Liquid Sensor Research Articles

Design and validation of a multi-electrode embedded capacitive sensor to monitor the electromagnetic properties in concrete structures

This paper discusses the development of a capacitive sensor embedded within concrete blocks in order to continuously monitor water content, which is a crucial parameter in the assessment of concrete degradation. The embedded capacitive sensor undergoes continuous interrogation by an automatic monitoring system, in order to track permittivity changes over time through a frequency measurement system. The methodology involves a two-step calibration process: first, obtaining permittivity from frequency, then converting permittivity profiles into water content profiles. This paper focuses on the sensor design and first calibration in the aim of assessing permittivity profiles. Numerical methods enable optimizing both electrode geometry and design of the embedded capacitive sensor. Experimental validation of the sensor in liquid and concrete environments, along with a metrological validation, reveals the sensor’s ability to monitor permittivity profiles as well as its uncertainty at 8 different depths inside the concrete structure. Permittivity measurements were also conducted using reference methods. The results demonstrate very good agreement with less than 10% difference between the embedded sensor and the reference results. This step provides insights into its applicability and potential perspectives for future research.

A Review on Gallium Nitride for Liquid Sensors: Fabrications to Applications

A Review on Gallium Nitride for Liquid Sensors: Fabrications to Applications

A liquid lever sensor based on an abrupt taper and micro‐arc Michelson interferometer in single‐mode fiber

AbstractA novel two‐parameter sensor is proposed based on the abrupt taper and micro‐arc Michelson interferometer (MI) in single‐mode fiber. When there is a regular change in the liquid level or temperature, the phase difference changes, and the spectral intensity or wavelength of the interfering valleys of this sensor is directionally shifted. This study enriches the construction of MI and provides a new perspective on liquid level measurement. We experimentally explored the sensor's sensing performance over temperature and liquid level: this sensor's temperature sensitivity and liquid level sensitivity were up to 62.9 pm/°C and 0.2896 dB/mm, respectively. In addition, this sensor is characterized by compactness, simplicity, low cost, and high reliability, and it is suitable for measurement of liquid level and temperature, expanding the application field of MI.

Construction of a Liquid Crystal Biosensor and Detection of Heavy Metal Ions and Organic Phosphate

Since the discovery of liquid crystal molecules have been widely used in electronic display devices. At the same time, as special “sensitive elements”, liquid crystal molecules have also been introduced into the field of sensors in recent years, especially in life science research, where they have been used to for constructing liquid crystal biosensors, the first appearance. Liquid crystal biosensors are fast, simple and low-cost, label-free, highly sensitive, and with low detection limits. Therefore, the development of new liquid crystal sensors is undoubtedly a great development in the field of chemical biosensors.

Combined laser-induced graphene and microcontact printing for processing scalable and stackable micro-stripe patterns toward multifunctional electronic devices

Laser-induced graphene (LIG) is a highly promising technology for assembling thin-film electronics with miniaturized surficial patterns, although hard to guarantee both high-quality formation of raw materials and high resolution of feature size. In this study, a combined microcontact printing (μCP) and LIG protocol is creatively utilized to fabricate ultra-thin graphene films with highly ordered micro-stripe arrays. In addition to realize various patterned structures with unique scalable and stackable characteristics, PAA concentration (4–8 wt%) is systematically investigated as a critical parameter to precisely control the feature size of micro-patterns before and after the irradiation process, including line width (before: 5.37–22.44 μm, after: 4.83–22.32 μm) and average height (before: 69.81–187.39 nm, after: 5.72–48.61 nm). By further exploring a defocused multi-lasing strategy, sheet resistance of the graphene array could be optimized dramatically from 634.1 kΩ/sq to 1.9 kΩ/sq, while maintaining low ablation (45.38 % porosity) and high carbon content (84.2 wt%). Lastly, the process is demonstrated to assemble different graphene based electronic devices with miniaturized sizes, including liquid sensors with sensitivity of 2.7 % μL−1 and electrothermal heaters with temperature-ramping rate as high as 24.7 °C/s and working temperature as high as 248 °C.

