Graphene oxide/polyaniline-based microwave split-ring resonator: A versatile platform towards ammonia sensing

Microwave Sensor with Light-Assisted Enhancement Based on Ti3C2Tx MXene: Toward ppb-Level NO2 Detection Limits

Chemiresistive sensors are currently the most popular gas sensors, and metal semiconductor oxides are often used as sensitive materials (SMs). However, their high operating temperature means that more energy is required to maintain normal operation of the SM, resulting in an increase in power consumption of the entire sensing system. In order to solve this problem, a microwave gas sensor embedded with multilayer Ti3C2Tx MXene and split ring resonator (SRR) for nitrogen dioxide (NO2) detection was reported in this work. The sensor takes advantage of the weak coupling between the two SRRs to achieve a highly concentrated electric field and high Q-factor, in which the weak coupling region serves as the sensitive region to avoid damage to the resonator structure caused by the excessive conductivity of Ti3C2Tx. The sensor has good selectivity, a lower detection limit of 2 ppb, with an average detection sensitivity of 98.66 mdB ppm-1 in the range of 2-10,000 ppb at room temperature. Additionally, the effect of different lighting source to the sensor performance is investigated, and the sensor reached the best response (1.54 dB) under blue light. Finally, the mechanism of the enhanced sensitivity is discussed in detail based on the results of simulations and tests. The sensor circuit designed in this work provides a new approach for MGSs and for the first time introduces the photocatalytic pathway into microwave sensors, which will contribute to the optimization of microwave gas sensors in the future.

Detection of carcinoembryonic antigen specificity using microwave biosensor with machine learning

Early diagnosis and screening of tumor markers are essential for effective cancer treatment and improve the treatment efficiency and prognosis of tumor recurrence and metastasis. In this study, a split-ring resonator (SRR) circuit based on an interdigital electrode structure was developed and applied to microwave biosensors along with machine learning to detect extremely low concentrations of Carcinoembryonic Antigen (CEA). CEA was detected using a microwave sensor operating at a resonance frequency of 4.33 GHz. When the microwave sensor is exposed to CEA analytes, it generates a new frequency in the range of 1-2 GHz. The position and intensity of the newly generated frequency can be used to characterize and predict the concentration of the CEA solution. The proposed sensor exhibits excellent resonance linearity for various concentrations of CEA (R2 = 0.999), as well as a very low detection limit (39 pg/mL) and high sensitivity (27.5 MHz/(ng/mL)). A machine learning approach was implemented to predict the CEA concentration in blood samples. The results showed close concurrence with the CEA concentration detected by the sensor. Western Blot (WB) was used to compare the CEA contents of four different cell types, and a biosensor was used for validation; the results of the two experiments showed good agreement. This is the first demonstration of the validation of biosensor reliability at the cellular level. The proposed concept exhibits outstanding detection performance with convenient and rapid tumor marker detection. Hence, it has important implications as an auxiliary diagnosis method for cancer.

Flexible Passive Wireless Sensing Platform with Frequency Mapping and Multimodal Fusion

As one of the core parts of the Internet-of-things (IOTs), multimodal sensors have exhibited great advantages in fields such as human-machine interaction, electronic skin, and environmental monitoring. However, current multimodal sensors substantially introduce a bloated equipment architecture and a complicated decoupling mechanism. In this work we propose a multimodal fusion sensing platform based on a power-dependent piecewise linear decoupling mechanism, allowing four parameters to be perceived and decoded from the passive wireless single component, which greatly broadens the configurable freedom of a sensor in the IOT. A systematic model is employed to analyze the linear sensing properties and ensure the feasibility of the scheme. The excitation power dependence provides an efficient and quantitative linear decoupling strategy of unidentified combinations for multiple stimuli. As a validation for a wearable device such as electronic skin (e-skin), the functionalized sensing film polyaniline/graphene oxide (PANI/GO) is served to synchronously monitor humidity, temperature, ultraviolet, and proximity through the mapping in resonant frequency (fs). Compared with the output errors of ∼18.00%, ∼17.50%, ∼15.00%, and ∼20.00%, the maximum experimental errors of temperature, humidity, ultraviolet, and proximity are 5.70%, 4.00%, 5.00%, and 8.30% after decoupling, respectively. In general, the developed single-component multimodal fusion sensing platform offers a strategic advantage for a miniaturization, passive wireless, and inexpensive (less than $1) signal identification system with a facile circuit layout.

