Rainfall Observation Leveraging Raindrop Sounds Acquired Using Waterproof Enclosure: Exploring Optimal Length of Sounds for Frequency Analysis.

This paper proposes a novel method to estimate rainfall intensity by analyzing the sound of raindrops. An innovative device for collecting acoustic data was designed, capable of blocking ambient noise in rainy environments. The device was deployed in real rainfall conditions during both the monsoon season and non-monsoon season to record raindrop sounds. The collected raindrop sounds were divided into 1 s, 10 s, and 1 min intervals, and the performance of rainfall intensity estimation for each segment length was compared. First, the rainfall occurrence was determined based on four extracted frequency domain features (average of dB, frequency-weighted average of dB, standard deviation of dB, and highest frequency), followed by a quantitative estimation of the rainfall intensity for the periods in which rainfall occurred. The results indicated that the best estimation performance was achieved when using 10 s segments, corresponding to the following metrics: accuracy: 0.909, false alarm ratio: 0.099, critical success index: 0.753, precision: 0.901, recall: 0.821, and F1 score: 0.859 for rainfall occurrence classification; and root mean square error: 1.675 mm/h, R2: 0.798, and mean absolute error: 0.493 mm/h for quantitative rainfall intensity estimation. The proposed small and lightweight device is convenient to install and manage and is remarkably cost-effective compared with traditional rainfall observation equipment. Additionally, this compact rainfall acoustic collection device can facilitate the collection of detailed rainfall information over vast areas.

Impacts of sustainable management on the spatial distributions of erosion susceptibility and probable sediment yield in a mixed-forested watershed.

Forest management practices play multifaceted roles in enhancing the geophysical properties that affect raindrop erosion in the watershed, and consequently, sediment deposition in the reservoir. The current work attempts to integrate empirical and physically-based modeling approaches to quantify the impacts of forest conservation on erosion risk and potential sediment accumulation in the mixed-forested Ogouchi Dam watershed in Japan. The reliability of the empirical model for estimating the total erodibility coefficient (TEr), as a function of various forest properties, was evaluated by applying the mathematical expression to multiple forest conditions and comparing the values to field-measured soil erosion rates. The spatial distribution of the empirically derived values showed that about 25.8% of the Government-managed forests and 45.1% of the private forests have higher risks of raindrop splash erosion compared to natural forests. The TEr value in each small Government-divided forest land (less than 5 ha) was then corresponded to the MUSLE management practice factor (MUSLE P) input in each hydrologic response unit (HRU) in the Soil and Water Assessment Tool (SWAT) model to create a sediment yield distribution map and to predict the amounts of sediment accumulation for different management scenarios. The spatial distribution of sediment yield for the base condition showed that 20.9% of the Government-managed forests and 61.6% of the private forests have higher probable amounts of sediment yield relative to the value simulated in the natural forest. A maximum cumulative sediment reduction of about 14.4% is likely attainable upon the complete control of the Government in the entire planted forest area. Overall, this study effectively utilized the field survey datasets to develop a robust empirical model for quantifying erosion risk and was able to couple the results to a GIS-based model that predicts the amounts of sediment yield under varying environmental conditions.

The biomechanics of leaf oscillations during rainfall events.

Plants are dynamic systems during rainfall events. As raindrops splash on leaf surfaces, the momentum of the raindrop is transferred to the leaf, causing the leaf to oscillate. The emphasis of this review is on the general principles of leaf oscillation models after raindrop impact and the ecological importance. Various leaf oscillation models and the underlying physical properties from biomechanics theory are highlighted. Additionally, we review experimental methods to derive the model parameters for and explore advances in our understanding of the raindrop-leaf impact process.

Inlays and the cornea.

Presbyopia is a growing problem in view of an aging global population and increasingly patients desire spectacle-free solutions to address this condition. Surgically implanted corneal inlays have been the topic of renewed research efforts in the past several years as a treatment option for presbyopia, with several approaches being used to modify the refractive properties of the cornea and enhance near vision. In this review we discuss historical approaches to corneal inlay surgery, critically appraise the current generation of presbyopia-correcting corneal inlays and their associated complications and consider the future prospects for emerging corneal inlay technologies that aim address the shortcomings of currently available inlays.

Self-Supervised Denoising Image Filter Based on Recursive Deep Neural Network Structure.

