Mechanical Sensors Research Articles

A Soft, Adhesive Self-Healing Naked-Eye Strain/Stress Visualization Patch.

Learning about the strain/stress distribution in a material is essential to achieve its mechanical stability and proper functionality. Conventional techniques such as universal testing machines only apply to static samples with standardized geometry in laboratory environment. Soft mechanical sensors based on stretchable conductors, carbon-filled composites, or conductive gels possess better adaptability, but still face challenges from complicated fabrication process, dependence on extra readout device, and limited strain/stress mapping ability. Inspired by the camouflage mechanism of cuttlefish and chameleons, here an innovative responsive hydrogel containing light-scattering "mechano-iridophores" is developed. Force induced reversible phase separation manipulates the dynamic generation of mechano-iridophores, serving as optical indicators of local deformation. Patch-shaped mechanical sensors made from the responsive hydrogel feature fast response time (<0.4 s), high spatial resolution (≈100µm), and wide dynamic ranges (e.g., 10-150% strain). The intrinsic adhesiveness and self-healing material capability of sensing patches also ensure their excellent applicability and robustness. This combination of chemical and optical properties allows strain/stress distributions in target samples to be directly identified by naked eyes or smartphone apps, which is not yet achieved. The great advantages above are ideal for developing the next-generation mechanical sensors toward material studies, damage diagnosis, risk prediction, and smart devices.

Micromachined Mechanical Resonant Sensors: From Materials, Structural Designs to Applications

AbstractDriving a micro and nanomechanical structure to resonance and observing its resonant motion in the physical world have led to numerous fundamental discoveries in physics, sciences, chemistry, biology, and engineering, as well as device commercialization. Scaling down mechanical structures from micrometric to nanometric size has enabled the utilization of resonant motions to probe material properties and various dynamical phenomena in quantum coherence and squeezing. Recent advances in material sciences and nanofabrication resulted in successful demonstration of ultra‐high frequency operation (GHz range) and ultra‐high quality factor (10 billion) micromachined mechanical resonators (MMRs). The resonant motion of these structures has been utilized as an indispensable tool to weigh biological and chemical species at resolution of atomic mass unit, sense a force as small as zepto‐newton, and to detect numerous other physical parameters. Here, a systematic view on the resonant sensing transduction is provided, underlying physics, and sensing structures realized with micro/nano‐electromechanical systems (MEMS/NEMS) technologies. It is also describe the roles of nanomaterials and structures, nano‐fabrication and rational designs on the resonance frequency and quality factor of MMRs toward high‐performance sensing. This paper discusses the most recent advances in the development of MMRs for material characterization as well as biological, chemical, and physical sensing. Finally, the paper discusses the challenges and perspectives on design, fabrication, and developments of resonant sensors with high quality factor toward quantum sensing, and ultra‐high sensitivity and resolution for classical sensing applications.

Highly Compressible 3D-Printed Soft Magnetoelastic Sensors for Human-Machine Interfaces.

Incorporating perception into robots or objects holds great potential to revolutionize daily human life. To achieve this, critical factors include the design of an integrable three-dimensional (3D) soft sensor with self-powering capability, a wide working range, and tuneable functionalities. Here, we introduce a highly compressible 3D-printed soft magnetoelastic sensor with a wide strain sensing range. Inspired by the lattice metamaterial, which offers a highly porous structure with tuneable mechanical properties, we realized a remarkably compliant 3D self-powering sensor. Using magnetoelastic composite materials and 3D printing combined with sacrificial molding, a broad design space for constituent materials and structures is investigated, allowing for tuneable mechanical properties and sensor performances. These sensors are successfully integrated with two robotic systems as the robot operation and perception units, enabling robot control and recognition of diverse physical interactions with a user. Overall, we believe that this work represents a cornerstone for compliant 3D self-powered soft sensors, giving impetus to the development of advanced human-machine interfaces.

Recent Advances in Nanowire-Based Wearable Physical Sensors.

