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Laser micromachining of lithium niobate-based resonant sensors towards medical devices applications

Authors: Zeyad Yousif Abdoon Al-Shibaany; Pavel Penchev; John Hedley; Stefan Dimov;

Laser micromachining of lithium niobate-based resonant sensors towards medical devices applications

Abstract

This paper presents a micromachining process for lithium niobate (LiNbO3) material for the rapid prototyping of a resonant sensor design for medical devices applications. Laser micromachining was used to fabricate samples of lithium niobate material. A qualitative visual check of the surface was performed using scanning electron microscopy. The surface roughness was quantitatively investigated using an optical surface profiler. A surface roughness of 0.526 μm was achieved by laser micromachining. The performance of the laser-micromachined sensor has been examined in different working environments and different modes of operation. The sensor exhibits a Quality-factor (Q-factor) of 646 in a vacuum; and a Q-factor of 222 in air. The good match between the modelling and experimental results shows that the laser-micromachined sensor has a high potential to be used as a resonance biosensor.

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Keywords

Chemical technology, Lasers, Niobium, lithium niobate, Oxides, TP1-1185, Biosensing Techniques, sensors, biosensors, Article, medical devices, Microscopy, Electron, Scanning, Microtechnology, laser micromachining, lcsh: lcsh:Chemical technology, lcsh: lcsh:TP1-1185

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    11
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Top 10%
Green
gold