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This article investigates the real-time diagnosis of single and double open circuit faults (OCFs) in three-phase voltage source inverters (VSIs). The method analyzes the phase current waveforms continuously in real-time, and abnormal patterns of the current waves due to the corresponding switch OCFs are extracted to define as the fault detection waveforms (FDW). The current values of the FDWs are analyzed and a new scheme is developed to distinguish current waveform patterns from those of normal to unbalanced loads situations and switch OCFs. The scheme detects the starting zero crossing point first and then checks the magnitudes of the FDW. Periodic detections are applied to identify whether the collected data samples are within the FDW current range. The OCFs of the inverter switches are identified by counting the fault points within the predicted samplings of FDWs. The method has been verified through both simulations and experiments. The results confirm the effectiveness of the proposed scheme.

A dc-link capacitor is an important device and the vulnerable electronic part of the train converter. The capacitance decline of the dc-link capacitor is accelerated because of the influence of voltage, current, charge–discharge frequency, temperature, and other factors. This will lead to circuit performance degradation and even capacitor failures. Therefore, the capacitance estimation of dc-link capacitors is necessary and of great significance to the safe operation of the train. However, the voltage sensors used in the train converter have large noise and low sampling frequency, which makes it difficult to obtain accurate capacitance estimations with existing methods. In this article, an effective capacitance estimation method is proposed to solve these problems. The precharging process is analyzed and an estimation model is built to weaken the impact of the sensor noise. Based on the model, a three-stage iteration algorithm is used for capacitance estimations, which can effectively search for the optimal solution at a low sampling frequency and further reduce the noise influence. The proposed method was verified on a metro vehicle and compared with other algorithms. The experimental results show that the aforementioned problems can be well solved by the proposed method and the estimation error is within 2%.

DC-link capacitor is one of the significant parts of traction converters. Due to the impact of electrical stress, high temperature and humidity, its capacitance degrades faster than expected. Accurate capacitance estimation is critical to the condition monitoring of DC-link capacitors, which is also the basis of online capacitor life prediction. Currently, there is a big challenge for capacitor capacitance estimation in railway applications. The noise fluctuation of the voltage sensor may be nearly equal to that of ripple voltage, leading to the considerable errors of the existing capacitor condition monitoring methods. Therefore, a capacitance estimation method based on precharging model and noise evaluation is proposed in this article. The capacitance is estimated by improved recursive extended least square. The influence of the noise can be effectively reduced and both the calculation accuracy and convergence speed can be well guaranteed through an independent noise estimation model. The proposed method has good immunity in a certain range of signal-noise ratio or signal bias. It shows good performance in experiments.

Passing the neutral section (NS) can causes transient impact and speed loss of the train. Therefore, whether the potential danger of the pantograph-catenary system (OCS) can be eliminated under the condition of full-load operation becomes one of the essential factors for the safe and efficient operation of electric locomotives. This article proposes an advanced method to optimize the structure and control algorithm, according to the drawbacks of the existing methods, such as miniature circuit capacity, poor output driving ability, low control accuracy, and slow system response speed. In this method, the pantograph-catenary arc is restrained by controlling the dynamic alternating transfer of instantaneous power. Besides, the voltage premodulation algorithm is used to realize flexible voltage switching between different adjacent power supply arms. Compared with the existing methods, this method can provide better system response output capability, and this can effectively suppress transient impact and ensure full-load train operation safety. Finally, in terms of transient suppression effect and resistance to external environmental interference, a series of functional verification and horizontal comparison experiments have proved the feasibility, superiority, and robustness of this method.

Micro-voids defects associated with materials formed by diffusion bonding and super-plastic connection limit their usage in the aerospace industry. A crystal plasticity finite element (CPFE) model was established in the current work to investigate the relationship between local stress concentration and the micro-void defects, and predict the fatigue crack initiation lifetime. Based on the concept of the curvature of the crack tip, the shape and size of the voids are strictly separated, so that the influence of the single parameter of voids on the microplasticity deformation behavior is better obtained. It's found that the micro-voids lead to the stress concentration phenomenon in the material, the effect of the curvature of the void tip surface is greater than that of the void size. Stress concentration tends to occur in the hard grains. When L/dis greater than 2.0, stress concentration factor reaches a constant small value. The simulated results based on the Manson-Collin law and Fatemi-Socie parameter show that when the void tip curvature is greater than 0.4 μm−1or L/d is less than 2.0, the fatigue crack initiation lifetime is less than 106cycles, indicating that the influence of such micro-voids on fatigue crack initiation is small. This work has a good guiding significance for properties and lifetime prediction of the material with defects.