Wearable electronics is a technology that closely integrates electronic devices with the human body or clothing, which can realize human-computer interaction, health monitoring, smart medical, and other functions. Wearable physical sensors are an important part of wearable electronics. They can sense various physical signals from the human body or the surrounding environment and convert them into electrical signals for processing and analysis. Nanowires (NW) have unique properties such as a high surface-to-volume ratio, high flexibility, high carrier mobility, a tunable bandgap, a large piezoresistive coefficient, and a strong light-matter interaction. They are one of the ideal candidates for the fabrication of wearable physical sensors with high sensitivity, fast response, and low power consumption. In this review, we summarize recent advances in various types of NW-based wearable physical sensors, specifically including mechanical, photoelectric, temperature, and multifunctional sensors. The discussion revolves around the structural design, sensing mechanisms, manufacture, and practical applications of these sensors, highlighting the positive role that NWs play in the sensing process. Finally, we present the conclusions with perspectives on current challenges and future opportunities in this field.

Spatial hetero-structured composites with ultrawide linear range for positive-negative pressure sensing and e-skin of bionic fish

For impelling practical applications of flexible sensors or electronic skins, it is challenging and urgent to fabricate multifunctional flexible mechanical sensors with good linearity over a wide working range in an economical and scalable manner. Currently, it is immensely difficult to simultaneously detect tension, pressure and bending with high linearity over a wide strain range by using one film without sensor integration. Herein, we present a porous flexible mechanical sensor with a spatial electron transport network consisting of ethylene-α-octene random copolymer (ORC) elastic skeleton with surface embedded carbon black (CB) and carbon fiber (CF) bridges. Such an interesting spatial hetero-structure can shunt the electron transport effectively to regulate the resistance change of the sensor during strain loading, resulting in linear electrical signal response to mechanical deformation for a tensile strain up to 320% and a pressure up to 1.3 MPa, as well as a bending angle ranging from− 90 o to 90 o, respectively. Besides, it shows the detection capability of ambient pressure ranging from −0.09 MPa to 0.4 MPa continuously. Such a multifunctional film sensor with ultrawide linear working range demonstrates potential applications for monitoring body motions of athletics and underwater soft robots.

High-Strength Amorphous Silicon Carbide for Nanomechanics.

For decades, mechanical resonators with high sensitivity have been realized using thin-film materials under high tensile loads. Although there are remarkable strides in achieving low-dissipation mechanical sensors by utilizing high tensile stress, the performance of even the best strategy is limited by the tensile fracture strength of the resonator materials. In this study, a wafer-scale amorphous thin film is uncovered, which has the highest ultimate tensile strength ever measured for a nanostructured amorphous material. This silicon carbide (SiC) material exhibits an ultimate tensile strength of over 10 GPa, reaching the regime reserved for strong crystalline materials and approaching levels experimentally shown in graphene nanoribbons. Amorphous SiC strings with high aspect ratios are fabricated, with mechanical modes exceeding quality factors 108 at room temperature, the highest value achieves among SiC resonators. These performances are demonstrated faithfully after characterizing the mechanical properties of the thin film using the resonance behaviors of free-standing resonators. This robust thin-film material has significant potential for applications in nanomechanical sensors, solar cells, biological applications, space exploration, and other areas requiring strength and stability in dynamic environments. The findings of this study open up new possibilities for the use of amorphous thin-film materials in high-performanceapplications.

Single CFOA-based active Negative Group Delay circuits for signal anticipation

The group delay of a signal prior to data monitoring is a crucial consideration in today’s real-time applications, especially for those that involve long sensor arrays or high-order filters. In this article, nine new second-order Negative Group Delay (NGD) circuits based on Current Feedback Operation Amplifier (CFOA) are proposed, and their transfer functions are demonstrated. These circuits have a wide range of applications, from audio to mechanical signals and sensor signal anticipation. An example design procedure is provided for one of the introduced circuits. A time-domain analysis is performed using both a single-tone sinusoidal and a band-limited audio recording in the frequency range of 1 Hz to 500 Hz. The article assesses the change in the signal using Root Mean Square Error (RMSE) and cross-correlation. Furthermore, the relationship between the NGD value and the operation range of the circuit is investigated and verified experimentally. The results show that an NGD value of approximately 100μs can be achieved with an amplitude error of 0.86% for a single-tone input and 1.54% for an audio recording, and an operation range of about 650 Hz.