The purpose of this paper is to propose a novel noise removal method based on deep neural networks that can remove various types of noise without paired noisy and clean data. Because this type of filter generally has relatively poor performance, the proposed noise-to-blur-estimated clean (N2BeC) model introduces a stage-dependent loss function and a recursive learning stage for improved denoised image quality. The proposed loss function regularizes the existing loss function so that the proposed model can better learn image details. Moreover, the recursive learning stage provides the proposed model with an additional opportunity to learn image details. The overall deep neural network consists of three learning stages and three corresponding loss functions. We determine the essential hyperparameters via several simulations. Consequently, the proposed model showed more than 1 dB superior performance compared with the existing noise-to-blur model.

Retrieval of Raindrop Size Distribution Using Dual-Polarized Microwave Signals from LEO Satellites: A Feasibility Study through Simulations.

In this paper, a novel approach for raindrop size distribution retrieval using dual-polarized microwave signals from low Earth orbit satellites is proposed. The feasibility of this approach is studied through modelling and simulating the retrieval system which includes multiple ground receivers equipped with signal-to-noise ratio estimators and a low Earth orbit satellite communicating with the receivers using both vertically and horizontally polarized signals. Our analysis suggests that the dual-polarized links offer the opportunity to estimate two independent raindrop size distribution parameters. To achieve that, the vertical and horizontal polarization attenuations need to be measured at low elevation angles where the difference between them is more distinct. Two synthetic rain fields are generated to test the performance of the retrieval. Simulation results suggest that the specific attenuations for both link types can be retrieved through a least-squares algorithm. They also confirm that the specific attenuation ratio of vertically to horizontally polarized signals can be used to retrieve the slope and intercept parameters of raindrop size distribution.

Multi-Scale Shape Adaptive Network for Raindrop Detection and Removal from a Single Image.

Removing raindrops from a single image is a challenging problem due to the complex changes in shape, scale, and transparency among raindrops. Previous explorations have mainly been limited in two ways. First, publicly available raindrop image datasets have limited capacity in terms of modeling raindrop characteristics (e.g., raindrop collision and fusion) in real-world scenes. Second, recent deraining methods tend to apply shape-invariant filters to cope with diverse rainy images and fail to remove raindrops that are especially varied in shape and scale. In this paper, we address these raindrop removal problems from two perspectives. First, we establish a large-scale dataset named RaindropCityscapes, which includes 11,583 pairs of raindrop and raindrop-free images, covering a wide variety of raindrops and background scenarios. Second, a two-branch Multi-scale Shape Adaptive Network (MSANet) is proposed to detect and remove diverse raindrops, effectively filtering the occluded raindrop regions and keeping the clean background well-preserved. Extensive experiments on synthetic and real-world datasets demonstrate that the proposed method achieves significant improvements over the recent state-of-the-art raindrop removal methods. Moreover, the extension of our method towards the rainy image segmentation and detection tasks validates the practicality of the proposed method in outdoor applications.

Development of a Novel Piezoelectric Harvester Excited by Raindrops.

The impact of raindrops on a dry surface leads to a splashing phenomenon that dissipates a lot of energy. To improve energy collection, a novel piezoelectric raindrop energy harvester equipped with a spoonful of water was developed. The advantages and the drawbacks of this solution were analyzed with the aid of numerical simulations. A series of experimental tests were carried out in a laboratory with simulated raindrops. Experimental results showed that the negative effect of the added water mass was exceeded by the positive effects related to the impact of the raindrop on a liquid surface. Tests carried out connecting the harvester to a resistive load showed that the prototype was able to collect more energy than a simple cantilever harvester.

Elastic Droplet-Based Magnetoelectric Generator for High-performance Energy Collection.

Conventional magnetoelectric generators are regarded as effective devices for harvesting concentrated hydraulic power but are ineffective for dispersed hydropower (e.g., raindrops) due to their bulkiness and immobility. Here, we propose a superhydrophobic magnetoelectric generator (MSMEG) based on an elastic magnetic film that can efficiently convert the energy of lightweight water droplets into electricity. The MSMEG consists of five parts: a superhydrophobic magnetic material-based film (SMMF), a coil, a NdFeB magnet, an acrylic housing, and an expandable polystyrene (EPS) base. The SMMF with coil can deform/recover when droplets impact/leave the MSMEG, resulting in a peak current, peak charge density, and peak power density of ∼13.02 mA, ∼1826.5 mC/m2, and ∼1413.0 mW/m2, respectively, with a load resistance of 47 Ω. Related working mechanism is analyzed through Maxwell numerical simulation, which is used for further guidance on increasing the electrical output of the MSMEG. Furthermore, the MSMEG can quickly charge a commercial capacitor with 2.7 V/1 F to 1.18 V within 200 s and power diverse electronic devices (e.g., light emitting diodes (LEDs), fans) with constant excitation by water droplets. We believe that such an MSMEG is expected to provide a promising strategy for efficiently harvesting dispersed raindrop energy.

