The reliable detection of ammonia at room temperature is crucial for not only maintaining environmental safety but also for reducing the risks of hazardous pollutants. In this study, the electrochemical modification of laser-induced graphene (LIG) with polyaniline (PANI) led to the development of a chemo-resistive nanocomposite (PANI@LIG) for detecting ammonia levels at room temperature. The composite is characterized by field emission scanning electron microscopy, Fourier transforms infrared, and Raman and X-ray photoelectron spectroscopy. This work marks the first utilization of PANI@LIG for gas sensing and introduces a simple but effective approach for fabricating low-cost wearable gas sensors with high sensitivity and flexibility.

The electrochemical synthesis of polypyrrole (PPy) on laser-induced graphene (LIG) electrodes is investigated in this study, along with the gas sensing applications of these modified laser-tailored materials. A simple and scalable method for the low-cost, large-scale production of polypyrrole LIG nanocomposites (PPy@LIG NCs) is proposed. This nanocomposite is subsequently applied to design chemo-resistive flexible gas sensors to detect ammonia (NH3) levels at room temperature. Following a brief gas exposure, PPy@LIG NCs sensors demonstrate changes in resistance with a sensitivity 14 times higher than that of pure LIG. Moreover, excellent repeatability in results and a low detection limit of 1 ppm were achieved. The LIG formation and electrochemical synthesis of PPy were confirmed through Raman spectroscopy and FTIR spectroscopy. The analysis by FE-SEM and TEM verified the formation of PPy@LIG NCs. In conclusion, this work introduces the novel PPy@LIG nanocomposites and its application in gas sensing, showcasing their unique selectivity, enhanced sensitivity, and cost-effective production. These attributes mark a significant step forward, presenting new possibilities for the development of advanced gas-sensing systems aimed at improving air quality monitoring.

In the era of man–machine interfaces, digital twins stand as a key technology, offering virtual representations of real-world objects, processes, and systems through computational models. They enable novel ways of interacting with, comprehending, and manipulating real-world entities within a virtual realm. The real implementation of graphene-based sensors and electronic devices remains challenging due to the integration complexities of high-quality graphene materials with existing manufacturing processes. To address this, scalable techniques for the in-situ fabrication of graphene-like materials are essential. One promising method involves using a CO₂ laser to convert polyimide into graphene. Optimizing this graphitization process is hindered by complex parameter interactions and nonlinear terms. This article explores how these digital replicas can enhance the fabrication of laser-induced graphene (LIG) through laser simulation and machine learning methods to enable rapid single-step LIG patterning. This approach aims to create a universal simulation for all CO₂ lasers, calculating optical energy flux and utilizing machine learning to control and predict LIG conductivity (ability to conduct current), morphology, and electrical resistance. The proposed procedure, integrating digital twins in the LIG production process, will avoid or reduce the preliminary tests required to determine the proper laser parameters to reach the desired LIG characteristics. Accordingly, this approach will reduce the time and costs associated with these tests and thus increase the efficiency and optimize the procedure.

This work proposes a low-cost battery-less near-field communication (NFC) tag for gas sensing based on a resistive gas sensor. A proof-of-concept tag is designed using commercially available off-the-shelf (COTS) components. The energy required for the tag operation comes from the magnetic field generated by the reader, and all the electronics are powered by connecting them to the energy-harvesting output of the NFC integrated circuit. Read ranges up to 25 mm have been obtained with commercial NFC-enabled smartphones. The reading of resistance variations due to the presence of gas is performed using a low-consumption timer. The oscillation frequency of this timer depends on the resistance of the gas sensor and is measured by a microcontroller integrated into the tag. This method does not require any gain adjustment for operation, allowing the use of sensors with different resistance ranges. Low-cost room temperature sensors have been integrated for NO2 detection in both ppb and ppm ranges using laser-induced graphene (LIG). A detection limit of up to 36 ppb has been achieved. The smartphone transmits the data to a cloud database, allowing users to analyze and postprocess the information.

Manganese dioxide (MnO₂) has drawn attention as a sensitiser to be incorporated in graphene-based chemoresistive sensors thanks to its promising properties. In this regard, a rGO@MnO₂ sensing material was prepared and deposited on two different substrates (silicon and Kapton). The effect of the substrate nature on the morphology and sensing behaviour of the rGO@MnO₂ material was thoroughly analysed and reported. These sensors were exposed to different dilutions of NO₂ ranging from 200 ppb to 1000 ppb under dry and humid conditions (25% RH and 70% RH) at room temperature. rGO@MnO₂ deposited on Kapton showed the highest response of 6.6% towards 1 ppm of NO₂ under dry conditions at RT. Other gases or vapours such as NH₃, CO, ethanol, H₂ and benzene were also tested. FESEM, HRTEM, Raman, XRD and ATR-IR were used to characterise the prepared sensors. The experimental results showed that the incorporation of nanosized MnO₂ in the rGO material enhanced its response towards NO₂. Moreover, this material also showed very good responses toward NH₃ both under dry and humid conditions, with the rGO@MnO₂ sensor on silicon showing the highest response of 18.5% towards 50 ppm of NH₃ under 50% RH at RT. Finally, the synthetised layers showed no cross-responsiveness towards other toxic gases.

With the rapid growth of online transactions, there has been a significant increase in fraud involving pharmaceuticals, textiles, and food, among others. This work proposes the use of non-cloneable authentication tags for product brand protection, in which both the type of substrate used and its geometry are combined, resulting in a unique spectral response. These tags are manufactured in two phases, a first one that forms of a laser-induced graphene (LIG) layer, and a second one, based on an electroplating process, which produces traces with variable sheet resistance depending on the manufacturing parameters. This technology can be carried out using a common laser (e.g. CO ₂ laser) to directly convert various precursors into graphene materials (e.g. polyimide). A prototype scanner for characterizing the electromagnetic signature of the tags is presented. Preliminary results obtained with simple resonators and complex images show the feasibility of this technology.