MicroElectroThermoForming (μETF): One-step Versatile 3D Shaping of Flexible Microelectronics for Enhanced Neural Interfaces

doi:10.21203/rs.3.rs-4924574/v1

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MicroElectroThermoForming (μETF): One-step Versatile 3D Shaping of Flexible Microelectronics for Enhanced Neural Interfaces

https://doi.org/10.21203/rs.3.rs-4924574/v1

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Increasing the proximity of microelectrode arrays (MEA) to targeted neural tissues is crucial for establishing efficient neural interfaces for both recording and stimulation applications. This has been achieved by constructing protruding three-dimensional (3D) structures on top of conventional planar microelectrodes via additional micromachining steps. However, this approach adds fabrication complexities and limits the 3D structures to certain shapes. We propose a one-step fabrication of versatile microscopic 3D structures for thin-film MEAs via “microelectrothermoforming (µETF)” of thermoplastics, by utilizing 3D-printed molds to locally deform planar MEAs into desired protruding and recessing shapes. Electromechanical optimization of the µETF process enabled a 3D MEA with 80 µm protrusions and/or recession for 100 µm diameter. Its versatile shaping capabilities are demonstrated by simple and simultaneous forming of diverse 3D structures on a single MEA. The benefits of 3D MEA are evaluated in retinal stimulation through numerical simulations and ex vivo experiments, confirming a threshold lowered by 1.7 times and spatial resolution enhanced by 2.2 times.

Physical sciences/Engineering/Electrical and electronic engineering

Biological sciences/Biotechnology/Nanobiotechnology/Bionanoelectronics

microelectrode arrays

liquid crystal polymer

neural interface

microthermoforming

3D electrode

High proximity of electrodes to neural cells plays a critical role in achieving efficient neural interfaces for various recording and stimulation applications^1–4. Improved signal quality in neural recordings can result from intimate contact between the electrode surface and targeted tissues^1,3,5,6, whereas in neural stimulation, lower stimulation thresholds and higher spatial resolution can be achieved through reduced current spreading^2,4,7,8. Thus far, improved electrode–cell proximity has typically been achieved using microelectromechanical system (MEMS) technologies, either by directly structuring rigid materials into needle-like shapes, such as Utah arrays, or by building various three-dimensional (3D) microstructures on top of thin film-based microelectrode arrays (MEAs), such as pillars^1,4,5,9–11, mushrooms^2,7,12, hemispheres¹³, sheaths¹⁴, and arrowheads¹⁵. However, despite their effectiveness, rigid 3D electrodes may exhibit mechanical mismatch with soft neural tissues. Furthermore, the creation of 3D microstructures on top of thin-film MEAs using conventional MEMS technologies requires additional fabrication steps, such as photolithography, vacuum deposition, electroplating, and wet and dry etching^16–18. These steps increase the complexity of the fabrication process, the degree of which usually scales with the complexity of the 3D structures. Moreover, it is challenging to fabricate 3D features with different shapes and heights within a single MEA, owing to the inherent 2D nature of the traditional microfabrication process.

To address these problems, we propose a novel “microelectrothermoforming (µETF)” process for producing versatile 3D microstructures on a polymer-based MEA through a simple one-step thermal pressing of conventional planar arrays. This method leverages a well-established thermoforming technique used in the plastic industry, in which a thermoplastic sheet is heated above the glass transition temperature (T_g) and pressed against a metal mold to create 3D structures in a simple manner¹⁹. The microelectronic adaptation of thermoforming in this study enables the creation of microscopically protruding and recessed versatile 3D structures with embedded electrical functionalities, facilitating the development of tailored structures for optimized electrode–cell interfaces. Thermoforming and microthermoforming for biomedical applications have been explored by Truckenmüller et al.¹⁹ and in subsequent studies, in which heated thermoplastic sheets were pneumatically or mechanically pressed against perforated metal molds to generate 3D shapes, such as microwell platforms^20,21, cell culture chips^22,23, and microchannels^24,25. However, the methods demonstrated in those studies primarily formed bulk polymer sheets that lacked active components such as electrical contacts and interconnections. Additionally, they required specialized tooling to exert pneumatic pressure, and their formable 3D structures were commonly limited to hemispherical shapes.

The proposed µETF process effectively addresses the challenges associated with fabrication complexity and structural restrictions in known 3D microstructures for enhanced neural interfaces. Microelectrothermoforming involves the one-step thermal pressing of a conventionally prepared thin-film planar MEA against a mold carrying the desired 3D structures. Therefore, two distinct advantages can be achieved compared to existing MEMS-based 3D forming: 1) process simplicity and 2) shape versatility. The proposed approach simplifies 3D fabrication by adding only one pressing step to the fabrication of a conventional planar thin-film MEA. Moreover, the use of 3D printing technology for preparing molds enables the formation of virtually any 3D microstructures, allowing heterogeneous structures of diverse shapes and heights to be created within a single electrode array via the same one-step µETF process. This simplicity and flexibility in forming 3D microstructures can expand design possibilities, facilitating the development of optimized electrode–neuron interfaces that align with the anatomical and neurophysiological features of a targeted nervous system.

Liquid crystal polymer (LCP) film was used as a thermoplastic substrate in this study, primarily owing to its mechanical strength, chemical inertness, and biocompatibility. Additionally, the low water absorption rate of LCP can contribute to the long-term reliability of chronically implanted devices²⁶. However, µETF can be utilized for other thermoplastics commonly used in biomedical applications.

