Electricity-Driven Strategies for Bioinspired Multifunctional Swimming Marangoni Robots Based on Super-Aligned Carbon Nanotube Composites.

Marangoni actuators that are propelled by surface tension gradients hold significant potential in small-scale swimming robots. Nevertheless, the release of "fuel" for conventional chemical Marangoni actuators is not easily controllable, and the single swimming function also limits application areas. Constructing controllable Marangoni robots with multifunctions is still a huge challenge. Herein, inspired by water striders, electricity-driven strategies are proposed for a multifunctional swimming Marangoni robot (MSMR), which is fabricated by super-aligned carbon nanotube (SACNT) and polyimide (PI) composite. The MSMR consists of a Marangoni actuator and air-ambient actuators. Owing to the temperature gradient generated by the electrical stimulation on the water surface, the Marangoni actuators can swim controllably with linear, turning, and rotary motions, mimicking the walking motion of water striders. In addition, the Marangoni actuators can also be driven by light. Importantly, the air-ambient actuators fabricated by SACNT/PI bilayer structures demonstrate the function of grasping objects on the water surface when electrically Joule-heated, mimicking the predation behavior of water striders. With the synergistic effect of the Marangoni actuator and air-ambient actuators, the MSMR can navigate mazes with tunnels and grasp objects. This research will provide a new inspiration for smart actuators and swimming robots.

Association study of FLT4 and HYDIN single nucleotide polymorphisms with atrial septal defect susceptibility in the Han Chinese population of Southwest China.

BACKGROUND: Atrial septal defect (ASD) is a common form of congenital heart disease. Although several genes related to ASD have been found, the genetic factors of ASD remain unclear. This study aimed to evaluate the correlation between 10 candidate single nucleotide polymorphisms (SNPs) and sporadic atrial septal defects. METHODS: Based on the results of 34 individual whole exome sequences, 10 candidate SNPs were selected. In total, 489 ASD samples and 420 normal samples were collected. The 10 SNPs in the case group and the control group were identified through Snapshot genotyping technology. The χ2-test and unconditional regression model were used to evaluate the relationship between ASD and each candidate SNP. Haploview software was used to perform linkage disequilibrium and haplotype analysis. RESULTS: The χ2 results showed that the FLT4 rs383985 (P = 0.003, OR = 1.115-1.773), HYDIN rs7198975 (P = 0.04621, OR = 1.003-1.461), and HYDIN rs1774266 (P = 0.04621, OR = 1.003-1.461) alleles were significantly different between the control group and the case group (P < 0.05). Only the association with the FLT4 polymorphism was statistically significant after adjustment for multiple comparisons. CONCLUSION: These findings suggest that a possible molecular pathogenesis associated with sporadic ASD is worth exploring in future studies.

"Sweat-Driven" MXene Composites with Energy-Storage and Thermal-Management Multifunctions: A Platform for Versatile Electronic Skins.

Most exogenous electronic skins (e-skins) currently face challenges of complex structure and poor compatibility with the human body. Utilizing human secretions (e.g., sweat) to develop e-skins is an effective solution strategy. Here, a new kind of "sweat-driven" e-skin is proposed, which realizes energy-storage and thermal-management multifunctions. Through the layer-by-layer assembly of MXene-carbon nanotube (CNT) composite with paper, lightweight and versatile e-skins based on supercapacitors and actuators are fabricated. Long CNTs wrap and entangle MXene nanosheets, enhancing their long-distance conductivity. Furthermore, the CNT network overcomes the structural collapse of MXene in sweat, improving the energy-storage performance of e-skin. The "sweat-driven" all-in-one supercapacitor with a trilayer structure is patternable, which absorbs sweat as electrolyte and harnesses the ions therein to store energy, exhibiting an areal capacitance of 282.3 mF cm-2 and a high power density (2117.8 µW cm-2 ). The "sweat-driven" actuator with a bilayer structure can be driven by moisture (bending curvature of 0.9 cm-1 ) and sweat for personal thermal management. Therefore, the paper serves as a separator, actuating layer, patternable layer, sweat extractor, and reservoir. The "sweat-driven" MXene-CNT composite provides a platform for versatile e-skins, which achieve the interaction with humans and offer insights into the development of multifunctional wearable electronics.

