Reliability of Screen-Printed Water-Based Carbon Resistors for Sustainable Wearable Sensors

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Sensors Journal Pub Date : 2025-01-09 DOI:10.1109/JSEN.2024.3525055
Udara S. Somarathna;Behnam Garakani;Darshana L. Weerawarne;Mohammed Alhendi;Mark D. Poliks;Matthew Misner;Andrew Burns;Gurvinder S. Khinda;Azar Alizadeh
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Abstract

Water-based carbon inks provide a cost-effective and sustainable alternative to organic-solvent-based metal conductive inks, making them attractive for wearable sensor applications. However, poor adhesion on nonporous polymer substrates and susceptibility to temperature and humidity fluctuations raise concerns about printability and reliability, hindering their widespread commercial adoption. This study focuses on screen-printing defect-free multilayer structures on flexible and stretchable polymer substrates using a commercial water-based conductive carbon black (CB) ink and evaluating their reliability. A robust printing process was developed by modifying the fabrication flow, optimizing printing parameters, and maintaining atmospheric relative humidity (RH) between 70% and 75%. Multilayer sweat-rate electrodes (SREs) with conductors and resistors were successfully screen-printed using a solvent-based silver ink and a water-based CB ink, respectively, and their environmental and mechanical reliability was comprehensively investigated. The water-based carbon resistors printed on polyimide substrate demonstrated promising results. Ambient-dried resistors on polyimide exhibited satisfactory electrical performance and reliability, while thermal curing further reduced their electrical resistance by 18% without compromising reliability. Moreover, these resistors demonstrated excellent environmental and mechanical reliability by withstanding thermal exposure at 125 ° C, RH of 15%, and 500 tensile bending cycles at a 1-cm bend radius, suggesting their suitability for wearable sensors. Failure analysis revealed the development of crater-like morphological structures during the drying process, which later acted as stress concentration points. Resistors printed on polyester, high-density polyethylene, and thermoplastic polyurethane (TPU) substrates failed due to cracking, delamination, ink-to-ink interactions, or out-of-plane deformation. Cracking and delamination patterns provided useful insights into failure mechanisms.
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用于可穿戴传感器的丝网印刷水基碳电阻的可靠性
水性碳油墨为有机溶剂型金属导电油墨提供了一种具有成本效益和可持续性的替代品,使其对可穿戴传感器应用具有吸引力。然而,非多孔聚合物基材的附着力差以及对温度和湿度波动的敏感性引起了人们对印刷性和可靠性的担忧,阻碍了它们的广泛商业应用。本研究的重点是使用商用水性导电炭黑(CB)油墨在柔性和可拉伸聚合物基材上丝网印刷无缺陷多层结构,并评估其可靠性。通过调整制造流程,优化打印参数,并将大气相对湿度(RH)保持在70%至75%之间,开发了一种健壮的打印工艺。采用溶质银墨和水性CB墨分别成功丝网印刷了带导体和电阻的多层汗液速率电极(SREs),并对其环境可靠性和机械可靠性进行了全面研究。在聚酰亚胺基板上印制的水基碳电阻显示出良好的效果。环境干燥的聚酰亚胺电阻器表现出令人满意的电性能和可靠性,而热固化进一步降低了18%的电阻,而不影响可靠性。此外,这些电阻器在125°C, 15%的相对湿度和500次弯曲半径为1厘米的拉伸弯曲循环下表现出优异的环境和机械可靠性,表明它们适用于可穿戴传感器。破坏分析表明,在干燥过程中形成了类似陨石坑的形态结构,这些形态结构后来成为应力集中点。印刷在聚酯、高密度聚乙烯和热塑性聚氨酯(TPU)基板上的电阻器由于开裂、分层、油墨之间的相互作用或面外变形而失效。开裂和分层模式提供了对破坏机制的有用见解。
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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