Due to the unique advantages of untethered connections and a high level of safety, magnetic actuation is a commonly used technique in microrobotics for propelling microswimmers, manipulating fluidics, and navigating medical devices. However, the microrobots or actuated targets are exposed to identical and homogeneous driving magnetic fields, which makes it challenging to selectively control a single robot or a specific group among multiple targets. This paper reviews recent advances in selective and independent control for multi-microrobot or multi-joint microrobot systems driven by magnetic fields. These selective and independent control approaches decode the global magnetic field into specific configurations for the individualized actuation of multiple microrobots. The methods include applying distinct properties for each microrobot or creating heterogeneous magnetic fields at different locations. Independent control of the selected targets enables the effective cooperation of multiple microrobots to accomplish more complicated operations. In this review, we provide a unique perspective to explain how to manipulate individual microrobots to achieve a high level of group intelligence on a small scale, which could help accelerate the translational development of microrobotic technology for real-life applications.
The adhesive behavior of one-dimensional (1D) materials, such as nanotubes and nanowires, plays a decisive role in the effective fabrication, functionality, and reliability of novel devices that integrate 1D components, as well as in biomimetic adhesives based on 1D arrays. This review compiles and critically evaluates recent experimental techniques that aim to characterize the adhesion behavior of interfaces formed by 1D materials, including when such materials are brought into contact with a substrate or adjacent 1D materials. The conformation of 1D material to surfaces and the associated occurrence of multi-asperity contact are discussed, and the coupling of adhesion and friction during interfacial attachment and detachment is explored. The use of 1D materials as reinforcement agents in nanocomposites and the associated interfacial characterization techniques are considered. The potential for the environmental conditions that exist during sample preparation and adhesion testing to influence 1D interfacial interactions and, ultimately, to alter the adhesion behavior of a 1D material is scrutinized. Finally, a brief perspective is provided on ongoing challenges and future directions, which include the methodical investigation of the testing environment and the alteration of adhesion through surface modification.
Since the first cloned sheep was produced in 1996, cloning has attracted considerable attention because of its great potential in animal breeding. Somatic cell nuclear transfer (SCNT) is widely used for creating clones. However, SCNT is very complicated to manipulate and inevitably causes intracellular damage during manipulation. Typically, only less than 1% of reconstructed embryos develop into live cloned animals. This low success rate is considered to be the major limitation in the extensive application of cloning techniques. In this study, we proposed an intracellular strain evaluation-based oocyte enucleation method to reduce potential intracellular damage in SCNT. We first calculated the intracellular strain based on the intracellular velocity field and then used the intracellular strain as a criterion to improve the enucleation operation. We then developed a robotic batch SCNT system to apply this micromanipulation method to animal cloning. Experimental results showed that we increased the blastocyst rate from 10.0% to 20.8%, and we successfully produced 17 cloned piglets by robotic SCNT for the first time. The success rate of cloning was significantly increased compared to that of traditional methods (2.5% vs 0.73% on average). In addition to the cloning technique, the intracellular strain evaluation-based enucleation method is expected to be applicable to other biological operations and for establishing a universal cell manipulation protocol to reduce intracellular damage.
This paper presents a three-dimensional (3D)-atomic force microscopy (AFM) method based on magnetically driven (MD)-orthogonal cantilever probes (OCPs), in which two independent scanners with three degrees of freedom are used to achieve the vector tracking of a sample surface with a controllable angle. A rotating stage is integrated into the compact AFM system, which helps to achieve 360° omnidirectional imaging. The specially designed MD-OCP includes a horizontal cantilever, a vertical cantilever, and a magnetic bead that can be used for the mechanical drive in a magnetic field. The vertical cantilever, which has a protruding tip, can detect deep grooves and undercut structures. The design, simulation, fabrication, and performance analysis of the MD-OCP are described first. Then, the amplitude compensation and home positioning for 360° rotation are introduced. A comparative experiment using an AFM step grating verifies the ability of the proposed method to characterize steep sidewalls and corner details, with a 3D topography reconstruction method being used to integrate the images. The effectiveness of the proposed 3D-AFM based on the MD-OCP is further confirmed by the 3D characterization of a micro-electromechanical system (MEMS) device with microcomb structures. Finally, this technique is applied to determine the critical dimensions (CDs) of a microarray chip. The experimental results regarding the CD parameters show that, in comparison with 2D technology, from which it is difficult to obtain sidewall information, the proposed method can obtain CD information for 3D structures with high precision and thus has excellent potential for 3D micro–nano manufacturing inspection.