A PEDOT:PSS/MXene-based actuator with self-powered sensing function by incorporating a photo-thermoelectric generator.

Actuators with sensing functions are becoming increasingly important in the field of soft robotics. However, most of the actuators are lack of self-powered sensing ability, which limits their applications. Here, we report a light-driven actuator with self-powered sensing function, which is designed to incorporate a photo-thermoelectric generator into the actuator based on poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)/MXene composite and polyimide. The actuator shows a large bending curvature of 1.8 cm-1 under near-infrared light (800 mW cm-2) irradiation for 10 s, which is attribute to photothermal expansion mismatch between PEDOT:PSS/MXene composite and polyimide. Simultaneously, the actuator shows enhanced thermoelectric properties with Seebeck coefficient of 35.7 µV K-1, which are mainly attributed to a combination of energy filtering effects between the PEDOT:PSS and MXene interfaces as well as the synergistic effect of its charge carrier migration. The output voltage of the actuator changes in accordance with the bending curvature, so as to achieve the self-powered sensing function and monitor the operating state of the actuator. Moreover, a bionic flower is fabricated, which not only simulates the blooming and closing of the flower, but also perceives the real-time actuation status through the output voltage signal. Finally, a smart Braille system is elaborately designed, which can not only simulate Braille characters for tactile recognition of the blind people, but also automatically output the voltage signal of Braille for self-powered sensing, enabling multi-channel output and conversion of light energy. This research proposes a new idea for exploring multifunctional actuators, integrated devices and self-powered soft robots.

A generalized deep learning model for heart failure diagnosis using dynamic and static ultrasound.

Objective: Echocardiography (ECG) is the most common method used to diagnose heart failure (HF). However, its accuracy relies on the experience of the operator. Additionally, the video format of the data makes it challenging for patients to bring them to referrals and reexaminations. Therefore, this study used a deep learning approach to assist physicians in assessing cardiac function to promote the standardization of echocardiographic findings and compatibility of dynamic and static ultrasound data. Methods: A deep spatio-temporal convolutional model r2plus1d-Pan (trained on dynamic data and applied to static data) was improved and trained using the idea of "regression training combined with classification application," which can be generalized to dynamic ECG and static cardiac ultrasound views to identify HF with a reduced ejection fraction (EF < 40%). Additionally, three independent datasets containing 8976 cardiac ultrasound views and 10085 cardiac ultrasound videos were established. Subsequently, a multinational, multi-center dataset of EF was labeled. Furthermore, model training and independent validation were performed. Finally, 15 registered ultrasonographers and cardiologists with different working years in three regional hospitals specialized in cardiovascular disease were recruited to compare the results. Results: The proposed deep spatio-temporal convolutional model achieved an area under the receiveroperating characteristic curve (AUC) value of 0.95 (95% confidence interval [CI]: 0.947 to 0.953) on the training set of dynamic ultrasound data and an AUC of 1 (95% CI, 1 to 1) on the independent validation set. Subsequently, the model was applied to the static cardiac ultrasound view (validation set) with simultaneous input of 1, 2, 4, and 8 images of the same heart, with classification accuracies of 85%, 81%, 93%, and 92%, respectively. On the static data, the classification accuracy of the artificial intelligence (AI) model was comparable with the best performance of ultrasonographers and cardiologists with more than 3 working years (P = 0.344), but significantly better than the median level (P = 0.0000008). Conclusion: A new deep spatio-temporal convolution model was constructed to identify patients with HF with reduced EF accurately (< 40%) using dynamic and static cardiac ultrasound images. The model outperformed the diagnostic performance of most senior specialists. This may be the first HF-related AI diagnostic model compatible with multi-dimensional cardiac ultrasound data, and may thereby contribute to the improvement of HF diagnosis. Additionally, the model enables patients to carry "on-the-go" static ultrasound reports for referral and reexamination, thus saving healthcare resources.

Self-chargeable supercapacitor made with MXene-bacterial cellulose nanofiber composite for wearable devices.

