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3D printing of conducting polymers

Engineering and Technology

3D printing of conducting polymers

H. Yuk, B. Lu, et al.

This groundbreaking research by Hyunwoo Yuk and colleagues unveils a high-performance 3D printable conducting polymer ink based on PEDOT:PSS. These innovative polymers enable the crafting of high-resolution microstructures that can be integrated with other materials, paving the way for devices like a soft neural probe for in vivo single-unit recording.... show more
Introduction

Conducting polymers combine intrinsic electrical conductivity with polymeric processability, stability, and biocompatibility, making them attractive for energy storage, flexible electronics, and bioelectronics. Existing fabrication approaches for conducting polymers—ink-jet, screen, and aerosol printing; electrochemical patterning; and lithographic techniques—are constrained by low resolution (typically >100 μm), predominantly 2D/low-aspect-ratio structures, and complex, costly multi-step processing that often requires cleanroom facilities. In contrast, 3D printing offers programmable, rapid, and flexible fabrication of microscale structures with freedom of design, and recent material developments have broadened printable material sets. Nonetheless, prior attempts at 3D printing conducting polymers achieved only simple geometries (e.g., isolated fibers) due to insufficient ink rheology. Here, the authors develop a high-performance 3D-printable PEDOT:PSS ink with tailored rheology enabling high-resolution, high-aspect-ratio printing, multimaterial integration (e.g., with PDMS), conversion to soft, conductive hydrogels, and demonstration of functional devices, including a flexible circuit and a soft neural probe capable of in vivo single-unit recording.

Literature Review
Methodology

Ink formulation: A commercial PEDOT:PSS aqueous solution (Clevios PH1000) was stirred 6 h and filtered (0.45 μm). The solution was cryogenically frozen (liquid nitrogen) and lyophilized for 72 h to isolate PEDOT:PSS nanofibrils while minimizing excessive PEDOT-rich crystallization. The nanofibrils were re-dispersed in a water:DMSO (85:15 v/v) solvent to prepare concentrated suspensions. Concentration tuning (1–10 wt%) transitioned the suspension from low-viscosity liquid to thixotropic, shear-thinning/yield-stress inks via nanofibril entanglement.

Rheology and structure: SAXS showed decreasing d-spacing (L = 2π/qmax) with increasing concentration (e.g., 16.1 nm at 1 wt% to 7.0 nm at 10 wt%), indicating closer packing. Rotational rheometry quantified apparent viscosity versus shear rate (0.01–100 s−1) and oscillatory storage/loss moduli versus shear stress (1–1000 Pa). Optimal printability occurred at 5–7 wt% nanofibrils: lower concentrations (1–4 wt%) spread on substrates due to low viscosity/yield stress; higher (>8 wt%) clogged nozzles due to aggregates. Inks were stable over ≥1 month at ambient conditions.

3D printing: A custom Cartesian gantry printer (Aerotech AG1000) dispensed the conducting ink and a PDMS ink (SE 1700) through various nozzles (200, 100, 50, 30 μm). CAD paths (SolidWorks) were converted to G-code (CADFusion and custom Python). High-resolution meshes and multi-layer/high-aspect ratio and overhanging features were printed. Multimaterial prints (ink + PDMS) fabricated MEA-like structures and soft neural probes.

Post-processing: Prints were dried at 60 °C (24 h) and annealed at 130 °C (3 cycles × 30 min) to form pure, dry PEDOT:PSS. Constrained drying on glass preserved microscale fidelity. Hydrogels were obtained by equilibrating in PBS (equilibrium water content ~87%).

Characterization: SEM (JEOL JSM-6010LA) with 5 nm Au sputter; TEM (JEOL 2100 FEG) and CryoTEM (Gatan CP3) to image pristine solution, ink, and annealed prints. SAXS (Bruker Nanostar, 1059.1 mm, 300 s exposure) with solvent background subtraction.

Mechanical testing: AFM nanoindentation (Asylum MFP-3D) used a 50 nm radius spherical tip; indentation depths 50 nm (dry) and 1 μm (hydrogel). Young’s modulus extracted via JKR model fits.

Electrical and electrochemical measurements: Four-point probe (Keithley 2700) on printed strips (30 × 5 mm; single layer; thickness 17 μm dry, 78 μm hydrogel). Copper (dry) or Pt (hydrogel) leads; conductivity computed from I–V with geometry factors. Bending tests used prints on polyimide, various radii (±1–20 mm) and up to 10,000 cycles.

Electrochemistry: CV (Princeton VersaSTAT 3) in PBS with Pt working/counter and Ag/AgCl reference; scan rates 50–500 mV s−1. EIS (Solartron 1287A/1260A) from 0.1–100 kHz at 10 mV vs. Ag/AgCl; data fitted to an equivalent circuit with electronic/ionic resistances and CPEs.

In vivo electrophysiology: Soft neural probes (nine 30 μm diameter PEDOT:PSS channels encapsulated in PDMS) were 3D-printed in one continuous process (<20 min), assembled with Omnetics connectors, and implanted in mouse dorsal hippocampus (1.8 mm AP; 1.5 mm ML; −1.0 mm DV). Recordings were made with a 64-channel system (Plexon) under freely moving conditions; LFP (0.5–250 Hz) and AP (300–40,000 Hz) signals were acquired, spike sorting performed in Offline Sorter.