This paper reports a method to measure the mechanical properties of a single cell using a microfluidic chip with integrated force sensing and a liquid exchange function. A single cell is manipulated and positioned between a pushing probe and a force sensor probe using optical tweezers. These two on-chip probes were designed to capture and deform the cells. The single cell is deformed by moving the pushing probe, which is driven by an external force. The liquid–liquid interface is formed between the probes by laminar flow to change the extracellular environment. The position of the interface is shifted by controlling the injection pressure. Two positive pressures and one negative pressure are adjusted to balance the diffusion and perturbation of the flow. The mechanical properties of a single Synechocystis sp. strain PCC 6803 were measured in different osmotic concentration environments in the microfluidic chip. The liquid exchange was achieved in approximately 0.3–0.7 s, and the dynamic deformation of a single cell was revealed simultaneously. Measurements of two Young's modulus values under alterable osmotic concentrations and the dynamic response of a single cell in osmotic shock can be collected within 30 s. Dynamic deformations of wild-type (WT) and mutant Synechocystis cells were investigated to reveal the functional mechanism of mechanosensitive (MS) channels. This system provides a novel method for monitoring the real-time mechanical dynamics of a single intact cell in response to rapid external osmotic changes; thus, it opens up novel opportunities for characterizing the accurate physiological function of MS channels in cells.
Microalgae are a group of microscopic eukaryotic organisms that can transform carbon dioxide into diverse bioactive compounds through photosynthesis using chlorophyll a. Over the past decade, biohybrid materials comprising live microalgae and other biocompatible components have exhibited tremendous potential in solving many medical challenges, such as oncotherapy, tissue reconstruction, and drug delivery. Microalgae immobilized within conventional biomaterials can maintain their photosynthetic activity for an extended period of time, thereby providing local oxygen and working as biocompatible interfacing materials for regulating cell activities. The motility of microalgae has also inspired the development of biohybrid microrobots, in which drug molecules can be bound to the surface of microalgae via noncovalent adsorption and delivered to the target area through precisely controlled locomotion. Moreover, the autofluorescence, phototaxis, and biomass production of microalgae can be integrated into the design of novel biohybrid materials with versatile functions. Furthermore, through appropriate genetic manipulation, engineered microalgae can endow biohybrid materials with novel properties, such as specific cell-targeting capability and the local release of recombinant proteins from algae cells—technologies that show promise for promoting and diversifying the clinical use of microalgae-based biohybrid materials (MBBMs) in several fields of biomedicine. Herein, we summarize the fabrication, physiology, and locomotion ability of MBBMs; we then review typical and recent reports on the use of MBBMs in the biomedical field; finally, we provide critical discussions on the challenges and future perspectives of MBBMs.
A novel intestinal-targeted θ-shaped capsule with a pumping effect for the controlled release of hydrophobic drugs is successfully developed. The proposed capsule is composed of a Ca-alginate–chitosan/protamine/silica (ACPSi) composite shell and two chambers forming an θ-shape (θ-ACPSi), which respectively encapsulate drugs and booster agents. Enteric hydroxypropyl methylcellulose phthalate (HPMCP) microspheres are embedded into the drug chamber shell. The θ-ACPSi composite shell offers improved protection for the encapsulated drug in the stomach environment and excellent intestinal-targeted drug release. Using indomethacin as the model drug and polyacrylic acid (PAA) as the booster agent, both the opening of ″microchannels″ in the drug chamber and the swelling of PAA in the booster chamber increase the release rate of high-concentration indomethacin and ensure a constant release of indomethacin in the small intestine. In the stomach (pH 2.5), less than 1% of the indomethacin is released. However, when the θ-ACPSi capsules enter the small intestine (pH 6.8), the HPMCP microspheres in the drug chamber shell dissolve to open the ″microchannels,″ while the PAA swells to provide pumping impetus. As a result, more than 60% of the indomethacin is released at a constant speed in the small intestine. The proposed θ-ACPSi capsules provide a potential and novel model for developing responsive pumping controlled-release systems and intestinal-targeted drug delivery systems.
