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Computer Prediction Used to Design Better Organic Semiconductors 32

Posted by Unknown Lamer
from the check-out-my-computer-pants dept.
An anonymous reader writes "Creating a flexible display requires finding an organic material that's both durable and capable of carrying an electric signal fast enough. To create such a material requires choosing the right compound and combining it with an organic base material. It's a hit and miss affair that can take years of synthesis to get right, but even then the final material may not be good enough. Stanford and Harvard researchers have come up with a much faster solution: use computer prediction to decide on the best compound before synthesizing begins. They also proved it works by developing a new organic semiconductor material 30x faster than the amorphous silicon used in LCDs."
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Computer Prediction Used to Design Better Organic Semiconductors

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  • I have scanned the article it is quite similar to the SARs modeling and prediction techniques that were developed by the pharmaceutical industry long before that; this is just a natural extension.

    • I forgot that SAR means about twelve things, so for the context insensitive people, in this context it means Structure activity relationship

  • Wow, leave it to Standford and Hardvard to come up with the idea to give some thought to a project before implementing an expensive test of viability.

  • What's going on? (Score:5, Insightful)

    by MozeeToby (1163751) on Thursday August 18, 2011 @04:55PM (#37135530)

    What's going on with Slashdot lately? There's a major advance in materials science research and so far a full 100% of the comments are either sarcasm about how stupid the research is or someone arguing that the solution is obvious.

    I just... don't even know what to say anymore. Companies have been pouring money down the drain trying to discover these materials and these guys figured out how to do it more quickly, more effectively, and at a fraction of the cost. Obviously this is a problem that has been looked at by hundreds of engineers and scientists, and this is the first group to successfully apply this technique; and all we can muster is a collective circle jerk trying to sound smart.

    Pathetic

    • I feel somewhat incriminated by your post. So please, let me explain my point of view.

      When I pointed out that this was a natural extension, I was just wondering why the engineer at those company that poured money down the drain have limited them-self to theirs field of research, if they at look at the chemistry involved in pharmaceutics they would have figured this out quite sooner.

      • Fair enough, and I'm certainly not a chemist so I'm in no position to say that you're wrong, and based on what little I know about modeling in the pharmaceutical industry it certainly sounds, on the surface at least, that you're right. Your comment could easily be read as a question, "why didn't they do this earlier?", which is probably a very good question to ask, rather than the way I read it. No offense meant.

        • chemistry is not my thing to, but combinatorics is... and it is used intensively in the pharmaceutical industry, but I only know this from the papers I read, for all I know it could be bullshit.

    • by rmstar (114746)

      I just... don't even know what to say anymore. Companies have been pouring money down the drain trying to discover these materials and these guys figured out how to do it more quickly, more effectively, and at a fraction of the cost. Obviously this is a problem that has been looked at by hundreds of engineers and scientists, and this is the first group to successfully apply this technique; and all we can muster is a collective circle jerk trying to sound smart.

      As someone who has looked into the issues, I ca

      • Well, the numbers in the paper are based on nanoscale assemblies. When you scale up to a 24" display, you'll lose a lot of that efficiency, so it's not really unbelievable.

        Lots and lots of chemists use computational studies, they just don't bother to publish the details because it's often such an obscure molecule that no one else will care. For computational studies to be of any use whatsoever, you have to already have in mind what you're planning on making. You can't just tell Spartan (or whatever softw

    • by Hatta (162192)

      Welcome to /.

    • Obviously this is a problem that has been looked at by hundreds of engineers and scientists, and this is the first group to successfully apply this technique; and all we can muster is a collective circle jerk trying to sound smart.

      This is the first group of scientists besides thousands of undergraduate chemists every year who take a physical chemistry class and had to use Spartan calculate bandgap and relaxation times [umass.edu]. Sorry, there's nothing cool about the computational work in this paper whatsoever, all the novelty is in what they made.

  • by JoshuaZ (1134087) on Thursday August 18, 2011 @04:59PM (#37135570) Homepage

    Over time, there have been more and more ways of getting computers to our scientific work for us. There's been success with this sort of thing for a long time. For example, in math the mid 1990s the Robbins conjecture http://en.wikipedia.org/wiki/Robbins_algebra [wikipedia.org] was proven using essentially an automated theorem proving system. Similarly, Simon Colton has done work with computer systems that can notice patterns and make novel mathematical definitions and conjectures without human input ahref=http://www.cs.uwaterloo.ca/journals/JIS/colton/joisol.htmlrel=url2html-7891 [slashdot.org]http://www.cs.uwaterloo.ca/journals/JIS/colton/joisol.html>. There's been work in other fields as well such as in automated experiment systems in biochemistry http://www.aejournal.net/content/2/1/1 [aejournal.net].