MARR-GAN: Memristive Attention Recurrent Residual Generative Adversarial Network for Raindrop Removal.

Since machine learning techniques for raindrop removal have not been capable of completely removing raindrops and have failed to take into account the constraints of edge devices with limited resources, a novel software-hardware co-designed method with a memristor for raindrop removal, named memristive attention recurrent residual generative adversarial network (MARR-GAN), is introduced in this research. A novel raindrop-removal network is specifically designed based on attention gate connections and recurrent residual convolutional blocks. By replacing the basic convolution unit with recurrent residual convolution unit, improved capturing of the changes in raindrop appearance over time is achieved, while preserving the position and shape information in the image. Additionally, an attention gate is utilized instead of the original skip connection to enhance the overall structural understanding and local detail preservation, facilitating a more comprehensive removal of raindrops across various areas of the image. Furthermore, a hardware implementation scheme for MARR-GAN is presented in this paper, where deep learning algorithms are seamlessly integrated with neuro inspired computing chips, utilizing memristor crossbar arrays for accelerated real-time image-data processing. Compelling evidence of the efficacy and superiority of MARR-GAN in raindrop removal and image restoration is provided by the results of the empirical study.

A shallow water numerical method for assessing impacts of hydrodynamics and nutrient transport processes on water quality values of Lake Victoria.

Lake Victoria is the world's largest tropical lake and the third-largest water body, providing significant water resources for surrounding environments including the cultural, societal, and livelihood needs of people in its basin and along the White Nile. The aim of this study was to use decade-long time series of measured lake flow in the lake system and phosphorus deposition to develop a suitable numerical model based on shallow water equations (SWE) for assessing water quality in Lake Victoria, an increasingly important tool under climate variation. Different techniques were combined to identify a numerical model that included: i) a high-resolution SWE model to establish raindrop diffusion to trace pollutants; ii) a two-dimensional (2D) vertically integrated SWE model to establish lake surface flow and vertically transported wind speed flow acting on lake surface water by wind stress; and iii) a site-specific phosphorus deposition sub-model to calculate atmospheric deposition in the lake. A smooth (non-oscillatory) solution was obtained by applying a high-resolution scheme for a raindrop diffusion model. Analysis with the vertically integrated SWE model generated depth averages for flow velocity and associated changes in water level profile in the lake system and showed unidirectional whole lake wind blowing from the southwest to northeast. The atmospheric phosphorous deposition model enabled water value assessment for mass balances with different magnitudes of both inflows and outflows demonstrating annual total phosphorus at 13,500 tons concentrating at mid-lake western and eastern parts. The model developed here is simple and suitable for use in assessing flow changes and lake level changes and can serve as a tool in studies of lake bathymetry and nutrient and pollution transport processes. Our study opens towards refining models of complex shallow-water systems.

Thallium release from biochar-amended soil to runoff in laboratory experiments.

Biochar has been widely used for trace metal(loid) (TM) immobilisation in contaminated soils. However, studies on the physicochemical mobility of TMs related to biochar application are highly limited, hampering the evaluation of the immobilisation efficiency of biochar. Therefore, after confirming the ability of biochar to decrease soil Tl bioavailability, this study examined the release of Tl in dissolved and particulate forms in surface runoff and leachate from soil mixed with biochar at different dosages and grain sizes under artificially simulated rainfall and irrigation experiments. The rainfall experimental results showed that the dissolved Tl in the surface runoff decreased from 1.30 µg in the control group to 0.75 µg and 0.54 µg in the groups with 3% and 5% biochar application, respectively. With the same dosages (5%), the finer the biochar applied, the higher the immobilisation ability achieved in surface runoff and the lower the Tl amounts in the leachate, indicating that the grain size of biochar can impact Tl mobility in dissolved forms. Comparisons between rainfall and irrigation experiments indicated that raindrops disturb the soil-water surface and enhance Tl diffusion. The mass in particulate form accounted for more than 95% of lateral released Tl in surface runoff. However, biochar application did not decrease the enrichment ratio of Tl in the eroded sediments. Notably, the finest biochar group produced less mass of eroded Tl owing to the low flux of soil erosion, indicating that grain size would indirectly impact sediment-bound Tl lateral mobility. Colloidal particles should be highlighted as they carried a maximum TI of up to 38% in the rainfall leachate. Focusing on the effect of biochar application on Tl chemical- and physical mobility from the soil matrix to runoff, this study contributes the comprehensive understanding of the role of biochar in TM remediation.