The development of wearable electronics is restricted by the developments of supporting energy storage devices, especially flexible supercapacitors. Nowadays, miniaturized supercapacitors based on MXenes due to their obvious advantages in the specific capacity have received extensive attention. The energy existing in the surrounding environment has been used to directly charge energy storage devices. However, the hybrid wearable electronics integrated supercapacitors are mechanically connected through metal wires leading to non-compact devices. Thus, it is urgent to develop a general and universal method to fabricate high-performance robust MXene-based flexible electrodes with high electrical conductivity and apply them to self-chargeable supercapacitors and compact wearable devices. Herein, the bacterial cellulose (BC) nanofibers are used as a crosslinking agent to connect two-dimensional MXene nanosheets through the hydrogen bond, which greatly improves the mechanical strength of MXene-bacterial cellulose (MXene-BC) composite films (Young's modulus reaching 6.8 GPa). The supercapacitors made with the electrodes of MXene-BC composite films (BC content is 10%) present high capacitance behavior (areal capacitance up to 346 mF cm-2) because the introduction of BC nanofibers increases the interlayer spacing of MXene nanosheets, providing more storage space for the ions in the electrolyte. Then, a self-chargeable supercapacitor is proposed based on the combination of a zinc-air (Zn-air) battery and a supercapacitor. The self-chargeable supercapacitor can realize self-charging after dropping a drop of electrolyte solution into the Zn-air battery. The charging voltage of a single self-chargeable supercapacitor can reach 0.6 V after adding artificial sweat as the electrolyte. Finally, a smart wristband with the function of self-charging is proposed, which can absorb the sweat generated by the human for self-chargeable supercapacitors to drive the pedometer integrated within the smart wristband to work. The proposed self-chargeable supercapacitors are simple and effective, not restricted by the use environment, providing a promising way for self-powered wearable electronics.

Generation of attosecond micro bunched beam using ionization injection in laser wakefield acceleration.

Micro bunched electron beams with periodic longitudinal density modulation at optical wavelengths give rise to coherent light emission. In this paper, we show attosecond micro bunched beam generation and acceleration in laser-plasma wakefield via particle-in-cell simulations. Due to the near-threshold ionization with the drive laser, the electrons with phase-dependent distributions are non-linearly mapped to discrete final phase spaces. Electrons can preserve this initial bunching structure during the acceleration, leading to an attosecond electron bunch train after leaving the plasma with separations of the same time scale. The modulation of the comb-like current density profile is about 2k0 ∼ 3k0, where k0 is the wavenumber of the laser pulse. Such pre-bunched electrons with low relative energy spread may have potential in applications related to future coherent light sources driven by laser-plasma accelerators and broad application prospects in attosecond science and ultrafast dynamical detection.

Automated deep neural network-based identification, localization, and tracking of cardiac structures for ultrasound-guided interventional surgery.

Background: The increase in the use of ultrasound-guided interventional therapy for cardiovascular diseases has increased the importance of intraoperative real-time cardiac ultrasound image interpretation. We thus aimed to develop a deep learning-based model to accurately identify, localize, and track the critical cardiac structures and lesions (9 kinds in total) and to validate the algorithm's performance using independent data sets. Methods: This diagnostic study developed a deep learning-based model using data collected from Fuwai Hospital between January 2018 and June 2019. The model was validated with independent French and American data sets. In total, 17,114 cardiac structures and lesions were used to develop the algorithm. The model findings were compared with those of 15 specialized physicians in multiple centers. For external validation, 516,805 tags and 27,938 tags were used from 2 different data sets. Results: Regarding structure identification, the area under the receiver operating characteristic curve (AUC) of each structure in the training data set, optimal performance in the test data set, and median AUC of each structure identification were 1 (95% CI: 1-1), 1 (95% CI: 1-1), and 1 (95% CI: 1-1), respectively. Regarding structure localization, the optimal average accuracy was 0.83. As for structure identification, the accuracy of the model significantly outperformed the median performance of the experts (P<0.01). The optimal identification accuracies of the model in 2 independent external data sets were 89.5% and 90%, respectively (P=0.626). Conclusions: The model outperformed most human experts and was comparable to the optimal performance of all human experts in cardiac structure identification and localization, and could be used in the external data sets.

