A highly sensitive and stretchable double-layer conductive network structure CB/TPU/CB/MXene strain sensor for human–machine interaction

Abstract

Flexible sensors have emerged as a transformative technology in human-centered applications, enabling real-time physiological monitoring, human–machine interaction, and adaptive responses through their unique conformability, sensitivity, and multi-modal sensing capabilities. However, achieving both high sensitivity and a broad detection range remains a critical challenge in current flexible strain sensor research. This study introduces a carbon black/thermoplastic polyurethane/carbon black/MXene (CTCM) film sensor featuring a dual-network architecture. The electrospun carbon black/thermoplastic polyurethane (CT) composite acts as a structural scaffold and a primary conductive network, ensuring mechanical compliance. A secondary conductive network, composed of ultrasonically assembled MXene/carbon black nanoparticles, is chemically crosslinked with the CT matrix. This configuration establishes multiscale interfacial coupling that synergistically enhances charge transport and mechanical robustness. Through this hierarchical design—leveraging dual-network interactions and hydrogen bonding reinforcement—the sensor exhibits exceptional performance: a high maximum gauge factor (GF_max = 1765), a 0.1% strain detection limit, rapid response times (62 ms loading and 67 ms unloading), and excellent durability (>8000 cycles at 100% strain). Notably, the tensile strain capability of the composite significantly surpasses that of pure TPU, extending from 97.6% to 298.7%. This dual-network strategy establishes a new paradigm for next-generation wearable electronics, effectively overcoming the typical trade-off between detection breadth and sensitivity via controlled hierarchical charge transport pathways and tailored energy dissipation mechanisms.

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1. Introduction

The rapid advancement of flexible electronics has driven the proliferation of stretchable strain sensors exhibiting exceptional extensibility, heightened sensitivity, and broad detection ranges, thereby accelerating innovations in electronic skins,^1–3 human–computer interfaces,^4,5 and biomedical monitoring.^6–9 Current flexible sensing platforms are categorized into four principal transduction mechanisms: piezoelectric,^10–12 capacitive,^13–16 resistive,^17–20 and triboelectric.^21–24 Resistive-type sensors have garnered particular research interest due to their straightforward operational principles, facile signal acquisition, and scalable fabrication processes.²⁵ Nevertheless, conventional flexible strain sensors frequently encounter the fundamental constraint of mutually exclusive high sensitivity and wide operational range, impeding their practical deployment in advanced applications.^26,27

Materials engineering and structural innovation represent two pivotal strategies for impacting these competing performance metrics. Contemporary approaches typically combine conductive nanofillers with elastomeric matrices to fabricate conductive polymer composites (CPCs) that maintain stable conductive pathways under mechanical deformation.²⁸ Widely employed matrix materials encompass thermoplastic polyurethane (TPU),^29,30 polydimethylsiloxane (PDMS),^27,31 Ecoflex,³² polyimide (PI),³³ and bio-derived polymers.³⁴ Among them, TPU is widely used in the preparation of flexible strain sensors due to its excellent mechanical properties and stretchability. The selection of conductive fillers critically determines sensor performance: zero-dimensional^35,36/two-dimensional^37,38 (0D/2D) nanofillers (carbon black [CB], MXene, and graphene) enable high gauge factors (GFs) through strain-induced conductive network disruption, while one-dimensional (1D)^39,40 nanostructures (carbon nanotubes [CNTs] and metallic nanofibers) preserve electrical continuity via high aspect ratios (L/D), extending sensing ranges. However, single-filler systems inherently suffer from structural limitations. Single-material engineering or structural engineering typically improves only a single performance metric, which is usually achieved at the expense of another. In materials engineering, Chen et al.⁴¹ achieved unprecedented GFs (∼70 000) using circularly patterned silver nanoparticle networks, yet they suffered from restrictive strain thresholds (<0.46%). Similarly, Wang et al.⁴² demonstrated MXene-enhanced TPU sensors with exponential resistance variation (GF = 3.23 × 10⁶) but narrow operational windows (<6% strain). Conversely, Li et al.⁴³ designed a carboxylate CNT-based sensor that exhibited 190% strain tolerance at the expense of sensitivity (GF = 33.29). In structural engineering, biomimetic architectures, such as crack-propagation designs reported by Wang et al.,⁴⁴ have enabled GF tuning from 11.40 to 690.95 across the 0–40% strain range. Liu et al.⁴⁵ further optimized this approach through dip-coated microcrack arrays, achieving 98% strain capability with GF = 2.36 × 10⁴. Therefore, the design approach of combining materials engineering and structural innovation might be a strategy to solve the existing problems.

