Multi-Level Pyramidal Microstructure-Based Pressure Sensors with High Sensitivity and Wide Linear Range for Healthcare Monitoring

Multilayer Step-like Microstructured Flexible Pressure Sensing System Integrated with Patterned Electrochromic Display for Visual Detection

Flexible pressure sensors have garnered significant attention for their potential in flexible electronics and interactive devices. However, such sensing devices typically rely on external bulky equipment for data visualization, which prevents flexible electronics from becoming smaller and more portable. Herein, we report a flexible pressure sensing system that combines a pressure sensor with a patterned electrochromic display. The pressure sensing layer has convex parallel line microarray structures, which are constructed by direct ink writing (DIW) printing technology. The multilayer microstructure in every microarray unit endows our sensors with a high sensitivity of 20.25 kPa-1, a wide linear response range up to 35 kPa, as well as excellent durability (∼5000 cycles). The electrochromic display is designed as a common cathode structure patterned via DIW printing, which exhibits fast coloring time (<0.4 s) and long-term durability (>6000 s). This work successfully demonstrates pressure visualization in human finger bending recognition and weight measurement. Moreover, this system will enhance the visualizable pressure identification capabilities of robotic hands and prosthetics, thereby offering users a more intuitive and real-time interactive experience.

ZnO Nanostructure-Based Flexible Pressure Sensors Deposited on Filter Paper for Wearable Application

Flexible pressure sensors have broad prospects in smart wearables, healthcare, and human-computer interaction. Nevertheless, flexible pressure sensors still face numerous thorny challenges. It has become a crucial problem to skillfully design and successfully achieve flexible pressure sensors with both a high sensing range and ultrahigh sensitivity. The sensor is designed and realized with inspiration drawn from the layered microstructure of human skin, and hierarchical structure flexible pressure sensors are fabricated, where PDMS microstructures/MWCNTs act as the top electrode, filter paper/ZnO nanostructures/MWCNTs act as the intermediate active layer, and an Ag interdigitated electrode acts as the bottom electrode. The sensing performance of the sensor is investigated to develop the application of pressure sensors for human health detection in daily life, and a pressure sensor array is prepared to investigate the detection of spatial pressure distribution. Sensors based on paper and PDMS can achieve low-pressure detection (30 Pa), high sensitivity (261.38 kPa-1), fast response time (∼73.8 ms), and excellent cyclic stability (10 000 cycles). Finally, the sensor demonstrates its functionality by lighting up a small lamp, which confirms that the as-prepared pressure sensor has excellent application scenarios and is beneficial for the development of flexible electronic devices.

Flexible iontronic sensing

The emerging flexible iontronic sensing (FITS) technology has introduced a novel modality for tactile perception, mimicking the topological structure of human skin while providing a viable strategy for seamless integration with biological systems. With research progress, FITS has evolved from focusing on performance optimization and structural enhancement to a new phase of integration and intelligence, positioning it as a promising candidate for next-generation wearable devices. Therefore, a review from the perspective of technological development trends is essential to fully understand the current state and future potential of FITS devices. In this review, we examine the latest advancements in FITS. We begin by examining the sensing mechanisms of FITS, summarizing research progress in material selection, structural design, and the fabrication of active and electrode layers, while also analysing the challenges and bottlenecks faced by different segments in this field. Next, integrated systems based on FITS devices are reviewed, highlighting their applications in human-machine interaction, healthcare, and environmental monitoring. Additionally, the integration of artificial intelligence into FITS is explored, focusing on optimizing front-end device design and improving the processing and utilization of back-end data. Finally, building on existing research, future challenges for FITS devices are identified and potential solutions are proposed.