A Hardware Vehicle Security and Accident Notification System using the Haar Cascade Algorithm

Low-cost vehicle security and accident notification system is essential in this modern society as vehicle theft and accidents that occur are increasing daily. In this proposed system, hardware for vehicle security is implemented, with authentication, and accident notification. Authentication is achieved by face detection and recognition using an open CV. The defaulter information is forwarded to the authenticated mobile number of the person by whom the vehicle is owned, using the GSM module and a notification email. The face authentication module was developed using the discrete wavelet transform-based Haar cascade algorithm. In addition to the face authentication, accident notifications will be sent to family members of the vehicle owner. Micro electrical mechanical system sensor was utilized to detect accident incidents using the accelerometer concept.

Unraveling the Role of PIEZO1 in Stressed Erythropoiesis: Implications for Dyserythropoiesis and Potential Therapeutic Targets in Dehydrated Hereditary Stomatocytosis

PIEZO1 is a mechanosensitive cation channel that plays a crucial role in various physiological processes as a mechanical force sensor. In erythrocytes, it is responsible for regulating cellular volume and hydration. Gain-of-function (GoF) mutations in PIEZO1 lead to dehydrated hereditary stomatocytosis (DHS) by slowing down the channel's inactivation kinetics. DHS patients often exhibit a range of clinical presentations, including mild to severe hemolytic anemia, and iron overload. In addition, studies on erythroid progenitor cells from DHS patients have indicated a mutation-dependent delay in erythroid differentiation. Furthermore, studies on constitutive GoF Piezo1 mice have revealed stressed erythropoiesis characterized by increased erythrocyte turnover. The primary aim of this study is to investigate the role of PIEZO1 during stressed erythropoiesis in DHS and identify potential druggable targets. A total of 80 DHS patients were analysed, and their BMRI (reticulocyte count × patient's Hb/normal Hb), EPO, and ERFE levels were measured. The findings revealed mutation-dependent dyserythropoietic features similar to those observed in CDAII patients (characterized by dyserythropoiesis). The engineered erythroid model of DHS, Hudep2-PIEZO1-KI (Hudep2-KI), was subjected to erythroid differentiation for 12 days and compared to Hudep2-WT. A notable reduction in CD235a expression was detected on the last day of differentiation, indicating that PIEZO1-mediated alteration occurs during the late stages of differentiation. Morphological analysis of differentiating cells indicated that KI cells experienced a significant reduction in proliferation rate (1.5-fold increase vs. day 0) compared to Hudep2-WT (3.1-fold increase vs. day 0) starting from day 7. By day 12 of differentiation, KI cells displayed only half the cell count of WT cells, with a substantial decrease in the percentage of orthochromatic normoblasts (13.7% vs. WT 54.5%). This was accompanied by a relative increase in reticulocytes (Hudep2-WT: 45.5% vs. Hudep2-KI: 86.3%). To identify the altered signalling pathways involved in differentiation deregulation, RNAseq was performed at various time points during differentiation. The gene ontology analysis indicated that the most enriched biological processes were related to apoptosis, cellular response to hypoxia, and glycolysis. During the differentiation process, various apoptosis-related processes were found significantly enriched on different days. Upon conducting a single gene analysis, an imbalance between pro-apoptotic and antiapoptotic signals became evident. Specifically, in Hudep2-KI cells compared to the WT, we observed that 70.8% of proapoptotic genes were upregulated. Conversely, the regulation of apoptosis did not seem to impact antiapoptotic signals, with 57.9% of them being upregulated and 42.1% downregulated. This observation led us to suggest that PIEZO1 GoF induces apoptosis by activating pro-apoptotic signals. The findings of this study demonstrate the role of PIEZO1 GOF mutation in stressed erythropoiesis in both DHS patients and the erythroid cellular system. PIEZO1 GOF variants, through their effect on intracellular calcium concentration, influence late-stage differentiation and disrupt several critical pathways, including apoptosis, response to hypoxia, and glycolysis. Ongoing research involves confirming the data in CD34+ cells from DHS patients and PIEZO1 GOF mice. Additionally, the identified deregulated markers hold promise as potential druggable targets for dyserythropoiesis treatment.

