Dataset Information

Highly Flexible, Self-Bonding, Self-Healing, and Conductive Soft Pressure Sensors Based on Dicarboxylic Cellulose Nanofiber Hydrogels.

ABSTRACT: Conductive hydrogels have gained a great deal of interest in the flexible electronics industry because of their remarkable inherent properties. However, a significant challenge remains for balancing hydrogel's conductivity, self-healing, and strength properties. Herein, double network ionic hydrogels were fabricated by concurrently introducing borax into dicarboxylic cellulose nanofiber (DCNFs) and polyacrylamide (PAM) hydrogels. The incorporation of borax provided a superabsorbent feature to the PAM/DCNF hydrogels (without borax) with the equilibrium water absorption rate increased from 552 to 1800% after 42 h. The compressive strength of the prepared hydrogel was 935 kPa compared to 132 kPa for the PAM hydrogel, with high cycling stability (stable after 1000 compression cycles with 50% strain). The hydrogel pressure sensor had a very sensitive response (gauge factor = 1.36) in the strain range from 10 to 80%, which made it possible to detect mechanical motion accurately and reliably. The developed hydrogels with high-performance, environmentally friendly properties are promising for use in future artificial skin and human-machine interface applications.

SUBMITTER: Abouzeid R

PROVIDER: S-EPMC10496109 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Highly Flexible, Self-Bonding, Self-Healing, and Conductive Soft Pressure Sensors Based on Dicarboxylic Cellulose Nanofiber Hydrogels.

Abouzeid Ragab R Shayan Mohammad M Wu Tongyao T Gwon Jaegyoung J Kärki Timo A TA Wu Qinglin Q

ACS applied polymer materials 20230808 9

Conductive hydrogels have gained a great deal of interest in the flexible electronics industry because of their remarkable inherent properties. However, a significant challenge remains for balancing hydrogel's conductivity, self-healing, and strength properties. Herein, double network ionic hydrogels were fabricated by concurrently introducing borax into dicarboxylic cellulose nanofiber (DCNFs) and polyacrylamide (PAM) hydrogels. The incorporation of borax provided a superabsorbent feature to th ...[more]

PMID: 37705714

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Project description:Soft and pliable conductive polymer composites hold promise for application as bioelectronic interfaces such as for electroencephalography (EEG). In clinical, laboratory, and real-world EEG there is a desire for dry, soft, and comfortable interfaces to the scalp that are capable of relaying the μV-level scalp potentials to signal processing electronics. A key challenge is that most material approaches are sensitive to deformation-induced shifts in electrical impedance associated with decreased signal-to-noise ratio. This is a particular concern in real-world environments where human motion is present. The entire set of brain information outside of tightly controlled laboratory or clinical settings are currently unobtainable due to this challenge. Here we explore the performance of an elastomeric material solution purposefully designed for dry, soft, comfortable scalp contact electrodes for EEG that is specifically targeted to have flat electrical impedance response to deformation to enable utilization in real world environments. A conductive carbon nanofiber filled polydimethylsiloxane (CNF-PDMS) elastomer was evaluated at three fill ratios (3, 4 and 7 volume percent). Electromechanical testing data is presented showing the influence of large compressive deformations on electrical impedance as well as the impact of filler loading on the elastomer stiffness. To evaluate usability for EEG, pre-recorded human EEG signals were replayed through the contact electrodes subjected to quasi-static compressive strains between zero and 35%. These tests show that conductive filler ratios well above the electrical percolation threshold are desirable in order to maximize signal-to-noise ratio and signal correlation with an ideal baseline. Increasing fill ratios yield increasingly flat electrical impedance response to large applied compressive deformations with a trade in increased material stiffness, and with nominal electrical impedance tunable over greater than 4 orders of magnitude. EEG performance was independent of filler loading above 4 vol % CNF (< 103 ohms).

Dataset Information

Highly Flexible, Self-Bonding, Self-Healing, and Conductive Soft Pressure Sensors Based on Dicarboxylic Cellulose Nanofiber Hydrogels.

Publications

Highly Flexible, Self-Bonding, Self-Healing, and Conductive Soft Pressure Sensors Based on Dicarboxylic Cellulose Nanofiber Hydrogels.

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