Herein, we report a high-performance strain sensor based on a carbon black/thermoplastic polyurethane/carbon black/MXene (CTCM) composite featuring a double-layer conductive network. The core of this research lies in proposing an interfacially coupled construction strategy, which aims to synergistically enhance both the sensitivity and sensing range of the sensor through a rational hierarchical structure and material combination design, ultimately leading to a novel polymer composite architecture. This approach strategically constructs a primary conductive network of electrospun CB/TPU fibers, which functions as a mechanically robust and stretchable scaffold. A secondary conductive network, composed of CB nanoparticles and MXene nanosheets, is subsequently integrated via a solution-based process, thereby establishing multiscale interfacial coupling. The innovation of this work is manifested not only in the exceptional performance achieved, a combination of a wide sensing range (∼298.7% strain) and high sensitivity (a maximum gauge factor of 1765), but also in the deliberate utilization of interfacial interactions. Furthermore, we provide an in-depth investigation into the hydrogen bonding mechanism between the surface functional groups of MXene and the polymer matrix, which underlies the enhanced electromechanical properties and durability. This interfacially coupled design paradigm offers a compelling pathway for the development of advanced sensing materials based on polymer composites.

2. Experimental

2.1 Materials

TPU pellets were purchased from BASF GmbH (1185 A), and N,N-dimethylformamide (DMF) was purchased from Kemiou Chemical Co., Ltd, Tianjin, China. Tetrahydrofuran (THF) was purchased from Chengdu Kelon Chemical Co., Ltd, China. CB (average particle size of about 60 nm, density of about 1.7–1.9 g cm⁻³) was purchased from Cabot Corp., USA. Anhydrous ethanol was purchased from Tianjin Fuyu Fine Chemical Co., Ltd. The MXene/NMP suspension (XFK04-1) was purchased from Nanjing/Jiangsu XFNANO Materials Tech Co., Ltd, China. The materials list is shown in SI Table S1.

2.2 Preparation of CB/TPU substrate spinning films (CT)

The solvent was a 1 : 1 mixed solution of N,N-dimethylformamide (DMF) and tetrahydrofuran (THF), and CB particles were poured into the mixed solution at a concentration of 1 wt% relative to the solvent for dispersion and placed in an ultrasonic device with an ultrasonic power of 120 W, and the ultrasonic treatment duration was 30 minutes. After the ultrasonic treatment was completed, TPU particles were added at a concentration of 10 wt% relative to the solvent to dissolve. The mixed solution was magnetically stirred for 4 hours to obtain a uniform precursor solution for the subsequent electrospinning process. Finally, 14 ml of the spinning solution was drawn with a medical needle for electrospinning. The specific spinning process parameters were: feed rate 0.8 mL h⁻¹, receiving distance 20 cm, collector speed 80 rpm, and working voltage 15 kV. In addition, the relative humidity and room temperature were controlled at 40 ± 5% and 20 ± 2 °C, respectively.

2.3 Preparation of a CB/TPU/CB/MXene flexible sensor (CTCM)

First, the CT spun film was cut into strips of 1 × 4 cm² for the subsequent ultrasonic treatment procedure. 0.6 g of CB particles and 0.6 g of MXene/NMP suspension were added to anhydrous ethanol solution (total volume of 100 ml) to prepare an ultrasonic mixture. Finally, the cut CT film was placed in the ultrasonic mixture for ultrasonic treatment. The ultrasonic parameters were 100 W and the ultrasonic treatment time was 10 minutes.