Key Findings
  • Developed a paste-like, high-performance 3D-printable PEDOT:PSS ink via cryogenic freezing, lyophilization, and controlled re-dispersion in water:DMSO (85:15 v/v).
  • Optimal ink concentration window of 5–7 wt% PEDOT:PSS nanofibrils enabled shear-thinning, yield-stress behavior and high-fidelity printing; <5 wt% spread on substrates, >8 wt% clogged nozzles.
  • Achieved high-resolution printing through 30–200 μm nozzles; features down to ~30 μm and high aspect ratios (≥20 layers); printed overhanging structures.
  • Printed structures retained geometry through drying and swelling; PEDOT:PSS hydrogels stable in PBS for ≥6 months without feature degradation.
  • Electrical conductivity: up to 155 S cm−1 (dry) and 28 S cm−1 (hydrogel). Smaller nozzles yielded higher conductivity, attributed to shear-induced fibril alignment.
  • Mechanical flexibility: withstood bending strains up to ~13% (dry, 17 μm thickness; 65 μm radius) and ~20% (hydrogel, 78 μm thickness; 200 μm radius) without failure.
  • Bending durability: conductivity changed <5% across ±1–20 mm radii; retained >100 S cm−1 (dry) and >15 S cm−1 (hydrogel) after 10,000 bending cycles.
  • EIS of hydrogel prints showed comparable ionic and electronic transport (Ri ≈ 105.5 Ω; Re ≈ 107.1 Ω) with semicircular Nyquist behavior.
  • CV indicated high charge storage capability and stability (<2% CSC reduction after 1000 cycles) versus bare Pt electrodes; broad, stable redox peaks consistent with non-diffusional redox.
  • Mechanics: Young’s modulus ~1.5 ± 0.31 GPa (dry) and ~1.1 ± 0.36 MPa (hydrogel), enabling soft tissue compatibility.
  • Multimaterial 3D printing (with PDMS) rapidly fabricated: (i) high-density flexible circuits with <100 μm features that powered LEDs and tolerated bending; (ii) soft neural probes (nine 30 μm PEDOT:PSS channels) with 50–150 kΩ impedance at 1 kHz.
  • In vivo demonstration: probes recorded stable LFP and action potentials in freely moving mice over two weeks; single-unit activity isolated via PCA and spike sorting.
Discussion

The study addresses the central challenge of directly 3D printing conducting polymers by engineering a PEDOT:PSS ink with tailored microstructure and rheology that supports high-resolution, high-aspect-ratio, and overhanging geometries. By establishing an optimal concentration regime of entangled nanofibrils and leveraging DMSO-assisted conductivity enhancement, the printed structures achieve conductivities comparable to state-of-the-art films while offering 3D form factors and multi-material integration. The ability to convert dry printed parts into soft, conductive hydrogels with MPa-scale modulus enables favorable mechanical matching to biological tissues. Electrical and electrochemical characterizations confirm robust performance under bending, mixed ionic/electronic transport, and high charge storage capacity. The demonstrations of flexible circuits and an integrated soft neural probe fabricated in minutes illustrate how 3D printing can streamline device production relative to lithographic methods, broadening access to custom bioelectronic and flexible electronic systems.

Conclusion

This work introduces a simple, scalable strategy to formulate a 3D-printable PEDOT:PSS ink and to fabricate conductive polymer microstructures with high resolution, high aspect ratio, and multimaterial integration. Printed structures exhibit high conductivity (155 S cm−1 dry; 28 S cm−1 hydrogel), mechanical compliance (MPa-scale hydrogels), durability under bending, and electrochemical stability. Rapid, continuous 3D printing enabled functional devices, including flexible circuits and soft neural probes capable of in vivo single-unit recording. Potential future directions include: extending the ink design to other conducting polymers and composites; optimizing rheology and nozzle/process windows for even finer features and higher throughput; integrating additional materials (e.g., stretchable dielectrics, sensors, and actuators) for fully printed systems; scaling to wafer- or roll-to-roll-compatible workflows; and conducting long-term, chronic in vivo studies to evaluate stability and biocompatibility in implanted bioelectronic applications.

Limitations
  • Material scope: The approach is demonstrated with PEDOT:PSS; generalization to other conducting polymers requires further validation.
  • Process window: Effective printing relies on a narrow concentration range (5–7 wt%); lower concentrations lead to spreading, while >8 wt% risks nozzle clogging due to aggregation.
  • Feature-dependent conductivity: Conductivity varies with nozzle diameter, indicating process sensitivity (e.g., shear alignment) that may complicate uniformity across features.
  • Post-processing: Multi-step drying/annealing is required to achieve high conductivity; process control is needed to preserve microscale fidelity.
  • In vivo demonstration: Neural recordings were shown over two weeks; longer-term stability, biointegration, and broader sample sizes were not reported.
  • Device breadth: While circuits and neural probes were demonstrated, comprehensive benchmarking against industrial manufacturing (throughput, yield) was not provided.
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