On the Fabrication and Characterization of Polymer-Based Waveguide Probes for Use in Future Optical Cochlear Implants.
Christian HelkeMarkus ReinhardtMarkus ArnoldFalk SchwenzerMicha HaaseMatthias WachsChristian GoßlerJonathan GötzDaniel KeppelerBettina Julia WolfJannis Justus SchaeperTim SaldittTobias MoserUlrich Theodor SchwarzDanny ReuterPublished in: Materials (Basel, Switzerland) (2022)
Improved hearing restoration by cochlear implants (CI) is expected by optical cochlear implants (oCI) exciting optogenetically modified spiral ganglion neurons (SGNs) via an optical pulse generated outside the cochlea. The pulse is guided to the SGNs inside the cochlea via flexible polymer-based waveguide probes. The fabrication of these waveguide probes is realized by using 6" wafer-level micromachining processes, including lithography processes such as spin-coating cladding layers and a waveguide layer in between and etch processes for structuring the waveguide layer. Further adhesion layers and metal layers for laser diode (LD) bonding and light-outcoupling structures are also integrated in this waveguide process flow. Optical microscope and SEM images revealed that the majority of the waveguides are sufficiently smooth to guide light with low intensity loss. By coupling light into the waveguides and detecting the outcoupled light from the waveguide, we distinguished intensity losses caused by bending the waveguide and outcoupling. The probes were used in first modules called single-beam guides (SBGs) based on a waveguide probe, a ball lens and an LD. Finally, these SBGs were tested in animal models for proof-of-concept implantation experiments.
Keyphrases
- high resolution
- small molecule
- living cells
- high speed
- single molecule
- fluorescence imaging
- hearing loss
- blood pressure
- room temperature
- soft tissue
- staphylococcus aureus
- spinal cord injury
- machine learning
- deep learning
- high intensity
- current status
- cystic fibrosis
- ionic liquid
- biofilm formation
- molecular dynamics
- convolutional neural network