Linear Strain Sensors via a Spatial Heteromodulus Tricontinuous Structure Design for High-Resolution Recording of Snoring Breath.

Porous conductive elastomer composites are very attractive for designing flexible and air-permeable mechanical sensors for healthcare, while it is challenging to achieve a linear and sensitive electromechanical response over a wide strain range for high-resolution recording of physiological activities and body motions. Here, a scalable strategy is developed to construct porous elastomer composites with a bamboo-shaped heteromodulus microstructure in the pores for the fabrication of linear stretchable strain sensors. Such a spatial heteromodulus microstructure is fabricated via phase separation and selective location of high-modulus phase during melt compounding of elastomers and thermoplastics, together with green etching of the water-soluble plastic in the tricontinuous elastomer composites. The bamboo-shaped heteromodulus microstructure is constructed on the pore struts via the fracture of a high-modulus polymer self-assembled on the pore surface and relaxation recovery of the elastomer matrix after prestretching, which blocks the propagation of cut-through microcracks upon stretching. The composites with super low resistance after in situ growth of silver nanoparticles sustain up to 110% tensile strain with a linear and sensitive electromechanical response, demonstrating potential applications in discriminating respiration status and monitoring snoring breath. This work unveils a new approach to fabricate high-performance air-permeable strain sensors in a simple and scalable way.

Sensorless HSPMSM Control of an Improved SMC and EKF Based on Immune PSO

Here, for controlling a high-speed flywheel permanent magnet synchronous motor (HSPMSM), a position sensorless control method for estimation of motor rotor position and speed is proposed to address the problems faced by mechanical position sensors of high cost, large size, and poor interference immunity. The extended Kalman filter (EKF) has difficulty obtaining the optimal covariance matrix when performing state estimation. Therefore, the particle swarm algorithm (PSO) with an immune mechanism is used to optimize the covariance matrix of the EKF. However, the EKF algorithm makes the system less robust due to its delay effect. Based on the traditional sliding mode control rate, the exponential convergence law is improved, and the continuous function sat(s) is used instead of the symbolic function sgn(s). This improves the convergence law and proves the asymptotic stability of the designed sliding mode variable structure controller based on Lyapunov’s stability theorem. Then, the novel control law is applied to the sliding mode surface (SMS). An ordinary sliding mode controller (OSMC) using a linear sliding mode controller (LSMC), a global sliding mode controller (GSMC) using a global sliding mode surface (GSMS), and an integral sliding mode controller (ISMC) using an integral sliding mode surface (ISMS) are designed for improving control. Joint simulation in MATLAB and Simulink verifies that the optimized EKF based on the immune PSO can improve precision and accuracy for controlling the electronic rotor position and speed. Comparing the new sliding mode controller with a traditional PI controller reveals that the proposed system has stronger resistance to load disturbance and better robustness.

Effect of taper ratio on 2-D mechanical wind sensors

In this paper, the effect of sensing-structure taper ratio on two-dimensional (2-D) mechanical wind sensors is demonstrated for the first time. The mechanical wind sensor consists of a sensing structure vertically arranged in the center of a cross cantilever. It detects the wind speed and direction by measuring the airflow-induced cantilever deformation with eight strain gauges attached to the beam surface. Five forms of sensing structures with different taper ratios are designed and manufactured to investigate their effects on the performance of 2-D mechanical wind sensors. A series of experiments are conducted and the results reveal that the taper ratio of the sensing structure can affect the measurement range and the sensitivity of the 2-D mechanical wind sensor. A lower taper ratio results in a higher critical wind speed, which makes the mechanical wind sensor a wider measurement range. Moreover, the results also show that a wider measurement range usually means a lower sensitivity for a single device, and hence the measurement range and the sensitivity of the mechanical wind sensor are a contradiction. The effect rule of the taper ratio presented in this paper can provide a valuable reference for the design and manufacture of 2-D mechanical wind sensors.

