formulation as Stern-Volmer, though Stern-Volmer was more rigorously derived mathematically.
Mixing fields is super cool and can allow a much deeper understanding of the underlying principles, as opposed to limiting yourself to one branch of science. While my PI’s recommendation would have given approximately the same answer, understanding and applying Stern-Volmer allowed me to really dig at the principles at play and generate a more accurate and in-depth model, which I managed to write up and defend at the 11th hour.
@drail@fedia.io built a wall made up of a 90 mins presentation around himself to defend his dissertation from his committee. The committee members built a wall of 120 mins of questions and internal discussions around that trapping @drail@fedia.io in for even longer. The whole affair was brutal. No one came out unscathed, yet no one can remember what happened except for the extremely troubling moments.
I’ve seen things. Things you’d never understand. All I can say is that the best dissertation defense is a good dissertation offense. So much blood on my hands…
Here goes:
During my dissertation, I was lookig for information on the emissiom of 172nm scintillation light in mixtures of gaseous Xe and CO2 (95:5% - 98:2%), with results being difficult to come by. I found a collaborator who had tested this at lower CO2 concentrations (0-0.5%), but nothing else, no predictions or generalizable applications. Not knowing the optimal search engine terms or what textbook to look in for rules governing gaseous light emission, I ended up looking in fluorescence chemistry papers (my previous field of study) which had something called the Stern-Volmer relation for different concentrations of quenchant in a fluorescent solution. I figured gas scintillation queching was probably similar to liquid fluorescence quenching, but the standard relation didn’t quite fit below 10% additive.
I dug around more and found a modification of this relation for diffusion-limited quenching of fluorescent solutions (the same limitation imposed in gas mixtures, quenching due to random Brownian collisions) that employed an exponential term, allowing for a smoother curve down to low additive concentrations. This perfectly matched the available data and allowed me to model the predicted behavior. I discussed this with the one member of my committee who was available, an organic chemist (my PI was on vacation, everyone else was sick, and my dissertation defense was in 2 weeks). He said my reasoning and math for using this formula made sense and gave me a thumbs up to include this analysis. When my PI came back from holiday, he asked me why I didn’t use some equation generally used in the field, or even just a generic exponential fit. I was ignorant of his suggestion, but it provided the same general formulation as Stern-Volmer, though Stern-Volmer was more rigorously derived mathematically.
Mixing fields is super cool and can allow a much deeper understanding of the underlying principles, as opposed to limiting yourself to one branch of science. While my PI’s recommendation would have given approximately the same answer, understanding and applying Stern-Volmer allowed me to really dig at the principles at play and generate a more accurate and in-depth model, which I managed to write up and defend at the 11th hour.
I understood so little of this lol. But good job.
The assignment was to infodump, so I will take that as a compliment. I was aiming for detailed and hyperspecific.
You achieved it
How did the defense go
@drail@fedia.io built a wall made up of a 90 mins presentation around himself to defend his dissertation from his committee. The committee members built a wall of 120 mins of questions and internal discussions around that trapping @drail@fedia.io in for even longer. The whole affair was brutal. No one came out unscathed, yet no one can remember what happened except for the extremely troubling moments.
A moment of silence in remembrance…
🧑🎓 🫡🫡🫡
I’ve seen things. Things you’d never understand. All I can say is that the best dissertation defense is a good dissertation offense. So much blood on my hands…
One of my professors likened it to overeducated wolves surrounding a wounded elk.
Obviously the elk is weak. But is it weak enough?
I am now Dr. Drail, so it went well! This was back in August, so I am still in recovery mode while I job search.
Congrats and good luck on the hunt
Interesting, yet another proof that math is useful!