Waveguide-Based Microwave Nitric Oxide Sensor for COVID-19 Screening: Mass Transfer Modulation Effect on Hollow Confined WO3 Structures

Serious acute respiratory syndrome coronavirus-2 (SARS-CoV-2) poses a tremendous threat to global public health. Recently, the Food and Drug Administration approved the emergency use of volatile organic components as detection biomarkers for COVID-19, ushering in a new era of portable, simple, and rapid epidemiological screening based on breath diagnosis. Nitric oxide (NO) is an important biomarker indicating the degree of inflammation in the respiratory tract. In this study, a hollow multishelled structured WO3 (HoMSs-WO3)-based waveguide microwave gas sensor (MGS) was fabricated to detect trace levels of NO in exhaled breath for the preliminary diagnosis of COVID-19. The sensor showed excellent reusability and selectivity and efficiently detected NO in the 10-100 ppb, with a sensitivity of 39.27 dB/ppm and a detection limit of 2.52 ppb. In addition, a sound correlation was observed in the measurement results between the MGS and the Sunvou detector for detecting NO from the exhaled breath of clinical COVID-19 patients. The difference between the two measurements was within 1.96 standard bias, and the consistency range was -12 to 17 ppb, thus fully demonstrating the significant potential of the sensor in COVID-19 screening.

Machine Learning Driven Atom-Thin Materials for Fragrance Sensing

Fragrance plays a crucial role in the daily lives. Its importance spans various sectors, from therapeutic purposes to personal care, making the understanding and accurate identification of fragrances essential. To fully harness the potential of fragrances, efficient and precise fragrance sensing and identification are necessary. However, current fragrance sensors face several limitations, particularly in detecting and differentiating complex scent profiles with high accuracy. To address these challenges, the use of atom-thin materials in fragrance sensors has emerged as a groundbreaking approach. These atom-thin sensors, characterized by their enhanced sensitivity and selectivity, offer significant improvements over traditional sensing technology. Moreover, the integration of Machine Learning (ML) into fragrance sensing has opened new opportunities in the field. ML algorithms applied to fragrance sensing facilitate advancements in four key domains: accurate fragrance identification, precise discrimination between different fragrances, improved detection thresholds for subtle scents, and prediction of fragrance properties. This comprehensive review delves into the synergistic use of atom-thin materials and ML in fragrance sensing, providing an in-depth analysis of how these technologies are revolutionizing the field, offering insights into their current applications and future potential in enhancing the understanding and utilization of fragrances.

Hybrid Nanocomposites Based on Poly(3,6-dianiline-2,5-dichloro-1,4-benzoquinone): Synthesis, Structure and Properties

Hybrid nanocomposites based on poly(3,6-dianiline-2,5-dichloro-1,4-benzoquinone) (PDACB) in salt form and graphene oxide (GO) have been obtained for the first time, and the significant influence of the preparation method on the composition and structure of nanocomposites and their functional properties has been demonstrated. Nanocomposites were prepared in three ways: via ultrasonic mixing of PDACB and GO; via in situ oxidative polymerization of 3,6-dianiline-2,5-dichloro-1,4-benzoquinone (DACB) in the presence of GO; and by heating a suspension of previously prepared PDACB and GO in DMF with the removal of the solvent. The results of the study of the composition, chemical structure, morphology, thermal stability and electrical properties of nanocomposites obtained via various methods are presented. Nanocomposites obtained by mixing the components in an ultrasonic field demonstrated strong intermolecular interactions between PDACB and GO both due to the formation of hydrogen bonds and π-stacking, as well as through electrostatic interactions. Under oxidative polymerization of DACB in the presence of GO, the latter participated in the oxidative process, being partially reduced. At the same time, a PDACB polymer film was formed on the surface of the GO. Prolonged heating for 4 h at 85 °C of a suspension of PDACB and GO in DMF led to the dedoping of PDACB with the transition of the polymer to the base non-conductive form and the reduction of GO. Regardless of the preparation method, all nanocomposites showed an increase in thermal stability compared to PDACB. All nanocomposites were characterized by a hopping mechanism of conductivity. Direct current (dc) conductivity σdc values varied within two orders of magnitude depending on the preparation conditions.

Dielectric Properties of Materials Used for Microwave-Based NOx Gas Dosimeters

Nitrogen oxides (NOx), primarily generated from combustion processes, pose significant health and environmental risks. To improve the coordination of measures against excessive NOx emissions, it is necessary to effectively monitor ambient NOx concentrations, which requires the development of precise and cost-efficient detection methods. This study focuses on developing a microwave- or radio frequency (RF)-based gas dosimeter for NOx detection and addresses the optimization of the dosimeter design by examining the dielectric properties of LTCC-based (Low-Temperature Co-fired Ceramics) sensor substrates and barium-based NOx storage materials. The measurements taken utilizing the Microwave Cavity Perturbation (MCP) method revealed that these materials exhibit more pronounced changes in dielectric losses when storing NOx at elevated temperatures. Consequently, operating such a dosimeter at high temperatures (above 300 °C) is recommended to maximize the sensor signal. To evaluate their high-temperature applicability, LTCC substrates were analyzed by measuring their dielectric losses at temperatures up to 600 °C. In terms of NOx storage materials, coating barium on high-surface-area alumina resolved issues related to limited NOx adsorption in pure barium carbonate powders. Additionally, the adsorption of both NO and NO2 was enabled by the application of a platinum catalyst. The change in dielectric losses, which provides the main signal for an RF-based gas dosimeter, only depends on the stored amount of NOx and not on the specific type of nitrogen oxide. Although the change in dielectric losses increases with the temperature, the maximum storage capacity of the material decreases significantly. In addition, at temperatures above 350 °C, NOx is mostly weakly bound, so it will desorb in the absence of NOx. Therefore, in the future development of a reliable RF-based NOx dosimeter, the trade-off between the sensor signal strength and adsorption behavior must be addressed.

