Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel.

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries1 and electrocatalysts2. Experimental characterizations of such materials by operando microscopy produce rich image datasets3-6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

Correlative operando microscopy of oxygen evolution electrocatalysts.

Transition metal (oxy)hydroxides are promising electrocatalysts for the oxygen evolution reaction1-3. The properties of these materials evolve dynamically and heterogeneously4 with applied voltage through ion insertion redox reactions, converting materials that are inactive under open circuit conditions into active electrocatalysts during operation5. The catalytic state is thus inherently far from equilibrium, which complicates its direct observation. Here, using a suite of correlative operando scanning probe and X-ray microscopy techniques, we establish a link between the oxygen evolution activity and the local operational chemical, physical and electronic nanoscale structure of single-crystalline ß-Co(OH)2 platelet particles. At pre-catalytic voltages, the particles swell to form an α-CoO2H1.5·0.5H2O-like structure-produced through hydroxide intercalation-in which the oxidation state of cobalt is +2.5. Upon increasing the voltage to drive oxygen evolution, interlayer water and protons de-intercalate to form contracted ß-CoOOH particles that contain Co3+ species. Although these transformations manifest heterogeneously through the bulk of the particles, the electrochemical current is primarily restricted to their edge facets. The observed Tafel behaviour is correlated with the local concentration of Co3+ at these reactive edge sites, demonstrating the link between bulk ion-insertion and surface catalytic activity.

Gross Hematuria Does not Affect the Selection of Nephrectomy Types for Clinical Stage 1 Clear Cell Renal Cell Carcinoma: A Multicenter, Retrospective Cohort Study.

PURPOSE: This study aimed to discuss the correlation between gross hematuria and postoperative upstaging (from T1 to T3a) in patients with cT1 clear cell renal cell carcinoma (ccRCC) and to compare oncologic outcomes of partial nephrectomy (PN) and radical nephrectomy (RN) in patients with gross hematuria. METHODS: A total of 2145 patients who met the criteria were enrolled in the study (including 363 patients with gross hematuria). The least absolute selection and shrinkage operator logistic regression was used to evaluate the risk factor of postoperative pathological upstaging. The propensity score matching (PSM) and stable inverse probability of treatment weighting (IPTW) analysis were used to balance the confounding factors. The Kaplan-Meier analysis and multivariate Cox proportional risk regression model were used to assess the prognosis. RESULTS: Gross hematuria was a risk factor of postoperative pathological upstaging (odds ratio [OR] = 3.96; 95% confidence interval [CI] 2.44-6.42; P < 0.001). After PSM and stable IPTW adjustment, the characteristics were similar in corresponding patients in the PN and RN groups. In the PSM cohort, PN did not have a statistically significant impact on recurrence-free survival (hazard ratio [HR] = 1.48; 95% CI 0.25-8.88; P = 0.67), metastasis-free survival (HR = 1.24; 95% CI 0.33-4.66; P = 0.75), and overall survival (HR = 1.46; 95% CI 0.31-6.73; P = 0.63) compared with RN. The results were confirmed in sensitivity analyses. CONCLUSIONS: Although gross hematuria was associated with postoperative pathological upstaging in patients with cT1 ccRCC, PN should still be the preferred treatment for such patients.

Patients with high nuclear grade pT1-ccRCC are more suitable for radical nephrectomy than partial nephrectomy: a multicenter retrospective study using propensity score.