2.4 Characterization

Scanning electron microscopy (Thermo Fisher Quattro S) was used to observe the surface structure of the spun membranes, and the chemical composition of the samples was analyzed by X-ray photoelectron spectroscopy (XPS, AXIS Ultra DLD), with Al Kα radiation as the excitation source. The interfacial interaction between the conductive filler and the matrix was studied by Fourier transform infrared spectroscopy (FTIR, Nicolet Nexus 670) and X-ray diffraction (XRD, X′Pert Pro MPD DY 129). A contact angle meter (JY-82B Kruss DSA) was used to measure the hydrophobicity of the films. An electrospinning machine (Yunfan Instrument Co., Ltd, YFSP-T) was used to prepare the spun films. A universal tensile testing machine (ZQ-95QB, Dongguan Zhiqu Precision Co., Ltd) was used to measure the applied pressure and frequency, a constant temperature and humidity testing machine (Hongsam Instrument Technology (Shenzhen) Co., Ltd) was used to dry the spun films, and an ultrasonic cell disruptor (LC-JY98-IIIDN) was used for ultrasonic processing.

3 Results and discussion

3.1 Fabrication process and structural characterization of CTCM

The fabrication procedure of CTCM is illustrated in Fig. S1 (SI). Initially, a CT precursor membrane was fabricated via electrospinning (detailed parameters are provided in the Experimental section). The as-spun membrane was subsequently oven-dried, followed by ultrasonic treatment in a CB/MXene suspension and secondary drying to yield the final CTCM composite. The resultant architecture features CB particles decorated on the nanofibers of the CT membrane and MXene nanosheets intercalated between the fiber interstices (Fig. 1a). The sequential incorporation of the CB and MXene establishes a dual conductive network: the first network, formed by CB introduction during electrospinning, creates inter-fiber crosslinks as visualized in Fig. S2, while physical crosslinking between fibers is evident in the magnified cross-sectional SEM image (Fig. 1a). The secondary network, constructed through ultrasonically-assisted CB/MXene integration, not only enhances conductivity but also induces weak interfacial hydrogen bonding between fibers (Fig. 1a). These hydrogen bonds reinforce fiber interactions, effectively mitigating interfacial slippage while conferring exceptional stretchability and durability. Mechanical characterization (Fig. 1b) confirms the composite's superior compliance, including lightweight design, twistability, bendability, and high extensibility, coupled with the absence of cytotoxic components, underscoring its viability for next-generation flexible sensing applications. The experimental results also substantiate the feasibility of CTCM flexible sensors in human–robot interaction applications utilizing robotic manipulators (Fig. 1c).

Fig. 1 (a) Schematic diagram of the pre-CT film and CTCM sensor. (b) Image of the CTCM and its actual performance under twisting, bending and stretching conditions. (c) Application of the CTCM sensor.

