Soft touch sensors with memory elements embedded in skin

ESR9

Objectives

Develop graphene based highly sensitive touch and strain sensors connected with memristors and embedded in soft materials such as eco-flex. The graphene is chosen as its optical transparency will allow us to study the transmission of external stimuli through the soft material surrounding the sensors. This will help us to establish the role of skin mechanics through artificial means. The fabrication and electro-optic characterization of flexible electrodes and touch and strain sensors will be carried out. For memristors, the dry fabrication (i.e. free from conventional chemical processing) of graphene oxide (GO) will be carried out by plasma oxidation. For counter electrode graphene will be transfer printed on top of GO and a thin gold layer will be deposited at the edges of sample for electrical contacts. The graphene-based sensors will have planar capacitive structures. The sensors will be interfaced with compact electronics developed in other projects.

Expected Results

Novel touch sensor with memory like effect to mimic the viscoelastic behavior of skin.

Placement

Host institution: University of Glasgow

Enrolments (in Doctoral degree): University of Glasgow

Supervisors

Ravinder Dahiya, Georges Gielen

Presentation of ESR9

PhD defense: To be announced

I am Yalagala Bhavani Prasad currently working as a Marie ESR in the University of Glasgow. My research expertise in the nanofabrication of different novel devices and its electrical testing especially sensors, photodetectors and memristors. I am experienced in the synthesis and characterization of novel materials since last 5 years and published more than 10 research articles and conference papers (total) in various reputed international journals. I have more than 4 years of experience in the cleanroom and the hands-on experience with multiple equipment’s like physical vapor deposition, chemical vapor deposition, spin coater, photolithography, laser writer etc.  Currently my project is based on the fabrication of flexible sensors, memristors and its integration to explore towards the bio-mimic of the soft e-skin.

Abstract of PhD goals

Highly sensitive pressure sensors with biocompatibility, biodegradability, and flexibility are needed in robotics, prostheses, medical implants, and wearable electronics. However, it is challenging to fabricate a pressure sensor with all these attributes due to material limitations or technological bottlenecks. Herein, we present a silk- Polyvinyl Alcohol (S-PVA) composite nanofiber-based flexible, biocompatible, and biodegradable capacitive pressure sensor developed using a facile and cost-effective screen-printing approach. The screen-printed silver was used as the top and bottom electrodes, with flexible and biodegradable chitosan as a substrate. The device exhibited extremely wide pressure sensing range varying from ~1 kPa to 800 kPa with a maximum sensitivity of ~2.83 kPa-1 (<10kPa) and fast response and recovery time of ~35 and ~40 ms. The high sensitivity in the low-pressure region is primarily due to the high porosity and surface area, and reduction in the effective distance between the multilayers of 1D S-PVA nanofibers. The device shows excellent cyclic repeatability and good stepwise cyclic increment in both low- and high-pressure regions for more than 2×103 and 3.2×103 cycles, respectively. Next, a flexible memristor is fabricated and integrated with the fabricated pressure sensor to emulate the functionality of the artificial sensory nervous system, with the memristor acting as a synapse and the pressure sensor acting as a mechanoreceptor. Different materials like Zinc Oxide, silicon nitride etc. have been explored as the active layer of the memristor device and the devices exhibit excellent repeatability and data retention property.  Finally, the biodegradability tests reveal that the device completely dissolved in pure DI water at room temperature in less than 24 hours. Thus, the novel S-PVA composite based nanofiber serves as an excellent biomaterial and paves the path for next generation wearable and implantable medical device applications.

Results

Deliverable 4.2 Graphene based touch sensor and benchmarking
Fabrication of graphene based touch sensors

Deliverable 4.4 Sensors with memory
Demonstrator of the properties of the sensors based on memristive device