| Co-Investigator(Kenkyū-buntansha) |
TAKAMI Seiichi Graduate School of Engineering, Tohoku Univ., Research Associate, 大学院・工学研究科, 助手 (40311550)
KUBO Momoji Graduate School of Engineering, Tohoku Univ., Research Associate, 大学院・工学研究科, 助手 (90241538)
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| Budget Amount *help |
¥15,000,000 (Direct Cost: ¥15,000,000)
Fiscal Year 2000: ¥4,900,000 (Direct Cost: ¥4,900,000)
Fiscal Year 1999: ¥10,100,000 (Direct Cost: ¥10,100,000)
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| Research Abstract |
Combinatorial chemistry has been developed as an experimental method where it is possible to synthesize hundreds of samples all at once and examine their properties. Originally combinatorial chemistry was proposed and has been developed mainly in the synthesis of organic compounds. Now it is indispensable in the development of drugs and biotechnology. Recently, combinatorial chemistry was introduced into the inorganic field. Especially, because of the increased utility of many elements system, such as thin films, luminous bodies, and magnetoresistances, combinatorial chemistry is expected to work as a highly efficient screening method even in inorganic material synthesis.
On the other hand, computational chemistry is used mainly to elucidate the catalytic mechanism, catalytic activity, and deactivation mechanism in the catalysis field. In addition to the investigation of the mechanism of the well known catalytic reactions at atomic and electronic levels, computational chemistry is expec
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ted to have an important role in predicting new catalysts with high activity, high selectivity, and high resistance to poisons. Recently, we introduced the combinatorial approach to computational chemistry for catalyst design and proposed a new method called "combinatorial computational chemistry". In this approach, the effects of a large number of metals, supports, and additives on the catalytic activity are calculated systematically using computer simulation techniques, in order to predict the best element for each catalytic reaction.
In this project, we developed a lot of programs for first-principle combinatorial computational chemistry, such as (1) accelerated quantum chemical molecular dynamics, (2) open-shell accelerated quantum chemical molecular dynamics, (3) hybrid first-principle quantum chemical molecular dynamics, (4) coarse-grained crystal growth simulator, (5) crystal growth simulator for surface chemical reactions and so on. Moreover, we applied our combinatorial computational chemistry approach to design (1) deNOx catalysts, (2) methanol synthesis catalysts, (3) Fischer-Tropsh synthesis catalysts, etc. and the effectivity and applicability of our combinatorial computational chemistry approach were strongly confirmed. Less
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