Artificial Q-Grader: Machine Learning-Enabled Intelligent Olfactory and Gustatory Sensing System.

Portable and personalized artificial intelligence (AI)-driven sensors mimicking human olfactory and gustatory systems have immense potential for the large-scale deployment and autonomous monitoring systems of Internet of Things (IoT) devices. In this study, an artificial Q-grader comprising surface-engineered zinc oxide (ZnO) thin films is developed as the artificial nose, tongue, and AI-based statistical data analysis as the artificial brain for identifying both aroma and flavor chemicals in coffee beans. A poly(vinylidene fluoride-co-hexafluoropropylene)/ZnO thin film transistor (TFT)-based liquid sensor is the artificial tongue, and an Au, Ag, or Pd nanoparticles/ZnO nanohybrid gas sensor is the artificial nose. In order to classify the flavor of coffee beans (acetic acid (sourness), ethyl butyrate and 2-furanmethanol (sweetness), caffeine (bitterness)) and the origin of coffee beans (Papua New Guinea, Brazil, Ethiopia, and Colombia-decaffeine), rational combination of TFT transfer and dynamic response curves capture the liquids and gases-dependent electrical transport behavior and principal component analysis (PCA)-assisted machine learning (ML) is implemented. A PCA-assisted ML model distinguished the four target flavors with >92% prediction accuracy. ML-based regression model predicts the flavor chemical concentrations with >99% accuracy. Also, the classification model successfully distinguished four different types of coffee-bean with 100% accuracy.

Liquid Metal-Based Sensor With Nonuniform Strain Distribution for Wearable Applications

Liquid Metal-Based Sensor With Nonuniform Strain Distribution for Wearable Applications

Soft crawling robot integrated with liquid metal-based flexible strain sensor and closed-loop feedback control

Due to the inherent softness and adaptability, soft robots have shown great application prospects in medical rehabilitation, environmental exploration, and other fields. However, the unpredictable and complex behaviors of the elastic materials greatly increased the difficulty in the control of soft robots. This study proposed an integrated soft crawling robot (ISCR) with flexible strain sensors to achieve the closed-loop feedback control of motion. First, a flexible strain sensor was fabricated by injecting liquid metal (LM) into an elastomer with a wavy structure. The key performances of the sensor were investigated. The developed flexible strain sensor can achieve a high gauge factor of 2.07, a low hysteresis of 1.902%, a wide detection range of 150% strain, a low detection limitation as low as 0.4% strain change, and an excellent stability and durability, which fully satisfy the requirements for the proprioception of soft robots. We built a closed-loop feedback control system to achieve closed-loop control of the ISCR. Finally, we successfully realized the continuous motion of the ISCR under closed-loop control. We believe this work will be helpful for the development of automation and intelligence of soft crawling robots.

Flexible and Fully Printed Passive RF Resonators for Contact‐Less Solution Sensing

AbstractIn recent years, several efforts have been dedicated to the development of portable and versatile microwave technologies for contact‐less liquid sensing and characterization. With respect to existing electrochemical and optical approaches, microwave liquid sensors enable high‐sensitivity and label‐free sensing with increased operation stability and robustness, and in relatively simple and inexpensive device formats. Nonetheless, current microwave solution sensing systems are still limited by either their reliance on wired connections to external electronics or by their widespread implementation on conventional rigid substrates. These limitations hinder the seamless integration of such sensors within conventional (micro)fluidic systems for real‐time solution monitoring, particularly when near‐field coupling between the sensors and the liquid under test needs to be established for operation. By leveraging the versatile material deposition capabilities granted by solution‐phase processing, a fully printed and mechanically flexible microwave resonator design is introduced that allows untethered solution sensing whether immersed in or in proximity to the liquid under test. The mechanical properties of this device facilitate the noninvasive/nondestructive integration of the device on commercial tubing. These characteristics, along with its cost‐effectiveness and its ease of fabrication, favor the seamless integration of this device into fluidic and microfluidic systems, for real‐life applications.