BACKGROUND: Partial nephrectomy (PN) is usually recommended for T1 stage clear cell renal cell carcinoma (ccRCC) regardless of the nuclear grades. However, the question remains unresolved as to whether PN is non-inferior to RN in patients with T1-ccRCC at higher risk of recurrence. In fact, we found that patients with high nuclear grades treated with PN had poorer prognosis compared with those treated with radical nephrectomy (RN). Therefore, this study was designed to evaluate the associations of PN and RN in the four nuclear grade subsets with oncologic outcomes. METHODS: A retrospective study was conducted in three Chinese urological centers that included 1,714 patients who underwent PN or RN for sporadic, unilateral, pT1, N0, and M0 ccRCC without positive surgical margins and neoadjuvant therapy between 2010 and 2019. Associations of nephrectomy type with local ipsilateral recurrence, distant metastases, and all-cause mortality (ACM) were evaluated using the Kaplan-Meier method and multivariable Cox proportional hazards regression models after overlap weighting (OW). RESULTS: A total of 1675 patients entered the OW cohort. After OW, in comparison to PN, RN associated with a reduced risk of local ipsilateral recurrence in the G2 subset (HR = 0.148, 95% CI 0.046-0.474; p < 0.05), G3 subset (HR = 0.097, 95% CI 0.021-0.455; p < 0.05), and G4 subset (HR = 0.091, 95% CI 0.011-0.736; p < 0.05), and resulting in increased five-year local recurrence-free survival rates of 7.0%, 17.9%, and 36.2%, respectively. An association between RN and a reduced risk of distant metastases in the G4 subset (HR = 0.071, 95% CI 0.016-0.325; p < 0.05), with the five-year distant metastases-free survival rate increasing by 33.1% was also observed. No significant difference in ACM between PN and RN was identified. CONCLUSIONS: Our findings substantiate that opting for RN, as opposed to PN, is more advantageous for local recurrence-free survival and distant metastases-free survival in patients with high nuclear grade (especially G4) pT1-ccRCC. We recommend placing a heightened emphasis on enhancing preoperative nuclear grade assessment, as it can significantly influence the choice of surgical plan. TRIAL REGISTRATION: This study was registered at Chinese Clinical Trial Registry (ID: ChiCTR2200063333).

Correlative image learning of chemo-mechanics in phase-transforming solids.

Constitutive laws underlie most physical processes in nature. However, learning such equations in heterogeneous solids (for example, due to phase separation) is challenging. One such relationship is between composition and eigenstrain, which governs the chemo-mechanical expansion in solids. Here we developed a generalizable, physically constrained image-learning framework to algorithmically learn the chemo-mechanical constitutive law at the nanoscale from correlative four-dimensional scanning transmission electron microscopy and X-ray spectro-ptychography images. We demonstrated this approach on LiXFePO4, a technologically relevant battery positive electrode material. We uncovered the functional form of the composition-eigenstrain relation in this two-phase binary solid across the entire composition range (0 ≤ X ≤ 1), including inside the thermodynamically unstable miscibility gap. The learned relation directly validates Vegard's law of linear response at the nanoscale. Our physics-constrained data-driven approach directly visualizes the residual strain field (by removing the compositional and coherency strain), which is otherwise impossible to quantify. Heterogeneities in the residual strain arise from misfit dislocations and were independently verified by X-ray diffraction line profile analysis. Our work provides the means to simultaneously quantify chemical expansion, coherency strain and dislocations in battery electrodes, which has implications on rate capabilities and lifetime. Broadly, this work also highlights the potential of integrating correlative microscopy and image learning for extracting material properties and physics.

Patterned Nanoparticle Arrays Fabricated Using Liquid Film Rupture Self-Assembly.

Self-assembly is an important bottom-up fabrication approach based on accurate manipulation of solid-air-liquid interfaces to construct microscale structures using nanoscale materials. This approach plays a substantial role in the fabrication of microsensors, nanosensors, and actuators. Improving the controllability of self-assembly to realize large-scale regular micro/nano patterns is crucial for this approach's further development and wider applications. Herein, we propose a novel strategy for patterning nanoparticle arrays on soft substrates. This strategy is based on a unique process of liquid film rupture self-assembly that is convenient, precise, and cost-efficient for mass manufacturing. This approach involves two key steps. First, suspended liquid films comprising monolayer polystyrene (PS) spheres are realized via liquid-air interface self-assembly over prepatterned microstructures. Second, these suspended liquid films are ruptured in a controlled manner to induce the self-assembly of internal PS spheres around the morphological edges of the underlying microstructures. This nanoparticle array patterning method is comprehensively investigated in terms of the effect of the PS sphere size, morphological effect of the microstructured substrate, key factors influencing liquid film-rupture self-assembly, and optical transmittance of the fabricated samples. A maximum rupture rate of 95.4% was achieved with an optimized geometric and dimensional design. Compared with other nanoparticle-based self-assembly methods used to form patterned arrays, the proposed approach reduces the waste of nanoparticles substantially because all nanoparticles self-assemble around the prepatterned microstructures. More nanoparticles assemble to form prepatterned arrays, which could strengthen the nanoparticle array network without affecting the initial features of prepatterned microstructures.

