In pursuit of a PhD and figuring things along the way
Recently, the hotplate I had been using was glitching a lot (it was fine when I was not using it this much). And then I saw this in my social media newsfeed and this seemed to hit right on point:
Currently, I think we have both started to understand each other more, so we have been getting along better. Now, I have nothing but honest praise for the hot plate.
Dear hotplate, you are the best! 🙂
(I took the image from this link but could not find whose brilliant theory this actually is).
When I am a little frustrated, I blog about it. I have found that it clears your head and is quite an effective release mechanism.
And recently, I have found another way for times when I am more frustrated – a LOT frustrated:
Wash glassware.
Just grab a brush, pour a dollop of soap and take it ALL out on the stupid organic stuff sticking in there that just won’t go away. Bonus points for you if you can get it sparkly clean (suitable for a dish-washing soap advertisement) and a gold medal (albeit imaginary) if you can make that water “sheet” over your glassware during your distilled water rinse (nothing more spiritually satisfying than that).
Washing glassware is my research-bane: it’s the rate limiting step to my progress – where I’m most likely to procrastinate when starting a new experiment. To a normal human mind, washing some glass bottles and beakers could look like a mundane and quick step, but it can be quite tiring and time-consuming depending on how finicky you are about your glassware (and of course, we scientists-of-the-wet-labs, have specific procedures for washing our dishes.)
(Also, if you would like to read in depth about the many things that can get your beakers sparkly clean (except for cracks and scratches, where the only remedy might be to get new sparkly-clean glassware), I highly recommend this link).
So if I can have really clean bottles in my cabinet and methodically washed glass slides in my drawer, I have one less excuse to laze around and can start working on my next steps. It’s like killing two birds with one stone and so this is where I can channel the frustration of my failed-lab-experiments.
Now, from my recent frustrations, I have accumulated a fair number of glass bottles and washed slides and I am good for a couple of upcoming series that I should be running.
After I run out, I can think about learning the art of strategic frustration so that I can always have some clean glassware at hand in future, or when needed (not sure how that would work, but if I do, that can be for another blog post).
Lately in science, I have been trying to dissolve a couple of salts in some “solvent” – I have now tried some options, but nothing has really worked so far.
So today, after around 3 weeks of trying to dissolve that salt, I sat down to compile the results of all my mixtures of salts-and-solvents – they could definitely not be called “solutions”.
And that was exactly what was wrong with these, not only scientifically and technically, but also on a literary level: What do I call them when I am writing my report to send to my supervisor?
We, scientists, are supposed to be very specific in terms of technical terms. So I could call them “solutions”, because I was ultimately aiming to make a solution but just was not getting there. But then, they weren’t really solutions, so how could I call them that? If I did, what kind of a scientist would that make me? Would I even be able to sleep at night?
It was a relief I could use the word “suspension” appropriately enough for some of them. That was really so considerate of that particular salt-solvent combination to give me the freedom to use another word.
For all other… Mixtures? Salt-solvent systems?… What do I call them? Or do I just craftily go on writing about them, carefully avoiding sentence structures where I would need to use the you-know-what word?
It’s crazy what people expect of a PhD student: they have to be a scientist in the lab, a writer when writing reports and papers and dissertations, and an excellent communicator when they are supposed to present their work (and the best sales person if they choose to go into entrepreneurship).
And being a writer at that particular moment of time, how many times could I allow myself to use the word “mixture” over and over again? Or using the same sentence structure for every next line?
I do not know how I managed all that today. I just hope I can sleep at night.
It hadn’t been past 12 yesterday when I had officially declared it a bad day for science.
The hot plate I was supposed to be using extensively broke down (again!) and I discovered that one of the good things going on seemed so rosy because I had been miscalculating some things (and misleading myself and others about how it was going so good at that end).
Having been through all that by 11, well, what could happen now that would make it a better day?
But in retrospect, I think I may have labelled yesterday a little too soon – because the day itself didn’t turn out that bad after all.
We, scientists, we label. And that’s a good thing. You should label all your solutions and chemicals as soon as possible, even before you put your stuff in a blank bottle, but essentially ahead of forgetting what you put in there (and until you have labelled these, your life hangs in some kind of a science-purgatory where you keep chanting the words in your head until you have penned it down where it belongs).