    One interesting thing about TFA is that it is suggesting that powerful enough systems might be able purely through simulation to predict what new compounds are worth investigating. In principle, this could lead eventually to self-improving systems where a system designs better and better algorithms and hardware for itself which it uses to then design even better ones and so on. This sort of Singularity scenario generally seems implausible to me but it is one of the more plausible Singularity scenarios and articles like this make me wonder if it should be taken seriously. Obviously, there are serious limits on that sort of thing, since one runs into the laws of physics and the laws of mathematics eventually. You can't improve algorithms beyond a certain point (you start running into P!=NP sort of issues). And you can't improve physical efficiency beyond the laws of physics. In essence, even if I can look through a search space a 1000 times as fast, that doesn't mean I will find a solution that is a 1000 times as good. But with access to both software and hardware improvements, substantial improvement may be possible.

    Of course, at the current stage this is highly limited. The simulations in question in their current forms can at best target specific molecules that look promising. They are very far from actually predicting the exact behavior. Indeed, my old college roomate is a physicist who works on computational physics and related issues, and one thing he and a few others have been working on for a long time is trying to derive accurate behavior for water from quantum mechanical principles. This is still not doable beyond a rough approximation. The computations are simply too difficult. And as TFA notes, figuring out how to synthesize new compounds can still take years. So this is a really interesting result, but it isn't something that is likely to see immediate impact. Still very cool though.

    • by Chris Burke (6130) on Thursday August 18, 2011 @06:53PM (#37136500) Homepage

      In essence, even if I can look through a search space a 1000 times as fast, that doesn't mean I will find a solution that is a 1000 times as good. But with access to both software and hardware improvements, substantial improvement may be possible.

      That is in essence the problem with Kurzweil-style Singularity predictions. That exponential growth of computing power is somehow magic that will make everything possible.

      Anyway, I personally think that the long term implications of this are a world kinda like Kurt Vonnegut's Player Piano [wikipedia.org], except the jobs of engineers and managers aren't safe either.

    • by godel_56 (1287256)

      One interesting thing about TFA is that it is suggesting that powerful enough systems might be able purely through simulation to predict what new compounds are worth investigating.

      Isn't this what grid computing projects on BOINC, such as Rosetta@Home and various World Community Grid projects are already doing?

  • ...Better Computer Prediction?
  • by jd (1658)

    Just because they're called "wafers" doesn't mean they're supposed to be edible!

    Seriously, protein-based and other forms of organic computing are fields that have been talked a lot about for decades. (References that I know of go back to the 70s, there may well have been earlier.) It's good that they're getting to this stage in organics, though I do have to ask why it has taken so long.

    • Re:Ummm.... (Score:4, Interesting)

      by RobinEggs (1453925) on Thursday August 18, 2011 @06:06PM (#37136088)

      though I do have to ask why it has taken so long.

      Take a few years of organic chemistry courses, especially the labs, and you'll become astounded that they've gotten even this far.

      Organic chemistry, compared to all other things considered "hard" science, is so difficult and the fundamentals so poorly understand that compared to physics or inorganic chemistry it might as well be mysticism. I struggled with it, trying to treat it like a science, for a whole year before my professor finally admitted that they don't know exactly how anything works; the core theories are good science, but have little more real-world proof than quantum physics. And succeeding at something novel in applied organic is far more art than science, despite the need for a post-doctoral scientific background.

      They deserve serious credit for this kind of breakthrough, not questions about why it's "taken so long".

      • by scheme (19778)

        I struggled with it, trying to treat it like a science, for a whole year before my professor finally admitted that they don't know exactly how anything works; the core theories are good science, but have little more real-world proof than quantum physics. And succeeding at something novel in applied organic is far more art than science, despite the need for a post-doctoral scientific background. .

        Are you talking about synthetic organic chemistry or theoretical? I think the theoretical stuff is moderately well understood and is certainly past the mysticism part. Synthetic o-chem OTOH seems to be more about rules of thumbs, guidelines, and art since there's a lot of factors that come into play when synthesizing a novel compound.

        BTW, quantum mechanics, especially the standard model, is very well proven and predicts things to extremely high accuracies. We're talking agreements to 10^-8 or better he

        • I'm definitely talking about the synthetic stuff, like the synthesizing necessary for the organic transistors discussed in TFA. All the side products, unofficial hunches, unpredictable results and all that weirdness combined with having only a moderate understanding (good way of saying it, I guess) of the theory underneath it made me feel like organic was just this side of total loopiness. I mean, in how many other productive fields do you feel awesome when you get 3% yield of something? Maybe a lot, in som
  • It sounds like great research.

    On the other hand, these computers they're using sound pretty damn smart.

    Like smart enough maybe to sabotage the search for their own replacements....

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