This study introduces a one-step µETF process for generating versatile protruding and recessed 3D structures on LCP-based MEAs (LCP MEA) with mechanical considerations for preserving the electrical properties of MEA. As a proof of concept, the 3D MEA was optimized for retinal stimulation, the benefits of which were assessed via both computational analysis and ex vivo experiments in mouse model. A variety of 3D structures, such as wells, domes, walls, and triangles, were constructed on LCP MEAs, demonstrating the potential utility of the µETF in a wide range of biomedical applications.

mETF for simple and versatile 3D structuring

Representative benefits of 3D MEA are illustrated in Fig. 1a. The protruding structures enable closer proximity to target cells, establishing more localized neural interfaces for both neural recording and stimulation^27–30. This is in contrast to conventional planar MEAs, in which the electrode surfaces inherently lie below the top surface^31–33. As outlined in Fig. 1b, the proposed one-step mETF process locally deforms a planar MEA into a 3D MEA with microscopic protruding and/or recessed structures. A planar 25-channel LCP MEA prepared via a conventional microfabrication process³² (see Supplementary Fig. S1) is thermally pressed (> T_g) against a 3D-printed mold within a set of metal jigs and elastomer layers for alignment (see Supplementary Fig. S2–3 for details), replicating the protruding and/or recessed 3D microstructures of the mold to the MEA, as shown in Fig. 1c.

Additionally, the microelectrothermoformed 3D MEA can be grossly deformed into nonplanar shapes to conform to surrounding tissues, such as eye curvature for retinal electrodes, through a similar “macro” electrothermoforming step (mETF, see Supplementary Fig. S4). Using a 3D mold with 80 mm-height pillars (Supplementary Fig. S5), the schematics (top row) and photographs (bottom row) in Fig. 1d show the evolution of a (i) 40-mm-thick planar LCP MEA to a (ii) protruding or (iii) recessed mETF MEA, and subsequently to a (iii) mETF + mETF MEA, achieving both high proximity to target cells and conformability to target tissues. The recessed structures in (iii) can be easily generated using the identical processes and tools to those for the protrusions, simply by flipping the planar array upside down in the fixture, offering a convenient approach to create well-like structures for highly localized electrode–cell environments²⁹. Scanning electron microscopy (SEM) images of individual electrode sites before and after mETF are presented in Fig. 1e, with their cross-sectional profiles shown in Fig. 1f. Each channel site with a diameter of 200 mm was selectively elevated or lowered by a height of 80 mm, which represents an optimized height for subretinal electrode arrays as a proof-of-concept application of mETF (details in subsequent sections). The optical surface profiles of the protruding (top) and recessed (bottom) channel sites are shown in Fig. 1g. The mETF produced 3D structures that replicated the original mold structures, exhibiting a slightly widened base diameter (~150%) and sloped sidewalls (~70°). The electrode diameter as small as 100 mm was also successfully thermoformed using the same mETF configuration (Supplementary Fig. S6), which was utilized for following ex vivo experiments.

Similarly, versatile protruding and recessed structures of diverse heights and shapes can be created without adding fabrication complexities. Figure 2a–f present 25-channel LCP MEAs formed with varying protrusion/recessed heights from 80 to 200 mm using a 3D mold (Supplementary Fig. S7). Their SEM images (Fig. 2a, b), cross-sectional images (Fig. 2c, d), and optical 3D profiles (Fig. 2e, f) confirm the faithful replication of the 3D mold structures onto the LCP MEAs. Furthermore, the versatility of the microthermoforming process was demonstrated with various microstructures, including polygons (triangles, rectangles, and hexagrams), ovals (sunken, plateau, and walled), domes, and S-shaped walls, as shown in Fig. 2g and h; their SEM images and optical profiles are shown in Fig. 2i and j, respectively. All distinct structures were created via one-step mETF using corresponding 3D molds shown in Supplementary Fig. S7. Such versatility and consequent design flexibility can be leveraged to create optimized 3D structures tailored for various in vivo and ex vivo neural interfacing applications.

Electromechanical considerations for mETF

Despite the simplicity and versatility of the mETF process, it is important to consider the tensile stress exerted on the thin gold layers, which may lead to cracks or disconnections. Therefore, the mETF process was optimized with respect to the 3D mold design and pattern layout.

Fig. 3a presents a finite element analysis (FEA) of the mechanical stress induced within the embedded thin gold layer during an 80-mm-height mETF. Based on the relative stress distribution for the top, bottom, and neutral planes within a gold layer (Fig. 3b), the highest tensile stresses are expected at the top and bottom corners of the sidewall (insets in Fig. 3a). On the other hand, the top protruding area remained relatively stress-free because of the pillar-shaped mold with a flat top surface. The resulting plateau-like structure of the mETF electrode ensured minimal damage to the circular electrode area, which were designed to be 10 mm smaller than the mold top diameter, as outlined on the transversal stress distribution in Fig. 3c. This is in contrast to forming a 3D structure using a dome-shaped mold, in which electrode sites are subjected to highest tensile stress, leading to significant cracks on the gold electrode surface after mETF (Supplementary Fig. S8).

The mechanical strength of microelectronic tracks was enhanced by electroplating the gold patterns up to 4 mm thickness (t). Additionally, the interconnection lines traversing the region under the greatest stress is configured with serpentine shapes for enhanced robustness against elongation, as shown in Fig. 3c and inset (r = 20 mm, d = 40 mm, and q = 180˚). Typical serpentines adopted in stretchable electronics exploit global out-of-plane buckling of thin gold tracks embedded within freestanding polymer layers^34,35. However, the gold serpentine layer in mETF is subject to in-plane constraint as they are pressed between jig and mold. Therefore, the stretchability of such in-plane serpentine gold interconnections was evaluated in comparison with the conventional out-of-plane wavy lines via FEA simulation under the maximum local elongation during 80 mm-height mETF (ε = 15%, red area in Fig. 3c). As shown in Fig. 3d and e, both in-plane and out-of-plane serpentines exhibited reduced maximum stress with lower w and greater q (more details in Supplementary Fig. S9). Although in-plane restriction resulted in 33% higher peak stress than out-of-plane buckling serpentines with w = 10 mm, the wavy patterns are still effective in relieving the tensile stress of gold lines during mETF, by reducing the peak stress by 90% from the straight line.