But today – today when I was again tempted to categorize the day in the bad-days* section, I reminded myself that a scientist should not label her days as hastily as she should label her sample bottles.
* A “bad” day for science constitutes all days that are worse than your usual days, when it’s normal that things don’t always work the way you want them to. A “bad” day happens when you discover having an outlier compared to your average kind of day (which can normally be rated quite close to each other on a scale of 1 to 10).
It’s a very good thing to practice optimism in life. Optimism can keep you going in the face of challenges, and absurd optimism can keep you going despite past failed experiences and your knowledge of all odds being against you.
But in general, optimism is healthy, and I have been thinking about practicing more of this optimistic approach to life in general.
Except when it comes to my lab work. There, I don’t see how optimism helps me.
Because lab work, well, you can never be too sure about lab work.
And, as past experiments have shown, 95% of experiments don’t usually work the way you want them to (and if you are optimizing some procedure or recipe, the success rate can be quite close to zero).
In principle, I could be optimistic about my experiments before I start them, that may be this is THE time they will work.
But being a scientist, how can you just ignore the evidence of your low success rate of past experiments? How can you disregard all that data?
The thing is, it is easy to be optimistic and hard to be a realistic pessimist. It’s also called “the planning fallacy”, which describes how we, humans, are optimistic about our abilities and predict we can do things much faster and smarter than we actually are able to.
And I have been subject to this planning fallacy numerous times. Dozens of times I have thought I could do my part in group assignments well in time, or that I could surely submit a work update to my supervisor by the end of a week. Or that by July, I’d surely be at a stage where I’d be making my own Perovskite solar cell devices (didn’t happen, just so you know).
90% of the times, though, I have found myself not even close to meeting those deadlines.
So with the lab work, I have no choice but to opt for pessimism as my approach-of-choice to go about it. That despite every strategy that I develop to get my next solution not-cloudy, is probably not going to work, because:
1) It didn’t work the last time, when I very well thought that may be this in THE time it will work.
2) If it, by some tiny amount of chance, does work, and the cloudiness from my solutions clear up, well then, that is exactly how I’d prefer it, wouldn’t I?
So, in the long run, pessimism in the lab is a better option. If it doesn’t work, you are not disappointed, because you knew it wouldn’t work.
And if it does work, you can be twice more happy compared to if you thought that may be this in THE time it will work.
P. S. However, of course, there is a catch. If all of a sudden, everything starts going right in the lab, well, that’s enough ground to include skepticism in your mix of pessimism.
I recently attended a PhD seminar of a student at the Physics department. One interesting question that came up was: What didn’t make it to your thesis?
After deep thought and much analysis, I have realized this is such a good question. It let the candidate show other things he did and learnt in his PhD that didn’t make it to his thesis, because they may have been slightly irrelevant or might have been disregarded as not-important-enough.
But with this question, he could highlight this stuff because he still did those during his PhD (or more likely, he could highlight this stuff well if he’d been prepared for such a question to come up – this may not be your average kind of opponent-speak).
But hang on, is it just this stuff that doesn’t make it to your thesis?
When I was doing my Masters, we’d always joke about how everybody should write 2 theses: One the more formal, “required” document; the other, a document of “failures”: the questions that we asked, and what we tried in the lab, that then didn’t work out, and that we then dropped… which then obviously wouldn’t make it to the thesis. The kind of information that you jot down in the side margins of your lab notebook, along with angry and frustrated emoticons and hashtags and exclamation marks.
The kind of information that doesn’t make it anywhere.
Because that information is also useful, although it mostly just tells you what NOT to do (which is quite the time-saving information). But this kind of information doesn’t have much space in the scientific world. Like people in all other fields, we just want to make noise about the best work that we do, disregarding the important stepping stones that our failures were that got us there.
So yeah, a lot of stuff doesn’t make it to the thesis at any level (or any important document, for that matter – except may be some internal lab communication).
There’s also a lot of other stuff that doesn’t make it to the thesis: the hardwork and energy that you put in, how you picked yourself up after repeated failures, how your informal collaborations helped you (and the people around you)…
… Although if you end up doing really good work, the thesis can become a reflection of it.
Scientists are the last kind of people you’d expect to have superstitions.
But it’s fairly true – science comes with its own set of superstitions.
