Reconfigurable, Reversible, and Redefinable Deformation of GO Based on Quantum-Confined-Superfluidics Effect.

Graphene oxide (GO) films with natural "quantum-confined-superfluidics" (QSF) channels for moisture actuation have emerged as a smart material for actuators and soft robots. However, programming the deformation of GO by engineering QSF nanochannels around 1 nm is extremely challenging. Herein, we report the reconfigurable, reversible, and redefinable deformation of GO under moisture actuation by tailoring QSF channels via moisture-assisted strain-induced wrinkling (MSW). The shape fixity ratio of a general GO film can reach ∼84% after the MSW process, and the shape recovery ratio is ∼83% at room temperature under moisture actuation. The flexible shaping and deformation abilites, as well as the self-healing property of GO make it possible to fabricate soft robots using GO. Besides, as a proof-of-concept, passive electronics and soft robots capable of crawling, turning, switching circuit, and automatic somersault are demonstrated. With unique shaping and deformation abilities, GO may bring great implications for future soft robotics.

An Unsupervised Tunnel Damage Identification Method Based on Convolutional Variational Auto-Encoder and Wavelet Packet Analysis.

Finding a low-cost and highly efficient method for identifying subway tunnel damage can greatly reduce catastrophic accidents. At present, tunnel health monitoring is mainly based on the observation of apparent diseases and vibration monitoring, which is combined with a manual inspection to perceive the tunnel health status. However, these methods have disadvantages such as high cost, short working time, and low identification efficiency. Thus, in this study, a tunnel damage identification algorithm based on the vibration response of in-service train and WPE-CVAE is proposed, which can automatically identify tunnel damage and give the damage location. The method is an unsupervised novelty detection that requires only sufficient normal data on healthy structure for training. This study introduces the theory and implementation process of this method in detail. Through laboratory model tests, the damage of the void behind the tunnel wall is designed to verify the performance of the algorithm. In the test case, the proposed method achieves the damage identification performance with a 96.25% recall rate, 86.75% hit rate, and 91.5% accuracy. Furthermore, compared with the other unsupervised methods, the method performance and noise immunity are better than others, so it has a certain practical value.

Light-Driven Magnetic Encoding for Hybrid Magnetic Micromachines.

Remote manipulation of a micromachine under an external magnetic field is significant in a variety of applications. However, magnetic manipulation requires that either the target objects or the fluids should be ferromagnetic or superparamagnetic. To extend the applicability, we propose a versatile optical printing technique termed femtosecond laser-directed bubble microprinting (FsLDBM) for on-demand magnetic encoding. Harnessing Marangoni convection, evaporation flow, and capillary force for long-distance delivery, near-field attraction, and printing, respectively, FsLDBM is capable of printing nanomaterials on the solid-state substrate made of arbitrary materials. As a proof-of-concept, we actuate a 3D polymer microturbine under a rotating magnetic field by implementing γ-Fe2O3 nanomagnets on its blade. Moreover, we demonstrate the magnetic encoding on a living daphnia and versatile manipulation of the hybrid daphnia. With its general applicability, the FsLDBM approach provides opportunities for magnetic control of general microstructures in a variety of applications, such as smart microbots and biological microsurgery.

Theoretical, Numerical, and Experimental Study on the Identification of Subway Tunnel Structural Damage Based on the Moving Train Dynamic Response.

As an important part of urban rail transit, subway tunnels play an important role in alleviating traffic pressure in mega-cities. Identifying and locating damage to the tunnel structure as early as possible has important practical significance for maintaining the long-term safe operation of subway tunnels. Summarizing the current status and shortcomings of the structural health monitoring of subway tunnels, a very economical and effective monitoring program is proposed, which is to use the train vibration response to identify and locate the damage of the tunnel structure. Firstly, the control equation of vehicle-tunnel coupling vibration is established and its analytical solution is given as the theoretical basis of this paper. Then, a damage index based on the cumulative sum of wavelet packet energy change rate (TDISC) is proposed, and its process algorithm is given. Through the joint simulation of VI-Rail and ANSYS, a refined 3D train-tunnel coupled vibration model is established. In this model, different combined conditions of single damage and double damage verify the validity of the damage index. The effectiveness of this damage index was further verified through model tests, and the influence of vehicle speed and load on the algorithm was discussed. Numerical simulation and experimental results show that the TDISC can effectively locate the damage of the tunnel structure and has good robustness.

Ag nanoparticle ink coupled with graphene oxide cellulose paper: a flexible and tunable SERS sensing platform.