Fig. S2 shows the SEM image of the CT membrane. The formation of beaded structure fibers can be observed. This is because the control of humidity during the spinning process leads to the agglomeration of CB, which gives the CT membrane initial conductivity. Fig. 2a shows the actual picture of the CT membrane. Fig. 2b–d and Fig. S3a and b show that due to the addition of carbon black during the spinning process, the carbon black particles fill the gaps between the fibers well, increase the conductive path, and cross-link the fibers to strengthen the interaction between the fibers. The actual picture of the CTCM membrane is shown in Fig. 2e. Fig. 2f (yellow circle part) and Fig. S3c and d clearly show the presence of MXene nanosheets on the surface of the CTCM membrane. Fig. 2g and h clearly show that the carbon black particles are attached to the nanofibers. The carbon black and MXene nanosheets attached to the fibers give the CTCM membrane high conductivity and constitute the second layer of the conductive network. Fig. 2i shows a schematic diagram of the element distribution of the CTCM film, from which it can be seen that MXene nanosheets and carbon black particles are uniformly dispersed inside the fiber. The synergistic effect of the dual conductive network, strain concentration, and fiber mesh structure endows CTCM with excellent sensing performance, which is conducive to maintaining a high strain factor (GF) in a wide detection range. Fig. 2j shows the stress–strain curves of TPU, CT, and CTCM films, where CTCM has an elongation at break of 298.7% and CT has an elongation at break of 163.9%, both of which are better than the 97.6% tensile fracture rate of pure TPU, indicating that the construction of the dual network can enhance the force between fibers. Fig. 2k shows the stress–strain curves of CTCM in the 1st, 2nd, 5th, 8th, and 10th stretching release processes at 50% strain, showing low hysteresis. The successful preparation of CTCM and the chemical reaction between the conductive filler (CB and MXene) and the substrate film (CT) were verified by FT-IR, XRD and XPS.

Fig. 2 Physical images and scanning electron microscope (SEM) micrographs of CT (a–d) and CTCM (e–h). (i) Energy dispersive spectroscopy (EDS) images of CTCM. (j) Stress–strain curves of TPU, CT and CTCM. (k) The 1st, 2nd, 5th, 8th, and 10th stress–strain curves at 50% strain.

As shown in Fig. 3a, from the FT-IR spectra of CT and CTCM, it can be clearly seen that for CT the peaks near 1995 and 2113 cm⁻¹ are the bending vibrations of C=O and –N=C=O, respectively. The peaks near 2955 and 3327 cm⁻¹ are the stretching vibrations of C–H and N–H, respectively. At the same time, the strong vibration peaks near 1078 and 1223 cm⁻¹ belong to C–H and C–O. Compared with CT, the peaks of C–H and N–H corresponding to CTCM have changed, which may be because the high conductivity of MXene nanosheets and the reflection of surface functional groups (such as –OH and –F) hinder the detection of C–H and N–H. At the same time, the C–H and C–O of CTCM shifted to the low wavelength direction (1063 and 1211 cm⁻¹, respectively), and the C=O and –N=C=O of CTCM shifted to the high wavelength direction (1998 and 2119 cm⁻¹, respectively), which indicates that the –OH or –F on the MXene surface interacted with the C=O and –N=C=O of CT to form weak hydrogen bonds, which contributed to the formation of good electromechanical properties and effective load transfer during dynamic stretching. In addition, XRD was used to further verify this conclusion. Fig. 3b shows the XRD patterns of MXene, CT, and CTCM from 5° to 60°. The typical peak at 2θ = 5.8° corresponds to the (002) crystal plane of MXene; this means that the delamination of MXene is relatively successful in this work.⁴⁶ There is a characteristic diffraction peak of TPU in the range of 14°–29°, centered at 2θ = 20.5°. Obviously, the CTCM peak presents two typical diffraction peaks of MXene and CT, which means that MXene and CT are successfully assembled together. In addition, the characteristic peak of CT at 2θ = 20.5° becomes broader and weaker, and the (002) peak obviously moves to the left.

Fig. 3 Characterization tests of CT and CTCM. (a) FT-IR spectra of CT and CTCM. (b) XRD patterns of CT, MXene and CTCM. (c) Contact angles of pure TPU, CT and CTCM. (d) XPS spectra of CT, MXene and CTCM. (e and f) Peak fitting of the carbon element for CT and CTCM.