Runoff and soil loss in biocrusts and physical crusts from the Tabernas Desert (southeast Spain) according to rainfall intensity.

Biological soil crusts (biocrusts) influence hydrological and erosive processes in drylands, and their effects increase with hypothetic successional development. Runoff and raindrops, both dependent on rain intensity, are among the main causes of erosion in these areas. However, little is known about the existence of soil loss nonlinearity in relation to rain intensity and crust types; this nonlinearity could control biocrust succession and dynamics. The assumption of biocrust types as successional stages, which allow space-for-time sampling, makes it advisable to include all the successional stages when exploring possible nonlinearity. We considered seven types of crusts, three physical and four biological. We created four rainfall intensity levels in controlled laboratory conditions: 18, 60, 120, and 240 mm/h. In all but the last, we conducted the experiments at two levels of antecedent soil moisture. Generalized Lineal Models enabled us to test for differences. These analyses confirmed previous knowledge regarding the significant effect of rainfall intensity, crust type and antecedent soil moisture and their interactions on runoff and soil loss, despite the small sample size of the sample units. For example, runoff, and particularly soil loss, decreased along succession. Moreover, some results were novel: the runoff coefficient increased only up to 120 mm/h of rain intensity. A decoupling between runoff and soil loss occurred at high intensities. Soil loss increased as rainfall intensity increased only up to 60 mm/h, and then it decreased, mainly due to physical crusts, because of the formation of a water sheet on the surface due to the incoming rainwater exceeding the drainage capacity. Although soil loss was greater in the incipient cyanobacteria than in the most developed lichen biocrust (Lepraria community), the protection provided by any biocrust against soil loss was great compared to the physical crust, and almost as strong at all rain intensities. Soil loss increased with antecedent soil moisture only in physical crusts. Biocrusts resisted the rain splash even at a rainfall intensity of 240 mm/h.

Context and detail interaction network for stereo rain streak and raindrop removal.

Recently stereo image deraining has attracted lots of attention due to its superiority of abundant information from cross views. Exploring interaction information across stereo views is the key to improving the performance of stereo image deraining. In this paper, we design a general coarse-to-fine deraining framework for stereo rain streak and raindrop removal, called CDINet, comprising a stereo rain removal subnet and a stereo detail recovery subnet to restore images progressively. Two types of interaction modules are devised to explore interaction information for rain removal and detail recovery, respectively. Specifically, a global context interaction module is proposed to learn long-range dependencies of stereo images and remove rain by utilizing stereo structural information. A local detail interaction module is designed to model local contextual correlation, which aims at restoring the detail information by using neighborhood information from cross views. Extensive experiments are conducted on the two datasets including a synthetic rain streak removal dataset (RainKITTI) and a real raindrop removal dataset (Stereo Waterdrop), which demonstrates that our method sets new state-of-the-art deraining performance in terms of both quantitative and qualitative metrics with faster speed.

An Integrated Solar Panel with a Triboelectric Nanogenerator Array for Synergistic Harvesting of Raindrop and Solar Energy.