Liquid Plug Motion Noninvasive Detecting in Opaque Microchannels via Grating Electrodes‐Based Liquid‐Solid Nanogenerator

AbstractThe precision in controlling fluid flow is crucial for the efficiency of microchannel devices. Consequently, it is essential to monitor the fluid within microchannels in real time. However, the microchannel flow's susceptibility to disturbance and small size present challenges in sensing. A Liquid‐Solid Triboelectric Nanogenerator (TENG) with grating electrodes is proposed for non‐invasive sensing of liquid plug movements in microchannels and is suitable for use with opaque channels. This sensor operates on the principle of initiating multiple pulse signals via grating electrodes. And analyze the motion of the liquid plug by the time difference between the signal peaks. It facilitates the measurement of liquid plug count, average speed, average acceleration, and the detection of flow direction. The liquid plug counters, and flow direction sensors yielded clear and distinguishable signals. The liquid plug average speed sensor achieves a 95% accuracy rate, and the acceleration sensor accurately distinguishes speed trends of the liquid plug with more than 85% precision. Grating electrodes are effectively employed for motion sensing. Analyzing the motion of an object by the time difference between voltage peaks offers greater stability than voltage magnitude analysis. Four portable prototypes are designed to make them applicable for fluid sensing in microchannel devices.

Red phenanthrenequinone dyes with high thermal and photo-stability for LCD color filters

Color filters (CF) are essential integral parts of the liquid crystal display (LCD) and image sensor. Compared to traditional pigment colorants, organic dyes offer a promising alternative to realize CF with improved optical properties and higher resolution. However, organic dyes usually suffer from inferior thermal and photo-stability, limiting their applications in CF. Herein, four robust donor-acceptor organic dyes based on phenanthrenequinone chromophore were designed and synthesized by introducing aromatic amine derivatives as the electron donors. The strong donor-acceptor interactions in these dyes contribute to intense broad charge-transfer absorption bands from 375 nm to 600 nm with high molar extinction coefficients, thus realizing red color. Also, these dyes exhibit high thermal and photo-stability, good compatibility with the polymer binder and low aggregation tendencies, resulting in high thermal and photo-stability for the fabricated CF films. Remarkably, among these phenanthrenequinone dyes, DTPAP with multi-donor substitution and extended π-conjugation exhibited the best performance in terms of molar extinction coefficient, thermal and photo-stability, contributing to the highest thermal and photo-stability for the CF film with color difference values (ΔEab) below 0.75 under simulated industrial manufacturing processes. This work confirms that phenanthrenequinone is a robust chromophore and is conducive to developing thermal and photo-stable CF dyes, and paves a way to improve the optical properties and stability of donor-acceptor dyes for CF.

FRET-Sensing of Multivalent Protein Binding at the Interface of Biomimetic Microparticles Functionalized with Fluorescent Glycolipids.

Cell adhesion is a central process in cellular communication and regulation. Adhesion sites are triggered by specific ligand-receptor interactions inducing the clustering of both partners at the contact point. Investigating cell adhesion using microscopy techniques requires targeted fluorescent particles with a signal sensitive to the clustering of receptors and ligands at the interface. Herein, we report on simple cell or bacterial mimics, based on liquid microparticles made of lipiodol functionalized with custom-designed fluorescent lipids. These lipids are targeted toward lectins or biotin membrane receptors, and the resulting particles can be specifically identified and internalized by cells, as demonstrated by their phagocytosis in primary murine bone marrow-derived macrophages. We also evidence the possibility to sense the binding of a multivalent lectin, concanavalin A, in solution by monitoring the energy transfer between two matching fluorescent lipids on the surface of the particles. We anticipate that these liquid particle-based sensors, which are able to report via Förster resonance energy transfer (FRET) on the movement of ligands on their interface upon protein binding, will provide a useful tool to study receptor binding and cooperation during adhesion processes such as phagocytosis.