NVAS: A non-interactive verifiable federated learning aggregation scheme for COVID-19 based on game theory.

The continued spread of COVID-19 seriously endangers the physical and mental health of people in all countries. It is an important method to establish inter agency COVID-19 detection and prevention system based on game theory through wireless communication and artificial intelligence. Federated learning (FL) as a privacy preserving machine learning framework has received extensive attention. From the perspective of game theory, FL can be regarded as a process in which multiple participants play games against each other to maximize their own interests. This requires that the user's data is not leaked during the training process. However, existing studies have proved that the privacy protection capability of FL is insufficient. In addition, the existing way of realizing privacy protection through multiple rounds of communication between participants increases the burden of wireless communication. To this end, this paper considers the security model of FL based on game theory, and proposes our scheme, NVAS, a non-interactive verifiable privacy-preserving FL aggregation scheme in wireless communication environments. The NVAS can protect user privacy during FL training without unnecessary interaction between participants, which can better motivate more participants to join and provide high-quality training data. Furthermore, we designed a concise and efficient verification algorithm to ensure the correctness of model aggregation. Finally, the security and feasibility of the scheme are analyzed.

Therapeutic strategies for retention of cranioplasty titanium mesh after mesh exposure.

BACKGROUND: Titanium mesh exposure after cranioplasty is a possible complication and is usually managed by mesh removal and flap transfer, but the advantages of the rigid prosthesis are then lost. This study aimed to present our experience with negative pressure wound therapy combined with soft tissue dilation for retaining the titanium mesh in patients with mesh exposure after cranioplasty. METHODS: This retrospective study included patients treated between 01/2016 and 05/2019 at the Jiangyin Hospital Affiliated to Southeast University School of Medicine. The wound was cleaned, and a cystic space was created for the tissue dilator, which was used with a self-designed negative pressure dressing. After the target dilation was achieved, the repair was conducted while retaining the titanium mesh. RESULTS: Eight patients were included (seven males and one female; 53.6 ± 8.8 (range, 43-65) years of age). The exposed mesh area ranged from 1 × 1 to 4 × 5.5 cm. The thinning scalp area around the exposed mesh ranged from 3.6 × 3.8 to 4 × 5.5 cm. Five patients had positive wound cultures and received sensitive antibiotics. The dilator embedding time was 20-28 days. The time of negative pressure wound therapy was 25-33 days. The hospital stay was 30-41 days. Primary wound healing was achieved in all eight patients. There were no signs of recurrence after 6-18 months of follow-up. The cranial CT scans were unremarkable. CONCLUSIONS: Negative pressure wound therapy combined with soft tissue dilation for exposed titanium mesh after cranioplasty might help retain the titanium mesh.

The Interface between Nanoenergy and Self-Powered Electronics.

In recent decades, nanogenerators based on several techniques such as triboelectric effects, piezoelectric effects, or other mechanisms have experienced great developments. The nanoenergy generated by nanogenerators is supposed to be used to overcome the problem of energy supply problems for portable electronics and to be applied to self-powered microsystems including sensors, actuators, integrated circuits, power sources, and so on. Researchers made many attempts to achieve a good solution and have performed many explorations. Massive efforts have been devoted to developing self-powered electronics, such as self-powered communication devices, self-powered human-machine interfaces, and self-powered sensors. To take full advantage of nanoenergy, we need to review the existing applications, look for similarities and differences, and then explore the ways of achieving various self-powered systems with better performance. In this review, the methods of applying nanogenerators in specific circumstances are studied. The applications of nanogenerators are classified into two categories, direct utilization and indirect utilization, according to whether a treatment process is needed. We expect to offer a line of thought for future research on self-powered electronics.

Amyotrophic Lateral Sclerosis-associated GGGGCC repeat expansion promotes Tau phosphorylation and toxicity.