Precise fabrication of spatially engineered brochosomes for in-situ investigation of cellular ROS secretion

Monitoring released hydrogen peroxide (H2O2), one of the most stable and abundant reactive oxygen species (ROS) molecule that regulate intra- and inter-cellular redox signalling pathways, is significant for understanding pysio-pathological mechanisms. In this work, a spatially engineered brochosomes array was developed for in situ surface-enhanced Raman scattering (SERS) investigation of cellular H2O2 secretion. The array, inspired by the nanostructures of brochosomes, has been functionalized with H2O2-specific probes. The optimal pit distribution and size in the brochosomes array, as confirmed by finite-difference time-domain (FDTD) simulation results, supports efficient trapping of light by multiple internal reflections within the pit to suppress overall reflection, leading to enhanced SERS signals. Benefiting from the optimized plasmonic properties of brochosomes and the distinctive spectroscopic fingerprint of the SERS technique, the brochosomes array exhibited a high selectivity toward H2O2 with the limit of detection as low as 3.65 × 10-9 M. In situ cellular monitoring shown real-time tracking of H2O2 secretion from cells, with the brochosomes array maintaining high stability against complicated extracellular microenvironment. This bioinspired SERS platform offers a promising tool for oxidative stress research and could aid in the early diagnosis of ROS-related diseases.

Interfacial Adhesive Adaptation Strategies for Flexible Multilayer Pressure Sensors in Sleep Monitoring

Flexible devices assembled with low-surface-energy PDMS substrates often face challenges, such as poor interfacial adhesion among multilayer films and mismatched mechanical moduli, complicating the development of stable and repeatable pressure sensors. Herein, a PDMS with internal dynamic cross-linking ability is synthesized to alleviate these issues, which shows good tensile properties, flexibility, and self-healing ability at room temperature. Taking advantage of the material homogeneity, the electrodes and sensing layer of the sensor made of the composite ink and PDMS, serving as the additive, have strong peeling resistance and interfacial adhesion. Furthermore, the multilayer sensing layer of the microconvex structures formed by pressing with a microstructural template effectively improves the sensitivity and sensing range of the multilayer pressure sensor. This multilayer flexible pressure sensor can be applied in medical health monitoring, effectively classifying symptoms related to sleep apnea-hypopnea syndrome through machine learning. The constructed neural network accurately learns the sleep conditions, including normal sleep, tachycardia, sleep apnea, sleep talking, snoring, and rapid eye movement. Utilizing the homogeneity and dynamic interfacial cross-linking of multilayer sensor materials, this design aims to improve the interfacial stability of flexible devices, expanding their application potential for long-term and reliable use.

Gradient Nanostructures and Machine Learning Synergy for Robust Quantitative Surface-Enhanced Raman Scattering

Surface-Enhanced Raman Scattering (SERS) holds significant promise for trace-level molecular detection but faces challenges in achieving reliable quantitative analysis due to signal variability caused by non-uniform "hot spots" and external factors. To address these limitations, a novel SERS platform based on gradient nanostructures is developed using shadow sphere lithography, enabling the acquisition of diverse spectral features from a single analyte concentration under identical conditions. The gradient design minimizes fabrication variability and enhances spectral diversity, while the machine learning (ML) model trained on the multi-spectral dataset significantly outperformed traditional single-spectrum approaches, with the test Mean Squared Error (MSE) reduced by 84.8% and the coefficient of determination (R2) improved by 61.2%. This strategy captures subtle spectral variations, improving the precision, robustness, and reproducibility of SERS-based quantification, paving the way for its reliable application in real-world scenarios.

Highly sensitive, breathable, and superhydrophobic dome structure nonwoven-based flexible pressure sensor utilizing machine learning for handwriting recognition

Wearable devices that incorporate flexible pressure sensors have shown great potential for human-machine interaction, speech recognition, health monitoring, and handwriting recognition. However, achieving high sensitivity, durability, wide detection range, and breathability through cost-effective fabrication remains challenging. Through ultrasound-assisted modification and impregnation-drying, dome-structured nonwovens/rGO/PDMS flexible pressure sensors were developed. The sensor exhibits high sensitivity (up to 0.65 kPa-1 in the range of 0-1.12 kPa), rapid response/recovery times (73/98 ms), a wide detection range (0-202 kPa), and superhydrophobic properties with a water contact angle of 166°. Additionally, it demonstrates excellent breathability (514.8 mm/s) and stability (>9000 cycles). With these excellent properties, the sensor is able to detect different pressure signals, allowing encrypted information to be transmitted; it can also be used for health monitoring and motion detection. Additionally, machine learning technology is also successfully used to recognize various handwritten words, with a 94 % accuracy rate in all cases. Consequently, the developed flexible pressure sensor has a wide range of potential applications, including information encryption, medical monitoring, motion detection, human-computer interaction, and handwriting recognition.