MXene Free Standing Films: Unlocking the Impact of Flake Sizes in Microwave Resonant Structures in Humid Environments

Microwave communication devices necessitate elements with high electrical conductivity, a property which was traditionally found in metals (e.g., copper). However, in applications such as satellite communications, metals prevent the payload from achieving lightweight and flexible characteristics. Here, we demonstrate the development of MXene film microwave resonators, leveraging MXene's high electrical conductivity and unique mechanical properties. To investigate resonant performance in humid conditions and study the effects of MXene's processing and treatment, MXene films with different flake sizes are prepared and exposed to cyclic humidity. For the large- and small-flake Ti3 C2 MXene films in cyclic humidity, the large-flake film demonstrates higher electrical conductivity, higher resonance quality factor (150 and 35 as unloaded, and loaded), and less fluctuation of performance (≈1.7% total shift in resonance frequency). Further, by implementing MXene films of two different diameters, the correlation between film size and resonant frequency is demonstrated. By introducing an active resonant configuration, the effect of MXene degradation and microwave losses can be compensated. This active feedback loop demonstrates a ≈300 times increase in the quality factor of MXene resonators. As a building block for terrestrial and satellite communication modules, MXene resonators potentiate the replacement of metals in achieving unique electrical and mechanical properties.

A Microwave Voyage into Swelling Phenomenon: Investigation of Polydimethylsiloxane and VOCs Interaction

When exposed to specific gases, polymers undergo swelling, leading to physiochemical changes that can significantly affect their performance. Monitoring this swelling phenomenon requires innovative approaches. This study focuses on investigating the real-time resonant microwave behavior of two polydimethylsiloxane (PDMS) structures (solid and porous) in interaction with tetrahydrofuran (THF) and acetone, which are primary swelling agents. A microwave measurement method is proposed using an 8.63 GHz planar split ring resonator (SRR). The device's resonant frequency downshifts to 7.75 and 8.42 GHz when solid and porous PDMS blocks are placed on the split ring gap. Interaction of the solid PDMS and porous PDMS with target gases caused a change in PDMS structure resulting in alterations in the dielectric properties of the PDMS/gas system, as evidenced by the resonator's transmission amplitude and resonant frequency shifts. The magnitude of these shifts depends on the type and concentration of the solvent gas. The PDMS-integrated SRR exhibits a sensitivity of 25.3 MHz/1 ppt THF and 7 MHz/1 ppt acetone. Additionally, the solid block demonstrates response times of 6800 and 4200 s for swelling and deswelling, respectively, when in exposure to 25 ppt concentrations of THF and acetone. Overall, this study underscores the substantial potential of microwave resonators as versatile tools for investigating the physical changes in polymers during their interaction with gases, contributing to the understanding of polymer-gas interactions and opening avenues for further research and diverse applications.

Multiplexed DNA-functionalized graphene sensor with artificial intelligence-based discrimination performance for analyzing chemical vapor compositions

This study presents a new technology that can detect and discriminate individual chemical vapors to determine the chemical vapor composition of mixed chemical composition in situ based on a multiplexed DNA-functionalized graphene (MDFG) nanoelectrode without the need to condense the original vapor or target dilution. To the best of our knowledge, our artificial intelligence (AI)-operated arrayed electrodes were capable of identifying the compositions of mixed chemical gases with a mixed ratio in the early stage. This innovative technology comprised an optimized combination of nanodeposited arrayed electrodes and artificial intelligence techniques with advanced sensing capabilities that could operate within biological limits, resulting in the verification of mixed vapor chemical components. Highly selective sensors that are tolerant to high humidity levels provide a target for "breath chemovapor fingerprinting" for the early diagnosis of diseases. The feature selection analysis achieved recognition rates of 99% and above under low-humidity conditions and 98% and above under humid conditions for mixed chemical compositions. The 1D convolutional neural network analysis performed better, discriminating the compositional state of chemical vapor under low- and high-humidity conditions almost perfectly. This study provides a basis for the use of a multiplexed DNA-functionalized graphene gas sensor array and artificial intelligence-based discrimination of chemical vapor compositions in breath analysis applications.