These design considerations were experimentally validated using patterns with varying shapes (straight and wavy) and thicknesses (t = 300 nm to 4 mm) in 80-mm-height mETF. The representative SEM images in Fig. 3f demonstrate that damages to the gold layers were caused by two distinct mechanisms, as quantified by yield analysis after mETF in Fig. 3g. The “electrode cracks” occurred mostly in the thin gold patterns (t = 300 nm and 2 mm) with relatively lower mechanical strength, resulting in a distributed crack-formation throughout the circular electrode sites. On the other hand, circular electrodes with higher gold thickness (4 mm) remained intact, while focused mechanical stress caused a single spot of line disconnection, which corresponds to the location of the highest stress estimated in Fig. 3c and d. The wavy shapes with w = 10 mm and t = 4 mm (III) was adopted as the optimized parameters throughout this study for the 80 mm-height-mETF, because they secured 100% tolerance (Fig. 3g). Thicker patterns than 4 mm did not provide mechanical enhancement (Supplementary Fig. S10).

Electrochemical and mechanical analysis of mETF MEA

The intactness of the neural interfaces during mETF was confirmed via electrochemical analyses, including electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) of MEAs before and after mETF. Additionally, iridium oxide (IrOx) layer was electrodeposited on top of the gold channels before and after deformation to demonstrate the compatibility of mETF process with nanoporous surface functionalization techniques widely used for enhancing the charge transfer capabilities of neural interfaces^36,37. As shown in Fig. 4a and b, the impedance magnitude and phase at 1 kHz showed no significant changes after mETF for both gold and EIROF electrodes (gold: 32.3 ± 10.8 to 27.3 ± 14.1 kW, IrOx: 4.1 ± 0.5 to 3.7 ± 0.4 kW; see Supplementary Fig. S11a and b for EIS spectra). Figure 4c presents the cathodic charge storage capacities (CSC_C), which also confirmed that mETF did not result in any significant degradation (gold: 0.24 ± 0.02 to 0.18 ± 0.02 mC/cm², IrOx: 38.8 ± 8.2 to 35.1 ± 11.7 mC/cm²; see Supplementary Fig. S11c for CV curves).

The mechanical resilience of mETF protruding structures against compression was evaluated to assess the potential deformation of the mETF LCP structures under physiological or surgical conditions. As shown in Fig. 4d, the mETF MEA with a height of 80 mm were subjected to increasing compression using a motorized force meter. The magnified plot in Fig. 4e suggests that the 3D electrodes are compressed by no greater than 2.2 mm under the normal range of pressures experienced in physiological conditions, including (i) intraocular pressure (1.3–2.8 kPa³⁸) and (ii) intracranial pressure (0.9–2 kPa³⁹), as described in Fig. 4f. Even after the mETF MEA was completely flattened under a load pressure of 150 kPa, the original height and mechanical properties were recovered after the force is released, as demonstrated by the three cycles of full compression and relaxation (Fig. 4d).

These results suggest that the proposed mETF with proper designs enables the reliable production of 3D structures without compromising the physical and electrochemical properties of neural interfaces.

Benefits of mETF MEA for subretinal stimulation in FEA study

The benefits of mETF MEA with protruding structures were evaluated for subretinal stimulation of blind patients through FEA in a human retinal model^40,41. A subretinal electrode is implanted under the retina, facing toward the bipolar cells and retinal ganglion cells (RGCs) (see Supplementary Fig. S12 and Table S1 for retinal model). Given the distance between the electrode surface and targeted bipolar cells in the inner nuclear layer (INL), subretinal stimulation is expected to benefit from protruding 3D structures which would create more focused current distribution at the target cells. Improvement in neural interfaces enabled by 3D subretinal electrodes was quantified in terms of stimulation threshold (I_th), dynamic range (DR), and spatial resolution, as shown in Fig. 5.

The I_th and DR were evaluated based on the E-field distribution at INL generated by current injection from a 3×3 subretinal electrode array with varying protruding heights from 0 to 100 mm. The I_th is defined as the current intensity required to induce an electric field (E-field) exceeding 3,000 V/m at the plane of the INL to activate bipolar cells^27,42,43. The DR is a current range from I_th to the maximum current (I_max), beyond which inter-channel interference occurs between adjacent electrodes. The representative E-field distributions at INL from planar and 80-mm-protruding MEA are presented with increasing stimulation currents from planar in Fig. 5a and b. Notably, the 80-mm-protruding electrodes lowered the I_th to 4.5 mA from 6 mA of the planar electrodes. Increasing current beyond the I_max began to induce inter-channel interference, at which the INL area activated by a channel (contoured by white dashed lines in Fig. 5b) overlapped with the area activated by adjacent channels. The onset of interferences defines the upper boundary of the stimulation DR, which was extended from 14.5 mA for the planar array to 18.9 mA for the 80-mm-protruding array. A similar analysis for varying protruding heights from 0 to 100 mm (see Supplementary Fig. S13) suggested that the higher protrusions resulted in lower I_th and wider DR, as plotted in Fig. 5c. Such enhancement of 3D electrodes can be explained by more focused current distribution at INL, as shown in Fig. 5d (I = I_th). The MEA with higher protrusion generated higher contrast in the E-field profiles between the targeted area and untargeted area. However, the 100-mm-protruding array induced an uneven E-field distribution, presumably due to an unmitigated edge effect from an excessively close electrode–cell distance. Therefore, we concluded that an 80 mm protrusion is the optimum height for efficient subretinal stimulation, which was adopted for the proof-of-concept 25-channel 3D array presented in the previous sections.

The protruding MEA is also predicted to enhance the spatial resolution of retinal stimulation, which was quantified using the Michelson contrast (MC), measuring the ratio of (E_max − E_min) to (E_max + E_min) (more details in the Methods), as shown in Fig. 5e. Higher protrusion of the electrodes led to a higher E-field contrast (Supplementary Fig. S14) and correspondingly higher MC values across the entire range of channel pitches from 250 to 600 mm.