Passive Electrical Components Based on Cotton Fabric Decorated with Iron Oxides Microfibers: The Influence of Static and Pulsed Magnetic Fields on the Equivalent Electrical Properties.

In this work, environmentally friendly and low-cost passive electrical components (PECs) are manufactured based on composites consisting of cotton fabrics soaked with solutions of silicone oil and different amounts of iron oxides microfibers (μFe). The μFe consists of a mixture of three phases: hematite (α-Fe2O3), maghemite (γ-Fe2O3), and magnetite (Fe3O4). The equivalent electrical capacitance (Cp) and resistance (Rp) of PECs are measured as a function of magnetic flux density B in a static and pulsed magnetic field superimposed on an alternating electric field of frequency 1 kHz. The relative variation in the hysteresis curves for both Cp and Rp are obtained by measuring them in the ascending and then the descending mode of B. We show that all these three quantities are sensibly influenced by the volume fractions of μFe and by the values of B. The main influence on this behavior is attributed to the semiconductor properties of the α-Fe2O3 and γ-Fe2O3 components of the oxide microfibers. In addition, it is found that at B≃ 175 mT, the maximum relative variance of the hysteresis curve is about 3.35% for Cp and 3.18 % for Rp. When a pulsed magnetic field is used, it is shown that Cp and Rp closely follow the variation in the magnetic field. Thus, the resulting electrical properties of PECs, together with the fast response to the application of pulsed magnetic fields, make them useful in the fabrication of various devices, such as electric, magnetic, and deformation fields, or mechanical stress sensors with applications in protection against electromagnetic smog, healthcare monitoring, or for human-machine interfacing.

Multi-scale time series analysis using TT-ConvLSTM technique for bearing remaining useful life prediction

This study advocates the utilization of a parallel neural network (PNN) architecture for the estimation of remaining useful life (RUL) of rolling element bearings. Conventional machine learning methods have often fallen short in processing machinery sensor data efficiently and accurately, given its vast nature and the temporal dynamics of component health conditions. To address this limitation, a robust PNN architecture is proposed which incorporates multiple parallel processing pathways. These pathways are equipped with diverse input neurons, capturing data from mechanical component condition sensors. The output neuron then efficiently predicts the RUL, capturing the degradation stages throughout the component's lifespan. The PNN structure provides better accuracy and computation time by efficiently handling huge amounts of data simultaneously and integrating both spatial and temporal information present. Additionally, time-transformer and recurrent neural networks (RNNs) are used to handle complex time series data. Improvement methodologies, such as positional encoding combined with a multi-headed self-attention mechanism and the convolutional long short-term memory (ConvLSTM) neural network, are employed. These methodologies adeptly handle spatiotemporal dependencies inherent in multidimensional features extracted across the time domain, frequency domain, and time–frequency domain, thereby considerably boosting the model's efficacy. Two case studies are conducted on XJTU-SY rolling element bearing dataset and FEMTO bearing dataset to validate and display the generalization capabilities of the proposed methodology, where PNN performed exceptionally in terms of accuracy and efficiency. It is concluded that with a novel implementation of variational stride temporal window strategy and utilizing the full capabilities of a PNN, the RUL of bearings can be predicted very accurately. The algorithm strategy is very robust and can be applied to other machine components as well. Subsequently, the code for the algorithm will be open-sourced.