Science is entering a new era—the fifth paradigm—that is being heralded as the main character of knowledge integrating into different fields to intelligence-driven work in the computational community based on the omnipresence of machine learning systems. Here, we vividly illuminate the nature of the fifth paradigm by a typical platform case specifically designed for catalytic materials constructed on the Tianhe-1 supercomputer system, aiming to promote the cultivation of the fifth paradigm in other fields. This fifth paradigm platform mainly encompasses automatic model construction (raw data extraction), automatic fingerprint construction (neural network feature selection), and repeated iterations concatenated by the interdisciplinary knowledge ("volcano plot"). Along with the dissection is the performance evaluation of the architecture implemented in iterations. Through the discussion, the intelligence-driven platform of the fifth paradigm can greatly simplify and improve the extremely cumbersome and challenging work in the research, and realize the mutual feedback between numerical calculations and machine learning by compensating for the lack of samples in machine learning and replacing some numerical calculations caused by insufficient computing resources to accelerate the exploration process. It remains a challenging of the synergy of interdisciplinary experts and the dramatic rise in demand for on-the-fly data in data-driven disciplines. We believe that a glimpse of the fifth paradigm platform can pave the way for its application in other fields.
The increasingly complex molecular structures and high requirements of advanced industries are triggering a transformation in chemical production modes. Bio-manufacturing provides efficient strategies and brings the advantages of high atomic economy, few side reactions, and strong adaptability to processes, as well as environmental friendliness, which can contribute toward global efforts against greenhouse effect and environmental pollution. The significance of bio-manufacturing can be specifically illustrated by examining the bio-manufacturing process from the scientific discovery of a key compound to its technological integration and engineering innovation. The development of statins—important drugs for hypercholesterolemia treatment—is a good example of the progress and application of bio-manufacturing. The production of the first-generation statins from microorganisms, the second-generation statins using bioconversion, and the third-generation statins through an evolution from total chemical synthesis to chemoenzymatic synthesis demonstrates the technological and engineering revolution of bio-manufacturing, which is of great importance for energy conservation, cost saving, and waste emission reduction. With advances in cutting-edge biotechnologies, as well as the integration of multiple disciplines, bio-manufacturing is expected to promote the advancement of more intelligent processes to realize sustainable and green industrial development.
Electrorheological (ER) technology is an advanced technology based on ER effects. The most common material in ER technology is an electrorheological fluid (ERF), which is a type of smart soft material. The viscosity of ERF is reversibly adjustable by an applied electric field. A new type of electroresponsive soft material, electrorheological elastomer (ERE), which is a derivative of ERFs, has attracted wide attention due to its advantages of not precipitating and easy packaging. ER materials are widely applied in mechanical engineering due to their reversibly tunable characteristics, fast response, and low energy consumption. In addition to basic ER material fabrication and application, ER technology is also used in energy material preparation, oil transportation, and energy storage. The application of ER technology in the energy field provides a good example of the potential applications of ER technology in other fields. This article systematically summarizes the research status and future development prospects of ER technology in materials, energy, and mechanical engineering from the mechanism to application, combined with the latest research results.
