Titlebook: Modeling of Magnetoelectric Effects in Composites; Mirza Bichurin,Vladimir Petrov Book 2014 Springer Science+Business Media Dordrecht 2014

果園

書目名稱Modeling of Magnetoelectric Effects in Composites影響因子(影響力)




書目名稱Modeling of Magnetoelectric Effects in Composites影響因子(影響力)學(xué)科排名




書目名稱Modeling of Magnetoelectric Effects in Composites網(wǎng)絡(luò)公開度




書目名稱Modeling of Magnetoelectric Effects in Composites網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Modeling of Magnetoelectric Effects in Composites被引頻次




書目名稱Modeling of Magnetoelectric Effects in Composites被引頻次學(xué)科排名




書目名稱Modeling of Magnetoelectric Effects in Composites年度引用




書目名稱Modeling of Magnetoelectric Effects in Composites年度引用學(xué)科排名




書目名稱Modeling of Magnetoelectric Effects in Composites讀者反饋




書目名稱Modeling of Magnetoelectric Effects in Composites讀者反饋學(xué)科排名

反抗者

0933-033X s for magnetoelectric coefficients enable finding an optimal.This book brings together numerous contributions to the field of magnetoelectric (ME) composites that have been reported so far. Theoretical models of ME coupling in composites relate to the wide frequency range: from low-frequency to micr

口味

身體萌芽

0933-033X ld, so that the potential of the field can be made transparent to new generations of talent to advance the subject matter..978-94-024-0347-3978-94-017-9156-4Series ISSN 0933-033X Series E-ISSN 2196-2812

Scleroderma

NEG

https://doi.org/10.1007/978-94-017-9156-4Electromechanical Resonance Frequency; Electromechanical Resonance Region; Laminate Composites; ME Effe

concert

繁重

Modeling of Magnetoelectric Effects in Composites978-94-017-9156-4Series ISSN 0933-033X Series E-ISSN 2196-2812

ethereal

Mirza Bichurin,Vladimir PetrovNumerous step-by-step tutorials help the reader to estimate the peak values of magnetoelectric parameters of a composite.Explicit expressions for magnetoelectric coefficients enable finding an optimal

陪審團(tuán)每個(gè)人

The State of Applications and Impacts of Biotechnology in the Livestock Sector,se category, namely, C?te d’Ivoire, Ethiopia, Ghana, Mali, Mauritius, Namibia, Nigeria, Sudan, Tanzania and Uganda. The remaining 33 countries for which information was available were categorized as ‘low’ or ‘very low’. Overall, livestock comes second to crops in terms of level of biotechnology applications in SSA.