SENSING MECHANISM AND APPLICATION OF MECHANICAL STRAIN SENSOR: A MINI-REVIEW

This study reviews the potential of flexible strain sensors based on nanomaterials such as carbon nanotubes (CNTs), graphene, and metal nanowires (NWs). These nanomaterials have excellent flexibility, conductivity, and mechanical properties, which enable them to be integrated into clothing or attached to the skin for the real-time monitoring of various activities. However, the main challenge is balancing high stretchability and sensitivity. This paper explains the basic concept of strain sensors that can convert mechanical deformation into electrical signals. Moreover, this paper focuses on simple, flexible, and stretchable resistive and capacitive sensors. It also discusses the important factors in choosing materials and fabrication methods, emphasizing the crucial role of suitable polymers in high-performance strain sensing. This study reviews the fabrication processes, mechanisms, performance, and applications of stretchable strain sensors in detail. It analyzes key aspects, such as sensitivity, stretchability, linearity, response time, and durability. This review provides useful insights into the current status and prospects of stretchable strain sensors in wearable technology and human–machine interfaces.

Nanomaterials‐Based Bioinspired Next Generation Wearable Sensors: A State‐of‐the‐Art Review

AbstractWith a constantly growing percentage of the population having access to high‐quality healthcare facilities, preventable pathogenic illnesses have been nearly eradicated in the developed parts of the world, which has led to a significant rise in the average human life expectancy over the last few decades. In such a highly developed world, age‐related illnesses will lead to an immense burden on healthcare providers. Remote health monitoring enabled by wearable sensors will play a significant role in the growth and evolution of Health 3.0 by providing intimate and valuable information to healthcare providers regarding the progression of disease in patients with critical life‐altering conditions. Especially, in the case of people suffering from neurodegenerative disorders, inexpensive and user‐friendly wearable sensors can enable physiotherapists monitor real‐time physiological parameters to design patient‐specific treatment plans. This review provides a comprehensive overview of the recent advances and emerging trends at the convergence of biomimicry and nanomaterial sensors, with a specific focus on wearable skin‐inspired mechanical sensors for applications in IoT‐enabled human physiological parameters monitoring. Skin‐inspired wearable mechanical sensors with relevance to the most common types of sensing mechanisms including piezoresistive, piezocapacitive, and triboelectric sensing are discussed along with their current challenges and possible future opportunities.

Cellulose-Based Conductive Materials for Energy and Sensing Applications.

Cellulose-based conductive materials (CCMs) have emerged as a promising class of materials with various applications in energy and sensing. This review provides a comprehensive overview of the synthesis methods and properties of CCMs and their applications in batteries, supercapacitors, chemical sensors, biosensors, and mechanical sensors. Derived from renewable resources, cellulose serves as a scaffold for integrating conductive additives such as carbon nanotubes (CNTs), graphene, metal particles, metal-organic frameworks (MOFs), carbides and nitrides of transition metals (MXene), and conductive polymers. This combination results in materials with excellent electrical conductivity while retaining the eco-friendliness and biocompatibility of cellulose. In the field of energy storage, CCMs show great potential for batteries and supercapacitors due to their high surface area, excellent mechanical strength, tunable chemistry, and high porosity. Their flexibility makes them ideal for wearable and flexible electronics, contributing to advances in portable energy storage and electronic integration into various substrates. In addition, CCMs play a key role in sensing applications. Their biocompatibility allows for the development of implantable biosensors and biodegradable environmental sensors to meet the growing demand for health and environmental monitoring. Looking to the future, this review emphasizes the need for scalable synthetic methods, improved mechanical and thermal properties, and exploration of novel cellulose sources and modifications. Continued innovation in CCMs promises to revolutionize sustainable energy storage and sensing technologies, providing environmentally friendly solutions to pressing global challenges.

Design and evaluation of a parallel mechanism for wearable lumbar support exoskeleton.