The recent proliferation of sustainable and eco-friendly renewable energy engineering is a hot topic of worldwide significance with regard to combatting the global environmental crisis. To curb renewable energy intermittency and integrate renewables into the grid with stable electricity generation, secondary battery-based electrical energy storage (EES) technologies are regarded as the most promising solution, due to their prominent capability to store and harvest green energy in a safe and cost-effective way. Due to the wide availability and low cost of sodium resources, sodium-ion batteries (SIBs) are regarded as a promising alternative for next-generation large-scale EES systems. This review discusses in detail the key differences between lithium-ion batteries (LIBs) and SIBs for different application requirements and describes the current understanding of SIBs. By comparing technological evolutions among LIBs, lead-acid batteries (LABs), and SIBs, the advantages of SIBs are unraveled. This review also offers highlights on commercial achievements that have been realized based on current SIB technology, focusing on an introduction of five major SIB companies, each with SIB chemistry and technology, as well as commercialized SIB products. Last but not least, it discusses outlooks and key challenges for the commercialization of next-generation SIBs.
With the development of smart grids and the energy Internet, large-scale monitoring of voltage and electric field data is required in all aspects of power systems, which requires the arrangement of various advanced sensors. Measurement of the electric field can replace traditional voltage transformers to realize the non-contact measurement of voltage, which reduces the insulation cost and the difficulty of operation and maintenance. Electric field measurement can also be applied in various other areas, such as equipment fault diagnosis, lightning warning, and electromagnetic environment measurement. Traditional electric field measurement devices, such as field mills, are bulky and costly, so they cannot be arranged flexibly on a large scale. In this paper, we present an electrostatically actuated micro-electric field sensor (E-sensor) with a piezoresistive sensing structure. The presented E-sensor is fabricated into a four-cantilever structure using microfabrication technology. The cantilevers are displaced under the drive of the electrostatic force, and the generated strain is transformed into measurable signals through piezoresistive materials. The presented E-sensor has the advantages of small size, low cost, low power consumption, and easy mass production. Moreover, the E-sensor has a high signal-to-noise ratio, high resolution, and wide measuring range. The experimental results show that the E-sensor has a linear electric field measurement range from 1.1 to 1100 kV·m−1 with an alternating current (AC) resolution of up to 112 V·m−1·Hz−1/2 and a cut-off frequency of 496 Hz, making it suitable for most applications in smart grids and the energy Internet.
Generating electricity from biomass combustion is an essential means of supporting basic demands in deprived regions, including lighting, communication, and medical care. In this work, a high-capacity portable biomass-combustion-powered thermoelectric generator (BCP-TEG) is developed and tested. Temperature distribution, power load feature, efficiencies at different levels, and a field test are comprehensively explored. The results show that the proposed 7.6 kg BCP-TEG can cogenerate a heating power of 750 W and an electric power of 23.4 W, corresponding to a combined heat and power (CHP) efficiency of 32.3%. The net power density of 2.41 W·kg−1 is much greater than those in previous reports based on water closed-loop cooling. Furthermore, this study demonstrates that a 3.7 V battery of 6.2 A·h can be fully charged by burning 1 kg of wood sticks. Finally, we provide a comprehensive discussion identifying existing issues and future opportunities in this field.
The river networks in the plains of China are in low-lying terrain with mild bed slopes and weak hydrodynamics conditions. Filled with intense human activities, these areas are characterized by serious water security problems, e.g., frequent floods, poor water self-purification capabilities, and fragile water ecosystems. In this paper, it's found that all these problems are related to hydrodynamics, and the spatiotemporal imbalance of river network hydrodynamics is identified as the common cause of these water-related problems. From this, a theory for the hydrodynamic reconstruction of plain river networks is proposed. In addition to the importance of the flow volume, this theory highlights the role of hydrodynamics and limited energy in improving the ecological water environment. The layout of water conservancy project systems (e.g., sluices and pumping stations) is optimized to fully tapping the potential integrative benefit of projects. The optimal temporal and spatial distributions of hydrodynamic patterns is reconstructed in order to meet the needs of the integrated management of complex water-related problems in river networks. On this basis, a complete theoretical method and technical system for multiscale hydrodynamic reconstruction and multi-objective hydraulic regulation in plain river networks with weak hydrodynamics is established. The principles of the integrated management of water problems in river network areas are put forward. The practical application and efficacy of the theory are demonstrated through a case study aiming to improve the water quality of the river network in the main urban area of Yangzhou City.