Which, if you are new or entirely foreign to the science world, wouldn’t make sense at first. But trust me, as you start delving deeper in there, everybody (or so I think) starts developing some strange set of beliefs that have no reasonable explanation.
For example, you have been trying something that has not been working for you, and you are baffled. It seems to work fine for all those other research groups that have a research publication out on the same topic every couple of months. So it definitely works, but what in the world are you doing wrong?
Then you either realize yourself that it must be your “handling”, or you talk to someone who is doing this already and they tell you something particular they do when they do it (in other words, it must be your handling). So you start doing some ritualistic “prep” steps before you begin the process (nothing creepy like animal sacrifice or the kind, but more related to some general lab washing protocols, or how many gloves you should set aside for a protocol, or some equipment settings).
So now, if it works, it was due to this “new” thing, although it doesn’t make any sense why that should have affected the procedure to such a great extent, if at all.
And if it still doesn’t work, then no idea why it didn’t. But congratulations, you have still added a dubious step to your protocol, which you are not sure of, but that’s how it is done, so that’s how it is going to be for all future generations of researchers (and let’s keep it, because it is “good” practice, after all).
So in a science lab, you’ll probably find lots of things that have no logic. People do specific things because they believe that if they don’t wash their slides exactly 4 times, in the right sequence, for the exact amount of seconds, then 11 steps later, they’d discover it didn’t work – again (and well, we are methodical). Or they have procedures that seem to have this seasonal dependency on what month they are being done in (which, again, is not related to position of stars in the sky or if Mars is in retrograde or not). And of course, if that machine is not starting up, drat! That’s because it’s Friday. It’d be fine on Monday.
When you are working in areas that you don’t know anything about, when you are wandering into the unknown (that is the whole point of getting a PhD: to add something new to the knowledge existing in the world), then it sometimes becomes an emotional need to hold onto some explanation before we find out the real one.
So we develop theories on why something isn’t working. We make links where none exist. And this is where we are supposed to be good at, too, because ultimately, on the verge of discovery, this exact habit comes into play, when a reason finally clicks into place for some phenomena that’s been defying all explanations so far.
And in the world of science, some things do work without you knowing why. And often, that’s just how it is (until someone writes a paper about it).
For the last four months, my PhD has accumulated into wonderful experiences of “okay so that doesn’t work”.
Which is good, because every time one thing doesn’t work, there’s one thing less to discover that doesn’t work, getting you one step closer to the thing that does work.
So you have this recipe/procedure/protocol that you need to optimize, or get the best out of. You start off with rather good energies, thinking the most it will take you is, what, three weeks? It seems pretty simple. You’ll easily find the best way to do it in that much of time.
As you try on and on, you realize there are so many factors and parameters that are affecting the whole process. And to get to the best possible option, you will need to twiddle with all of those (ALL of those, one at a time. And then of course you have to make sure that once you are checking one factor, something else doesn’t meddle in and give you some kind of false positive or negative).
But…
… Do you even have all the options jotted down? There might be more. There must be something you are missing.
… What if option G was the best recipe? It did give some results but you probably went ahead trying H, I, J, K, L because you may discover something better (there might be no “better”, but you’ll need to find that out for yourself, now, won’t you?).
… Would “better” pass off as “best”? What even is meant by “best-possible recipe/procedure/protocol”? Is there a “better” than what you are considering “best”?
After everything, you end up with lots of data, most of which is just proof of how, mostly, it doesn’t work (if you are lucky, it may be otherwise). Obviously, there’s always a chance that nothing is going to work. And it might be some time before you realize that you need to change the whole game plan.
I mean, a PhD is like life in real time. So you want to learn about life, go get a PhD: It will teach you things in a couple years that you might take decades to learn otherwise.
If you’ll come to my lab, you’d see strangely labelled glass vials of different shapes and sizes, with all kinds of materials in them.
That is also probably one reason why I couldn’t initially find my way in the lab. Someone might tell me to use a particular solution and there I would be, lost in the freezer, trying to tell one solution apart from another by its color and consistency, or by the fact that there was p10 written on top of it (which I was later told was actually “old” – I’d just been reading it upside down).
The codes, of course, only serve their masters. All I can tell by those are that this is definitely something not I labelled.
