Evaluation of Durability of Transparent Graphene Electrodes Fabricated on Different Flexible Substrates for Chronic in vivo Experiments

Objective: To investigate chronic durability of transparent graphene electrodes fabricated on polyethylene terephthalate (PET) and SU-8 substrates for chronic in vivo studies. Methods: We perform systematic accelerated aging tests to understand the chronic reliability and failure modes of transparent graphene microelectrode arrays built on PET and SU-8 substrates. We employ graphene microelectrodes fabricated on PET substrate in chronic in vivo experiments with transgenic mice. Results: Our results show that graphene microelectrodes fabricated on PET substrate work reliably after 30 days accelerated aging test performed at 87 °C, equivalent to 960 days in vivo lifetime. We demonstrate stable chronic recordings of cortical potentials in multimodal imaging/recording experiments using transparent graphene microelectrodes fabricated on PET substrate. On the other hand, graphene microelectrode arrays built on SU-8 substrate exhibit extensive crack formation across microelectrode sites and wires after one to two weeks, resulting in total failure of recording capability for chronic studies. Conclusion: PET shows superior reliability as a substrate for graphene microelectrode arrays for chronic in vivo experiments. Significance: Graphene is a unique neural interface material enabling cross-talk free integration of electrical and optical recording and stimulation techniques in the same experiment. To date, graphene-based microelectrode arrays have been demonstrated in various multi-modal acute experiments involving electrophysiological sensing or stimulation, optical imaging and optogenetics stimulation. Understanding chronic reliability of graphene-based transparent interfaces is very important to expand the use of this technology for long-term behavioral studies with animal models.

[1]  T. Lucas,et al.  Transparent and flexible low noise graphene electrodes for simultaneous electrophysiology and neuroimaging , 2014, Nature Communications.

[2]  Yalin Lu,et al.  Capacitance of carbon-based electrical double-layer capacitors , 2014, Nature Communications.

[3]  Hee Chul Lee,et al.  Neural Probes for Chronic Applications , 2016, Micromachines.

[4]  S. Cogan Neural stimulation and recording electrodes. , 2008, Annual review of biomedical engineering.

[5]  E. Meng,et al.  Characterization and Modification of Adhesion in Dry and Wet Environments in Thin-Film Parylene Systems , 2018, Journal of Microelectromechanical Systems.

[6]  Justin C. Sanchez,et al.  Electrode impedance analysis of chronic tungsten microwire neural implants: understanding abiotic vs. biotic contributions , 2014, Front. Neuroeng..

[7]  Virginia Woods,et al.  Long-term recording reliability of liquid crystal polymer µECoG arrays , 2018, Journal of neural engineering.

[8]  W. Denk,et al.  Two-photon laser scanning fluorescence microscopy. , 1990, Science.

[9]  M. Selvaraj,et al.  Evaluation of heat resistant properties of silicone based coatings by SEM and a.c. impedance techniques , 1996 .

[10]  D W L Hukins,et al.  Accelerated aging for testing polymeric biomaterials and medical devices. , 2008, Medical engineering & physics.

[11]  T. Schneider,et al.  The influence of surface roughness on the adhesion force , 2004 .

[12]  Andreas Hierlemann,et al.  Impedance characterization and modeling of electrodes for biomedical applications , 2005, IEEE Transactions on Biomedical Engineering.

[13]  G. Gabriel,et al.  SU-8 based microprobes with integrated planar electrodes for enhanced neural depth recording. , 2012, Biosensors & bioelectronics.

[14]  Study of crack formation in high-aspect ratio SU-8 structures on silicon , 2007 .

[15]  Stefan R. Pulver,et al.  Ultra-sensitive fluorescent proteins for imaging neuronal activity , 2013, Nature.

[16]  L. Cauller,et al.  Biocompatible SU-8-Based Microprobes for Recording Neural Spike Signals From Regenerated Peripheral Nerve Fibers , 2008, IEEE Sensors Journal.

[17]  P. Alpern,et al.  Moisture-Induced Delamination in Plastic Encapsulated Microelectronic Devices: A Physics of Failure Approach , 2008, IEEE Transactions on Device and Materials Reliability.

[18]  F J Blanco,et al.  Fabrication of SU-8 multilayer microstructures based on successive CMOS compatible adhesive bonding and releasing steps. , 2005, Lab on a chip.