The triboelectric nanogenerator (TENG) is regarded as an effective strategy for harvesting energy from raindrops, and is a complementary solution with solar cells to achieve all-weather energy harvesting and sustainable energy supply. However, due to the irregularity of natural rainfalls in the volume, frequency, density, and location, designing high-efficiency raindrop TENG (R-TENG) arrays faces great challenges. In this work, a highly transparent, large-area, and high-efficiency R-TENG array with rational material choice, electrode structure, and array distribution is developed for efficiently harvesting irregular raindrop energy. The problem of electrical signal cancellation among adjacent raindrops can be fully avoided, as viewed from the high-resolution space-time analyses of high-speed camera and electrical signal characteristics. With the rationally designed electrode instead of multiple complex electrodes, all charges can be exported by the R-TENG array in a simulated irregular raindrop scenario. Moreover, it is demonstrated that the R-TENG possesses higher average power density (40.80 mW m-2 ) than that of the solar cell (37.03 mW m-2 ) in rainy condition. Additionally, a self-powered wireless light-intensity-monitoring system is demonstrated for real-time and all-day weather monitoring. This work provides useful guidance for designing high-efficiency TENG arrays integrated with solar panels for harvesting irregular raindrop energy and solar energy.

Effects of cyanobacteria- and moss-biocrusts on soil aggregate stability and splash erosion in croplands of the China Mollisols area.

To investigate the effects of biocrusts development on aggregate stability and splash erosion of Mollisols and to understand its function in soil and water conservation, we collected biocrusts (cyano crust and moss crust) samples in croplands during the growing season and measured the differences in aggregate stability between biocrusts and uncrusted soil. The effects of biocrusts on reduction of raindrop kinetic energy were determined and splash erosion amounts were obtained with single raindrop and simulated rainfall experiments. The correlations among soil aggregate stability, splash erosion characteristics, and fundamental properties of biocrusts were analyzed. The results showed that compared to uncrusted soil, the cyano crust and the moss crust decreased the proportion of soil water-stable aggregates <0.25 mm by 10.5% and 21.8%, respectively, while their soil water-stable aggregates 5-10 mm were 4.0 and 8.8 times as that of uncrusted soil. In contrast to uncrusted soil, the macroaggregate content (R0.25), mean weight diameter (MWD), and geometric mean diameter (GMD) of biocrusts were 31.5%, 76.2%, and 33.5% higher, respectively. In addition, biocrusts reduced raindrop kinetic energy by an average of 0.48 J compared to uncrusted soil. The breakthrough raindrop kinetic energy of cyano crust and moss crust were 2.9 and 26.2 times as that of uncrusted soil, while the reduction of raindrop kinetic energy by cyano crust with high biomass was 1.3 and 6.6 times as that of medium and low biomass, respectively. Under the single raindrop and simulated rainfall conditions, biocrusts reduced splash erosion amounts by 47.5% and 79.4%, respectively. The proportion of aggregates >0.25 mm in the splash soil particles of biocrusts (37.9%) was 40.3% lower than that of uncrusted soil, while the proportion of aggregates >0.25 mm decreased as biocrust biomass increased. Moreover, the aggregate stability, splash erosion amount, and fundamental properties of biocrusts were significantly correlated. The MWD of aggregates was significantly and negatively correlated with the splash erosion amount under single raindrop and simulated rainfall conditions, indicating that the improved aggregate stability of surface soil caused by biocrusts accounted for reducing splash erosion. The biomass, thickness, water content, and organic matter content of biocrusts had significant effects on aggregate stability and splash characteristics. In conclusion, biocrusts significantly promoted soil aggregate stability and reduced splash erosion, which had great significance to soil erosion prevention and the conservation and sustainable utilization of Mollisols.

Links between aerosol radiative forcing and rain characteristics: Stratiform and convective precipitation.

The radiative forcing before and after rain events was studied between 12 February 2016 and 14 March 2017 in León, Spain. For this purpose, the radiative forcing fluxes were calculated using the Radiative Transfer Model Global Atmospheric ModEl (RTM GAME). After the application of a set of selection criteria (based on the availability of AERONET data, rain characteristics and lightning maps), 16 stratiform rain events were identified, concentrated in spring and winter, and 15 convective rain events were found concentrated in spring and summer. Rainfall events were grouped according to the atmospheric forcing (ΔFATM) before rain: "low" or "high" (lower or higher than 30 W m-2). The threshold has been set at this value because it is the mean ΔFATM of all the selected events before rain. There were significant statistical differences between stratiform and convective events in rain duration, mean raindrop diameter and parameters a and b of radar reflectivity Z and rainfall intensity R relationship (Z = a Rb). When comparing "low" and "high" groups, raindrop diameter was similar in stratiform (0.51 ± 0.08 vs 0.48 ± 0.12 mm) and convective events (0.96 ± 0.98 vs 0.83 ± 0.63 mm), registering higher values for the latter. In stratiform events, the rain scavenging effect on aerosol particles is clearly observed in the "high" group with a decrease of radiative forcing of -27.0 ± 25.3%, and to a lesser extent, in the "low" group, probably because of a lower aerosol load in the atmosphere. In stratiform events, the mode of the raindrop size gamma distribution presented statistical differences between "low" (0.25 ± 0.13 mm) and "high" (0.35 ± 0.05 mm) groups. We claim that this points towards a relationship between radiative forcing before rain and the specific characteristics of rainfall measured at ground level. This study increases our knowledge on the important role of rainwater as a clean agent of the atmosphere and its impact on climate (through radiative forcing).

