Sarma, Shrutidhara

F1exible micro and nano sensors are a highly attractive option for the monitoring of physiological parameters like temperature, respiration rate, heartbeat, etc. in the healthcare field. Smart textiles and wearables are one of the most suitable ways in which vital parameters of a person can be monitored continuously without severely affecting the comfort and health of the person. In this paper, a textile based flexible sensor has been developed to create a thin wrist band which can be used to monitor the temperature of the person wearing it so as to detect alarming changes in temperature like in the case of fever or hypothermia. The constituent materials and the weaving pattern have been selected so as to facilitate temperature sensing with high precision. Through a series of experiments in a controlled environment, the optimal number of strands, optimal weaving pattern and the optimal length of the fabric are found by varying the aforementioned parameters and calculating the temperature coefficient of resistance (TCR). The readings obtained from the sensor do not fluctuate vividly with the passage of time, which indicates that the readings are stable. From the change in resistance the corresponding change in temperature (from the body temperature for which the fabric is calibrated for) is calculated on the basis of TCR.

Accurate monitoring and control of localized temperature is crucial to assess health conditions, to detect and diagnose diseases early and to offer possibilities of building smart healthcare systems. Flexible temperature sensors offer conformal attachment with the human skin for stable and continuous measurements and have therefore garnered extensive attention in recent years. However, although significant achievement has been made in terms of enhancing sensitivity or gaining stability under deformation, they are still limited by low accuracy under large mechanical strain, slow response in dynamic environments, increasing hysteresis and limited measurement range. In addition, large and continuous mapping in flexible formats is required to accurately realize temporal and spatial variation of physiological temperature before such devices can be practically applied for continuous health monitoring or in electronic skin measurements. This review comprehensively presents significant advances in flexible temperature sensors based on nanocomposite materials categorizing the work according to materials, sensor design, sensing mechanisms and compatible fabrication strategies. For comparison, a few traditional temperature sensors are also reported. Finally, critical issues in the field are discussed, technical gaps are highlighted and possible solutions are suggested that may help overcome the existing challenges.

Metallic nanoparticles and carbon nanotubes are two of the most promising nanomaterials, due to their distinctive properties occurring from spatial confinement of electron-hole pairs. The unique combination of metallic nanoparticles and carbon nanotubes (CNTs) in a polymer matrix offers unparalleled advantages, making them highly desirable in various fields. Advanced methods and techniques for synthesizing and characterizing hybrid metal-CNT-polymer nanocomposites have undergone significant progress in recent years, paving their integration into various fields, including aerospace, electronics, energy, water treatment and environmental remediation. These advances have allowed better understanding of nanocomposite properties and imparted ability to tune specific properties through size, shape, and distribution control of the nanofillers within the matrix material or by altering filler properties through functionalization. This study aims to critically judge the emerging tools, techniques and methods used in polymer nanocomposites with specific focus on metal-CNT based hybrid polymer nanocomposites, and suggest new avenues for research in the field. Furthermore, by examining the mechanisms affecting the performance of these composites, we can understand how the inclusion of fillers alters the microstructure and overall behavior of the material. Ultimately, this knowledge could lay the foundation for the development of novel nanocomposites with tailored properties and enhanced performance in a plethora of applications.

This work presents a comprehensive exploration of printed strain sensor array fabrication encompassing selection of substrate material, sensing layer deposition, design and fabrication of the sensor array, and the electronic component used to obtain sensor output. The objective of this study is to design a strain sensor array that exhibits highest sensitivity against bending conditions without degradation. Three distinct designs of resistance element arrays were tested rigorously to identify the most suitable sensor for application involving repetitive bending conditions such as respiration monitoring.

Thin film sensor (TFS) is one of the most promising candidates for instantaneous temperature measurements owing to their extremely small response time (~milliseconds) aided with fair accuracy. Since they are capable of making quick and precise temperature measurements, they can be also used as heat flux gauges to measure surface heat fluxes in dynamic environments like high speed aerospace applications, gas turbine blades etc. Usual TFS are made by depositing a thin metallic film over insulating substrate. In this work we developed an Ag-Carbon nanotube (CNT) nanocomposite film as the sensing element of a TFS and compare it with pure Ag TFS, both having Macor as substrate. Static calibration established a better temperature coefficient of resistance (TCR) value i.e. better sensitivity, for the nanocomposite TFS. X-ray diffraction (XRD) and Energy Dispersive X-ray (EDX) studies are done to probe behind the increase in sensitivity of the nanocomposite TFS compared to its conventional metallic counterpart.