[19]  K. Djupsund,et al.  Flexible polyimide microelectrode array for in vivo recordings and current source density analysis. , 2007, Biosensors & bioelectronics.

[20]  Samuel E. Root,et al.  Quantifying the Fracture Behavior of Brittle and Ductile Thin Films of Semiconducting Polymers , 2017 .

[21]  V. Rao,et al.  Fracture in Microscale SU-8 Polymer Thin Films , 2017 .

[22]  Hwa-Teng Lee,et al.  Relationship between EDM parameters and surface crack formation , 2003 .

[23]  J. J. Siegel,et al.  Ultraflexible nanoelectronic probes form reliable, glial scar–free neural integration , 2017, Science Advances.

[24]  Nae-Eung Lee,et al.  Effect of surface roughness on the adhesion properties of Cu/Cr films on polyimide substrate treated by inductively coupled oxygen plasma , 2005 .

[25]  Duygu Kuzum,et al.  Ultralow Impedance Graphene Microelectrodes with High Optical Transparency for Simultaneous Deep Two‐Photon Imaging in Transgenic Mice , 2018, Advanced functional materials.

[26]  Yuhan Shi,et al.  A Compact Closed-Loop Optogenetics System Based on Artifact-Free Transparent Graphene Electrodes , 2018, Front. Neurosci..

[27]  K. Loh,et al.  Electrochemical delamination of CVD-grown graphene film: toward the recyclable use of copper catalyst. , 2011, ACS nano.

[28]  J. Kysar,et al.  Measurement of the Elastic Properties and Intrinsic Strength of Monolayer Graphene , 2008, Science.

[29]  Stéphane Colin,et al.  A novel fabrication method of flexible and monolithic 3D microfluidic structures using lamination of SU-8 films , 2005 .

[30]  Brian J. Kim,et al.  Annealing effects on flexible multi-layered parylene-based sensors , 2014, 2014 IEEE 27th International Conference on Micro Electro Mechanical Systems (MEMS).

[31]  Jared P. Ness,et al.  Graphene-based carbon-layered electrode array technology for neural imaging and optogenetic applications , 2014, Nature Communications.

[32]  Justin C. Sanchez,et al.  Quantifying long-term microelectrode array functionality using chronic in vivo impedance testing , 2012, Journal of neural engineering.

[33]  Andre K. Geim,et al.  The rise of graphene. , 2007, Nature materials.

[34]  H. Brown Adhesion of Polymers , 1996 .

[35]  Rafael Kurtz,et al.  Application of multiline two-photon microscopy to functional in vivo imaging , 2006, Journal of Neuroscience Methods.

[36]  B. Chakrabarti,et al.  Crack propagation in solids and crack-surface roughness , 1999 .

[37]  Riaz Ahmed,et al.  Study of Influence of Electrode Geometry on Impedance Spectroscopy , 2011, International Journal of Electrochemical Science.

[38]  Yuyuan Tian,et al.  Measurement of the quantum capacitance of graphene. , 2009, Nature nanotechnology.

[39]  J. Dai,et al.  Three-dimensional graphene foam as a biocompatible and conductive scaffold for neural stem cells , 2013, Scientific Reports.

[40]  Igor A. Lavrov,et al.  Flexible parylene-based multielectrode array technology for high-density neural stimulation and recording , 2008 .

[41]  Anna Devor,et al.  Deep 2-photon imaging and artifact-free optogenetics through transparent graphene microelectrode arrays , 2018, Nature Communications.

[42]  Stephen P. DeWeerth,et al.  PDMS-based conformable microelectrode arrays with selectable novel 3-D microelectrode geometries for surface stimulation and recording , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[43]  R. Puers,et al.  Diffusing and swelling in SU-8: insight in material properties and processing , 2010 .

[44]  James M Tour,et al.  Biocompatibility of pristine graphene for neuronal interface. , 2013, Journal of neurosurgery. Pediatrics.

[45]  Jonathan Viventi,et al.  In vitro assessment of long-term reliability of low-cost μΕCoG arrays , 2016, EMBC.

[46]  Kang L. Wang,et al.  Robust bi-stable memory operation in single-layer graphene ferroelectric memory , 2011 .

[47]  Xin Liu,et al.  Graphene-based neurotechnologies for advanced neural interfaces , 2018, Current Opinion in Biomedical Engineering.