Advanced Sensor Research最新文献

This study introduces a novel fluorescent light-up electrospun membrane, integrating PbBr₂, which serves as an exceptionally selective probe for the detection of cesium ions (Cs⁺). Leveraging the superior optical properties of CsPbBr₃ perovskite nanocrystals (PNCs), the researchers employ electrospinning technology to fabricate a test strip, namely PbBr₂@polyacrylonitrile (PbBr₂@PAN) nanofiber membranes, capable of swiftly detecting Cs⁺ in water merely by observing changes in the nanocrystals' luminescence with the naked eye. By the introduction of NH₄⁺-modified montmorillonite (NH₄⁺-MMT), PbBr₂-MT@PAN nanofiber membranes is obtained. The selectivity and sensitivity to Cs⁺ can be further improved because NH₄⁺-MMT endows PbBr₂-MT@PAN nanofiber membranes with the hydrophilic property and selective adsorption toward Cs⁺ ions. The membrane's fabrication is simple, scalable, and cost-effective, with high cesium selectivity and sensitivity down to 44 ppb. This innovation enables efficient, on-site cesium monitoring critical for environmental safety and nuclear waste management.

In medical diagnosis, detecting disease biomarkers at ultra-low concentrations is vital. Point-of-care (POC) diagnostics require rapid detection, live monitoring, high sensitivity, low detection threshold, and cost-effectiveness. Carbon-based nanomaterials (CBNs) are promising due to their large surface-to-volume ratio, conductivity, biocompatibility, and stability, making them ideal for biosensors. Recent advancements in CBN applications, including biosensing, drug delivery, and cancer therapy, highlight their potential in enhancing detection sensitivity and specificity. Electrochemical sensors and biosensor platforms using carbon nanocomposites are pivotal in diagnostics. This review explores the current state and future challenges of CBN integration in POC settings, envisioning a transformative impact on healthcare diagnostics and therapeutics.

A novel approach is demonstrated to identify glucose concentration in aqueous solutions based on the combined effect of its frequency-dependent interaction with microwaves propagating in graphene channels and the modification of graphene radio frequency (RF) conductivity caused by physisorbed molecules. This approach combines broadband microwave sensing and chemical field effect transistor sensing in a single device, leading to information-rich, multidimensional datasets in the form of scattering parameters. A sensitivity of 7.30 dB(mg/L)⁻¹ is achieved, significantly higher than metallic state-of-the-art RF sensors. Different machine learning methods are applied to the raw, multidimensional datasets to infer concentrations of the analyte, without the need for parasitic effect removals via de-embedding or circuit modeling, and a classification accuracy of 100% is achieved for aqueous glucose solutions with a concentration variation of 0.09 mgL⁻¹.

Wearable electronics revolutionize human–machine interfaces (HMIs) for robotic or prosthetic control. Yet, the challenge lies in eliminating conventional rigid and impermeable electronic components, such as batteries, while considering the comfort and usability of HMIs over prolonged periods. Herein, a self-powered, flexible, and breathable HMI is developed based on piezoelectric sensors. This interface is designed to accurately monitor subtle changes in body and muscle movements, facilitating effective communication and control of robotic prosthetic hands for various applications. Utilizing engineered porous structures within the polymeric material, the piezoelectric sensor demonstrates a significantly enhanced sensitivity, flexibility, and permeability, highlighting its outstanding HMI applications. Furthermore, the developed control algorithm enables a single sensor to comprehensively control robotic hands. By successfully translating piezoelectric signals generated from bicep muscle movements into Morse Code, this HMI serves as an efficient communication device. Additionally, the process is demonstrated by illustrating the execution of the daily task of “drinking a cup of water” using the developed HMI to enable the control of a human-interactive robotic prosthetic hand through the detection of bicep muscle movements. Such HMIs pave the way toward self-powered and comfortable biomimetic systems, making a significant contribution to the future evolution of prosthetics.

Surface acoustic waves (SAWs) have shown great potential for developing sensors for structural health monitoring (SHM) and lab-on-a-chip (LOC) applications. Existing SAW sensors mainly rely on measuring the frequency shifts of high-frequency (e.g., >0.1 GHz) resonance peaks. This study presents frequency-locked wireless multifunctional SAW sensors that enable multiple wireless sensing functions, including strain sensing, temperature measurement, water presence detection, and vibration sensing. These sensors leverage SAW resonators on piezoelectric chips, inductive coupling-based wireless power transmission, and, particularly, a frequency-locked wireless sensing mechanism that works at low frequencies (e.g., <0.1 GHz). This mechanism locks the input frequency on the slope of a sensor's reflection spectrum and monitors the reflection signal's amplitude change induced by the changes of sensing parameters. The proof-of-concept experiments show that these wireless sensors can operate in a low-power active mode for on-demand wireless strain measurement, temperature sensing, and water presence detection. Moreover, these sensors can operate in a power-free passive mode for vibration sensing, with results that agree well with laser vibrometer measurements. It is anticipated that the designs and mechanisms of the frequency-locked wireless SAW sensors will inspire researchers to develop future wireless multifunctional sensors for SHM and LOC applications.

Integrated Microwave Photonic Sensors

Sensors stand as pivotal cornerstones of technologies. In article 2300145, Xiaoke Yi and co-workers demonstrate integrated microwave photonic sensors using microresonators for ultra-sensitive, high-resolution, and rapid detection. These compact sensors, enhanced through integration techniques and artificial intelligence, offer great potential across various applications, representing a significant advancement in modern sensing technologies.

Deformation-Insensitivity

Flexible sensor array using kirigami structural and soft-hinge design enables deformation-insensitive pressure detection. The sensitivity of sensor is enhanced by the modification with micropillars on conductive rubber. Characterization tests verify the almost negligible effects to sensor caused by 40% stretching and 180° bending interferences. The proposed sensor array is capable of functioning on the deformable surfaces with stable detection signals. More details can be found in article 2400012 by Yancheng Wang and co-workers.

The heart produces bioelectrical signals, which can be measured as an electrocardiogram (ECG) for the detection of rhythm disturbances. Rapid and precise detection of these arrhythmias is crucial for their termination by closed-looped therapeutic interventions to counteract detrimental effects. However, there is a current lack of such systems tailored for experimental cardiovascular applications. This hampers not only in-depth mechanistic studies but also translational testing of new therapeutic strategies, especially in an untethered manner in awake animal models. To break new ground, recent advances to develop a non-invasive AI-supported heart rhythm monitoring system for untethered automated arrhythmia detection in a continuous manner is combined. This system is housed in a lightweight jacket for mobile use and includes an on-skin ECG sensor, a low-power microprocessor unit, a massive data storage unit, and a power-management system. By implementing a novel hybrid algorithm based on so-called heart rate (R-R) variability and a case-specific AI model, 100% sensitivity and 95% specificity is achieved in detecting atrial arrhythmias within 2 s upon initiation in adult rats. Thereby, the novel system sets the stage for advanced mechanistic studies and therapeutic testing, including closed-loop applications aiming for the termination of a broad range of atrial arrhythmias.