Work-related musculoskeletal disorders (WMSDs) are a serious problem, and manual material handling (MMH) tasks remain common in most industries. Thus, a lightweight and active exoskeleton is to be needed. A facile, convenient, multifunctional, wearable lumbar support exoskeleton (WLSE) was proposed to relieve the muscular tension and fatigue especially in the way of WMSDs. Based on the screw theory and virtual power principle, the parallel structure was used as the scheme choice for selecting suitable actuators and joints. The exoskeleton, which was characterized by high adaptability and complied with human motion, included branch unit, mechanism branch units, control units and sensors. Furthermore, using surface electromyography (sEMG) signal evaluation, an experiment which contains several tests were designed to evaluate whether WLSE had effect on supporting and reliving muscular fatigue while lifting-up different weight of objects under wearing without traction (T1) and wearing with traction (T2). Data collected were analyzed statistically by the two-way ANOVA. It showed that the RMS of sEMG was obviously reduced while carrying the heavy objects with WLSE under T2, and the MF values always performed the decreasing trend in T2/T1. This paper proposed a facile, convenient, multifunctional WLSE. From the results, it was concluded that the WLSE was significantly effective in reliving the muscle tension and muscle fatigue while lifting to prevent and treat WMSDs.

Mechanical responsive visible structural colors based on chiral-nematic cellulose nanocrystals photonic hydrogels

It has been extensively reported that cellulose nanocrystals (CNCs) are capable of exhibiting structural colors due to their unique chiral nematic self-assembly. However, further investigation is required to effectively utilize these remarkable properties for addressing real-world challenges, such as development of advanced materials like mechanical sensors and smart wearable devices. One particular challenge has been maintaining the refractive properties of structural colors resulting from the CNCs structure within the visible spectrum. In this study, we introduce a one-step hydrogel fabrication method involving chiral nematic CNC films embedded within poly(acrylic acid). These hydrogels exhibit naked-eye-visible structural colors and exhibit responsiveness to mechanical stresses. The resulting photonic hydrogels exhibit a blue shift in response to mechanical stretching. The hydrogels demonstrated self-recovery capabilities, as observed through cyclic loading–unloading stress tests. The color of the materials was characterized using UV–Vis spectroscopy to determine the wavelength of the reflected light. Additionally, we investigated the mechanism of CNCs orientation change using 2D-X-ray diffraction. Demonstrated by our simulation study, the morphology of the CNC bundles significantly influenced the characteristics of the chiral nematic structure as they orient due to the force application. Notably, the color change of the photonic hydrogels was reversible within the optimal range of applied force and can be repeated numerous times. This work presents a new strategy for fabricating optically functional photonic hydrogels with stimuli-responsive properties, enabling their potential applications in biomedical engineering and wearable responsive sensor technologies.

Mechanically Induced Anisotropic Fragments in Sn-Doped In2O3 Nanoparticle Films for Flexible Strain Sensing Based on Surface Plasmons.

Recently, mechanical strain sensors have been extensively developed to quantify large mechanical deformations for stretchable and wearable applications. In this study, we propose a plasmonic strain sensor based on the mechanical control of optical properties using an assembled film comprising In2O3: Sn nanoparticles (ITO NP film). The resonant reflectance in the infrared range could effectively be tuned by applying strain to the ITO NP film deposited on an elastomeric polydimethylsiloxane (PDMS) sheet. The change in reflectance was caused by the mechanical deformation of the PDMS sheet. The operating mechanism of the proposed plasmonic strain sensor was related to anisotropic fragments induced by cracks formed perpendicular to the direction of the applied strain. These anisotropic fragments were functionalized as optical modulators to change the reflectance depending on the applied strain. The sensing performance of the proposed plasmonic strain sensor was evaluated by using a PDMS sheet with a circular hole that produced nonuniform stress distributions. Finally, to evaluate the flexible and wearable performance of the proposed sensor, the optical detection of human motion was performed by detecting joint-related movements. The optical detection of human motion could be achieved because a change in motion (e.g., bending and stretching of the index finger) was reversibly associated with reflectance changes. Therefore, this study provides new insights into plasmon-based strain sensing for various applications in flexible instruments and human motion detection.