Transcatheter closure of perimembranous ventricular septal defect using a novel fully bioabsorbable occluder: multicenter randomized controlled trial.

Although the use of bioabsorbable occluder is expected to reduce the risk of metal occluder-related complications, it has not been approved due to incomplete degradation and new complications. Novel fully bioabsorbable occluders were designed to overcome such limitations. The aim of this study was to investigate the efficacy and safety of a fully biodegradable occluder in patients with ventricular septal defects. 125 patients with perimembranous ventricular septal defect (VSD) larger than 3 mm were screened from April 2019 to January 2020 in seven centers. 108 patients were enrolled and randomized into the bioabsorbable occluder group (n = 54 patients) and nitinol occluder group (n = 54). A non-inferiority design was utilized and all patients underwent transcatheter device occlusion. Outcomes were analyzed with a 24-month follow-up. All patients were successfully implanted and completed the trial. No residual shunt >2 mm was observed during follow-up. Transthoracic echocardiography showed a hyperechoic area corresponding to the bioabsorbable occluder which decreased primarily during the first year after implantation and disappeared within 24 months. Postprocedural arrhythmia was the only occluder-related complication with an incidence of 5.56% and 14.81% for the bioabsorbable and nitinol groups, respectively (P = 0.112). The incidence of sustained conduction block was lower in the bioabsorbable occluder group (0/54 vs. 6/54, P = 0.036) at 24-month follow-up. In conclusion, the novel fully bioabsorbable occluder can be successfully and safely implanted under echocardiography guidance and reduce the incidence of sustained postprocedural arrythmia. The efficacy and safety of this fully biodegradable occluder are non-inferior to that of a traditional nitinol one.

Cardiac function evaluated by two-dimensional speckle tracking imaging in fetuses with congenital heart disease of ventricular afterload increase.

AIMS: To study myocardial deformation in fetuses with ventricular afterload increase compared with gestational age-matched controls using speckle tracking echocardiography. METHODS AND RESULTS: Eighty-nine fetuses were retrospectively selected from the pregnancy screen by echocardiography. There are 41 fetuses with gestational age-matched normal heart served as the control group, 25 fetuses with congenital heart disease (CHD) leading to left ventricular (LV) afterload increase as group LVA and 23 fetuses with CHD leading to right ventricular(RV) afterload increases as group RVA. LV and RV fractional shortening (FS) were measured by conventional methods. The longitudinal strain (LS) and strain rate (LSr) were analyzed by EchoPac software. Group LVA and RVA compared with control group, the LV FS was no significant difference, but LS and LSr values of LV were lower in fetuses with LVA compared to the control group (LS:-15.97(-12.50,-22.52)vs -27.53(-24.33,-29.16) %, p < .01; systolic strain rate (SRs):-1.34(-1.12,-2.16) vs -2.55(-2.28,-2.92) 1/sec, p < .01; early diastolic strain rate (SRe):1.70 ± 0.57 vs 2.46 ± 0.61 1/sec, p < 0.01; late diastolic strain rate (SRa):1.62 ± 0.82 vs 2.39 ± 0.81 1/sec, p < .01). LS and LSr values of LV or RV were lower in fetuses with RVA compared to the control group (LV: LS:-21.52 ± 6.68 vs -26.79 ± 3.22%, p < .01; SRs:-2.11 ± 0.78 vs -2.56 ± 0.43 1/sec; p = .02; RV: LS:-17.64 ± 7.58 vs -26.38 ± 3.97%, p < .01; SRs:-1.62 ± 0.67 vs -2.37 ± 0.44 1/sec; p < .01). CONCLUSION: The results of this study showed that the ventricular LS, LSr, SRs, SRe, SRa values were lower in fetuses with LV or RV afterload increasing CHD estimated by speckle tracking imaging but LV and RV FS were normal,which indicated the strain imaging is feasible in evaluating cardiac function of fetus, and may be more sensitive.

Pencil-Drawn Generator Built-in Actuator for Integrated Self-Powered/Visual Dual-Mode Sensing Functions and Rewritable Display.