Surface-enhanced Raman scattering (SERS) is highly promising for ultra-sensitive detection in a series of applications. Although extensive advances have been achieved in SERS technologies, the preparation of highly efficient SERS substrates still suffers from several limitations, including complex preparation procedures, high cost, and instability for long time storage. To address these problems, we report a novel, to the best of our knowledge, SERS platform that combines graphene oxide (GO) and cellulose composite paper with colloidal silver nanoparticle (Ag NP) ink. As an efficient substrate, the GO and cellulose composite paper that features hierarchical micro-nanostructures and improved interaction with target molecules can be fabricated on a large scale, and the Ag NP ink can be well stored, avoiding being oxidized in ambient conditions. In this way, our SERS platform not only reduces the cost, but also improved the stability. The sensitivity, reproducibility, and tunable SERS detection performance were evaluated using rhodamine 6G as probing molecules. To demonstrate the capability of our SERS platform in practical analysis, the SERS spectra of two monosodium salt solutions of different concentrations have been collected. The SERS platform has revealed great potential for practical application of SERS technologies.

Laser fabrication of graphene-based electrothermal actuators enabling predicable deformation.

Electrothermal actuators (ETAs) that can convert electric energy into mechanical works have been extensively studied for their great potential in artificial muscles and robotics. However, the production of ETAs that enable complex and predictable deformation is still challenging. In this Letter, an ETA based on reduced graphene oxide (RGO) and polyethylene (PE) bimorph is developed through a facile laser-scribing method. Since the laser-scribing technology permits flexible patterning, conductive RGO electrodes with complex circuit patterns can be readily produced on a thermally active PE film, forming an ETA capable of fast and reversible deformation. In addition, the laser-scribed ETA demonstrated orientation-defined bending performance, enabling more sophisticated deformation control. The laser scribing of graphene oxide has opened up a new way to produce ETAs towards cutting-edge applications such as soft robotics and intelligent systems.

Hierarchically structuring and synchronous photoreduction of graphene oxide films by laser holography for supercapacitors.

Herein, we report a simple laser holography technology for hierarchically structuring and synchronous photoreduction of graphene oxides (GO), toward the development of efficient graphene-based electrodes for supercapacitor applications in cost effectively manners. Hierarchical micro-nanostructures, formed due to laser treatment induced photoreduction and ablation effect. Interestingly, both the morphology and reduction degree of the laser holography reduced GO (LHRGO) show strong dependence on the laser intensity, providing the feasibility for controlling the micro-nanostructures, chemical composition, and the conductivity of the graphene electrodes. Furthermore, the supercapacitors based on LHRGO show higher capacitance values and better electrochemical performance compared to that based on thermal reduced GO (TRGO) of same reduction level. Photoredution and micro-nanostructuring of GO using laser holography may hold great promise for production of effective carbon-based electrodes towards practical applications in energy storage devices.

Kraft Mesh Origami for Efficient Oil-Water Separation.

Inspired from fish scales that exhibit unique underwater superoleophobicity, artificial porous membranes featuring similar wettability have been successfully developed for oil-water separation. However, most of the superoleophobic meshes are workable only for underwater oil/water separation and become disabled in air. In this article, we reported the facile fabrication of underwater superoleophobic kraft mesh and demonstrated efficient oil-water separation using kraft mesh origamis. Kraft paper that features porosity, natural hydrophilicity, and relatively high elasticity and tear resistance has been found to be an ideal candidate for developing underwater superoleophobic origami. Direct laser drilling has been employed to make microhole arrays on the kraft paper, forming a flexible mesh. The hydrophilic nature and the hierarchical microstructures that consist of microhole arrays and porous microfiber networks make the resultant kraft mesh superoleophobic underwater, enabling oil-water separation. More importantly, the kraft mesh can retain a large amount of water (2.5 times its weight under dry conditions) owing to its porous and hydrophilic structure. Thus, the wet kraft mesh became a slippery surface for oil droplets when it was taken out of the water. This unique feature makes it possible to directly fish out oil droplets from water using a simple kraft mesh origami. Direct laser drilling of paper mesh for flexible origami may open up a new route to the rational design and fabrication of oil-water separation devices.

A Stroke Risk Detection: Improving Hybrid Feature Selection Method.