Hierarchical Synergetic Strategy for Iontronic Pressure Sensors with High Sensitivity and Broad Linearity Range

Flexible iontronic pressure sensors have attracted extensive attention in intelligent robots and wearable healthcare devices for their flexible properties and sensing functions. Introducing surface microstructures in iontronic pressure sensors has remarkably enhanced sensitivity, whereas achieving flexible pressure sensors with high sensitivity over a broad linear range remains challenging. Here, we propose a hierarchical synergetic strategy for flexible iontronic pressure sensors by combining hemisphere and porous microstructure, realizing high sensitivity (9.27 kPa-1), fast response speed (<15 ms), and linear pressure response (R2 = 0.998) over a broad range (10 Pa-400 kPa). The high linearity of the pressure sensor is attributed to the porous hemispherical microstructure, which improves compressibility and compensates for the effect of structural stiffening. The excellent application potential of our pressure sensors in healthcare monitoring and spatial pressure distribution is demonstrated. The porous hierarchical hemispherical microstructure provides a general strategy expected to be applied to other types of pressure sensors calling for both high sensitivity and high linearity.

Iron-Supported Asymmetric Iontronic Pressure Sensors with High Sensitivity and Extended Linearity

Iontronic pressure sensors (IPSs) are emerging as promising candidates for integration into wearable electronics and healthcare monitoring systems due to their high sensitivity and low power consumption. However, achieving high sensitivity across a broad linear pressure range remains a significant challenge. This study presents a novel IPS device with an asymmetric sandwich structure, which includes a three-dimensional electrode made of nickel manganese oxide/carbon nanotubes (NMO/CNT) and an embedded iron needles ionic dielectric layer. The proposed device demonstrates exceptional linearity over 1700 kPa, with a sensitivity exceeding 7700 kPa-1. It exhibits rapid response and recovery times in the millisecond range and maintains a consistent capacitive response over 15,000 loading-unloading cycles. Moreover, the device enables noncontact sensing in response to magnetic field variations, broadening its potential applications. The innovative IPS design effectively balances high sensitivity and a wide linear pressure range, rendering it suitable for various applications such as nonverbal communication aids and healthcare monitoring systems.

A Patient-Centered Approach in Sensor Science: Embracing Patient Engagement for Translational Clinical Technologies

With the goal of impacting patient quality of life and outcomes, sensor science offers significant potential to revolutionize healthcare by providing advances in the detection of molecular biomarkers for personalized clinical technologies. The sensor community has achieved significant technical advancements that can impact diagnostics, health monitoring, and disease treatment; however, many sensor innovations remain confined to the laboratory, failing to bridge the translational gap between research and real-world clinical applications. This perspective presents a new direction for the sensor community, where sensor development centers on the needs and experiences of the primary beneficiaries: the patients. We provide guidelines and resources for researchers to engage with patients early and continuously throughout the research process to inform sensor specifications and better align sensor technologies with real-world clinical needs, improving their adoption and impact. We also present examples for implementing a patient-centered approach in sensor development and planning for patient engagement in sensor research. In the design of impactful sensors for patients, researchers must expand focus beyond technical specifications to embrace a patient-centered approach, which will likely lead to new opportunities for collaboration and evolution in the sensor science community.

