Prediction of acentric crystal structure of complex crystals by neural net analysis

机译：神经网络分析预测复杂晶体的无心晶体结构

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Neural net analysis is tested as a tool for prediction of acentricity of crystal structure. A set of input parameters is defined that gives the prediction with as high probability as ~80%. The neural net is used for prediction of new binary acentric molybdates.

机译：神经网络分析被测试为预测晶体结构的偏心度的工具。定义了一组输入参数，该参数以高达〜80％的高概率给出预测。神经网络用于预测新的二元无心钼酸盐。

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《10th International Conference and Seminar on Micro/Nanotechnologies and Electron Devices (EDM 2009)》|2009年|20-22|共3页
会议地点 Novosibirsk(RU);Novosibirsk(RU)
作者
Korotkov A.S.; Atuchin V.V.;
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Lab. of Opt. Mater. Struct., SB RAS, Novosibirsk, Russia;

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caesium compounds; crystal structure; materials science computing; neural nets; nonlinear optics; optical materials; zinc compounds; Cssub6/subZnsub5/subMosub8/subOsub32/sub; binary acentric molybdates; neural net analysis; nonlinear optical materials; Neural net; acentric structure; complex molybdate;

机译：铯化合物;晶体结构;材料科学计算;神经网络;非线性光学;光学材料;锌化合物; Cs _{6 Zn _{5 Mo _{8 O _{32 ;二元非中心钼酸盐;神经网络分析;非线性光学材料;神经网络;非中心结构;复合钼酸盐;}}}}

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Prediction of acentric crystal structure of complex crystals by neural net analysis

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