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Algorithm Predicts New Superhard Materials 85

Posted by samzenpus
from the what's-harder-than-hard dept.
An anonymous reader writes "Researchers in New York have developed an algorithm that can predict new superhard materials — a relatively small class of compounds of which diamond is the most famous. Beyond the pluses this represents for, say, the drilling industry, the physicists claim say their computational approach can be used to think up new materials of all sorts. 'New materials with desired properties will be routinely discovered using supercomputers,' they say, 'instead of the expensive trial-and-error method that is used today.'"
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Algorithm Predicts New Superhard Materials

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  • by John Sokol (109591) on Wednesday September 14, 2011 @06:41PM (#37404524) Homepage Journal

    I wrote up a plan for something like this about 2 1/2 years ago and posted on my blog about 9 months ago when it became obvious to me that as cool of an idea as it was, it wasn't something I wanted to work on.

    The basic idea is to take a computational chemistry package and run it through a genetic algorithm to search for suitable candidates that solve certain problems.
    Better solar cells, dielectrics for supercaps, or materials with specific properties.

    The physics quickly went over my head and I was never able to get funding or grants for this without a PhD.

    I am glad to see this is starting to happen.

    Project - Mc Lab / Magic Chemist, in a Box.
      http://johnsokol.blogspot.com/2010/12/project-mc-lab-magic-chemist-in-box.html [blogspot.com]
      http://thegreentank.blogspot.com/2010/12/project-mc-lab-magic-chemist-in-box.html [blogspot.com]

  • by John Sokol (109591) on Wednesday September 14, 2011 @07:20PM (#37404798) Homepage Journal

    Well with enough input knowledge of molecules. You could also use Neural networks or GA to evolve better models, but I did realize the problem you are referring to.

    Again it's not going to be 100%, maybe not even 50% but even 10% would still reduce the search space immensely. The downside is you could easily overlook optimal solutions that don't model correctly.

  • by Anonymous Coward on Thursday September 15, 2011 @12:45AM (#37406586)

    Actually, superconductivity has not been properly modeled in quantum mechanics. There are theories about it, but proper models are Not There Yet (TM).

    So, they can do hardness and such, but not superconductivity. But this is pioneering work so...

    From TFA,

    The suggestion that a high-pressure form of TiO2 is the hardest oxide was made by Swedish researchers in a highly-cited paper published in 2001 in Nature. However, calculations show that all possible forms of TiO2 are much softer than common corundum, Al2O3, and therefore the experimental data from 2001 has to be reconsidered. The latest experiments done at Yale University and the University of Tokyo point in the same direction.

    I'm not certain who wrote this, but experimental data always trumps calculation. If calculation does not match experiment, it is calculation that is wrong. Only experimental data, as in the last sentence, can counter experimental data... Who writes these things?

Slowly and surely the unix crept up on the Nintendo user ...

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