Perspective on Automation of Statistical Modeling Process for Battery Lifetime Prediction

Author(s):  
Benben Jiang
iScience ◽  
2021 ◽  
Vol 24 (2) ◽  
pp. 102060
Author(s):  
Md Sazzad Hosen ◽  
Joris Jaguemont ◽  
Joeri Van Mierlo ◽  
Maitane Berecibar

Joule ◽  
2021 ◽  
Author(s):  
Valentin Sulzer ◽  
Peyman Mohtat ◽  
Antti Aitio ◽  
Suhak Lee ◽  
Yen T. Yeh ◽  
...  

Author(s):  
Fotis Kerasiotis ◽  
Aggeliki Prayati ◽  
Christos Antonopoulos ◽  
Christos Koulamas ◽  
George Papadopoulos

Actuators ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 68 ◽  
Author(s):  
Takuya Taniguchi ◽  
Loïc Blanc ◽  
Toru Asahi ◽  
Hideko Koshima ◽  
Pierre Lambert

Mechanically responsive materials are promising as next-generation actuators for soft robotics, but have scarce reports on the statistical modeling of the actuation behavior. This research reports on the development and modeling of the photomechanical bending behavior of hybrid silicones mixed with azobenzene powder. The photo-responsive hybrid silicone bends away from the light source upon light irradiation when a thin paper is attached on the hybrid silicone. The time courses of bending behaviors were fitted well with exponential models with a time variable, affording fitting constants at each experimental condition. These fitted parameters were further modeled using the analysis of variance (ANOVA). Cubic models were proposed for both the photo-bending and unbending processes, which were parameterized by the powder ratio and the light intensity. This modeling process allows such photo-responsive materials to be controlled as actuators, and will possibly be effective for engineering mechanically responsive materials.


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