Critical review and recent advances of 2D materials-Based gas sensors for food spoilage detection

Many people around the world are concerned about meat safety and quality, which has resulted in the ongoing advancement of packaged food technology. Since the emergence of graphene in 2004, the number of studies on layered two-dimensional materials (2DMs) for applications ranging from food packaging to meat quality monitoring has been expanding quickly. Recently, scientists have been working hard to develop a novel class of 2DMs that keep the good things about graphene but don't have zero bandgaps at room temperature. Much work has been done on layered transition metal dichalcogenides (TMDCs) like different metal sulfides and selenides for meat spoilage gas sensors. This review looks at (i) the main indicators of meat spoilage and (ii) the detection methods that can be used to find out if meat has been spoiled, such as chemiresistive, electrochemical, and optical methods. (iii) the role of 2DMs in meat spoilage detection and (iv) the emergence of advanced methods for selective classification of target analytes in meat/food spoilage detection in recent years. Thus, this review demonstrates the potential scope of 2DMs for developing intelligent sensor systems for food and meat spoilage detection with high viability, simplicity, cost-effectiveness, and other multipurpose tools.

Advanced polymeric/inorganic nanohybrids: An integrated platform for gas sensing applications

Rapid industrial development, vehicles, domestic activities and mishandling of garbage are the main sources of pollutants, which are destroying the atmosphere. There is a need to continuously monitor these pollutants for the safety of the environment and human beings. Conventional instruments for monitoring of toxic gases are expensive, bigger in size and time-consuming. Hybrid materials containing organic and inorganic components are considered potential candidates for diverse applications, including gas sensing. Gas sensors convert the information regarding the analyte into signals. Various polymeric/inorganic nanohybrids have been used for the sensing of toxic gases. Composites of different polymeric materials like polyaniline (PANI), poly (4-styrene sulfonate) (PSS), poly (3,4-ethylene dioxythiophene) (PEDOT), etc. with various metal/metal oxide nanoparticles have been reported as sensing materials for gas sensors because of their unique redox features, conductivity and facile operation at room temperature. Polymeric nanohybrids showed better performance because of the larger surface area of nanohybrids and the synergistic effect between polymeric and inorganic materials. This review article focuses on the recent developments of emerging polymeric/inorganic nanohybrids for sensing various toxic gases including ammonia, hydrogen, nitrogen dioxide, carbon oxides and liquefied petroleum gas. Advantages, disadvantages, operating conditions and prospects of hybrid composites have also been discussed.

Macromolecule Relaxation Directed 3D Nanofiber Architecture in Stretchable Fibrous Mats for Wearable Multifunctional Sensors

Elastomer fiber mat sensors, which are capable of perceiving mechanical stimuli, temperature, and vapor of chemicals, are highly desirable for designing wearable electronics and human-robot interfacing devices due to good wearability, skin affinity, and durability, and so on. However, it is still challenging to fabricate multiresponsive flexible wearable sensors with three-dimensional (3D) architecture using simple material and structure design. Herein, we report an all-in-one multiresponsive thermoplastic polyurethane (TPU) nanofiber mat sensors composed of crimped elastomer fibers with deposited platinum nanoparticles (PtNPs) on the fiber surface. The 1D TPU nanofibers could be transferred to nanofibers with different 3D nanofiber architectures by controllable macromolecular chain relaxation of aligned elastomer polymers upon poor solvent annealing. The conductive networks of PtNPs on wavy TPU fibers enable the sensor susceptible to multiple stimuli like strain/pressure, humidity, and organic vapors. Besides, the 3D nanofiber architectures allow the strain sensor to detect wider tensile strain and pressure with higher sensitivity due to delicate fiber morphology and structure control. Therefore, this work provides new insights into the fabrication of multifunctional flexible sensors with 3D architecture in an easy way, advancing the establishment of a multiple signal monitoring platform for the health care and human-machine interfacing.

Research Progress of Graphene and Its Derivatives towards Exhaled Breath Analysis

The metabolic process of the human body produces a large number of gaseous biomarkers. The tracking and monitoring of certain diseases can be achieved through the detection of these markers. Due to the superior specific surface area, large functional groups, good optical transparency, conductivity and interlayer spacing, graphene, and its derivatives are widely used in gas sensing. Herein, the development of graphene and its derivatives in gas-phase biomarker detection was reviewed in terms of the detection principle and the latest detection methods and applications in several common gases, etc. Finally, we summarized the commonly used materials, preparation methods, response mechanisms for NO, NH₃, H₂S, and volatile organic gas VOCs, and other gas detection, and proposed the challenges and prospective applications in this field.