Computer Prediction Used to Design Better Organic Semiconductors 32
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."
this sounds pretty much like SAR + comb. chem. (Score:2)
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.
Re:this sounds pretty much like SAR + comb. chem. (Score:3)
I forgot that SAR means about twelve things, so for the context insensitive people, in this context it means Structure activity relationship
good thinking! (Score:2)
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.
Re:good thinking! (Score:0)
How did you manage to misspell BOTH universities?
Re:good thinking! (Score:0)
Both by adding a superfluous 'd', even.
Re:good thinking! (Score:3)
Oh they're supposed to be Standfor and Hardvar? I've been saying them wrong all these years!
seriously? (Score:-1)
Welcome to computer modeling.. its been around, oh what? 20, 30 years?
I Have A Better Idea: +4, Ingenious (Score:0)
steal the design from this Patent Troll [intellectualventures.com].
Yours In Beijing,
Kilgore T.
What's going on? (Score:5, Insightful)
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
Re:What's going on? (Score:2)
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.
Re:What's going on? (Score:2)
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.
Re:What's going on? (Score:3)
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.
Re:What's going on? (Score:2)
As someone who has looked into the issues, I can tell you that it is very unlikely for these claims to be true to the full extent of the summary. If they really solved the problem as thoroughly as the summary claims, then great. But frankly, I don't believe it. The Nature article seems to be unreachable now, and Nature is about high impact, not actual truth or quality.
Re:What's going on? (Score:3)
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 software you're using), "Show me molecular combinations that give me a 2.8 eV bandgap," it's not the computer of the Enterprise. You have to build the molecules that you think will give you an appropriate bandgap, set the various computational options (which particular molecular theories you want it to use to do the computation, because they all do something well and something poorly), and then sit back for hours while the little beastie chugs along and tries every possible rotation of every bond in the molecules to find the minimum-energy configuration of the interaction. Only at that point will it bother to calculate the bandgap for you based on the overlap of the molecular orbitals.
Re:What's going on? (Score:2)
Welcome to /.
Re:What's going on? (Score:0)
You must be new here...Slashdot is functioning as designed. Move along...nothing to see.
Re:What's going on? (Score:2)
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.
Re:What's going on? (Score:-1)
Re:What's going on? (Score:0)
It's not real news. I do this in the pharmaceutical context every day as a chemo-informaticist and have applied it to macromolecular materials as well as small ligands. If it took someone this long to "discover" combinatorial QSAR, someone's dumb enough to publish it as a discovery, and slashdot laps it up, that reflects poorly on all three parties.
Boinc FTW (Score:0)
It is good to see the worldcommunitygrid.org's clean energy project is doing so well.
Long-term implications? (Score:4, Informative)
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.
Re:Long-term implications? (Score:4, Insightful)
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.
Re:Long-term implications? (Score:1)
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?
Re:Long-term implications? (Score:0)
Similar things happened in the arena of protein folding prediction. Over thirty years people were putting effort into it, with little result. Human genome project was part of such efforts. I just stumbled on one ten year old paper where people figured how to predict if two proteins will "glue" together, but it did not catch too much attention. Despite the fact that computer analysis in mentioned paper was much much faster, since they did not calculate protein conformation, but used totally different approach, in 10 years that followed, nobody continued that work.
Sometimes, if you find something, it may not be usable in an instant. That is the way it goes through the history of science.
Computer Prediction Used to Design... (Score:1)
Ummm.... (Score:2)
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)
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".
Re:Ummm.... (Score:2)
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 here between theoretical predictions and experiments. If it's lacking real-world proof, then well everything else is simply fairytales in comparison.
Re:Ummm.... (Score:2)
I don't know anything about quantum mechanics; I was just thinking about all the really crazy things you hear about with wormholes and time travel and shit that seems (from popular literature and slashdot articles) to have almost certain mathematical proof but almost zero measurable evidence.
Re:Ummm.... (Score:0)
As one of the above ACs who commented that he does combinatorial QSAR for small ligands and materials every day, let me add in: I also make the compounds I model. Chemical theory is highly advanced and a great deal of benchtop work could be eliminated if more synthetic chemists took the time to model their compounds and the reactions they try to perform - often a steric or torsional strain can destroy the necessary alignment of orbitals for bond formation to occur and this can be predicted pretty damn well from ab initio or even force field based simulations.
The old guys at the top of organic chem in academia right now do not have the wherewithal to leverage these tools but once they do, we should finally see a significant reduction in the average of ~5 years required to get an organic chemistry PhD.
Beware! (Score:2)
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....
must watch (Score:0)