Evaluating the impact of multi-source uncertainties in complex forecasting systems is essential to understanding and improving the systems Previous studies have paid little attention to the influence of multi-source uncertainties in complex meteorological and hydrological forecasting systems. In this study, we developed a general ensemble framework based on Bayesian model averaging (BMA) for evaluating the impact of multi-source uncertainties in complex forecast systems. Based on this framework, we used eight numerical weather prediction products from the International Grand Global Ensemble (TIGGE) dataset, four hydrological models with different structures, and 1000 sets of parameters to comprehensively account for the input, structure, and parameter uncertainties. The framework's application to the Chitan Basin in China revealed that the numerical weather prediction input uncertainty in the forecasting system was more significant than the hydrological model uncertainty. The hydrological model structure uncertainty was more prominent than the parameter uncertainty. The accuracy of the numerical weather prediction dominates the accuracy of the forecast of high flows. In addition, the structures and parameters of the hydrological model and their interactions contributed to the main uncertainty of the low flow forecasts. The streamflow was more realistically represented when the three uncertainty sources were considered jointly. By accounting for the significant uncertainty sources in complex forecast systems, the BMA ensemble forecasting produces more realistic and reliable predictions and reduces the influences of other incomplete considerations. The developed multi-source uncertainty assessment framework improves our understanding of the complex meteorological and hydrological forecasting system. Therefore, the framework is promising for improving the accuracy and reliability of complex forecasting systems.
Runoff prediction is of great significance to flood defense. However, due to the complexity and randomness of the runoff process, it is hard to predict daily runoff accurately, especially for peak runoff. To address this issue, this study proposes an enhanced long short-term memory (LSTM) model for runoff prediction, where novel loss functions are introduced and feature extractors are integrated. Two loss functions (peak error tanh (PET), peak error swish (PES)) are designed to strengthen the importance of the peak runoff's prediction while weakening the weight of the normal runoff's prediction. The feature extractor consisting of three LSTM networks is established for each meteorological station, aiming to extract temporal features of the input data at each station. Taking the upper Huai River Basin in China as a case study, daily runoff from 1960–2016 is predicted using the enhanced LSTM model. Results indicate that the enhanced LSTM model performed well, achieving Nash–Sutcliffe efficiency (NSE) coefficient ranging from 0.917–0.924 during the validation period (November 2005–December 2016), outperforming the widely used lumped hydrological models (Australian Water Balance Model (AWBM), Sacramento, SimHyd and Tank Model) and the data-driven models (artificial neural network (ANN), support vector regression (SVR), and gated recurrent units (GRU)). The enhanced LSTM with PES as loss function performed best on extreme runoff prediction with a mean NSE for floods of 0.873. In addition, precipitation at a meteorological station with a higher altitude contributes more runoff prediction than the closest stations. This study provides an effective tool for daily runoff prediction, which will benefit the basin's flood defense and water security management.
Inspired by state-of-the-art material science, computer techniques, artificial intelligence, and automatic control, new-generation transportation infrastructures are becoming digitalized and intelligent. Many major developed countries around the globe are actively promoting the application of innovative intelligence-based technologies in transportation infrastructures in accordance with local conditions. This review begins with a brief discussion on the basic definition, scientific foundation, and development process for the intellectualization of transportation infrastructures. Then, following the whole life-cycle chain of design, construction, operational maintenance, and elimination, the current research status and major challenges presented by intellectualization technologies are systematically investigated. Subsequently, recent achievements in intellectual technologies are comprehensively presented by selecting the Beijing–Zhangjiakou High-Speed Railway—the world's first railway built based on the concept of intelligent construction—as an example. Finally, a discussion on the future development of the intellectualization of transportation infrastructures is provided from the three dimensions of standard systems, theoretical methods, and talent training.