Benefits of mETF MEA for subretinal stimulation in ex vivo experiments

The effectiveness of mETF MEA for enhanced neural interfaces in subretinal stimulation were evaluated through ex vivo retina experiments, by comparing the protruding mETF MEA and planar MEA in terms of stimulation threshold and spatial resolution. Activation of RGCs was monitored by imaging the calcium transients in response to electrical subretinal stimulation, using a custom-built fluorescence microscopy setup (Fig. 6a). As shown in Fig. 6b, the MEA placed under the mouse retina patch included both planar and 80-μm-mETF protruding electrodes with a diameter of 100 mm (Supplementary Fig. S6). A genetically-encoded calcium indicator, sRGECO, was introduced to the retina via adeno-associated viral (AAV) vectors and its expression in RGC layer was confirmed three weeks after the injection (Fig. 6c). A typical calcium transient, in response to biphasic current pulses, is represented by normalized changes in fluorescence, DF/F₀= (F_peak– F₀)/F₀, as shown in Supplementary Fig. S15.

The stimulation threshold was evaluated by quantifying DF/F₀of RGCs placed within the diameter of stimulating electrode (Fig. 6d) while increasing the current injection. As shown in Fig. 6e, the resulting responses were fitted into sigmoidal functions, from which the threshold was defined as the stimulation current at the half of the maximum DF/F₀. The protruding electrode significantly lowered the median stimulation threshold to 0.91 mA, compared to 1.55 mA of the planar electrode, as shown in Fig. 6f. This suggests that the closer proximity of protruding structure to bipolar cells and RGCs allowed for neural activation with a lower current.

The spatial extent of electrical activation was quantified by DF/F₀of RGCs depending on their distances from the center of stimulating electrode (Fig. 6d) at a fixed current of I = 20 mA, as shown in Fig. 6g. The response curves were fitted by Gaussian functions to determine the spatial extents, defined as the half-width at half maximum (HWHM) of DF/F₀. The protruding electrode produced more focused retinal activation by reducing the HWHM from 94.8 to 43.7 mm, which well agrees with the FEA estimation in Fig. 5d. Stimulation with I = 10 mA resulted in consistent outcome (99.7 to 39.2 mm), as shown in Supplementary Fig. S16. The HWHM of the protruding electrode comparable to its radius (50 mm) indicates that the mETF MEA activates the retina with high contrast and minimized inter-channel interference, potentially providing artificial vision with higher spatial resolution.

Previous reports have indicated that retinal cells gradually migrate into the voids around the pillars of protruding electrodes after six weeks of in vivo implantation^2,44. Such migration reduces the separation between the electrodes and target cells with preserved axonal network²⁷, suggesting the benefits of 3D mETF MEA may also be applicable to in an in vivo retinal environment.

In this study, we presented a novel µETF process for creating simple and versatile 3D microstructures on thin-film polymer-based neural interfaces using 3D-printed molds to locally deform planar MEAs into desired protruding or recessing shapes. This approach builds upon the widely used polymer thermoforming technology in the plastic industry, but adapts it for microelectronic 3D structuring to create neural interfaces that are intimate with the nervous system. Our proposed technology uses one-step pressing of conventionally prepared planar MEAs to enable virtually any 3D microstructure to be created on microelectrode arrays without requiring additional fabrication steps. This implies that complex structures with different shapes and heights can be created within a single array using the same one-step thermoforming process. This contrasts with previous 3D-shaping techniques for neural interfaces, which require complicated fabrication steps and are limited in their ability to create different structural profiles on the same array, primarily because of the nature of the MEMS process.

The simplicity and versatility of our proposed method in forming 3D microstructures expand design possibilities, enabling optimized electrode–neuron interfaces that reflect the anatomical and neurophysiological characteristics of various nervous systems. Additionally, by combining gross macrothermoforming and local microthermoforming, it allowed for an even wider range of customized macrostructures and microstructures beyond the 3D structures presented in this study. We expect that the proposed technique will have potential applications in areas such as wearable electronics, microfluidic systems, and cell culture platforms, where the integration of 3D microstructures and microelectrodes can contribute to achieving optimal performance. Besides, the µETF is compatible with various thermoplastic materials commonly used in implantable and wearable biomedical applications, including parylene-C¹⁴, cyclic olefin copolymer⁴⁵, perfluoroalkoxy alkane⁴⁶, thermoplastic polyurethane⁴⁷, polymethyl methacrylate⁴⁸, polycarbonate^22,49, and polyvinyl alcohol⁵⁰.

The µETF produces 3D structures with inherent round edges and gently sloped sidewalls, which help minimize tissue damage during and after surgical implantation. Mechanical stress within MEA and surrounding tissue was assessed via FEA during forced sliding of an 80-µm height 3D structure into viscoelastic tissue, as shown in Supplementary Fig. S17. The µETF LCP electrode with native round edges was estimated to reduce the maximum stress within the electrode and on tissue by more than 60%, compared to LCP MEA with sharp edges. The stress mitigation of the µETF LCP structure was more pronounced when comparison was made against silicon-based 3D structure with the same shapes.

Although degenerated retinas are known to undergo structural changes over time^51–53, a normal human retinal model was employed in this study for the computational simulation of subretinal stimulation. This was primarily due to a lack of consistent structural information available for degenerated retinas in humans. While discrepancies may exist between computational simulations and clinical applications, it is anticipated that the benefits of protruding electrodes predicted in a normal retinal model can also be applied to degenerated retinas, primarily because of the reduced distance between the target cells and electrode surfaces.

The accuracy and minimum feature size of the µETF structures are associated with two factors: the precision of the 3D-printed mold, and the mold–MEA alignment. In this study, a printing resolution of 2 µm for the horizontal plane and 5 µm for the vertical axis was employed. Although this resolution is generally suitable for a wide range of neural interfacing applications, recent rapid advancements in 3D printing suggest the potential future availability of molds with even higher precisions. The mold was aligned with the planar MEAs by matching the laser-drilled holes on the arrays with corresponding pins on the metal jig, ensuring a minimum in-plane feature size of approximately 100 µm. However, this approach may be susceptible to mismatches caused by different thermal expansion ratios between the metal jig, epoxy mold, and polymer array. To enhance the accuracy, the 3D microstructures and aligned pins could be printed monolithically, and error-compensating laser drilling could be employed to further reduce the impact of thermal expansion mismatches.

