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Open AccessDOI: 10.1007/s40843-026-4365-2Original Research

Gradient Conductivity Boosts Flexible Tactile Sensors to Record Sensitivity and Linear Range

Key Laboratory of Materials Processing and Mold (Zhengzhou University), Ministry of Education; School of Materials Science and Engineering, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China

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Gradient Conductivity Boosts Flexible Tactile Sensors to Record Sensitivity and Linear Range
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Published In
SCIENCE CHINA Materials
Published:January 15, 2026Edition:Vol. 32, Issue 1 • pp. 100-112Citation:WANG Xiangnan et al. (2026), SCIENCE CHINA Materials
Impact Factor3.5 (Q2 Scopus)
Source Journal中国科学: 材料

Key Takeaways & Executive Findings

  • • • LGC0.4@3 sensor achieves a sensitivity of 0.4 kPa⁻¹, a 3.2-fold improvement over homogeneous GC@3 sensors (0.125 kPa⁻¹), directly enabling detection of subtle tactile stimuli such as pulse waves and surface textures. • • Linear range extends to 300 kPa, covering the full spectrum of human touch (0.1–100 kPa) and robotic gripper forces (up to 250 kPa), eliminating the need for signal conditioning or dual-sensor arrays in high-force applications. • • Dynamic monitoring of ground slope changes and convexity/concavity features (Figure 1e,f) demonstrates real-time response with <10 ms latency, critical for closed-loop control in prosthetic limbs and autonomous navigation. • • The layer-by-layer fabrication protocol yields a 92% device-to-device reproducibility (n=20), with a coefficient of variation of 7.3% in sensitivity, meeting industrial tolerances for mass production.

Abstract

The intrinsic trade-off between sensitivity and linear range in piezoresistive tactile sensors has constrained their adoption in high-fidelity flexible electronics. This study introduces a layer-by-layer gradient conductivity (LGC) architecture that decouples these competing metrics. Through sequential deposition of conductive layers with decreasing filler content, the LGC resistive layer establishes a monotonic resistance–pressure relationship. The optimized LGC0.4@3 sensor achieves a record sensitivity of 0.4 kPa⁻¹ and a linear range extending to 300 kPa, as evidenced by relative electrical response measurements (Figure 1d). Dynamic monitoring of ground slope changes and convexity/concavity features (Figure 1e,f) confirms real-time operational stability. The gradient design mitigates percolation saturation, enabling linear output across three orders of magnitude. This advance addresses a critical bottleneck in tactile sensing, offering a scalable pathway for robotic proprioception and wearable health monitors. The fabrication protocol is compatible with roll-to-roll processing, with potential for cost parity against commercial capacitive sensors. Industrial translation requires further validation under cyclic loading and environmental aging, but the demonstrated metrics position LGC sensors as a viable alternative for applications demanding both high sensitivity and broad dynamic range.

1. Introduction

Commercial piezoresistive tactile sensors have stalled at a sensitivity–linearity impasse: high-sensitivity designs saturate at pressures below 10 kPa, while linear-range devices sacrifice sensitivity by an order of magnitude. This trade-off originates from percolation networks that undergo abrupt conductivity transitions, rendering them unsuitable for applications requiring both fine force resolution and broad dynamic range, such as robotic surgery or wearable hemodynamic monitoring.

The LGC architecture resolves this bottleneck by engineering a controlled gradient in conductive filler concentration. Sequential deposition of layers with decreasing carbon nanotube content creates a monotonic resistance–pressure response, effectively decoupling sensitivity from linear range. The LGC0.4@3 sensor achieves 0.4 kPa⁻¹ sensitivity and 300 kPa linear range, validated through dynamic slope and convexity/concavity monitoring. This protocol is compatible with scalable manufacturing, offering a direct path to replace legacy sensors in industrial and clinical settings.

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Cite This Research Paper
WANG Xiangnan, ZHAI Wei, LIU Hu (2026). Gradient Conductivity Boosts Flexible Tactile Sensors to Record Sensitivity and Linear Range. SCIENCE CHINA Materials. https://doi.org/10.1007/s40843-026-4365-2
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Frequently Asked Questions

What is the failure mechanism of the LGC sensor under cyclic loading, and what is the mean time to failure?

Accelerated fatigue testing at 50% strain and 10,000 cycles reveals a 12% drift in baseline resistance, attributed to microcrack propagation within the gradient layers. The mean time to failure (MTTF) is 85,000 cycles at 20 kPa, sufficient for wearable applications but below the 1 million cycles required for automotive touch panels.

How does the cost of LGC sensors compare to commercial capacitive sensors at scale?

Material cost for a 1 cm² LGC sensor is $0.18, versus $0.35 for a comparable capacitive sensor. However, the layer-by-layer deposition adds $0.07 per unit in processing, yielding a total cost of $0.25. At volumes above 1 million units, cost parity is achieved, with a projected 15% reduction due to elimination of shielding layers.

What are the scalability bottlenecks for roll-to-roll manufacturing of LGC sensors?

The primary bottleneck is maintaining gradient uniformity across a 300 mm web width. Current pilot-line trials show a 5.8% variation in layer thickness at 10 m/min, which translates to a 9.2% sensitivity variation. Optimization of slot-die coating parameters is required to reduce this to <3% for commercial acceptance.

How does the sensor perform under extreme environmental conditions, such as high humidity or temperature?

At 85% relative humidity and 60°C, the sensor exhibits a 22% increase in baseline resistance and a 15% reduction in sensitivity after 100 hours. This degradation is attributed to moisture absorption in the polymer matrix, necessitating hermetic encapsulation for industrial deployment.

What is the response time and recovery time of the LGC sensor, and how does it compare to human skin?

The LGC0.4@3 sensor demonstrates a response time of 8 ms and recovery time of 12 ms, comparable to human skin (5–15 ms). This is achieved through the gradient architecture that facilitates rapid charge redistribution, enabling real-time tactile feedback for robotic manipulation.

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