Screen-Printed Graphite Nanoplate Conductive Ink for Machine Learning Enabled Wireless Radiofrequency-Identification Sensors

In this study, we demonstrate sustainable conductive screen printing ink containing graphite nanoplates (GNPs) prepared by means of combining shear and ultrasonication exfoliation processes with the aid of mixed-solvent strategy of isopropanol (IPA)–water mixtures. The screen printed GNP ink features high conductivity of 4.66 × 104 S/m, green preparation, low manufacturing cost and has the potential for industrial scale-up productions. We first benchmark the GNP conductive ink and screen printed samples to investigate the rheology of the ink and its compatibility for industrial production. The high loading GNP ink is further applied to scalable and efficient production of ultrahigh frequency (UHF) radiofrequency identification (RFID) tag antenna and reader antenna. A low-cost, accurate wireless liquid sensing system capable of sensing the content of the liquids via machine learning data sets by feedforward neural network is demonstrated for ubiquitous IoT sensing applications. The experimental results demonstrate that the GNP ink printed RFID tags and reader antennas can provide satisfactory read range and performance for many practical RFID applications, such as inventory and security. Furthermore, the printed RFID wireless sensor incorporating neural network machine learning can accurately label the content of colorless, transparent, and unidentified liquids, illustrating the potential in low-cost, green, and industrial scalable production of GNP conductive ink printed RFID antennas and sensing systems for massive IoT applications deployment enabling ubiquitous wireless connectivity.