Hierarchical Iontronic Flexible Sensor with High Sensitivity over Ultrabroad Range Enabled by Equilibration of Microstructural Compressibility and Stability

Despite improved sensitivity of iontronic pressure sensors with microstructures, structural compressibility and stability issues hinder achieving exceptional sensitivity across a wide pressure range. Herein, the interplay between ion concentration, mechanical properties, structural geometry, and aspect ratio (AR) on the sensitivity of lithium bis(trifluoromethanesulfonyl) imide/thermoplastic polyurethane (LiTFSI/TPU) ionogel is delved into. The results indicate that cones exhibit superior compressibility compared to pyramids and hemispheres, manifesting in an enhanced sensitivity toward the LiTFSI/TPU ionogel. Subsequently, by strategically combining cones with varying ARs, a harmonious balance between structural stability and compressibility is achieved, culminating in the fabrication of hierarchical iontronic flexible sensors (HIFS). Remarkably, HIFS-III with a three-level hierarchical conical microstructure demonstrates a preeminent sensitivity of 127.65 kPa-1 within ∼500 kPa. Even within the ultrabroad pressure range of 1500-3000 kPa, the sensitivity remains exceeding 10 kPa-1. Furthermore, HIFS-III boasts swift response and relaxation times (∼11 and 18 ms, respectively), a low detection limit (∼6.35 Pa), as well as remarkable durability (15,000 cycles). The exceptional sensing capabilities of HIFS-III underscore its emergence as a promising high-performance sensing and feedback solution tailored for applications in human-machine interaction and e-skin.

A Comprehensive Review on Iron-Based Sulfate Cathodes for Sodium-Ion Batteries

Sodium-ion batteries (SIBs) are advantageous for large-scale energy storage due to the plentiful and ubiquitous nature of sodium resources, coupled with their lower cost relative to alternative technologies. To expedite the market adoption of SIBs, enhancing the energy density of SIBs is essential. Raising the operational voltage of the SIBs cathode is regarded as an effective strategy for achieving this goal, but it requires stable high-voltage cathode materials. Sodium iron sulfate (NFSO) is considered to be a promising cathode material due to its stable framework, adjustable structure, operational safety, and the high electronegativity of SO4-. This paper reviews the research progress of NFSO, discusses its structure and sodium storage mechanism on this basis, and summarizes the advantages and disadvantages of NFSO cathode materials. This study also evaluates the advancements in enhancing the electrochemical characteristics and structural reliability of SIBs, drawing on both domestic and international research. The findings of this paper offer valuable insights into the engineering and innovation of robust and viable SIB cathodes based on NFSO at ambient temperatures, contributing to their commercial viability.

Highly Elastic, Fatigue-Resistant, and Antifreezing MXene Functionalized Organohydrogels as Flexible Pressure Sensors for Human Motion Monitoring

Conductive organohydrogels-based flexible pressure sensors have gained considerable attention in health monitoring, artificial skin, and human-computer interaction due to their excellent biocompatibility, wearability, and versatility. However, hydrogels' unsatisfactory mechanical and unstable electrical properties hinder their comprehensive application. Herein, an elastic, fatigue-resistant, and antifreezing poly(vinyl alcohol) (PVA)/lipoic acid (LA) organohydrogel with a double-network structure and reversible cross-linking interactions has been designed, and MXene as a conductive filler is functionalized into organohydrogel to further enhance the diverse sensing performance of flexible pressure sensors. The as-fabricated MXene-based PVA/LA organohydrogels (PLBM) exhibit stable fatigue resistance for over 450 cycles under 40% compressive strain, excellent elasticity, antifreezing properties (<-20 °C), and degradability. Furthermore, the pressure sensors based on the PLBM organohydrogels show a fast response time (62 ms), high sensitivity (S = 0.0402 kPa-1), and excellent stability (over 1000 cycles). The exceptional performance enables the sensors to monitor human movements, such as joint flexion and throat swallowing. Moreover, the sensors integrating with the one-dimensional convolutional neural networks and the long-short-term memory networks deep learning algorithms have been developed to recognize letters with a 93.75% accuracy, representing enormous potential in monitoring human motion and human-computer interaction.