Multifunctionality is important to the development of next-generation actuators and intelligent robots. However, current multi-functional actuating systems are achieved based on the integration of diverse functional units with complex design, especially lacking in multi-mode sensing and displaying functions. Herein, a light-driven actuator integrated with self-powered/visual dual-mode sensing functions and rewritable display function is proposed. The actuator demonstrates a bending curvature of 0.93 cm-1 under near-infrared light irradiation. Meanwhile, by embedding a pencil-drawn graphite generator and thermochromic materials, the actuator also provides two independent sensing functions. First, owing to the photo-thermoelectric effect of graphite, the actuator spontaneously outputs a self-powered voltage (Seebeck coefficient: 23 µV K-1 ), which can reflect the deformation trend of actuator. Second, color changes occur on the actuator during deformation, which provide a visual sensing due to the thermochromic property. Furthermore, the actuator can be utilized as a rewritable display, owing to the integrated color-memorizing component. Intelligent robots, switches, and smart homes are further demonstrated as applications. All of them can spontaneously provide self-powered and visual sensing signals to demonstrate the working states of actuating systems, accompanied by rewritable displays on the actuators. This study will open a new direction for self-powered devices, multi-functional actuators, and intelligent robots.

A Detailed Study to Discover the Trade between Left Atrial Blood Flow, Expression of Calcium-Activated Potassium Channels and Valvular Atrial Fibrillation.

Background: The present study aimed to explore the correlation between calcium-activated potassium channels, left atrial flow field mechanics, valvular atrial fibrillation (VAF), and thrombosis. The process of transforming mechanical signals into biological signals has been revealed, which offers new insights into the study of VAF. Methods: Computational fluid dynamics simulations use numeric analysis and algorithms to compute flow parameters, including turbulent shear stress (TSS) and wall pressure in the left atrium (LA). Real-time PCR and western blotting were used to detect the mRNA and protein expression of IKCa2.3/3.1, ATK1, and P300 in the left atrial tissue of 90 patients. Results: In the valvular disease group, the TSS and wall ressure in the LA increased, the wall pressure increased in turn in all disease groups, mainly near the mitral valve and the posterior portion of the LA, the increase in TSS was the most significant in each group near the mitral valve, and the middle and lower part of the back of the LA and the mRNA expression and protein expression levels of IKCa2.3/3.1, AKT1, and P300 increased (p < 0.05) (n = 15). The present study was preliminarily conducted to elucidate whether there might be a certain correlation between IKCa2.3 and LA hemodynamic changes. Conclusions: The TSS and wall pressure changes in the LA are correlated with the upregulation of mRNA and protein expression of IKCa2.3/3.1, AKT1, and P300.

Are There Any Differences in the Prognostic Value of Left Ventricular Ejection Fraction in Coronary Artery Disease Patients With or Without Moderate and Severe Mitral Regurgitation?

Background: Left ventricular ejection fraction (LVEF) is a vital variable to describe left ventricle systolic function and contractility of left ventricle. However, the association between LVEF and the prognostic effect in patients with moderate or severe mitral regurgitation (MR) is still controversial. Methods: This study comprised 30,775 coronary artery disease (CAD) patients who underwent coronary arteriography (CAG) in the Cardiorenal ImprovemeNt (CIN) registry from January 2007 to December 2018. Patients were divided into none or mild MR group and moderate or severe MR group, and 3 levels of LVEF ≥50, 40-50%, and <40% were further distinguished according to hospital baseline. Univariate and multivariate Cox proportional analyses were used to investigate the association between LVEF levels and long-term all-cause mortality in patients with different MR severities. Results: Of 30,775 CAD patients (62.9 ± 10.6 years, females 23.8%), 26,474 (86.0%) patients had none or mild MR. Compared with none or mild MR patients, patients with moderate or severe MR were older and had worse cardio-renal function. In multivariable Cox proportional analysis, LVEF <40% was independently associated with higher mortality compared with LVEF ≥ 50% in all kinds of MR severity {none or mild MR [adjusted hazard ratio (HR): 1.79; 95% CI: 1.56-2.05, p < 0.001], moderate or severe MR [adjusted HR: 1.57; 95% CI: 1.29-1.91, p < 0.001]}. Conclusions: LVEF is a reliable prognostic index in CAD patients, even in those with moderate or severe MR. LVEF monitoring would still be clinically useful in CAD patients with moderate or severe MR. Clinical trials are needed to prospectively evaluate the optimal threshold for LVEF in patients with moderate or severe MR.

