scholarly journals Fabrication of highly pressure-sensitive, hydrophobic, and flexible 3D carbon nanofiber networks by electrospinning for human physiological signal monitoring

Nanoscale ◽  
2019 ◽  
Vol 11 (13) ◽  
pp. 5942-5950 ◽  
Author(s):  
Zhiyuan Han ◽  
Zhiqiang Cheng ◽  
Ying Chen ◽  
Bo Li ◽  
Ziwei Liang ◽  
...  

A versatile 3D carbon nanofiber network with an ultrahigh pressure-sensitivity is prepared to monitor human physiological signals.

2017 ◽  
Vol 5 (35) ◽  
pp. 7352-7359 ◽  
Author(s):  
Ayesha Sultana ◽  
Sujoy Kumar Ghosh ◽  
Vitor Sencadas ◽  
Tian Zheng ◽  
Michael J. Higgins ◽  
...  

An electrospun PLLA fiber based flexible, piezoelectric bio-e-skin that can detect human physiological signals is presented.


Lubricants ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 29
Author(s):  
Carl F. O. Dahlberg ◽  
Jonas Faleskog ◽  
Per-Lennart Larsson

Correlation of sharp indentation problems is examined theoretically and numerically. The analysis focuses on elastic-plastic pressure-sensitive materials and especially the case when the local plastic zone is so large that elastic effects on the mean contact pressure will be small or negligible as is the case for engineering metals and alloys. The results from the theoretical analysis indicate that the effect from pressure-sensitivity and plastic strain-hardening are separable at correlation of hardness values. This is confirmed using finite element methods and closed-form formulas are presented representing a pressure-sensitive counterpart to the Tabor formula at von Mises plasticity. The situation for the relative contact area is more complicated as also discussed.


2017 ◽  
Vol 14 (3) ◽  
pp. 20161178-20161178 ◽  
Author(s):  
Long Chen ◽  
Xining Yang ◽  
Jianfeng Wu ◽  
Lingyan Fan

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5188
Author(s):  
Mitsugu Hasegawa ◽  
Daiki Kurihara ◽  
Yasuhiro Egami ◽  
Hirotaka Sakaue ◽  
Aleksandar Jemcov

An artificial neural network (ANN) was constructed and trained for predicting pressure sensitivity using an experimental dataset consisting of luminophore content and paint thickness as chemical and physical inputs. A data augmentation technique was used to increase the number of data points based on the limited experimental observations. The prediction accuracy of the trained ANN was evaluated by using a metric, mean absolute percentage error. The ANN predicted pressure sensitivity to luminophore content and to paint thickness, within confidence intervals based on experimental errors. The present approach of applying ANN and the data augmentation has the potential to predict pressure-sensitive paint (PSP) characterizations that improve the performance of PSP for global surface pressure measurements.


1990 ◽  
Vol 57 (1) ◽  
pp. 40-49 ◽  
Author(s):  
F. Z. Li ◽  
J. Pan

Plane-strain crack-tip stress and strain fields are presented for materials exhibiting pressure-sensitive yielding and plastic volumetric deformation. The yield criterion is described by a linear combination of the effective stress and the hydrostatic stress, and the plastic dilatancy is introduced by the normality flow rule. The material hardening is assumed to follow a power-law relation. For small pressure sensitivity, the plane-strain mode I singular fields are found in a separable form similar to the HRR fields (Hutchinson, 1968a, b; Rice and Rosengren, 1968). The angular distributions of the fields depend on the material-hardening exponent and the pressure-sensitivity parameter. The low-hardening solutions for different degrees of pressure sensitivity are found to agree remarkably with the corresponding perfectly-plastic solutions. An important aspect of the effects of pressure-sensitive yielding and plastic dilatancy on the crack-tip fields is the lowering of the hydrostatic stress and the effective stress directly ahead of the crack tip, which may contribute to the experimentally-observed enhancement of fracture toughness in some ceramic and polymeric composite materials.


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