The above phenomena indicate that there is a rich interaction between the conductive filler and the CT matrix, which is consistent with the FT-IR results. Similarly, Fig. 3c shows the water contact angles of TPU, CT, and CTCM; it can be seen that the addition of conductive fillers changes the hydrophobic angle of the composite film, which also confirms the formation of interfacial interactions. As shown in Fig. 3d, XPS was performed to analyze the surface chemical composition of the CT, MXene, and CTCM. Obviously, all the typical peaks of the MXene, Ti 2p, Ti 2s, and F 1s, were observed from the XPS spectrum of CTCM, which confirmed the successful preparation of CTCM. In addition, the chemical composition of CT in the 280–292 eV range (Fig. 3e) and the chemical composition of CTCM in the 280–292 eV range (Fig. 3f) showed that C–O and C–Ti–T_x changed, which may be due to the reaction of the active functional groups (–OH or –F) on the surface of the MXene with CT.

3.2 Electromechanical performance of the CTCM strain sensor

The performance of strain sensors is primarily evaluated through three critical response characteristics under tensile loading: sensing range, sensitivity (quantified by the gauge factor, GF), and response time. As calculated using formulae (S1) and (S2), the CTCM sensor demonstrates GF values of 165, 744, and 1765 across distinct strain regimes (0–100%, 100–200%, and 200–298.7%, respectively) and the conductivity is 48.715 m S⁻¹, as shown in Fig. 4a and Fig. S11. This staged sensitivity enhancement, coupled with an extended 298.7% sensing range (Fig. S4), validates the dual conductive network's efficacy in balancing sensitivity and operational breadth. Mechanical reinforcement is evidenced in Fig. S4, where CB/MXene incorporation improves composite strength without compromising the TPU matrix.

Fig. 4 The electromechanical properties of CTCM. (a) Gauge factor (GF) of CTCM. (b) The 0.1% resolution detection and its response time. (c) ΔR/R₀ responses under different strains of 10%, 20%, 30%, 40%, and 50%, respectively. (d) ΔR/R₀ responses under different small strains of 20%, 50%, 100%, and 150%, respectively. (e) ΔR/R₀ responses under different rates at 50% strain. (f) The I–V curves under strains of 0–100%. (g) Comparison of sensing ranges and the maximum GFs with reported works of literature. (h) ΔR/R₀ response of CTCM in 8000 s stretching–releasing cycles under 100% strain.^{41,44,47–51}

The sensor exhibits exceptional resolution (0.1% strain detection) with rapid response/recovery times (62 ms/67 ms), confirmed through pre-stretching to 200% strain followed by 0.1% incremental loading (Fig. 4b). Stable signal output is maintained across varying strain magnitudes (10–50% in Fig. 4c; up to 150% in Fig. 4d) and different stretching rates at 50% strain (Fig. 4e). Ohmic behavior under 0–100% strain is verified via linear I–V characteristics (Fig. 4f). Comparative analysis (Fig. 4g) highlights CTCM's superior GF-range combination relative to existing flexible sensors. Long-term durability is confirmed through 8000 s loading tests at 100% strain, showing consistent response stability (Fig. 4h).

3.3 Analysis of the sensing mechanism of the CTCM sensor

The exceptional sensing performance of the CTCM strain sensor originates from its dual conductive network architecture: an upper layer comprising MXene nanosheets and CB particles and a lower flexible electrospun CT film. The sensor transduces mechanical deformation into measurable electrical signals, governed by the integrity of conductive pathways formed through interconnected MXene–MXene, MXene–CB, and CB–CB junctions. Applied strain modulates interparticle distances between conductive elements in both the brittle MXene layer and the underlying fiber network, thereby altering electrical conductivity. Fig. S5 and Fig. 1a reveal the CT film's grid-like nodal structure from randomly distributed electrospun fibers, a consequence of slow DMF solvent evaporation (high boiling point) during processing. Fig. S6 illustrates dynamic conductive path evolution under strain, where tensile deformation amplifies crack propagation within the mesh structure, enhancing sensitivity. Crucially, robust MXene–CT interfacial interactions maintain inter-fiber conductive connectivity, ensuring sustained electron transport despite structural reorganization.