Initial experiences of transapical beating-heart mitral valve repair with a novel artificial chordal implantation device.

BACKGROUND: Severe mitral regurgitation (MR) is associated with progressive heart failure and impairment of survival. Degenerative MR accounts for most MV repair surgeries. Conventional mitral valve repair surgery requires cardiopulmonary bypass and is associated with significant morbidity and risks. Transapical beating-heart mitral valve repair by artificial chordae implantation with transesophageal echocardiography (TEE) guidance has the potential to significantly reduce surgical morbidity. We report the first-in-human experience of degenerative MR repair using a novel artificial chordae implantation device (MitralstitchTM system). METHODS: Ten patients with severe MR underwent transapical artificial chordae implantation using MitralstitchTM system. The procedure was performed through a small left thoracotomy under general anesthesia and TEE guidance. Patients underwent transthoracic echocardiography and other assessments during the follow-up. RESULTS: All 10 patients with an average age of 63.7 ± 9.6 years successfully received transapical artificial chordae implantation. Their MR reduced from severe to none or trace in five patients, mild in five patients before discharge. Five patients received one artificial chordal implantation, four patients received two, and one patient received three and edge-to-edge repair by locking two of them. The safety and efficacy endpoint were achieved in all patients at 1-month follow-up. At 1-year follow-up, six patients had mild MR, three patients had moderate MR, one patient had recurrence of severe MR and underwent surgical repair. CONCLUSIONS: The results of this first-in-human study show safety and feasibility of transapical mitral valve repair using MitralStitch system. Patient selection and technical refinement are crucial to improve the outcomes.

Understanding Smartphone Users From Installed App Lists Using Boolean Matrix Factorization.

Smartphones are changing humans' lifestyles. Mobile applications (apps) on smartphones serve as entries for users to access a wide range of services in our daily lives. The apps installed on one's smartphone convey lots of personal information, such as demographics, interests, and needs. This provides a new lens to understand smartphone users. However, it is difficult to compactly characterize a user with his/her installed app list. In this article, a user representation framework is proposed, where we model the underlying relations between apps and users with Boolean matrix factorization (BMF). It builds a compact user subspace by discovering basic components from installed app lists. Each basic component encapsulates a semantic interpretation of a series of special-purpose apps, which is a reflection of user needs and interests. Each user is represented by a linear combination of the semantic basic components. With this user representation framework, we use supervised and unsupervised learning methods to understand users, including mining user attributes, discovering user groups, and labeling semantic tags to users. Extensive experiments were conducted on three data subsets from a large-scale real-world dataset for evaluation, each consisting of installed app lists from over 10 000 users. The results demonstrated the effectiveness of our user representation framework.

Pressure-Perceptive Actuators for Tactile Soft Robots and Visual Logic Devices.

Soft actuators with sensing capabilities are important in intelligent robots and human-computer interactions. However, present perceptive actuating systems rely on the integration of multiple functional units with complex circuit design. Here, a new-type pressure-perceptive actuator is reported, which integrates functions of sensing, actuating, and decision making at material level without complex combination. The actuator is composed of an actuating unit and a pressure-sensing unit, both of which are fabricated by carbon nanotube (CNT), silk, and polymer composite. On the one hand, the actuating unit can be driven by low voltages (<13 V), owing to a Joule-heating effect. On the other hand, the current passing the pressure-sensing unit can be controlled by tactile pressure. In the integrated actuator, it is able to control the deformation amplitude of actuating unit by applying different pressures on the pressure-sensing unit. A portable tactile-activated gripper is fabricated to operate an object through pressure control, demonstrating its application in tactile soft robots. Finally, three visual logic gates (AND, OR, and NOT) are proposed, which convert "tactile" inputs into "visible" deformation outputs, using the CNT-silk-based material for sensing and actuating in the decision-making process. This study provides a new path for intelligent soft robots and new-generation logic devices.