Microtubule-associated protein Tau (MAPT) and GGGGCC (G4C2) repeat expansion in chromosome 9 open reading frame 72 (C9ORF72) are the major known genetic causes of frontotemporal dementia (FTD) and other neurodegenerative diseases, such as Amyotrophic Lateral Sclerosis (ALS). Although expanded G4C2 repeats and Tau traditionally are associated with different clinical presentations, pathological and genetic studies have suggested a strong association between them. Here we demonstrate a strong genetic interaction between expanded G4C2 repeats and Tau. We found that co-expression of expanded G4C2 repeats and Tau could produce a synergistic deterioration of rough eyes, motor function, life span and neuromuscular junction morphological abnormalities in Drosophila. Mechanistically, compared with the normal allele containing (G4C2)3 repeats, the (G4C2)30 allele increased Tau phosphorylation levels and promoted Tau R406W aggregation. These results together suggest a potential crosstalk between expanded G4C2 repeats and Tau in modulating neurodegeneration.

Fluid-enhanced surface diffusion controls intraparticle phase transformations.

Phase transformations driven by compositional change require mass flux across a phase boundary. In some anisotropic solids, however, the phase boundary moves along a non-conductive crystallographic direction. One such material is LiXFePO4, an electrode for lithium-ion batteries. With poor bulk ionic transport along the direction of phase separation, it is unclear how lithium migrates during phase transformations. Here, we show that lithium migrates along the solid/liquid interface without leaving the particle, whereby charge carriers do not cross the double layer. X-ray diffraction and microscopy experiments as well as ab initio molecular dynamics simulations show that organic solvent and water molecules promote this surface ion diffusion, effectively rendering LiXFePO4 a three-dimensional lithium-ion conductor. Phase-field simulations capture the effects of surface diffusion on phase transformation. Lowering surface diffusivity is crucial towards supressing phase separation. This work establishes fluid-enhanced surface diffusion as a key dial for tuning phase transformation in anisotropic solids.

Quantifying and Elucidating Thermally Enhanced Minority Carrier Diffusion Length Using Radius-Controlled Rutile Nanowires.

The minority carrier diffusion length (LD) is a crucial property that determines the performance of light absorbers in photoelectrochemical (PEC) cells. Many transition-metal oxides are stable photoanodes for solar water splitting but exhibit a small to moderate LD, ranging from a few nanometers (such as α-Fe2O3 and TiO2) to a few tens of nanometers (such as BiVO4). Under operating conditions, the temperature of PEC cells can deviate substantially from ambient, yet the temperature dependence of LD has not been quantified. In this work, we show that measuring the photocurrent as a function of both temperature and absorber dimensions provides a quantitative method for evaluating the temperature-dependent minority carrier transport. By measuring photocurrents of nonstoichiometric rutile TiO2-x nanowires as a function of wire radius (19-75 nm) and temperature (10-70 °C), we extract the minority carrier diffusion length along with its activation energy. The minority carrier diffusion length in TiO2-x increases from 5 nm at 25 °C to 10 nm at 70 °C, implying that enhanced carrier mobility outweighs the increase in the recombination rate with temperature. Additionally, by comparing the temperature-dependent photocurrent in BiVO4, TiO2, and α-Fe2O3, we conclude that the ratio of the minority carrier diffusion length to the depletion layer width determines the extent of temperature enhancement, and reconcile the widespread temperature coefficients, which ranged from 0.6 to 1.7% K-1. This insight provides a general design rule to select light absorbers for large thermally activated photocurrents and to predict PEC cell characteristics at a range of temperatures encountered during realistic device operation.

Interface Engineering in Two-Dimensional Heterostructures: Towards an Advanced Catalyst for Ullmann Couplings.

The design of advanced catalysts for organic reactions is of profound significance. During such processes, electrophilicity and nucleophilicity play vital roles in the activation of chemical bonds and ultimately speed up organic reactions. Herein, we demonstrate a new way to regulate the electro- and nucleophilicity of catalysts for organic transformations. Interface engineering in two-dimensional heteronanostructures triggered electron transfer across the interface. The catalyst was thus rendered more electropositive, which led to superior performance in Ullmann reactions. In the presence of the engineered 2D Cu2 S/MoS2 heteronanostructure, the coupling of iodobenzene and para-chlorophenol gave the desired product in 92 % yield under mild conditions (100 °C). Furthermore, the catalyst exhibited excellent stability as well as high recyclability with a yield of 89 % after five cycles. We propose that interface engineering could be widely employed for the development of new catalysts for organic reactions.

Zwitterionic Eutectogels with High Ionic Conductivity for Environmentally Tolerant and Self-Healing Triboelectric Nanogenerators.