Finally, the thermoplastic LCP substrate employed in this study is known to exhibit an exceptionally low water absorption rate (< 0.04%), potentially ensuring the long-term stability of the 3D MEA^32,54. Therefore, combining versatile 3D forming with durable LCP packaging is considered a suitable approach for various neural interface applications.

Microfabrication of LCP MEA

A planar LCP MEA was fabricated using a previously reported procedure based on conventional microfabrication technologies for thin-film polymer–metal–polymer structures^26,32,54, as illustrated in Supplementary Fig. S1. Briefly, Ti/Au seed layers (50 nm/50 nm) evaporated on a 25-µm-thick LCP film (Vecstar CTQ-25, Kuraray) underwent photolithography to define negative patterns (8 µm thickness, AZ P4620, Merck), followed by gold electroplating. After and seed layer removal (gold etchant and buffered oxide etchant 10:1, Sigma-Aldrich), a 25 µm-thick LCP cover layer (Vecstar CTF-25, Kuraray) was thermally laminated at 285°C with a pressure of 4 kgf/cm² for 30 min using a heating press (Model 381, Carver).

3D Mold preparation for µETF

A master mold carrying microscopic 3D structures and alignment keys was created via precision 3D printing (microArch S130, Boston Micro Fabrication) and then replicated using a high-temperature epoxy to tolerate the thermoforming process at 200°C. The replication was performed via double casting using polydimethylsiloxane (PDMS) as the negative mold, as illustrated in Supplementary Fig. S2. High-temperature-resistant epoxy (Duralco 4460, Cotronics) was poured over the PDMS negative mold, which was cured in two steps: first at 120°C for 4 h, followed by post-curing at 230°C for 16 h to reinforce its thermal and mechanical tolerance.

Alignment and pressing setup for µETF

The alignment and pressing setup consisted of a pair of top and bottom metal jigs; a rubber sheet (RBSM5-100, Misumi) and a rubber frame for uniform pressure; and a cylindrical rubber stamp and a rubber frame for pressing the electrode array against the mold (see Supplementary Fig. S3 for more details). The epoxy mold was assembled onto the bottom metal jig, on which the planar MEA array was loaded. Precise alignment was achieved by matching the laser-drilled align holes on the electrode layer with the align pins on the mold. The µETF was performed at a pressure of 6.4 kgf/cm² applied at 200°C for 30 min. A UV laser cutter (Samurai UV marking system, DPSS Lasers Inc.) was used for site opening and outlining. Oxygen plasma cleaning (CIONE 4, Femto Science) was performed at 80 W and 80 sccm for 30 min to remove the laser burrs.

Electromechanical considerations of 3D MEAs with varying pattern designs

The 25-channel MEAs were prepared with varying gold thicknesses and line shapes. The 300-nm-thick gold patterns were prepared via evaporation of Ti/Au layers, photolithography with a negative photoresist (NR9-3000py, Futurrex), and wet etching. The MEAs were not encapsulated by cover layers to facilitate observation of cracks in the gold patterns. The failures of gold patterns after µETF were categorized into two mechanisms. The “electrode crack” is defined as a failure due to distributed cracks within the gold electrode sites, whereas “line disconnection” refers to a disconnection of gold lines. Number of samples for analyzing the failure rate are: 20 for (I)-straight, 20 for (I)-wavy, 40 for (II)-straight, 50 for (II)-wavy, 50 for (III)-straight, and 50 for (III)-wavy.

IrOx electrodeposition

The laser-opened gold electrodes were electrodeposited with IrOx, following the previously reported protocol^36,37 using a potentiostat (CompactStat, Ivium Technologies). The electrodes were subjected to four cleaning cycles of voltage sweep in 1 M sulfuric acid from − 0.4 V to 1.4 V at 50 mV/s. Triangular potentials (0 to 0.55 V) were then iterated for 200 cycles at 50 mV/s, followed by 2,000 cycles of rectangular pulses (0.55 V, 0.5 s and 1 Hz).

Electrochemical characterization

The electrochemical characterizations were performed with a three-electrode system in the frequency range of 1 Hz to 100 kHz using the potentiostat and phosphate-buffered saline (1X, PH 7.4, Gibco). The CV curves were measured at a scan rate of 50 mV/s in the voltage range of − 0.6 V to 0.8 V, from which the CSC_C was calculated using the time integral of the cathodically enclosed area in Eq. (1):

$$\:{\text{C}\text{S}\text{C}}_{\text{C}}=\:\frac{1}{vA}{\int\:}_{{E}_{c}}^{{E}_{a}}\left|i\right|dE\:\:\:\:\:[\text{m}\text{C}/{\text{c}\text{m}}^{2}],\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(1\right)$$

where v is the scan rate, A is the geometric area of microelectrode, i is the current, and E_a and E_c are the anodic and cathodic potential limits, respectively¹¹. Number of samples for comparing EIS of the MEAs before and after µETF are: 56 for planar gold, 31 for protruding gold, 43 for planar IrOx, and 63 for protruding IrOx. Number of samples for comparing CSC_C of the MEAs before and after µETF are: 12 for planar gold, 16 for protruding gold, 10 for planar IrOx, and 15 for protruding IrOx.

FEA simulations

Mechanical stress induced in the gold traces was computed using Structural Mechanics module in COMSOL Multiphysics 6.0. The in-plane serpentines were implemented by applying a constraint in gold layers to only deform in the axial direction, while no constraints were applied to the out-of-plane serpentines allowing both axial elongation and 3D buckling.