Highlights•[email protected]3ZnC0.7 was successfully synthesized as an effective adsorbent and oxidation catalyst.•Surface hydroxyl groups are the key active sites of both adsorption and degradation.•The degradation process regenerates the adsorption capacity of the catalyst.•Non-radical pathway is the main pathway of degradation in ZN-CS/PMS system.•The magnetic composite can be easily separated and the reusability was verified excellent.The heterogeneous catalytic activation of peroxymonosulfate for wastewater treatment is attracting increased research interest. Therefore, it is essential to find a sustainable, economical, and effective activated material for wastewater treatment. In this study, metal–organic frameworks (MOF)-5 was used as the precursor, and a stable and recyclable material [email protected]3ZnC0.7 that exhibited good adsorption and catalytic properties, was obtained by the addition of nickel and subsequent calcination. To investigate and optimize the practical application conditions, the elimination of rhodamine B (RhB) in water was selected as the model process. This study demonstrated that the degradation of organic matter in the system involved a coupling of the adsorption and degradation processes. Based on this, the mechanism of the entire process was proposed. The results of scanning electron microscopy, infrared spectrum analysis, and theoretical analysis confirmed that the van der Waals forces, electrostatic attraction, and hydrogen bonding influenced the adsorption process. Electron paramagnetic resonance analysis, masking experiments, and electrochemical tests conducted during the oxidative degradation process confirmed that the degradation mechanism of RhB included both radical and non-free radical pathways, and that the surface hydroxyl group was the key active site. The degradation of the adsorbed substrates enabled the regeneration of the active sites. The material regenerated using a simple method exhibited good efficiency for the removal of organic compounds in four-cycle tests. Moreover, this material can effectively remove a variety of organic pollutants, and can be easily recovered owing to its magnetic properties. The results demonstrated that the use of heterogeneous catalytic materials with good adsorption capacity could be an economical and beneficial strategy.
The microbial conversion of alkanes to methane in hydrocarbon contaminated environments is an intrinsic bioremediation strategy under anoxic conditions. However, the mechanism of microbial methanogenic alkane degradation is currently unclear. Under ten-years of continuous efforts, we obtained a methanogenic n-alkane-degrading (C15–C20) enrichment culture that exhibited sustained improvements in the kinetic properties of methane production. The integrated metagenomic and metatranscriptomic analyses revealed that n-alkanes were mainly attacked by members of Desulfosarcinaceae, Firmicutes, and Synergistetes using the fumarate addition strategy, and were then further degraded in a common effort by Tepidiphilus members. Meanwhile, the abundant members of Anaerolineaceae were mainly responsible for cell debris recycling. However, according to the metatranscriptomic analyses, methane was predicted to be produced mainly via H2-dependent methylotrophic methanogenesis, primarily from necromass-derived trimethylamine mediated by Methanomethyliaceae within the candidate phylum Verstraetearchaeota. These findings reveal that H2-dependent methylotrophic methanogens, as well as methylotrophic methanogens, may play important ecological roles in the carbon cycle of hydrocarbon enriched subsurface ecosystems.
DNA is considered to be not only a carrier of the genetic information of life but also a highly programmable and self-assembled nanomaterial. Different DNA structures are related to their biological and chemical functions. Hence, understanding the physical and chemical properties of various DNA structures is of great importance in biology and nanochemistry. However, the bulk assay ignores the heterogeneity of DNA structures in solution. Single-molecule methods are powerful tools for observing the behavior of individual molecules and probing the high heterogeneity of free energy states. In this review, we introduce single-molecule methods, including single-molecule detection and manipulation methods, and discuss how these methods can be conducive to measuring the molecular properties of single-/double-stranded DNA (ss/dsDNA), DNA higher-order structures, and DNA nanostructures. We conclude by providing a new perspective on the combination of DNA nanotechnology and single-molecule methods to understand the biophysical properties of DNA and other bio-matter and soft matter.