Eutectogels have garnered considerable attention for the development of wearable devices, owing to their inherent mechanical elasticity, ionic conductivity, affordability, and environmental compatibility. However, the low conductivity of existing eutectogels has impeded their progression in electronic applications. Here, we report a zwitterionic eutectogel with an impressive ionic conductivity of up to 15.7 mS cm-1. The incorporation of zwitterionic groups into the eutectogel creates ample mobile charges by dissociating the cation and anion of solvents, thereby yielding exceptional ionic conductivity. Moreover, the abundant electrostatic and hydrogen bonding interactions within the eutectogel endow it with prominent self-healing and adhesive properties. By integrating the eutectogel with a roughly patterned polydimethylsiloxane film, we have successfully constructed a triboelectric nanogenerator (TENG) with a maximum output power density of 112 mW m-2. This TENG is capable of generating stable electrical signals even in extreme temperature conditions ranging from -80 to 100 °C and effectively powering electronic devices. Furthermore, the assembled TENG displays high sensitivity as a self-powered sensor, enabling real-time and precise monitoring of signals derived from human motions. This study establishes a promising approach for the development of sustainable and multifunctional flexible electronics that are resilient in extreme environments.

Beyond Constant Current: Origin of Pulse-Induced Activation in Phase-Transforming Battery Electrodes.

Mechanistic understanding of phase transformation dynamics during battery charging and discharging is crucial toward rationally improving intercalation electrodes. Most studies focus on constant-current conditions. However, in real battery operation, such as in electric vehicles during discharge, the current is rarely constant. In this work we study current pulsing in LiXFePO4 (LFP), a model and technologically important phase-transforming electrode. A current-pulse activation effect has been observed in LFP, which decreases the overpotential by up to ∼70% after a short, high-rate pulse. This effect persists for hours or even days. Using scanning transmission X-ray microscopy and operando X-ray diffraction, we link this long-lived activation effect to a pulse-induced electrode homogenization on both the intra- and interparticle length scales, i.e., within and between particles. Many-particle phase-field simulations explain how such pulse-induced homogeneity contributes to the decreased electrode overpotential. Specifically, we correlate the extent and duration of this activation to lithium surface diffusivity and the magnitude of the current pulse. This work directly links the transient electrode-level electrochemistry to the underlying phase transformation and explains the critical effect of current pulses on phase separation, with significant implication on both battery round-trip efficiency and cycle life. More broadly, the mechanisms revealed here likely extend to other phase-separating electrodes, such as graphite.

Intelligent soft robotic fingers with multi-modality perception ability.

In the context of industry 4.0, automatic sorting is becoming prevalent in production lines. Herein, we developed a bionic sensing system to achieve real-time object recognition. The system consists of 9 single-layer triboelectric nanogenerators (SL-TENGs) as touch sensors and 3 comb-shaped TENGs (CS-TENGs) as bending sensors, with a sensitivity of 110 V/kPa and stable output after 20,000 press cycles. These sensors were attached to a manipulator composed of three soft actuators, serving as soft robotic fingers. An enhanced electrical output of these sensors was achieved successfully, demonstrating their feasibility in detecting grasping location, contact pressure, and bending curvature. A one-dimensional convolutional neural network (1D-CNN) with 98.96% accuracy extracted information from the sensors, enabling the manipulator to serve as an intelligent sensing system with multi-modality perception ability. This robotic manipulator successfully integrated TENG-based self-powered sensors, soft actuators, and artificial intelligence, demonstrating the potential for future digital twin applications, particularly in automatic component sorting.

Highly stretchable and self-healing photoswitchable supramolecular fluorescent polymers for underwater anti-counterfeiting.

Thanks to the non-destructiveness and spatial-controllability of light, photoswitchable fluorescent polymers (PFPs) have been successfully applied in advanced anti-counterfeiting and information encryption. However, most of them are not suitable for use in harsh underwater environments, including high salinity seawater. In this study, by integrating photochromic molecules into a hydrophobic polymer matrix with the fluorine elastomer, including dipole-dipole interactions, we describe a class of novel photoswitchable supramolecular fluorescent polymers (PSFPs) that can adaptively change their fluorescence between none, green and red by the irradiation of different light. The PSFPs not only exhibited excellent photoswitchable properties, including fast photo-responsibility, prominent photo-reversibility, and photostability, but also exhibited some desired properties, including exceptional stretchability, hydrophobicity, antifouling, self-healing ability, simple preparation process, and processability. We thus demonstrated their applications in underwater data encryption and anti-counterfeiting labels.