Accurate Liquid Level Measurement with Minimal Error: A Chaotic Observer Approach

This paper delves into precisely measuring liquid levels using a specific methodology with diverse real-world applications such as process optimization, quality control, fault detection and diagnosis, etc. It demonstrates the process of liquid level measurement by employing a chaotic observer, which senses multiple variables within a system. A three-dimensional computational fluid dynamics (CFD) model is meticulously created using ANSYS to explore the laminar flow characteristics of liquids comprehensively. The methodology integrates the system identification technique to formulate a third-order state–space model that characterizes the system. Based on this mathematical model, we develop estimators inspired by Lorenz and Rossler’s principles to gauge the liquid level under specified liquid temperature, density, inlet velocity, and sensor placement conditions. The estimated results are compared with those of an artificial neural network (ANN) model. These ANN models learn and adapt to the patterns and features in data and catch non-linear relationships between input and output variables. The accuracy and error minimization of the developed model are confirmed through a thorough validation process. Experimental setups are employed to ensure the reliability and precision of the estimation results, thereby underscoring the robustness of our liquid-level measurement methodology. In summary, this study helps to estimate unmeasured states using the available measurements, which is essential for understanding and controlling the behavior of a system. It helps improve the performance and robustness of control systems, enhance fault detection capabilities, and contribute to dynamic systems’ overall efficiency and reliability.

Liquid Metal Composites-Enabled Real-Time Hand Gesture Recognizer with Superior Recognition Speed and Accuracy.

Prosthetic hands play a vital role in restoring forearm functionality for patients who have suffered hand loss or deformity. The hand gesture intention recognition system serves as a critical component within the prosthetic hand system. However, accurately and swiftly identifying hand gesture intentions remains a challenge in existing approaches. Here, a real-time motion intention recognition system utilizing liquid metal composite sensor bracelets is proposed. The sensor bracelet detects pressure signals generated by forearm muscle movements to recognize hand gesture intent. Leveraging the remarkable pressure sensitivity of liquid metal composites and the efficient classifier based on the optimized recognition algorithm, this system achieves an average offline and real-time recognition accuracy of 98.2% and 92.04%, respectively, with an average recognition speed of 0.364 s. Thus, this wearable system shows advantages in superior recognition speed and accuracy. Furthermore, this system finds applications in master-slave control of prosthetic hands in unmanned scenarios, such as electrically powered operations, space exploration, and telemedicine. The proposed system promises significant advances in next-generation intent-controlled prosthetic hands and robots.

Geometric phase-encoded stimuli-responsive cholesteric liquid crystals for visualizing real-time remote monitoring: humidity sensing as a proof of concept

Liquid crystals are a vital component of modern photonics, and recent studies have demonstrated the exceptional sensing properties of stimuli-responsive cholesteric liquid crystals. However, existing cholesteric liquid crystal-based sensors often rely on the naked eye perceptibility of structural color or the measurement of wavelength changes by spectrometric tools, which limits their practical applications. Therefore, developing a platform that produces recognizable sensing signals is critical. In this study, we present a visual sensing platform based on geometric phase encoding of stimuli-responsive cholesteric liquid crystal polymers that generates real-time visual patterns, rather than frequency changes. To demonstrate this platform’s effectiveness, we used a humidity-responsive cholesteric liquid crystal polymer film encoded with a q-plate pattern, which revealed that humidity causes a shape change in the vortex beam reflected from the encoded cholesteric liquid crystal polymers. Moreover, we developed a prototype platform towards remote humidity monitoring benefiting from the high directionality and long-range transmission properties of laser beams carrying orbital angular momentum. Our approach provides a novel sensing platform for cholesteric liquid crystals-based sensors that offers promising practical applications. The ability to generate recognizable sensing signals through visual patterns offers a new level of practicality in the sensing field with stimuli-responsive cholesteric liquid crystals. This platform might have significant implications for a broad readership and will be of interest to researchers working in the field of photonics and sensing technology.

Liquid Metal and Carbon Nanofiber-Based Strain Sensor for Monitoring Gesture, Voice, and Physiological Signals

Liquid Metal and Carbon Nanofiber-Based Strain Sensor for Monitoring Gesture, Voice, and Physiological Signals

Electromagnetic guided waves in composite liquid crystal-based interfaces

We study an air–crown glass planar interface that includes a thin layer of a cholesteric liquid crystal doped with silver spheres of nanometer size. We propose a new theoretical model for the propagation of electromagnetic waves through the liquid crystal part and use the Marcuvitz–Schwinger form of the Maxwell equations to compute guided surface wave profiles. The results suggest the presence of anisotropic surface modes with negligible attenuation. The dependence of the surface wave parameters on the liquid crystal layer parameters can be used in liquid crystal-based sensors.

