Category: General Science

Posted on

Doing Dishes

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).

Posted on

Problem: Solutions

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.

Posted on

Bad Day for Science?

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).

Posted on

The Pessimist In The Lab

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.

Posted on

Storry Telling – Part I

When you are a scientist, there’ll be countless times when you’ll be required to “communicate your work”. It’s necessary, it’s woven into the current system, and it makes sure people don’t have to reinvent the wheel (or at least that’s the point).

But sciieeeence… is too technical for good communication. And when it gets too specific (as in a PhD research), then it appears very far off from being relevant to general life. This means that often when science IS being communicated, it may not be reaching the ears it should be reaching.

Now that doesn’t matter in a lot of cases, because, after all, it is science and not a novel that we want to sell a 100 million copies of. It’s for other scientists, more specifically for those who are related to your own field of work… And even in there, people who really read your writings will be people who are almost exactly working on the same thing as you (how many people in the world does that mean, especially for a junior scientist? 10? Maaaay be 20, if they find your article)… And even they will not be reading it word to word, but mostly just skimming it, and extracting those precious couple of sentences that they’d find most relevant for their own work (and that you, by the way, spent months working to get).

So yeah, it is okay if it is boring and technical, because it is not meant to torture a whole lot of people (just the ones who might really need to read it).

Now this may seem sloppy on behalf of a scientist (although most of us are making a sincere effort to put forth that gibberish-to-your-ears in the most understandable way possible). And then, of course, we need to interact with people from other disciplines of science, and no matter how big of a scientist you are, it still helps that people from other fields can break their stuff down to bare basics for you to understand.

So good communication is still the king.

One of the key ways of communicating effectively is to tell it as a story (and this fad has been going on for a while now). And the thing, which I have always had a hard time understanding, is: how do you tell a scientific work as a story?

Story telling has so many elements, and so many styles: so which one is most suitable for the communication of a scientific work?

Okay, so you can give a good introduction. Start off by introducing the theme and “characters” of your story. If you give your audience (or readers) a really good introduction to ground them in understanding, it becomes easier (on both sides) as you progress.

Another aspect of this can be to tell your story with the story of your work. So you tried something, and it didn’t work (or, surprise!, this time it did work), and that’s how you jumped on this new idea that you’ll be telling people about (but hang on! you shall not overdo it, because, after all, thou shalt talk about science more).

Because story telling involves a lot of elements that can directly affect the integrity of your science. Like exaggerations. Or sometimes unnecessary and frilly details. It often also requires knowledge of the complete picture (which you never have in science until may be after you have gone through everything).

 

In science communication, I find this quite interesting as a scientist myself: What limits can you test and how far can you push the boundaries of science communication by applying principles of story telling?

(And how sorry should you be if you fail at it).

Posted on

What Doesn’t Make It To THE Thesis

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.

Jargon that only the person who owns the lab notebook may understand – And now I realize how I don’t make much useful or interesting notes in my lab notebook :'(

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.

Posted on

Blocked

I find writer’s block to be quite a fascinating thing.

It’s really a great reason for an author to be not-writing (read reason as excuse). And the best part is, it is considered a valid one, too. It’s the exact reason I am not writing a blog post every day.

In fact, it’d be pretty great to come up with terminologies for every kind of block that a PhD student might face. Like the “lab-experiment-block” or the “reader’s-block”. Or just plain old “work-block” that could fill in every time we don’t feel like working.

However, I do think even the far-better-evolved excuse of writer’s block would stop working so well for me once I start writing my PhD thesis (like everything else in science that doesn’t work).

Anyway, the other day, I was listening to this podcast “No Such Thing (As Writer’s Block)“. It tells, among other things, the routine of Isaac Asimov, the big sci-fi writer. He got up early morning, sat down and wrote… whether or not he felt like it. Every day.

Writing daily is a little daunting. I have given it a try in the recent past, and well, you can write daily if you want to, but you surely wouldn’t be producing your best work every day. Some days, yes, but not every day. However, statistically speaking, if you write something daily, then you increase your chances of producing something worthy at least some of the days.

Just as doing science daily is a little daunting, and somewhat demotivating if you are not seeing immediate results at least some of the times. But every experiment that you run, adds up, whether it was a failure or moderately successful. The more you put in, the better chances you have of seeing patterns.

Although you can sometimes get lost in “the cloud”, as this professor notes in this rather interesting TED Talk (that you might want to listen to if you are in science, or a problem solver in general).

Posted on

Buried Under Literature

I recently learned I could get updates on recently published research of my particular field by creating alerts in Google Scholar.

After “learning” this, I realized I had to have it. What was I doing, did I want to get out of my hole after four years of my PhD and realized I didn’t know where the world was going? That was not the way to go.

I should know what the current trends are in my field, where the research is going, and how many people (and which groups) are publishing work that is identical to my own (also so that I can send them hate mail if they publish something I was just about to submit).

So I did that. I followed some of the most notable names in my field, created alerts for their works, and also for articles related to their expertise. Breezy easy. I now just had to follow through.

The thing is, if you have very famous people, they seem to be publishing something every other day (probably some kind of “you become famous, you publish more, you become more famous, you get published even more” infinite loop). And the mails I receive every other day have something from a couple to around ten or eleven titles. But of course, if you have related people in your alerts, then some papers are obviously going to overlap.

Now I am blindly downloading papers I know I’m not even going to read half of – there are lots of interesting titles that I would like to get to know more, but then again, they are not related to the “core” of what I’m doing, and having so much to read already ensures that I’m probably never going to read most of them. But that does not deter me from the simple act of saving all pdfs to my downloads folder, with arbitrary, unintelligible titles, further decreasing the probability of me ever reading them, or even knowing why I downloaded them in the first place.

The only fear I have, is downloading the same paper more than once. I do not want to have it so that I read a paper twice, despite all my precautions, because I apparently had two copies ( one of which did not land in my “Read” folder after I’d read it).

I do not want to waste my precious time on a single paper, time that I could have easily wasted elsewhere, in more fun manner.

Sigh. I should now get back to my other form of wasting time, cataloging all literature in my computer to see if I have a second copy of something lurking in my hard drive (I seem to only have downloaded papers in the past four months rather than reading actual literature).

Posted on

Very Superstitious

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).

Posted on

That Doesn’t Work

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.