The I_th, DR, and spatial resolution in subretinal stimulation were numerically simulated using AC/DC module in COMSOL Multiphysics 6.0 based on a human retinal model^40,41 (see Supplementary Fig. S12 and Table S1). The stimulation threshold was defined as the stimulating current that generates an electric field of 3,000 V/m at the location of the bipolar cells in the INL, which is the target layer for subretinal stimulation^27,42,43. The spatial resolution estimates the extent of inter-channel interference as evaluated by the Michelson contrast (MC)¹¹. The MC measures the ratio of the minimum and maximum electric field strengths at the plane of the INL upon simultaneous current injection from neighboring channels using Eq. (2):

$$\:\text{M}\text{C}=\:\frac{{\left|E\right|}_{max}-{\left|E\right|}_{min}}{{\left|E\right|}_{max}+{\left|E\right|}_{min}}\:.\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(2\right)$$

Modeling of insertion of MEA in Fig. S17 employed the retina and electrode modeled as linear elastic materials, as described in Table S2.

Fluorescent Calcium imaging system

A custom-built optical system incorporated both fluorescence and bright field microscopes. The bright field microscope utilized a Köhler illumination configuration, consisting of a near-infrared light emitting diode (LED) at λ = 780 nm (M780L3, Thorlabs), a collector lens, a condenser lens, and two iris diaphragms to ensure uniform illumination of the sample. The fluorescent microscope involved a 565 nm LED (SOLIS-565C, Thorlabs), a dichroic mirror in combination with excitation and emission filters (MDF-MCHA, Thorlabs) to separate the excitation light from emission light. Images were focused onto the CMOS camera using a 40X objective lens (LUMPLFLN40XW, Olympus) with a numerical aperture of 0.8, and a tube lens with a focal length of 200 mm.

AAV-meditated gene transfection and retinal preparation

All animal experimental procedures were approved by the Institutional Animal Care and Use Committee (IACUC; PNU-2023-3237) of Pusan National University. Male C57BL/6 mice (10-week-old, 20–25 g) were housed in a cage under a 12 h light/dark cycles with controlled temperature (22 ± 2°C) and humidity (55% ± 5%), and ad libitum access to food and water. The AAV vectors were used to transfect mouse retinal neurons with sRGECO (AAV8-Ef1a-sRGECO; 2×10¹³ GC/mL in HBSS, plasmid number of 137125; Addgene). The mice were anesthetized with avertin (250 mg/kg, Sigma-Aldrich) and placed on a heating pad at 37°C. A 30 G syringe was used to puncture a hole around the limbus. The AAV vectors carrying the genetically encoded calcium indicator were injected into the vitreous for 10 s using a 33G blunt needle (World Precision Instruments)^55,56. After 3 weeks of injection⁵⁵, the retina was prepared following the previously reported protocol by authors⁵⁷. Detached retina was transferred into the electrode-mounted chamber (RC-27L, Warner Instruments LLC) with the photoreceptor facing down, and immobilized by a nylon-mesh anchor (HSG, Ala Scientific Instruments). Total four retinas were used in this study.

Ex vivo retinal experiments

During the procedures, the prepared chamber was continuously perfused by oxygenated Ames' medium (A1420, Sigma-Aldrich) containing a synaptic blocker cocktail of CNQX (25µM; Hello Bio) and D-AP5 (25µM; Hello Bio) at 34°C with a constant flow rate of 5 mL/min^56,58. The stimulating MEA was connected to a stimulus generator (STG4004, Multi-Channel Systems) with a reference platinum wire electrode (MW-4310, BASI Research Product). Electrical stimulation was delivered in a burst of seven cathodic-first biphasic pulses at a frequency of 60 Hz, duration of 60 µs and inter-phase delay of 100 µs with varying amplitudes (Supplementary Fig. S15).

Data processing for ex vivo experiments

The stimulation threshold was determined by fitting ΔF/F₀ = (F_peak – F₀)/F₀ versus current amplitudes, using a modified sigmoid function, S(x) in Eq. (3):

$$\:S\left(x\right)=\frac{a}{a-\frac{a}{1+{exp}\left(b\times\:c\right)}}\times\:\left(\frac{a}{1+{exp}\left(-b\times\:\left(x-c\right)\right)}-\frac{a}{1+{exp}\left(b\times\:c\right)}\right),$$

where x is the stimulation current, and a, b, and c are fitting parameters. The threshold is defined as the current corresponding to 0.5F_max. The spatial extents were determined by fitting ΔF/F₀ versus distance from the electrode center using a Gaussian function, $\:G\left(x\right)$ in Eq. (4):

$$\:G\left(x\right)=a\times\:exp\left(-b\times\:{x}^{2}\right)$$

where x is the distance away from the electrode center, and a and b are fitting parameters. The spatial extent was defined as half of HWHM. All the fittings were performed through nonlinear least-squares methods in Matlab.

Competing interests

All authors declare no competing interests.

Author Contribution

D. H. L. and J. J. conceived and planned the experiments. D. H. L. carried out the experiments and simulations. Y. P. and K.E. designed the optical system for calcium imaging and conducted ex vivo experiments. D. H. L., Y. S., H. J., J. -M. S., M. -H. S., and J. J. contributed to sample preparation, measurements, and interpretation of the results. D. H. L. and J. J. took the lead in writing the manuscript. J. J. supervised the project. All authors helped shape the research and revise the manuscript.

Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2022R1C1C1010422, RS-2023-00217893, and NRF 2020R1C1C1010505).

Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Steins, H. et al. A flexible protruding microelectrode array for neural interfacing in bioelectronic medicine. Microsystems Nanoeng. 8, (2022).
Flores, T. et al. Optimization of pillar electrodes in subretinal prosthesis for enhanced proximity to target neurons. J. Neural Eng. 15, (2018).
Wijdenes, P. et al. Three dimensional microelectrodes enable high signal and spatial resolution for neural seizure recordings in brain slices and freely behaving animals. Sci. Rep. 11, 1–13 (2021).
Airaghi Leccardi, M. J. I., Vagni, P. & Ghezzi, D. Multilayer 3D electrodes for neural implants. J. Neural Eng. 16, (2019).
Beach, S., Grundeen, S., Doyle, A. & Theogarajan, L. Fabrication and validation of flexible 3D pillar electrodes for neural electrophysiological recording. Eng. Res. Express 2, (2020).
Wang, J. et al. A Highly Selective 3D Spiked Ultraflexible Neural (SUN) Interface for Decoding Peripheral Nerve Sensory Information. Adv. Healthc. Mater. 7, 1–8 (2018).
Losada, P. G. et al. Protuberant electrode structures for subretinal electrical stimulation: Modeling, fabrication and in vivo evaluation. Front. Neurosci. 13, 1–14 (2019).
Borda, E. et al. Three-dimensional multilayer concentric bipolar electrodes restrict spatial activation in optic nerve stimulation. J. Neural Eng. 19, 036016 (2022).
Tomaskovic-Crook, E. et al. Human Neural Tissues from Neural Stem Cells Using Conductive Biogel and Printed Polymer Microelectrode Arrays for 3D Electrical Stimulation. Adv. Healthc. Mater. 8, 1–10 (2019).
Butterwick, A. et al. Effect of shape and coating of a subretinal prosthesis on its integration with the retina. Exp. Eye Res. 88, 22–29 (2009).
Seo, H. W. et al. A 3D flexible microelectrode array for subretinal stimulation. J. Neural Eng. 16, (2019).
Mateus, J. C. et al. Improved in vitro electrophysiology using 3D-structured microelectrode arrays with a micro-mushrooms islets architecture capable of promoting topotaxis. J. Neural Eng. 16, (2019).
Rui, Y., Liu, J., Wang, Y. & Yang, C. Parylene-based implantable Pt-black coated flexible 3-D hemispherical microelectrode arrays for improved neural interfaces. Microsyst. Technol. 17, 437–442 (2011).
Kuo, J. T. W. et al. Novel flexible Parylene neural probe with 3D sheath structure for enhancing tissue integration. Lab Chip 13, 554–561 (2013).
Koo, K. et al. Arrowhead-shaped micro-electrode array on polyimide substrate for retinal prostheses enabling close approach to target cells. in TRANSDUCERS 2009–2009 International Solid-State Sensors, Actuators and Microsystems Conference 342–345 (IEEE, 2009). doi:10.1109/SENSOR.2009.5285492.
Vetter, R. J., Williams, J. C., Hetke, J. F., Nunamaker, E. A. & Kipke, D. R. Chronic neural recording using silicon-substrate microelectrode arrays implanted in cerebral cortex. IEEE Trans. Biomed. Eng. 51, 896–904 (2004).
Musick, K., Khatami, D. & Wheeler, B. C. Three-dimensional micro-electrode array for recording dissociated neuronal cultures. Lab Chip 9, 2036–2042 (2009).
Kundu, A. et al. Fabrication and characterization of 3D printed, 3D microelectrode arrays for interfacing with a peripheral nerve-on-a-chip. ACS Biomater. Sci. Eng. 7, 3018–3029 (2021).
Truckenmüller, R. et al. Thermoforming of film-based biomedical microdevices. Adv. Mater. 23, 1311–1329 (2011).
Vrij, E. J. et al. 3D high throughput screening and profiling of embryoid bodies in thermoformed microwell plates. Lab Chip 16, 734–742 (2016).
Hadavi, E. et al. In vitro degradation profiles and in vivo biomaterial–tissue interactions of microwell array delivery devices. J. Biomed. Mater. Res. - Part B Appl. Biomater. 109, 117–127 (2021).
Baptista, D. et al. 3D Lung-on-Chip Model Based on Biomimetically Microcurved Culture Membranes. ACS Biomater. Sci. Eng. 8, 2684–2699 (2022).
Borowiec, J. et al. Thermoforming techniques for manufacturing porous scaffolds for application in 3D cell cultivation. Mater. Sci. Eng. C 49, 509–516 (2015).
Stumpf, F. et al. LabDisk with complete reagent prestorage for sample-to-answer nucleic acid based detection of respiratory pathogens verified with influenza A H3N2 virus. Lab Chip 16, 199–207 (2016).
Truckenmüller, R. et al. Flexible fluidic microchips based on thermoformed and locally modified thin polymer films. Lab Chip 8, 1570–1579 (2008).
Jeong, J. et al. A miniaturized, eye-conformable, and long-term reliable retinal prosthesis using monolithic fabrication of liquid crystal polymer (LCP). IEEE Trans. Biomed. Eng. 62, 982–989 (2015).
Palanker, D., Vankov, A., Huie, P. & Baccus, S. Design of a high-resolution optoelectronic retinal prosthesis. J. Neural Eng. 2, (2005).
Ho, E. et al. Characteristics of prosthetic vision in rats with subretinal flat and pillar electrode arrays. J. Neural Eng. 16, (2019).
Flores, T. et al. Honeycomb-shaped electro-neural interface enables cellular-scale pixels in subretinal prosthesis. Sci. Rep. 9, 1–12 (2019).
Hogan, N. C., Talei-Franzesi, G., Abudayyeh, O., Taberner, A. & Hunter, I. Low-cost, flexible polymer arrays for long-term neuronal culture. Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS 1010, 803–806 (2012).
Kim, J. M., Im, C. & Lee, W. R. Plateau-shaped flexible polymer microelectrode array for neural recording. Polymers (Basel). 9, 1–17 (2017).
Jeong, J., Min, K. S. & Kim, S. J. Microfabrication process for long-term reliable neural electrode arrays using liquid crystal polymer (LCP). Microelectron. Eng. 216, 111096 (2019).
