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10篇 您的检索式：作者名="Feiler W"

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		题名	作者	年代	出处	被引量
	1	A two dimensional analytical model for the current distribution in a lateral IGBT 显示文摘	HENKEL I FEILER W KOSTKA A	2001	Solid State Electronies2001，45，10：	1
	2	Multistep field plates for high-voltage planar p-n junctions显示文摘	FEILER W FLACK E GERLACH W	1992	IEEE Trans Electron Devices1992，39，6：	1
	3	Multistep field plates forhigh-voltage planar p-n junctions显示文摘	FEILER W FALCK E GERLACH W	1992	IEEE Trans Electron Devices1992，39，6：	1
	4	Effect of relative humidity on adhesion and frictional properties of microand nano-scopic contacts 显示文摘	Adam A Feiler Pal Jenkins Mark W Rutland	2005	Joumal of Adhesion Science and Technology2005，19，：	1
	5	Multistep Field Plates for High-voltage Planar p-n Junctions显示文摘	Feiler W Falck E Gerlach W	1992	IEEE Transactions on Electron Devices1992，39，6：	1
	6	Cell division in higher plants:a cdc2 gene,its 34-kDa product,and histone H1 kinase activity in pea显示文摘	FEILER H S JACOBS T W	1990	Proc Natl Acad Sci USA1990，87，14：	1
	7	Cloning of the pea cdc2 homologue by efficient immunological screening of PCR products显示文摘	FEILER H S JACOBS T W	1991	Plant Mol Biol1991，17，3：	1
	8	Multistepfield plates for high-voltage planar p-n junctions显示文摘	FEILER W FALCK E GERLACH W	1992	IEEE Trans Elec Dev1992，39，6：	1
	9	Multistep field plates for high-voltage planar p-n junctions显示文摘	FEILER W HACK E GERLACH W	1992	IEEE Trans Elec-tron Devices1992，39，6：	1
	10	Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models显示文摘The degradation behaviour of magnesium and its alloys can be tuned by small organic molecules.However,an automatic identification of effective organic additives within the vast chemical space of potential compounds needs sophisticated tools.Herein,we propose two systematic approaches of sparse feature selection for identifying molecular descriptors that are most relevant for the corrosion inhibition efficiency of chemical compounds.One is based on the classical statistical tool of analysis of variance,the other one based on random forests.We demonstrate how both can—when combined with deep neural networks—help to predict the corrosion inhibition efficiencies of chemical compounds for the magnesium alloy ZE41.In particular,we demonstrate that this framework outperforms predictions relying on a random selection of molecular descriptors.Finally,we point out how autoencoders could be used in the future to enable even more accurate automated predictions of corrosion inhibition efficiencies.	Elisabeth J.Schiessler Tim Würger Sviatlana V.Lamaka Robert H.Meißner Christian J.Cyron Mikhail L.Zheludkevich Christian Feiler Roland C.Aydin	2021	npj Computational Materials2021，，1：	0

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