BACKGROUND: Stroke is one of the most common diseases that cause mortality. Detecting the risk of stroke for individuals is critical yet challenging because of a large number of risk factors for stroke. OBJECTIVE: This study aimed to address the limitation of ineffective feature selection in existing research on stroke risk detection. We have proposed a new feature selection method called weighting- and ranking-based hybrid feature selection (WRHFS) to select important risk factors for detecting ischemic stroke. METHODS: WRHFS integrates the strengths of various filter algorithms by following the principle of a wrapper approach. We employed a variety of filter-based feature selection models as the candidate set, including standard deviation, Pearson correlation coefficient, Fisher score, information gain, Relief algorithm, and chi-square test and used sensitivity, specificity, accuracy, and Youden index as performance metrics to evaluate the proposed method. RESULTS: This study chose 792 samples from the electronic records of 13,421 patients in a community hospital. Each sample included 28 features (24 blood test features and 4 demographic features). The results of evaluation showed that the proposed method selected 9 important features out of the original 28 features and significantly outperformed baseline methods. Their cumulative contribution was 0.51. The WRHFS method achieved a sensitivity of 82.7% (329/398), specificity of 80.4% (317/394), classification accuracy of 81.5% (645/792), and Youden index of 0.63 using only the top 9 features. We have also presented a chart for visualizing the risk of having ischemic strokes. CONCLUSIONS: This study has proposed, developed, and evaluated a new feature selection method for identifying the most important features for building effective and parsimonious models for stroke risk detection. The findings of this research provide several novel research contributions and practical implications.

Femtosecond laser direct writing of ion exchangeable multifunctional microstructures.

We report on the fabrication of ion exchangeable microstructures by femtosecond laser direct writing of an ion exchange photopolymer, poly(2-acrylamido-2-methyl-1-propanesulfonic acid) (PAMPS). The resultant microstructures are negatively charged in aqueous solution, and can adsorb positively charged species, such as metal ions, nanoparticles, and proteins by electrostatic interaction, forming functional components for chip functionalization. In addition, it is possible to modify the microstructures with positively charged species that make the microstructures sensitive to negatively charged species. As a typical example, a crossed 3D microvessel functionalized with antibodies was fabricated, which reveals great potential for organ-on-a-chip systems. The fabrication of ion exchangeable microstructures holds great promise for flexible chip functionalization.

Intense Femtosecond Laser-Mediated Electrical Discharge Enables Preparation of Amorphous Nickel Phosphide Nanoparticles.

Reported here is a high-efficiency preparation method of amorphous nickel phosphide (Ni-P) nanoparticles by intense femtosecond laser irradiation of nickel sulfate and sodium hypophosphite aqueous solution. The underlying mechanism of the laser-assisted preparation was discussed in terms of the breaking of chemical bond in reactants via highly intense electric field discharge generated by the intense femtosecond laser. The morphology and size of the nanoparticles can be tuned by varying the reaction parameters such as ion concentration, ion molar ratio, laser power, and irradiation time. X-ray diffraction and transmission electron microscopy results demonstrated that the nanoparticles were amorphous. Finally, the thermogravimetric-differential thermal analysis experiment verified that the as-synthesized noncrystalline Ni-P nanoparticles had an excellent catalytic capability toward thermal decomposition of ammonium perchlorate. This strategy of laser-mediated electrical discharge under such an extremely intense field may create new opportunities for the decomposition of molecules or chemical bonds that could further facilitate the recombination of new atoms or chemical groups, thus bringing about new possibilities for chemical reaction initiation and nanomaterial synthesis that may not be realized under normal conditions.

Wet-etching-assisted femtosecond laser holographic processing of a sapphire concave microlens array.

We report rapid and mask-free fabrication of a sapphire concave microlens array by a combined method of femtosecond laser holographic processing and wet etching. The method features high fabrication efficiency, as crater arrays can be created on sapphire through a parallel processing manner, and the subsequent wet etching facilitates the formation of microlens arrays with a smooth surface. More importantly, the size and spacing of the concave microlenses can be well tuned by varying the distance of craters and etching time. Two types of microlens arrays with a spacing of 25 and 40 µm have been successfully fabricated, both of which showed good imaging performance. This method holds great promise for developing sapphire-based micro-optical components.

Facile fabrication of flexible graphene FETs by sunlight reduction of graphene oxide.

We reported here a facile fabrication of flexible graphene-based field effect transistors (FETs) by sunlight reduction of graphene oxide (GO) as channel material. As a mask-free and chemical-free method, sunlight photoreduction of GO without the use of any complex equipments is simple and green. The resultant FET demonstrated excellent electrical properties (e.g., an optimized Ion/Ioff ratio of 111, hole mobility of 0.17 cm2 V-1 s-1), revealing great potential for development of flexible microelectrics. Additionally, since the reduced GO channel could be fabricated by sunlight treatment between two pre-patterned electrodes, the process features post-fabrication capability, which makes it possible to integrate graphene-based devices with given device structures.

Surface and Interface Engineering of Graphene Oxide Films by Controllable Photoreduction.