High-performance hybrid nanogenerator for self-powered wireless multi-sensing microsystems.

Wireless sensor network nodes are widely used in wearable devices, consumer electronics, and industrial electronics and are a crucial component of the Internet of Things (IoT). Recently, advanced power technology with sustainable energy supply and pollution-free characteristics has become a popular research focus. Herein, to realize an unattended and reliable power supply unit suitable for distributed IoT systems, we develop a high-performance triboelectric-electromagnetic hybrid nanogenerator (TEHNG) to harvest mechanical energy. The TEHNG achieves a high load power of 21.8 mW by implementing improvements of material optimization, configuration optimization and pyramid microstructure design. To realize a self-powered integrated microsystem, a power management module, energy storage module, sensing signal processing module, and microcontroller unit are integrated into the TEHNG. Furthermore, an all-in-one wireless multisensing microsystem comprising the TEHNG, the abovementioned integrated functional circuit and three sensors (temperature, pressure, and ultraviolet) is built. The milliwatt microsystem operates continuously with the TEHNG as the only power supply, achieving self-powered operations of sensing environmental variables and transmitting wireless data to a terminal in real time. This shows tremendous application potential in the IoT field.

Integrated hybrid sensing and microenergy for compact active microsystems.

Wearable electronics, as essential components of the Internet of Things (IoT), have attracted widespread attention, and the trend is to configure attractive wearable smart microsystems by integrating sensing, powering, and other functions. Herein, we developed an elastic hybrid triboelectric-electromagnetic microenergy harvester (named EHTE) to realize hybrid sensing and microenergy simultaneously. This EHTE is a highly integrated triboelectric nanogenerator (TENG) and electromagnetic nanogenerator (EMG). Based on the triboelectric-electromagnetic hybrid mechanism, an enhanced electrical output of the EHTE was achieved successfully, which demonstrates the feasibility of the EHTE for microelectronics powering. Moreover, with the merits of the EMG, the developed hybrid microenergy harvester integrated both active frequency sensing and passive inductive sensing capabilities. Specifically, the almost linear correlation of the electromagnetic outputs to the frequencies of the external stimulus endowed the proposed EHTE with an outstanding active frequency sensing ability. In addition, due to the unique structural configuration of the EMG (i.e., a conductive permanent magnet (PM), hybrid deformation layer, and flexible printed circuit board (FPCB) coil), an opportunity was provided for the developed EHTE to serve as a passive inductive sensor based on the eddy current effect (i.e., a form of electromagnetic induction). Therefore, the developed EHTE successfully achieved the integration of hybrid sensing (i.e., active frequency sensing and passive inductive sensing) and microenergy (i.e., the combination of electromagnetic effect and triboelectric effect) within a single device, which demonstrates the potential of this newly developed EHTE for wearable electronic applications, especially in applications of compact active microsystems.

Wearable Multi-Functional Sensing Technology for Healthcare Smart Detection.

In recent years, considerable research efforts have been devoted to the development of wearable multi-functional sensing technology to fulfill the requirements of healthcare smart detection, and much progress has been achieved. Due to the appealing characteristics of flexibility, stretchability and long-term stability, the sensors have been used in a wide range of applications, such as respiration monitoring, pulse wave detection, gait pattern analysis, etc. Wearable sensors based on single mechanisms are usually capable of sensing only one physiological or motion signal. In order to measure, record and analyze comprehensive physical conditions, it is indispensable to explore the wearable sensors based on hybrid mechanisms and realize the integration of multiple smart functions. Herein, we have summarized various working mechanisms (resistive, capacitive, triboelectric, piezoelectric, thermo-electric, pyroelectric) and hybrid mechanisms that are incorporated into wearable sensors. More importantly, to make wearable sensors work persistently, it is meaningful to combine flexible power units and wearable sensors and form a self-powered system. This article also emphasizes the utility of self-powered wearable sensors from the perspective of mechanisms, and gives applications. Furthermore, we discuss the emerging materials and structures that are applied to achieve high sensitivity. In the end, we present perspectives on the outlooks of wearable multi-functional sensing technology.