Experimental Investigation of 3D-Printed TPU Triboelectric Composites for Biomechanical Energy Conversion in Knee Implants

Although total knee replacements have an insignificant impact on patients' mobility and quality of life, real-time performance monitoring remains a challenge. Monitoring the load over time can improve surgery outcomes and early detection of mechanical imbalances. Triboelectric nanogenerators (TENGs) present a promising approach as a self-powered sensor for load monitoring in TKR. A TENG was fabricated with dielectric layers consisting of Kapton tape and 3D-printed thermoplastic polyurethane (TPU) matrix incorporating CNT and BTO fillers, separated by an air gap and sandwiched between two copper electrodes. The sensor performance was optimized by varying the concentrations of BTO and CNT to study their effect on the energy-harvesting behavior. The test results demonstrate that the BTO/TPU composite that has 15% BTO achieved the maximum power output of 11.15 μW, corresponding to a power density of 7 mW/m<sup>2</sup>, under a cyclic compressive load of 2100 N at a load resistance of 1200 MΩ, which was the highest power output among all the tested samples. Under a gait load profile, the same TENG sensor generated a power density of 0.8 mW/m<sup>2</sup> at 900 MΩ. By contrast, all tested CNT/TPU-based TENG produced lower output, where the maximum generated apparent power output was around 8 μW corresponding to a power density of 4.8 mW/m<sup>2</sup>, confirming that using BTO fillers had a more significant impact on TENG performance compared with CNT fillers. Based on our earlier work, this power is sufficient to operate the ADC circuit. Furthermore, we investigated the durability and sensitivity of the 15% BTO/TPU samples, where it was tested under a compressive force of 1000 N for 15,000 cycles, confirming the potential of long-term use inside the TKR. The sensitivity analysis showed values of 37.4 mV/N for axial forces below 800 N and 5.0 mV/N for forces above 800 N. Moreover, dielectric characterization revealed that increasing the BTO concentration improves the dielectric constant while at the same time reducing the dielectric loss, with an optimal 15% BTO concentration exhibiting the most favorable dielectric properties. SEM images for BTO/TPU showed that the 10% and 15% BTO/TPU composites showed better morphological characteristics with lower fabrication defects compared with higher filler concentrations. Our BTO/TPU-based TENG sensor showed robust performance, long-term durability, and efficient energy conversion, supporting its potential for next-generation smart total knee replacements.

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Journal
Sensors
Published
2025-10-18
DOI
https://doi.org/10.3390/s25206454
Citations
2
Primary Topic
Muscle activation and electromyography studies
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article
Field-Weighted Citation Impact
1.35
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article

Experimental Investigation of 3D-Printed TPU Triboelectric Composites for Biomechanical Energy Conversion in Knee Implants

Shahrzad Towfighian, Ryan Willing, A. Ameli, Milutin Stanaćević et al.
2 citations
Sensors
Muscle activation and electromyography studies
1.35
article

Experimental Investigation of 3D-Printed TPU Triboelectric Composites for Biomechanical Energy Conversion in Knee Implants

Shahrzad Towfighian, Ryan Willing, A. Ameli, Milutin Stanaćević, Emre Salman, Milad Azami, Osama Abdalla
article en
2 citations

Abstract

Although total knee replacements have an insignificant impact on patients' mobility and quality of life, real-time performance monitoring remains a challenge. Monitoring the load over time can improve surgery outcomes and early detection of mechanical imbalances. Triboelectric nanogenerators (TENGs) present a promising approach as a self-powered sensor for load monitoring in TKR. A TENG was fabricated with dielectric layers consisting of Kapton tape and 3D-printed thermoplastic polyurethane (TPU) matrix incorporating CNT and BTO fillers, separated by an air gap and sandwiched between two copper electrodes. The sensor performance was optimized by varying the concentrations of BTO and CNT to study their effect on the energy-harvesting behavior. The test results demonstrate that the BTO/TPU composite that has 15% BTO achieved the maximum power output of 11.15 μW, corresponding to a power density of 7 mW/m<sup>2</sup>, under a cyclic compressive load of 2100 N at a load resistance of 1200 MΩ, which was the highest power output among all the tested samples. Under a gait load profile, the same TENG sensor generated a power density of 0.8 mW/m<sup>2</sup> at 900 MΩ. By contrast, all tested CNT/TPU-based TENG produced lower output, where the maximum generated apparent power output was around 8 μW corresponding to a power density of 4.8 mW/m<sup>2</sup>, confirming that using BTO fillers had a more significant impact on TENG performance compared with CNT fillers. Based on our earlier work, this power is sufficient to operate the ADC circuit. Furthermore, we investigated the durability and sensitivity of the 15% BTO/TPU samples, where it was tested under a compressive force of 1000 N for 15,000 cycles, confirming the potential of long-term use inside the TKR. The sensitivity analysis showed values of 37.4 mV/N for axial forces below 800 N and 5.0 mV/N for forces above 800 N. Moreover, dielectric characterization revealed that increasing the BTO concentration improves the dielectric constant while at the same time reducing the dielectric loss, with an optimal 15% BTO concentration exhibiting the most favorable dielectric properties. SEM images for BTO/TPU showed that the 10% and 15% BTO/TPU composites showed better morphological characteristics with lower fabrication defects compared with higher filler concentrations. Our BTO/TPU-based TENG sensor showed robust performance, long-term durability, and efficient energy conversion, supporting its potential for next-generation smart total knee replacements.

SensorsVol. 25(20)
Binghamton University (US), Western University (CA), University of Massachusetts Lowell (US), Stony Brook University (US)
Openalex Percentile: Top 17%
Muscle activation and electromyography studies
1.35
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