The microscopic deformation behavior of Inconel 625 superalloy has been investigated by means of nanoindentation experiments and crystal plasticity finite element simulations. Based on the electron backscattered diffraction characterizations, the nanoindentation simulations were performed on grains with various orientations. The simulated load–displacement curves match well with those of experiment and the maximum difference in materials hardness between the experimental and the simulation result is about 6.86%, which is within the accuracy of the model. Moreover, surface Schmid factor (SSF) and interior Schmid factor (ISF) were proposed out and the scanning electron microscope and atomic force microscope characterizations were carried out. The results show that the pile-up tends to occur at the locations with a large SSF. Subsequently, the simulations of nanoindentation on [001]-, [011]-, and [111]-oriented grains were performed by the established model. It is revealed that the residual topography changes periodically when the indenter is fixed and the crystal only rotates around the Z-axis of the sample coordinate system. Combining with the analysis of the ISF, this periodicity of residual topography reflects the superimposed effect of the slip systems, and a large ISF promotes the in-plane displacement of the interior material which inhibiting the evolution of pile-up, while a small ISF leads to a high pile-up.

The development of protocols for the construction of congested quaternary centers is highly sought-after. Herein, we report a method for the cross-coupling of C(sp3) tertiary Grignard reagents with C(sp2) styrenyl bromides using readily available nickel precatalysts. We identified conditions that afford the products in practical yield for several combinations of electrophiles and nucleophiles, including sensitive α-magnesiated Grignard reagents. Dependent upon the nature of their substituents, regiodivergency was observed when α-vinyl bromides were employed.

The epidermal growth factor receptor (EGFR) plays an important role in the proliferation of various cancers, and the expression level of EGFR in tumor tissues can provide a basis for the diagnosis and prognosis. Improving the detection technology of EGFR to achieve high sensitivity and faster speed will benefit the diagnosis of many types of tumors. Trace biological samples can be sensitively measured with terahertz (THz) metamaterial devices. Here, a bow-tie array THz metamaterial biosensor is presented and modified with gold nanoparticles (GNPs) and EGFR antibodies for specific EGFR detection. The effect of the size of the GNP on the sensitivity enhancement was also analyzed. Enhanced sensing for EGFR was achieved with the assistance of GNPs and EGFR antibodies. Importantly, the metamaterial functionalized by GNPs and antibodies with a bigger GNP diameter achieves a greater resonance frequency shift. The proposed metamaterial biosensor can also realize tiny-volume EGFR solution detection. Our proposed technique can therefore sense EGFR sensitively with high speed, and can potentially be applied to achieve quick and accurate detection of EGFR related tumors.

We demonstrated a method of fabricating three-dimensional (3D) metal structures in hydrogels with good conductivity by using femtosecond laser ablation and electroplating. The hydrogel containing Ag^+ was first ablated by a femtosecond laser to form microchannels with an entrance achieving surface and then sandwiched between the anode and cathode to operate electroplating. Silver structures were formed along the microchannel from the microchannel entrance close to the cathode due to reduction of Ag^+. The average resistivity of metal structures is measured to be about 4×10^−7Ωm. A tetrahedron metallic microstructure embedded in hydrogel by this method was demonstrated to show its ability of 3D micromachining.

We herein report an effective hydrosilylation of 1,1-disubstituted allenes with a palladium catalyst modified by a monophosphorus ligand, leading to a series of α-tertiary allylsilanes in high yields and exceptional regioselectivities. The employment of BI-DIME is essential for the high reactivities and selectivities. A chiral α-tertiary allylsilane is formed in excellent eefor the first time by employing a chiral monophosphorus ligand.

