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Details of Grant 

EPSRC Reference: EP/Y002172/1
Title: Nano-structured RC Networks - A Pathway To Artificial Skin
Principal Investigator: Amit, Dr I
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Ben Gurion University of the Negev
Department: Engineering
Organisation: Durham, University of
Scheme: Standard Research - NR1
Starts: 01 April 2024 Ends: 31 March 2026 Value (£): 165,557
EPSRC Research Topic Classifications:
Optoelect. Devices & Circuits
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
24 May 2023 ECR International Collaboration Grants Panel 2 Announced
Summary on Grant Application Form
The ambitious research programme will see the development of a location sensitive touch sensor that can conform, after its fabrication, to flexible irregular surfaces and thus, can function as the sensing element in an artificial skin graft. The vision for the sensor is that its low power consumption, large area and simple device architecture will contribute to its ability to adapt to use in healthcare applications.

The concept for the 'random impedance network sensors', or RINS, stems from the morphology of artificially synthesised atomically thin materials, that are grown almost exclusively as polycrystalline. Polycrystallinity in semiconductors is usually avoided in high-end applications because i) their resistivity is higher than their monocrystalline (MC) equivalents, and ii) each pair of crystallites (or grains) is separated by an amorphous and defect-rich interface (grain boundary) which is an additional source of resistivity. The few exceptions to the rule, such as degenerately doped polycrystalline (PC) silicon, which is used as gate metal in MOSFETs, or PC-Si photovoltaic cells marketed at the low-end of consumer-grade products, highlight the marginal position PC materials occupy in the global microelectronics industry.

The first hypothesis is that PC thin films are inherently depleted of free charge carriers due to dielectric mismatch with their environment. Fewer charge carriers mean that the electrostatic screening efficiency is diminished and is manifested in extraordinarily long screening lengths and wide capture cross sections. This translates to a long-distance sensitivity to electrostatic events, such as the touch of a finger.

The second hypothesis is that the intricate network of grains and grain boundaries forms a randomly oriented network of resistors (grains) and voltage-controlled capacitors (boundaries), which display both DC resistance and AC reactance. The resulting film impedance is bias-dependent, non-linear, and, crucially, position dependent, as each current pathway along the material carries a signature impedance characteristic. The combination of these hypotheses enables positioning of any electrostatic event, such as a finger touch, by triangulation of its position on the surface, making PC thin films the ideal substrates for position sensitive applications.

To realise this new paradigm in location sensitive touch sensing, the full electronic structure of the grain-grain boundary system needs to be known, and the transport mechanism of traversing charge carriers across it needs to be well understood. The research methodology will include a combination of functional probe microscopy with macroscopic transport measurements, which will inform the design of the RINS detector. Finally, we aim to develop the sensor itself, and design the methodology by which electrostatic 'events' on its surface are mapped to their exact location using the reading from few low power peripheral probes.

The stark difference between the proposed sensing mechanism and the sensors available today translate to exciting opportunities for new applications. Currently, capacitive touch sensors, such as those used in mobile phones and tablet devices, consist of orthogonal grid of transparent electrodes made of rare earth materials. This limits their use to applications on rigid surfaces, or surfaces that are flexible on a large, pre-defined radius of curvature. The sensor proposed here overcomes this limitations by using only peripheral electrodes, alleviating the need of rigid grid patterning. Furthermore, in current sensors location is inferred through capacitive changes at an overlap node between two orthogonal electrodes, and their nearby nodes. This means that nodes need to be sequentially addressed and read, making the response time long, especially on large surfaces. The use of few peripheral probes, all continuously read, means that processing the information can be done quickly, and on a much larger scale.

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