Wireless Rehabilitation Training Sensor Arrays Made with Hot Screen-Imprinted Conductive Hydrogels with a Low Percolation Threshold.

PDA-PPy nanofibers high sensitivity low percolation threshold piezoresistive sensor array rehabilitation training

Journal

ACS applied materials & interfaces
ISSN: 1944-8252
Titre abrégé: ACS Appl Mater Interfaces
Pays: United States
ID NLM: 101504991

Informations de publication

Date de publication:
16 Mar 2022
Historique:
pubmed: 2 3 2022
medline: 8 4 2022
entrez: 1 3 2022
Statut: ppublish

Résumé

Herein, we propose a highly sensitive wireless rehabilitation training ball with a piezoresistive sensor array for patients with Parkinson's disease (PD). The piezoresistive material is a low percolation threshold conductive hydrogel which is formed with polypyrrole (PPy) nanofibers (NFs) as a conductive filler derived from a polydopamine (PDA) template. The proton acid doping effect and molecular template of PDA are essential for endowing PPy NFs with a high aspect ratio, leading to a low percolation threshold (∼0.78 vol %) and a low Young's 004Dodulus of 37.69 kPa and hence easy deformation. The piezoresistive sensor exhibited a static and dynamic stability of 10,000 s and 15,000 cycle times, respectively. This stability could be attributed to the increased hydrophilicity of conductive fillers, enhancing the interfacial strength between the conductive filler and the matrix. The interaction between the PDA-PPy NFs and the hydrogel matrix endows the hydrogel with toughness and ensures the stability of the device. Additionally, the microdome structure of the conductive hydrogel, produced by hot screen-imprinting, dramatically improves the sensitivity of the piezoresistive sensor (∼856.14 kPa

Identifiants

pubmed: 35230075
doi: 10.1021/acsami.2c01630
doi:

Substances chimiques

Hydrogels 0
Polymers 0
Pyrroles 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

12734-12747

Auteurs

Bing Yao (B)

State Key Lab of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China.

Zhihao Ye (Z)

School of Computer Science and Technology of Zhejiang Province, Zhejiang University, Hangzhou 310027, China.

Xiang Lou (X)

State Key Lab of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China.

QiLong Yan (Q)

State Key Lab of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China.

ZheYi Han (Z)

State Key Lab of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China.

YaBo Dong (Y)

School of Computer Science and Technology of Zhejiang Province, Zhejiang University, Hangzhou 310027, China.

Shaoxing Qu (S)

State Key Laboratory of Fluid Power & Mechatronic System, Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province, Center for X-Mechanics, Zhejiang University, Hangzhou 310027, China.

Zongrong Wang (Z)

State Key Lab of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China.

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Classifications MeSH