We report herein the engineering of the surface/interface properties of graphene oxide (GO) films by controllable photoreduction treatment. In our recent works, typical photoreduction processes, including femtosecond laser direct writing (FsLDW), laser holographic lithography, and controllable UV irradiation, have been employed to make conductive reduced graphene oxide (RGO) microcircuits, hierarchical RGO micro-nanostructures with both superhydrophobicity and structural color, as well as moisture-responsive GO/RGO bilayer structures. Compared with other reduction protocols, for instance, chemical reduction and thermal annealing, the photoreduction strategy shows distinct advantages, such as mask-free patterning, chemical-free modification, controllable reduction degree, and environmentally friendly processing. These works indicate that the surface and interface engineering of GO through controllable photoreduction of GO holds great promise for the development of various graphene-based microdevices.

A facile synthesis of three dimensional graphene sponge composited with sulfur nanoparticles for flexible Li-S cathodes.

Compared with a two dimensional graphene sheet, a three dimensional (3D) graphene sponge has a continuous conductive structure and numerous pores, which are beneficial for sulfur utilization and anchoring. However, strategies for the construction of 3D graphene sponges composited with sulfur nanoparticles (3DGS) are either energy consuming or involve toxic reagents. Herein, a 3DGS is fabricated via a reduction induced self-assembly method, which is simple but facile and scalable. The structural design of this 3DGS promises fast Li(+) transport, superior electrolyte absorbability and effective electrochemical redox reactions of sulfur. As a result, this 3DGS achieves a stable capacity of 580 mA h g(-1) after 500 cycles at a high rate of 1.5 A g(-1), which corresponds to a low fading rate of 0.043% per cycle. The present study effectively demonstrates that the 3D construction strategy is propitious for obtaining flexible high performance Li-S batteries.

Controllable assembly of silver nanoparticles induced by femtosecond laser direct writing.

We report controllable assembly of silver nanoparticles (Ag NPs) for patterning of silver microstructures. The assembly is induced by femtosecond laser direct writing (FsLDW). A tightly focused femtosecond laser beam is capable of trapping and driving Ag NPs to form desired micropatterns with a high resolution of ∼190 nm. Taking advantage of the 'direct writing' feature, three microelectrodes have been integrated with a microfluidic chip; two silver-based microdevices including a microheater and a catalytic reactor have been fabricated inside a microfluidic channel for chip functionalization. The FsLDW-induced programmable assembly of Ag NPs may open up a new way to the designable patterning of silver microstructures toward flexible fabrication and integration of functional devices.

Reconfigurable Microlens Array Enables Tunable Imaging Based on Shape Memory Polymers.

Microlens arrays (MLAs) with a tunable imaging ability are core components of advanced micro-optical systems. Nevertheless, tunable MLAs generally suffer from high power consumption, an undeformable rigid body, large and complex systems, or limited focal length tunability. The combination of reconfigurable smart materials with MLAs may lead to distinct advantages including programmable deformation, remote manipulation, and multimodal tunability. However, unlike photopolymers that permit flexible structuring, the fabrication of tunable MLAs and compound eyes (CEs) based on transparent smart materials is still rare. In this work, we report reconfigurable MLAs that enable tunable imaging based on shape memory polymers (SMPs). The smart MLAs with closely packed 200 × 200 microlenses (40.0 µm in size) are fabricated via a combined technology that involves wet etching-assisted femtosecond laser direct writing of MLA templates on quartz, soft lithography for MLA duplication using SMPs, and the mechanical heat setting for programmable reconfiguration. By stretching or squeezing the shape memory MLAs at the transition temperature (80 °C), the size, profiles, and spatial distributions of the microlenses can be programmed. When the MLA is stretched from 0 to 120% (area ratio), the focal length is increased from 116 to 283 µm. As a proof of concept, reconfigurable MLAs and a 3D CE with a tunable field of view (FOV, 160-0°) have been demonstrated in which the thermally triggered shape memory deformation has been employed for tunable imaging. The reconfigurable MLAs and CEs with a tunable focal length and adjustable FOV may hold great promise for developing smart micro-optical systems.

