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Cover Image, Volume 39, Issue 4
Journal of Computational Chemistry ( IF 3 ) Pub Date : 2017-12-12 , DOI: 10.1002/jcc.25131


On page 191, Al'ona Furmanchuk and coworkers present ThermoEl, a tool to predict properties of thermoelectric materials without restriction to fixed stoichiometry. ThermoEl is designed to predict the Seebeck coefficient in the temperature range between 300K and 100K. For production of the tool a set of regression models was used to learn features of 927 synthesized crystalline materials. In order to generate prediction, ThermoEl prompts users to input the chemical formula, the production method, and crystallinity type of the material of interest. (DOI: 10.1002/jcc.25067).
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中文翻译:

封面图片,第39卷,第4期

在第191页上,Al'ona Furmanchuk和同事们提出了ThermoEl,这是一种预测热电材料特性的工具,而不受固定化学计量的限制。ThermoEl设计用于在300K至100K的温度范围内预测塞贝克系数。为了生产该工具,使用了一组回归模型来学习927种合成晶体材料的特征。为了生成预测,ThermoEl会提示用户输入目标材料的化学式,生产方法和结晶度类型。(DOI:10.1002 / jcc.25067)。
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更新日期:2017-12-12
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