3.4 Human motion detection and human–machine interaction

The CTCM strain sensor demonstrates exceptional versatility in full-spectrum human biomechanical monitoring by converting physiological motions into quantifiable relative resistance changes. Stable cyclic signals generated during facial muscle activation (Fig. 5a) and distinct resistance profiles from wrist articulation (Fig. 5b) validate macroscopic motion tracking, while index finger bending at 15°, 30°, 60°, and 90° yields angle-dependent responses (Fig. 5c). The sensor precisely captures elbow flexion dynamics with reversible resistance modulation (Fig. 5d) and resolves subtle deformations through phonetic recognition, differentiating monosyllabic (“A”) from disyllabic (“sensor”) utterances based on their characteristic peak patterns (Fig. 5e). Deglutition monitoring reveals water volume-dependent resistance variations (Fig. 5f), and radial pulse detection identifies triphasic waveforms (P1/P2/P3) with clinical precision (Fig. 5g). Extended functionalities include Morse code communication (“hello”, “ctcm”, “kust”, “sensor”) through timed resistance pulses (Fig. 6a and b), LED brightness regulation via strain-dependent current control (Fig. 6c), the schematic diagram of an LED in Fig. S9, and human–robot interaction where finger gestures are translated into robotic movements through real-time analog signal conversion (Fig. 6d).

Fig. 5 (a) ΔR/R₀ curve of cheek bulging. (b–d) ΔR/R₀ curves of different joint movements: wrist (b), finger (c) and elbow (d), respectively. (e and f) pronunciations of different rhythms. (g) Detection of the pulse beat.

Fig. 6 (a and b) Morse code used for sending information. (c) Changes in LED light when CTCMs are subjected to different strain levels. (d) The application of a human–machine interface.

4. Conclusions

In summary, a CTCM flexible strain sensor was constructed via a rationally designed dual-layer conductive architecture, comprising an upper network modified with MXene nanosheets and carbon black (CB) nanoparticles, integrated with a lower carbon black/thermoplastic polyurethane (CT) substrate that serves as both a flexible skeleton and an intrinsic conductive pathway. This hierarchical configuration leverages synergistic interactions between the two conductive layers to achieve simultaneously high sensitivity (GF up to 1765) and a broad sensing range (strains from 97.6% to 298.7%). Material characterization via XPS, XRD, and FTIR confirmed interfacial interactions between the porous CT substrate and MXene and revealed interfacial hydrogen bonding between MXene surface groups (–OH/–F) and TPU's C=O/–N=C=O moieties, which stabilize electromechanical performance. Systematic testing revealed exceptional sensor metrics: ultrahigh resolution (0.1% strain detection), rapid response/recovery kinetics (62 ms/67 ms), and robust durability (>8000 s cycle at 100% strain). Human biomechanical validation demonstrated multiscale detection capability—from subtle physiological signals (facial muscle movements and vocal cord vibrations) to gross articular motions (finger/elbow flexion)—with clearly distinguishable resistance signatures. The sensor's operational versatility was further evidenced through LED brightness modulation and human–robot interface applications, where real-time finger gestures were accurately translated into proportional robotic motions. These advancements, underpinned by the unique dual-network structure and a scalable fabrication route, establish the CTCM film as a promising platform for next-generation wearable electronics and intelligent human–machine interaction systems.

Author contributions

Renhan Li: writing – original draft, investigation, formal analysis, and data curation. Bokai Zhang: methodology and formal analysis. Ying Wang: methodology and investigation. Lingjie Kong: formal analysis. Chengbang Zhang: supervision and conceptualization. Jian Zhang: supervision and conceptualization. Yafei Qin: supervision and resources.

Conflicts of interest

There are no conflicts to declare.

Data availability

The data supporting this article have been included as part of the supplementary information (SI). Supplementary information is available. See DOI: https://doi.org/10.1039/d5py00753d.

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (No. 52165066), Yunnan Fundamental Research Projects (Grant No. 202401AT070354), and the Xingdian Talent Support Program of Yunnan Province (No. 2022).

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