Correlation between serum uric acid to high-density lipoprotein cholesterol ratio and atrial fibrillation in patients with NAFLD.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is independently associated with atrial fibrillation (AF) risk. The uric acid (UA) to high-density lipoprotein cholesterol (HDL-C) ratio (UHR) has been shown to be closely associated with cardiovascular disease (CVD) and NAFLD. The aim of this study is to clarify whether elevated UHR is associated with the occurrence of AF in patients with NAFLD and to determine whether UHR predicted AF. METHODS: Patients diagnosed with NAFLD in the Department of Cardiovascular Medicine of the Second Hospital of Shanxi Medical University from January 1, 2020, to December 31, 2021, were retrospectively enrolled in this study. The study subjects were categorized into AF group and non-AF group based on the presence or absence of combined AF. Logistic regression was performed to evaluate the correlation between UHR and AF. Sensitivity analysis and subgroup interaction analysis were performed to verify the robustness of the study results. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff value for UHR to predict the development of AF in patients with NAFLD. RESULTS: A total of 421 patients with NAFLD were included, including 171 in the AF group and 250 in the non-AF group. In the univariate regression analysis, NAFLD patients with higher UHR were more likely to experience AF, and the risk of AF persisted after confounding factors were adjusted for (OR: 1.010, 95%CI: 1.007-1.013, P<0.001). AF risk increased with increasing UHR quartile (P for trend < 0.001). Despite normal serum UA and HDL-C, UHR was still connected with AF in patients with NAFLD. All subgroup variables did not interact significantly with UHR in the subgroup analysis. The ROC curve analysis showed that the areas under the curve for UA, HDL-C, and UHR were 0.702, 0.606, and 0.720, respectively, suggesting that UHR has a higher predictive value for AF occurrence in NAFLD patients compared to HDL-C or UA alone. CONCLUSION: Increased UHR level was independently correlated with a high risk of AF in NAFLD patients.

Hyper-branched CdTe nanostructures based on the self-assembling of quantum dots and their optical properties.

As the priority of interconnects and active components in nanoscale optical and electronic devices, three-dimensional hyper-branched nanostructures came into focus of research. Recently, a novel crystallization route, named as "nonclassical crystallization," has been reported for three-dimensional nanostructuring. In this process, Quantum dots are used as building blocks for the construction of the whole hyper-branched structures instead of ions or single-molecules in conventional crystallization. The specialty of these nanostructures is the inheritability of pristine quantum dots' physical integrity because of their polycrystalline structures, such as quantum confinement effect and thus the luminescence. Moreover, since a longer diffusion length could exist in polycrystalline nanostructures due to the dramatically decreased distance between pristine quantum dots, the exciton-exciton interaction would be different with well dispersed quantum dots and single crystal nanostructures. This may be a benefit for electron transport in solar cell application. Therefore, it is very necessary to investigate the exciton-exciton interaction in such kind of polycrystalline nanostructures and their optical properites for solar cell application. In this research, we report a novel CdTe hyper-branched nanostructures based on self-assembly of CdTe quantum dots. Each branch shows polycrystalline with pristine quantum dots as the building units. Both steady state and time-resolved spectroscopy were performed to investigate the properties of carrier transport. Steady state optical properties of pristine quantum dots are well inherited by formed structures. While a suppressed multi-exciton recombination rate was observed. This result supports the percolation of carriers through the branches' network.

MUE-CoT: multi-scale uncertainty entropy-aware co-training framework for left atrial segmentation.

Objective.Accurate left atrial segmentation is the basis of the recognition and clinical analysis of atrial fibrillation. Supervised learning has achieved some competitive segmentation results, but the high annotation cost often limits its performance. Semi-supervised learning is implemented from limited labeled data and a large amount of unlabeled data and shows good potential in solving practical medical problems.Approach. In this study, we proposed a collaborative training framework for multi-scale uncertain entropy perception (MUE-CoT) and achieved efficient left atrial segmentation from a small amount of labeled data. Based on the pyramid feature network, learning is implemented from unlabeled data by minimizing the pyramid prediction difference. In addition, novel loss constraints are proposed for co-training in the study. The diversity loss is defined as a soft constraint so as to accelerate the convergence and a novel multi-scale uncertainty entropy calculation method and a consistency regularization term are proposed to measure the consistency between prediction results. The quality of pseudo-labels cannot be guaranteed in the pre-training period, so a confidence-dependent empirical Gaussian function is proposed to weight the pseudo-supervised loss.Main results.The experimental results of a publicly available dataset and an in-house clinical dataset proved that our method outperformed existing semi-supervised methods. For the two datasets with a labeled ratio of 5%, the Dice similarity coefficient scores were 84.94% ± 4.31 and 81.24% ± 2.4, the HD95values were 4.63 mm ± 2.13 and 3.94 mm ± 2.72, and the Jaccard similarity coefficient scores were 74.00% ± 6.20 and 68.49% ± 3.39, respectively.Significance.The proposed model effectively addresses the challenges of limited data samples and high costs associated with manual annotation in the medical field, leading to enhanced segmentation accuracy.