Non-Arrhenius conductivity in the fast lithium conductorLi1.2Ti1.8Al0.2(PO4)3: ALi7NMR and electric impedance study

2005 ◽  
Vol 72 (9) ◽  
Author(s):  
K. Arbi ◽  
M. Tabellout ◽  
M. G. Lazarraga ◽  
J. M. Rojo ◽  
J. Sanz
2011 ◽  
Vol 406 (13) ◽  
pp. 2565-2569 ◽  
Author(s):  
Saadi Abdul Jawad ◽  
Adnan S. Abu-Surrah ◽  
Mufeed Maghrabi ◽  
Ziad Khattari

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4129
Author(s):  
Sisay Mebre Abie ◽  
Ørjan Grøttem Martinsen ◽  
Bjørg Egelandsdal ◽  
Jie Hou ◽  
Frøydis Bjerke ◽  
...  

This study was performed to test bioimpedance as a tool to detect the effect of different thawing methods on meat quality to aid in the eventual creation of an electric impedance-based food quality monitoring system. The electric impedance was measured for fresh pork, thawed pork, and during quick and slow thawing. A clear difference was observed between fresh and thawed samples for both impedance parameters. Impedance was different between the fresh and the frozen-thawed samples, but there were no impedance differences between frozen-thawed samples and the ones that were frozen-thawed and then stored at +3 °C for an additional 16 h after thawing. The phase angle was also different between fresh and the frozen-thawed samples. At high frequency, there were small, but clear phase angle differences between frozen-thawed samples and the samples that were frozen-thawed and subsequently stored for more than 16 h at +3 °C. Furthermore, the deep learning model LSTM-RNN (long short-term memory recurrent neural network) was found to be a promising way to classify the different methods of thawing.


2021 ◽  
Vol 158 ◽  
pp. 106927
Author(s):  
T. Schirra ◽  
G. Martin ◽  
S. Puchtler ◽  
E. Kirchner

2017 ◽  
Vol 29 (4) ◽  
pp. 2966-2973 ◽  
Author(s):  
Y. Suresh Reddy ◽  
Y. Markandeya ◽  
B. Appa Rao ◽  
G. Bhikshamaiah

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