Intelligent Song Recognition via a Hollow-Microstructure-Based, Ultrasensitive Artificial Eardrum

Artificial ears with intelligence, which can sensitively detect sound-a variant of pressure-and generate consciousness and logical decision-making abilities, hold great promise to transform life. However, despite the emerging flexible sensors for sound detection, most success is limited to very simple phonemes, such as a couple of letters or words, probably due to the lack of device sensitivity and capability. Herein, the construction of ultrasensitive artificial eardrums enabling intelligent song recognition is reported. This strategy employs novel geometric engineering of sensing units in the soft microstructure array (to significantly reduce effective modulus) along with complex song recognition exploration leveraging machine learning algorithms. Unprecedented pressure sensitivity (6.9 × 103 kPa-1) is demonstrated in a sensor with a hollow pyramid architecture with porous slants. The integrated device exhibits unparalleled (exceeding by 1-2 orders of magnitude compared with reported benchmark samples) sound detection sensitivity, and can accurately identify 100% (for training set) and 97.7% (for test set) of a database of the segments from 77 songs varying in language, style, and singer. Overall, the results highlight the outstanding performance of the hollow-microstructure-based sensor, indicating its potential applications in human-machine interaction and wearable acoustical technologies.

Biomimetic Contact Behavior Inspired Tactile Sensing Array with Programmable Microdomes Pattern by Scalable and Consistent Fabrication

Flexible sensor arrays have attracted extensive attention in human-computer interaction. However, realizing high-performance sensor units with programmable properties, and expanding them to multi-pixel flexible arrays to maintain high sensing consistency is still struggling. Inspired by the contact behavior of octopus antenna, this paper proposes a programmable multistage dome structure-based flexible sensing array with robust sensing stability and high array consistency. The biomimetic multistage dome structure is pressurized to gradually contact the electrode to achieve high sensitivity and a large pressure range. By adjusting the arrangement of the multistage dome structure, the pressure range and sensitivity can be customized. More importantly, this biomimetic structure can be expanded to a multi-pixel sensor array at the wafer level with high consistency through scalable and high-precision imprinting technologies. In the imprinting process, the conductive layer is conformally embedded into the multistage dome structure to improve the stability (maintain stability over 22 000 cycles). In addition, the braced isolation structure is designed to effectively improve the anti-crosstalk performance of the sensor array (crosstalk coefficient: 26.62 dB). Benefitting from the programmable structural design and high-precision manufacturing process, the sensor array can be customized and is demonstrated to detect human musculation in medical rehabilitation applications.

High-Performance Flexible Pressure Sensor with Micropyramid Structure for Human Motion Signal Detection and Electromagnetic Interference Shielding

Flexible pressure sensors have a wide range of applications in the field of human motion signal detection, but the electromagnetic radiation generated during the monitoring process has become an unavoidable problem. Nowadays, it is still a challenge to develop high-performance pressure sensors with excellent electromagnetic interference (EMI) shielding performance. Herein, the Ti3C2TX MXene/carbon fiber/multiwalled carbon nanotube/polydimethylsiloxane (MXene/CMP) films with a micropyramidal structure were developed by the technology of vacuum high-temperature hot pressing and spray deposition. Benefiting from the dielectric loss of the conductive fillers and the presence of the microstructure, the MXene/CMP film exhibits excellent EMI shielding performance, and the EMI shielding efficiency (SE) can reach 49.37 dB. Besides, the introduction of CF effectively improves the mechanical properties of the MXene/CMP films, and the MXene nanosheets deposited on the surface of the film can reduce stress concentration, which in turn delays the expansion of cracks. Furthermore, the MXene/CMP sensor exhibits high sensitivity (89.76 kPa-1) and fast response/recovery time (61/60 ms). The deformation of microstructure and the construction of conductive networks enable the sensor to realize the monitoring of human motion signals (such as finger bending, knee bending, wrist bending, etc.). Meanwhile, the sensor maintains sensing stability even after 2000 pressure cycles, which can be attributed to the improvement in mechanical properties. In summary, the developed high-performance flexible pressure sensor with micropyramid structure has great application prospects in wearable devices and healthcare.