Interface Engineering for Efficient Raindrop Solar Cell.

A raindrop solar cell can work either on rainy days to collect mechanical energy of the raindrops or on sunny days to harvest solar energy, which achieves high energy conversion efficiency in various energy environments. However, the low efficiency of raindrop energy harvesting is a dominating barrier to the raindrop solar cells in practical applications. In this work, a MoO3/top electrode-based triboelectric nanogenerator (MT-TENG) with high rain droplet energy conversion efficiency, integrated with a perovskite solar cell through shared electrodes, has been proposed. The interface electrons between the triboelectric layer and electrode can be blocked by the MoO3 layer with high permittivity and wide bandgap, and the MoO3-based TENG (M-TENG) therefore increases the surface charge density. Thus, the top electrode structure in the solid-liquid interface can greatly increase the output charge by 101.1 times in total. By adjusting the water droplet parameters of tap water to simulate the actual application scenario, the raindrop output power and mechanical energy conversion efficiency can reach 0.68 mW and 12.49%, respectively. In addition, due to the high transmittance of the MT-TENG, the perovskite solar cell can still sustain a high photovoltaic power conversion efficiency of 19.38%. By virtue of the shared electrode circuit design, the raindrop solar cell can continue to purvey electric power on rainy and sunny days, and it only takes about 175 s to charge a 2.2 µF capacitor to 5 V.

Review of Presbyopia Treatment with Corneal Inlays and New Developments.

Presbyopia may represent the largest segment of refractive errors that is without an established and effective refractive surgery treatment. Corneal Inlays are materials (synthetic or allogenic) implanted in the stroma of patients' corneas to improve presbyopia. These inlays, introduced into the United States in 2015 via the small-aperture corneal inlay (KAMRATM, SightLife Surgical/CorneaGen, Seattle, Washington, United States), were met with an initial wave of enthusiasm. Subsequent models like the shape-changing corneal inlay (RAINDROPTM, Revision Optics, Lake Forest, California, United States) offered excellent results for patients, but longer-term research raised questions about patient safety. At the time of this article, no synthetic corneal inlays are available in the United States for the correction of presbyopia. Other options for presbyopia correction include allograft corneal inlays, trifocal synthetic corneal inlays, pharmacologic therapies, scleral incisions or additive techniques and PresbyLASIK. Presently, allograft inlays consist of corneal lenticules removed from patients undergoing Small Incision Lenticule Extraction (SMILE). We will review corneal inlays and other alternative procedures that may provide effective and predictable treatments for patients with presbyopia.

Textile Triboelectric Nanogenerators Simultaneously Harvesting Multiple "High-Entropy" Kinetic Energies.

Distributed renewable kinetic energies are ubiquitous but with irregular amplitudes and frequencies, which, as one category of "high-entropy" energies, are crucial for next-generation self-powered electronics. Herein, we present a flexible waterproof dual-mode textile triboelectric nanogenerator (TENG), which can simultaneously scavenge multiple "high-entropy" kinetic energies, including human motions, raindrops, and winds. A freestanding-mode textile TENG (F-TENG) and a contact-separation-mode textile TENG (CS-TENG) are integrated together. The structure parameters of the textile TENG are optimized to improve the output performances. The raindrop can generate a voltage of up to ∼4.3 V and a current of about ∼6 µA, while human motion can generate a voltage of over 120 V and a peak power density of ∼500 mW m-2. The scavenged electrical energies can be stored in capacitors for powering small electronics. Therefore, we demonstrated a facile preparation of a TENG-based energy textile that is highly promising for kinetic energy harvesting and self-powered electronics.