Oldroyd, P. & Malliaras, G. G. Achieving long-term stability of thin-film electrodes for neurostimulation. Acta Biomater. 139, 65–81 (2022).
Zhang, Y. et al. Experimental and theoretical studies of serpentine microstructures bonded to prestrained elastomers for stretchable electronics. Adv. Funct. Mater. 24, 2028–2037 (2014).
Ji, B. et al. Stretchable Parylene-C electrodes enabled by serpentine structures on arbitrary elastomers by silicone rubber adhesive. J. Mater. 6, 330–338 (2020).
Jeong, H. S., Hwang, S., Min, K. S. & Jun, S. B. Fabrication of planar microelectrode array using laser-patterned ito and su-8. Micromachines 12, 1–16 (2021).
Kakooei, S. Electrochemical Study of Iridium Oxide Coating on Stainless Steel Substrate. Int. J. Electrochem. Sci. 48, 2128–32 (2013).
Zhang, W., Huang, L., Weinreb, R. N. & Cheng, H. Wearable electronic devices for glaucoma monitoring and therapy. Mater. Des. 212, 110183 (2021).
Czosnyka, M. & Pickard, J. D. Monitoring and interpretation of intracranial pressure. J. Neurol. Neurosurg. Psychiatry 75, 813–821 (2004).
Cao, X., Sui, X., Lyu, Q., Li, L. & Chai, X. Effects of different three-dimensional electrodes on epiretinal electrical stimulation by modeling analysis. J. Neuroeng. Rehabil. 12, 1–15 (2015).
Zhou, D. D. & Greenberg, R. J. Microelectronic Visual Prostheses. in Implantable Neural Prostheses 1: Devices and Applications (eds. Greenbaum, E. & Zhou, D.) 1–42 (Springer US, 2009). doi:10.1007/978-0-387-77261-5_1.
Kasi, H. et al. Simulations to study spatial extent of stimulation and effect of electrode-tissue gap in subretinal implants. Med. Eng. Phys. 33, 755–763 (2011).
Asghar, S. A. & Mahadevappa, M. Honeycomb-Patterned Graphene Microelectrodes: A Promising Approach for Safe and Effective Retinal Stimulation Based on Electro-Thermo-Mechanical Modeling and Simulation. IEEE Trans. Nanobioscience 23, 262–271 (2024).
Vu, Q. A. et al. Structural changes in the retina after implantation of subretinal three-dimensional implants in mini pigs. Front. Neurosci. 16, (2022).
Baek, C., Kim, J., Lee, Y. & Seo, J. M. Fabrication and Evaluation of Cyclic Olefin Copolymer Based Implantable Neural Electrode. IEEE Trans. Biomed. Eng. 67, 2542–2551 (2020).
Kim, J. S., Jang, K. H., Ahn, S. H. & Seo, J. M. Micro Electrode Arrays Fabrication Using Flexible Perfluoroalkoxy Alkane Films∗. Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS 4350–4353 (2019) doi:10.1109/EMBC.2019.8856807.
Lis-Bartos, A., Smieszek, A., Frańczyk, K. & Marycz, K. Fabrication, characterization, and cytotoxicity of thermoplastic polyurethane/poly(lactic acid) material using human adipose derived mesenchymal stromal stem cells (hASCs). Polymers (Basel). 10, (2018).
Trinh, K. T. L., Thai, D. A., Chae, W. R. & Lee, N. Y. Rapid Fabrication of Poly(methyl methacrylate) Devices for Lab-ona-Chip Applications Using Acetic Acid and UV Treatment. ACS Omega 5, 17396–17404 (2020).
Lee, J., Jeong, H., Kim, J. & Seo, J. Investigation of neural electrode fabrication process on Polycarbonate substrate. 3138–3142 (2022).
Patnam, H., Dudem, B., Graham, S. A. & Yu, J. S. High-performance and robust triboelectric nanogenerators based on optimal microstructured poly(vinyl alcohol) and poly(vinylidene fluoride) polymers for self-powered electronic applications. Energy 223, 120031 (2021).
Aplin, F. P. et al. Stimulation of a suprachoroidal retinal prosthesis drives cortical responses in a feline model of retinal degeneration. Investig. Ophthalmol. Vis. Sci. 57, 5216–5229 (2016).
Kim, K. H. et al. Monitoring mouse retinal degeneration with high-resolution spectral-domain optical coherence tomography. J. Vis. 8, (2008).
Hariri, S., Moayed, A. A., Choh, V. & Bizheva, K. In vivo assessment of thickness and reflectivity in a rat outer retinal degeneration model with ultrahigh resolution optical coherence tomography. Invest. Ophthalmol. Vis. Sci. 53, 1982–1989 (2012).
Seung Woo Lee, Kyou Sik Min, Joonsoo Jeong, Junghoon Kim & Sung June Kim. Monolithic Encapsulation of Implantable Neuroprosthetic Devices Using Liquid Crystal Polymers. IEEE Trans. Biomed. Eng. 58, 2255–2263 (2011).
Park, S. W., Kim, J. H., Park, W. J. & Kim, J. H. Limbal approach-subretinal injection of viral vectors for gene therapy in mice retinal pigment epithelium. J. Vis. Exp. 2015, 1–8 (2015).
Cunquero, M. et al. Calcium Imaging In Electrically Stimulated Flat-Mounted Retinas. J. Vis. Exp. 2023, 1–15 (2023).
Park, Y. et al. Focused Ultrasound as a Novel Non-Invasive Method for the Delivery of Gold Nanoparticles to Retinal Ganglion Cells. Transl. Vis. Sci. Technol. 13, 5 (2024).
Reutsky-Gefen, I. et al. Holographic optogenetic stimulation of patterned neuronal activity for vision restoration. Nat. Commun. 4, 1–9 (2013).

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MicroElectroThermoForming (μETF): One-step Versatile 3D Shaping of Flexible Microelectronics for Enhanced Neural Interfaces

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Version 1

Abstract

Figures

Introduction

Results

Discussion

Methods

Microfabrication of LCP MEA

3D Mold preparation for µETF

Alignment and pressing setup for µETF

Electromechanical considerations of 3D MEAs with varying pattern designs

IrOx electrodeposition

Electrochemical characterization

FEA simulations

Fluorescent Calcium imaging system

AAV-meditated gene transfection and retinal preparation

Declarations

Competing interests

Author Contribution

Acknowledgements

Data Availability

References

Additional Declarations

Supplementary Files

Status:

Version 1