Now, may be I find it strange and may be you wouldn’t, because perhaps you yourself have used similar systems, and lived in the same habitats, as my current lab.
I haven’t ever been a part of this kind of system. I have never had so many samples to deal with in my previous research experiences that I’d need to evolve complicated naming systems and rituals for my samples. So in the past, I had been naming my samples with their original name, and putting an underscore/hyphen/period/slash for labeling them specifically for whatever needed specification. The names can get a little long, but it had been working for me just fine.
But now, that I’m going to have lots of samples and solutions to keep track of, and following lab culture, I needed to come up with my own system of naming. And, hey! that system had to be good enough for at least four years for me: What if I stopped liking it halfway past my second year? I’d be stuck and miserable for the rest of my time here! (If not for my whole future career that hopefully lay before me). So I had to be very, very careful.
So how should I carry out the naming of my samples? The alphabets and numbers may make sense to a lot of people, but I am pretty sure that after two weeks of sample initiation, I’d most probably forget what it was and why I had a particular number assigned to it (and what good would be those alphabets and numbers to me then, if I cannot tell what they mean?).
To be able to tell which sample is which, you need to develop an emotional connection with your solutions and samples. So perhaps, you can name them like that as well, like you would name pets, or people.
So, my first sample in the series I did today could be Linda (and Linda, I’m afraid, is not doing too well in the lab). And Scruffy died a couple weeks ago, when I put a colder glass slide on a hot surface and cracked it all the way through (I still have his remains in my drawer). But Sunshine, Sunshine is looking good so far, I hope I can show her to my supervisor sometime in the near future and then take her down to the Physics department. If only Joe, Cookie, and Cheeseburger, will learn something from Sunshine, and keep to their good behavior for just a couple more experiments, It’d be great to take them down, too.
This can be pretty practical but what I particularly love about this system is it’s versatility. So many options and I doubt that I’d ever forget my best sample, Mikasa, from the Tape Effect series.
I guess I should wind up this post now… I have to go put Linda, Joe, Tin Tin, Sunshine, Cookie, Moon Crater, Bloo, and Cheeseburger in the oven.
P. S. I, obviously, also have a more professional, alphanumeric system in place to show the world.
Work in the lab is a slow, agonizing grind (looking forward to that in the four years of my PhD). It’s not like everything works perfectly (except may be on some lucky days).
In fact, behind each successful attempt, there may have been tens or hundreds of experiments gone wrong, done by God-knows-how-many people.
I think I don’t mind my experiments going wrong so much if they can still tell me something I can work on (and they are telling me something new everyday). But I have been so far doing this for only three months in the recent past so sure I don’t mind my experiments going wrong (yet, but ask me in a couple months and I am sure I’ll give you a different answer then).
So I have been trying to get some thick metal oxide coatings (thick, so to speak, but they will still be thinner than half a millimeter by a factor of 1000). For the past three tries, I have ended up destroying the coatings completely.
This time around, I decided to try everything I could think of, so that may be one out of my eight samples might make it to the finish line (I have three back up glass slides just in case things start going south for all eight of them). And one of the coatings, which already appears to have gone every which way, left this sparkly substance on all my gloves.
And a strange happening as this, in a lab, gets all these questions popping in your head: Was that really fine glitter? Did it just happen or did I make it? Did I just discover a method to make, I don’t know, plenty of glitter? Do I now want to drop out of my PhD and open a glitter factory? (after obviously I have done some tests and made the process sustainable).
But it’s a real comfort to me, that I might have possibilities of alternate career paths in the world of glitter-making if my PhD doesn’t go as planned, thank you very much thick-metal-oxide-coatings. However, I need to remember that all that glitters is not gold, and a little, one-time glitter in the lab most certainly doesn’t mean I will also get it once I actually start to aim for it (in fact, more reason for the process to completely stop working).
But back to the topic of experiments that go wrong, sometimes those are the ones that really tell you what’s happening. If everything was going all right, all the time, well then, there wouldn’t be any reason to dig deeper, no need to understand the process behind it. So it’s kind of important to fail in science and learn something from it every time.
But when a series of failures, going on for months, makes you finally realize that what you have been trying may not have been even possible from the beginning, that can be quite frustrating (happens in science all the time and doesn’t feel good to be the one that’s happening to).