In recent decades, terahertz (THz) radiation has been widely applied in many chemical and biomedical areas. Due to its ability to resolve the absorption features of many compounds noninvasively, it is a promising technique for chemical recognition of substances such as drugs or explosives. A key challenge for THz technology is to be able to accurately classify spectral measurements acquired in unknown complicated environments, rather than those from ideal laboratory conditions. Support vector machine (SVM) and deep neural networks (DNNs) are powerful and widely adopted approaches for complex classification with a high accuracy. In this article, we explore and apply the SVM and DNN methods for classifying the frequency spectra of glucose and lactose. We measured 372 groups of independent signals under different conditions to provide a sufficient training set. The classification accuracies achieved were 99% for the SVM method and 89.6% for the DNN method. These high classification accuracies demonstrate great potential in chemical recognition.

We herein report a general, practical, and highly efficient method for asymmetric synthesis of a wide range of chiral vicinal diamines via reductive coupling of imines templated by chiral diboron. The protocol features high enantioselectivity and stereospecificity, mild reaction conditions, simple operating procedures, use of readily available starting materials, and a broad substrate scope. The method signifies the generality of diboron-enabled [3,3]-sigmatropic rearrangement.

We propose a genetic algorithm (GA)-based method to improve the sampling efficiency in terahertz time-domain spectroscopy (THz-TDS). For a typical time-domain THz signal, most information are contained in a short region of the pulse, which needs to be densely sampled, while the other regions fluctuating around zero can be represented by fewer points. Based on this clustering feature of the THz signal, we can use much fewer sampling points and optimize the distribution by using a GA to achieve an accurate scanning in less time. Both reflection and transmission measurements were conducted to experimentally verify the performance. The measurement results show that the sampling time can be greatly reduced while maintaining a very high accuracy in both time and frequency domains compared with a high-resolution step scan. This method significantly improves the measurement efficiency. It can be easily adapted to most THz-TDS systems equipped with a mechanical delay stage for fast detection and THz imaging.

Metamaterial (MM) assisted terahertz (THz) label-free biosensing has promising applications. However, the sensitive THz detection of highly absorptive liquid samples remains challenging. Here, we present a novel multi-microfluidic-channel MM biosensor for highly sensitive THz sensing of small-volume liquid samples. The multichannels are set mostly in the strong electric field enhancement area of the MM, which significantly decreases the liquid's amount and enhances the interaction between the sensing targets and the THz wave (thus increasing the sensitivity). The sensing results of isopropyl-alcohol–water mixtures and bovine serum albumin solutions based on the bow-tie array MM with multichannels demonstrate the effectiveness of the proposed design and the great potential in THz biosensing. This design has the advantages of being highly sensitive, label-free, cost-effective, easy to operate, and only needing a tiny liquid volume. Thus, our device provides a robust route for MM-assisted THz label-free biosensing of liquid-based substances.

Rechargeable lithium–iodine batteries with abundant raw materials and low cost are promising electrochemical energy storage systems. Herein, we demonstrate that anchoring iodine to N-doped hollow carbon fold-hemisphere (N-FHS) is highly efficient to overcome slow kinetics and low stability of iodine cathode in lithium–iodine batteries. For the first time, significant effects of carbon framework architecture on the lithium storage performance of iodine cathode are studied in detail. Notably, the fold-hemisphere (N-FHS) is more effective than the similar architectures, such as hollow sphere (N-S) or hemisphere (N-HS), in modifying slow ion transport capability and fast structure deterioration. The superior property of iodine@N-FHS is associated with its highly porous structure and strong interconnection to iodine. The iodine deterioration mechanism in lithium–iodine battery is analyzed, and the deterioration processes of iodine in different carbon frameworks during cycling are investigated. This work opens a new avenue to solve the key problems in lithium–iodine batteries, allowing it an important candidate for energy storage.

During carbon oxidation, the apparent reaction order nranges from 0 to 1. Considering the importance of the value of nto the accuracy of char combustion rate prediction models and the error caused by subjective selections of its value, this study proposes a fast, simple, and accurate method to determine n, the results of which can be applied to improve the accuracy of kinetic models. In the kinetic control region, the apparent carbon oxidation reaction order nwas first determined using a microfluidized bed (MFB). As an example of its application, the value of nthus determined was applied to a universal prediction model of the char combustion rate; the model was further developed using the shrinking-core model to predict the combustion rate of graphite during the entire reaction process. The result shows that the apparent reaction order is close to zero (0.178). The accuracy of predictions using the aforementioned modified model was found to be improved, and the accuracy of the model, as further developed, is nearly unaffected, indicating that this method of determining nhas a broader application potential.