Real-time optical detection of mercury contamination in drinking water using an amphiphilic recognition probe at liquid crystal/aqueous interfaces.

Mercury contamination is a global environmental issue due to its toxicity and persistence in ecosystems. It poses a particular risk in aquatic systems, where it bioaccumulates and biomagnifies, leading to serious health impacts on humans. Therefore, effective detection technologies for mercuric ions in natural water resources are highly desirable. However, most existing detection methods are time-consuming, require complicated sample pre-treatment, and rely on expensive equipment, which hinders their widespread use in real-time detection. Here, we present a convenient, rapid, portable, user-friendly, and cost-effective sensing system for detecting Hg2+ ion contamination in water. This system utilizes a highly selective, amphiphilic, and structurally simple molecular probe, N-dodecylamine-di-thiocarbamate (DDC). DDC molecules align at the interface between the liquid crystal (LC) and water, inducing a homeotropic LC orientation. In water samples contaminated with Hg2+, a bright optical texture is observed, indicating the alignment of the 5CB LC in a planar manner at the LC/aqueous boundary. The minimum detectable concentration (LOD) for Hg2+ ions is 5.0 μM in distilled water, with a broad detection range from 5.0 μM to 2 mM. The sensor selectively detects Hg2+ ions over other common interfering metal ions, including Pb2+, Co2+, Ni2+, Cu2+, Cd2+, Zn2+, Cr2+, Mg2+, Na+, K+, and Ca2+. Boolean logic gates, bar graphs, and truth tables are employed to explain the selectivity of this liquid crystal-based sensor. This work demonstrates the significant potential of the sensor for monitoring mercuric ions in natural water resources, offering a promising strategy for controlling mercury pollution.

An Ultrawide Range, Highly Stretchable Liquid Metal Force and Strain Sensor Based on Spiral Multilayer Microfluidic Fibers

Presently, a variety of soft sensing technologies are available, but there is still an opportunity to research on flexible sensors that can withstand high loads. Here, we report a highly stretchable, wide measuring range, and easy-to-fabricate liquid metal sensor capable of detecting force and strain modes. The key enabling design feature of the proposed sensor is the spiral winding combination of two different types of stretchable liquid metal microfluidic fibers. Pressing or elongating the fibers changes the geometry and, thus, the electrical resistance in a predictable way. The proposed sensor can offer a simple mechanism to measure force up to about 400N and strain up to about 200% under limited laboratory conditions. The sensor signal is repeatable in both cases. The ability of our sensor in wide measuring range in actual application is verified via detecting the loads of one human body and driving car wheel. We further show a proof of concept of the soft sensor by a soft robotic actuator, enabling the identification of bending angles and object surface features.

A self-powered droplet sensor based on a triboelectric nanogenerator toward the concentration of green tea polyphenols.

Self-powered liquid droplet sensors based on triboelectric nanogenerators have attracted extensive attention in the field of biochemical sensing applications. Numerous research studies have investigated the effects of factors such as molecular species, molecular concentration, molecular charge, and molecular dipole moment in solution on the output electrical signals of the sensor. In this study, we prepared a self-powered droplet sensor using conductive copper film tape, polytetrafluoroethylene, and conductive aluminum foil tape. The sensor can continuously output pulsed electrical signals with minimal environmental impact. In comparison with other types of sensors, this sensor boasts a rapid response time of 10 ms and excellent sensitivity. The relationship between the friction-induced output current and voltage of the droplets and the concentration of green tea polyphenols (GTPs) was studied using the self-powered liquid droplet sensor with five different green tea samples. It was found that GTPs were the main factor contributing to the changes in output electrical signals in green tea water droplets. Fluorescence spectroscopy was used to reveal that the magnitude of the output current was inversely proportional to the concentration of GTPs in green tea. These results demonstrate the potential application of self-powered liquid droplet sensors in biochemical sensing applications based on concentration-dependent output signals.