Chinese ink: a programmable, dual-responsive and self-sensing actuator using a healing-assembling method.

Actuators have wide applications in soft robotics and bionic devices. Since the healing ability not only makes actuators have longer service lives, but also allows them to be programmable through welding and assembling, it is regarded as an important feature for state-of-the-art actuators. Nevertheless, it remains a great challenge to integrate multi-functional merits, such as multi-responsiveness, programmable shape-morphing, healing and self-sensing function, simultaneously into a monolithic actuating material. Here, we introduce Chinese ink, a carbon-based material used in traditional calligraphy, to develop programmable, dual-responsive and self-sensing actuators by a healing-assembling method. The ink is combined with graphene oxide (GO) to fabricate a double-layer ink/GO actuator, which shows bi-directional bending under near-infrared light or humidity, owing to the mismatch of the volume change between ink and GO films. The maximal bending curvature is up to 5.2 cm-1. Importantly, the entire ink/GO actuator can be healed with the aid of ink solution. Using the healing-assembling method to fabricate advanced structures including a Mobius ring, triangular rings and square rings, diverse actuating modes and complex 3D deformations such as a wavy shape and saddle shape are realized. This method also enables the construction of an artificial mimosa that shows a biomimetic stimulus-responsive behavior. In addition, the ink/GO actuator shows a self-sensing function, which is attributed to the thermoresistivity of the ink film. This research shows the huge potential of Chinese-ink-based actuators for use in smart materials, providing a new idea for the development of new generation multi-functional actuators.

A multi-functional light-driven actuator with an integrated temperature-sensing function based on a carbon nanotube composite.

Actuators play an important role in the fields of intelligent robots and wearable electronics. Temperature has a great impact on the performances of many actuators. However, most of the traditional actuators only have an actuating function, failing to monitor and send real-time feedback of the temperature of the actuator. To solve the existing problem and break the single-function limit of traditional actuators, we propose a multi-functional light-driven actuator integrated with a temperature-sensing function, which is based on a carbon nanotube (CNT) and methylcellulose (MC) composite. When the CNT-MC film is assembled with biaxially oriented polypropylene (BOPP) to form a bilayer structure, the CNT-MC/BOPP actuator can be driven by near-infrared (NIR) light. Its morphing is based on thermal expansion differences between two layers and shrinkage of MC induced by water loss. The maximal bending curvature is up to 1.03 cm-1. Meanwhile, the resistance of the actuator can change by about 10%, which realizes real-time temperature monitoring and feedback. Furthermore, we demonstrate two practical applications. First, the CNT-MC film can work as a temperature sensor, as its resistance changes with the temperature in real time. Second, we design an intelligent gripper, which can monitor the temperature during the entire working process. This multi-functional CNT-based device is expected to have a broad application prospect in artificial muscles, soft robotics and wearable electronics.

Investigation of Dropwise Condensation on a Super-Aligned Carbon Nanotube Mesh-Coated Surface.

Enhanced vapor condensation is a critical issue for improving the efficiency of energy conversion, thermal management, water recovery, and treatment. Low-energy surfaces incorporating micro/nanoscale roughness have been reported to significantly promote vapor condensation. In this research, the mesh structures of super-aligned carbon nanotube (SACNT) films were prepared by crossing monolayer SACNT films on a copper substrate. Then, the sustaining dropwise condensation was achieved on the SACNT mesh-coated surface. The SACNT mesh-coated surface could obviously enhance the coalescence and sweeping departure of the condensing droplets. Additionally, the measured overall heat transfer coefficient (HTC) of the SACNT mesh-coated surface demonstrated a 36% enhancement compared to that on the bare copper surface. The parallel stacking of SACNT films with different groove structures was also studied, and a 15% enhancement in the HTC was shown as compared with the bare copper surface. Furthermore, we developed a morphology-based model to theoretically analyze the condensation-enhancement mechanism on a SACNT mesh-coated surface. The SACNT surfaces also have advantages of low cost, durability, flexibility, and extensibility. Our findings revealed that the SACNT films could be readily used as vapor condensation-strengthening surfaces, further extending their potential applications to industrial equipment.