In this work, a strain sensor was fabricated using conductive electrospun polyvinylidene fluoride (PVDF) nanofiber film coated with carbon nanotubes (CNTs) on a polyimide (PI) substrate. An investigation of the sensor’s properties during stretching and relaxation under varying experimental conditions was undertaken. The morphologies of the sensing films were examined to gain an understanding of their structure. The experimental design was complemented by simulation to optimize the shape and size of the substrate to ensure uniform and consistent straining under loading conditions. The insight derived from the computational analysis played an instrumental role in selecting the appropriate substrate design and determining the ideal location for placing the PVDF/CNTs sensing film. The difference in the deformation value of the substrate with the selected design during the computational and experimental analysis was 17.5%. An integrated approach, combining both experimental and computational methodologies, was used to significantly enhance the study’s value and facilitate the development of an efficient and effective strain sensor. The sensor displayed a gauge factor (GF) of 1.83 and 1.19 under the incremental loads of 0.98 and 1.96 N, respectively. In conclusion, this study contributes to an improved understanding of the strain sensor’s characteristics and potential applications in structural health monitoring technologies.

A robust understanding of structure–property relations of electrospun fibers is vital for device design. However, these relationships are inherently complex and hard to model using data from limited trial and error experiments. Machine learning has emerged as an efficient approach to model multidimensional relationships but fundamentally require diverse data to learn these relationships from. In this study, we present a novel Electrospun Fiber Experimental Attributes Dataset (FEAD) by collating experimental data from literature, developing new features, and complementing with our own experiments. Fiber diameter, a key parameter for controlling electrical and thermal properties of electrospun polyvinylidene fluoride (PVDF) polymer, is modeled using a large number of solution and electrospinning process experimental parameters using a multi-model machine learning approach. This is complemented with a model-agnostic interpretable game-theoretic approach to identify the relative and absolute relationships between the variables. Experimental attributes such as feed, polymer concentration, Flory-Huggins Chi parameter, and relative energy difference were found to be most impactful for modeling fiber diameter. This study overcomes several limitations in existing literature such as non-availability of meta datasets, application of latest machine learning techniques, and state-of-the-art approaches for interpreting these “black box” models, thus bridging the gap between experimental and computational studies. This improved ability to generalize structure–property relationships across any PVDF-polymer solvent system presents a promising ability to reduce expensive lab testing required for developing PVDF fibers of desired mechanical and electrical properties.

Combining high sensitivity with fast response and high resolution remains a critical challenge for flexible temperature sensors. The present study leverages the intrinsically high surface-to-volume ratio of nanocomposite fibers as well as the high mechanical properties of nanomaterials for achieving conformable temperature sensors with accurate and fast detection of temperature. To achieve this, nanocomposite films of electrospun polyvinylidene fluoride (PVDF) with embedded silver (Ag) nanoparticles were layered with multiwall carbon nanotubes (MWCNT). The sensor showed a negative temperature coefficient (NTC) with excellent sensitivity of −0.18%/°C and a quick response rate of 11 s. The sensor also exhibited low self-heating errors for an activation current of 1 mA and excellent anti-interference ability when tested for bending forces and wet environments. The nanocomposite fiber-based sensor can be used for real-time monitoring of human body temperature as confirmed by successful experiments. The present work lays the foundation for integrating the sensor further with a user interface to create a wearable temperature monitoring system for mobile healthcare.

Formation of a stable Taylor cone is an important phenomenon during electrospinning of nanofibers for controlling nanofiber properties. Optimizing electrospinning process parameters such as solution feed rate, applied electric voltage and tip to mandrel distance, a stable Taylor cone can be achieved and by maneuvering the parameters within a certain range, the height of the cone can be controlled. Here, we study the influence of the process parameters on the height of the Taylor cone and the corresponding nanofibers produced for polyvinylidene fluoride (PVDF) using dimethylformamide (DMF) as solvent. Characterization of the produced fibers and image analysis confirmed the optimal values as 1 mL/h, 10.8 kV and 10 cm for feed rate, applied voltage and spinning distance, respectively. Observations from the study reveal that contrary to proportional variation of Taylor cone height with nanofiber diameter in case of changing feed rate and applied voltage, the relationship gets inversely proportional when tip to mandrel distance is varied.

This work represents the in-house chemical synthesis of silver (Ag) nanoparticles, electrospinning of the synthesized Ag nanoparticles and polyvinylidene fluoride (PVDF) by using optimized parameters and then air spraying different amounts of multiwall carbon nanotubes (MWCNTs) on top of the prepared electrospun Ag-PVDF films, to check the electrical conductivity of the films. The morphology of the prepared sample films were examined by standard characterization techniques such as scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDS) to carry out the elemental analysis or chemical characteristics of the films. The temperature vs resistance behavior of the prepared films depicted linear variation in temperature with temperature coefficient of resistance (TCR) α = − 0.43 %/°C and − 0.63 %/°C, for the Ag-PVDF films having 0.16 mg and 0.8 mg MWCNTs sprayed, respectively, which are comparable to TCR values of reported temperature sensors. The mechanical properties of the films were also determined using tensile tests, which showed great improvement in the tensile strength and Young's modulus for the MWCNTs sprayed films. These results justify the potential of these hybrid nanocomposite films for energy, environment and sensing (especially temperature sensing) related applications.