Oximation reaction induced reduced graphene oxide gas sensor for formaldehyde detection

High-performance gas sensors can offer great potentials for monitoring and detection ofvolatile organic compounds (VOCs) in both domestic and industrial environment. In the presentwork, a new HCHO gas sensor was constructed with reduced graphene oxide (RGO) induced bythe oximation reaction. The gas-sensing performance test results suggested that the RGO hydrox-ylamine hydrochloride (RGO/HA-HCl) sensor presented a high response of 75% at 16 ppm HCHOat room temperature, and a high selectivity for HCHO suffering little interference with high concen-trations of volatile organic compounds, including methanol, ethanol, and methylbenzene, dichlor-omethane and water. Additionally, the RGO/HA-HCl sensor also showed a good long-termstability with RSD of 5.83% for a 15-day continuous sensing test, and the detection limit (DL)could reach 0.023 ppm under ambient conditions. Moreover, the mechanism for the high sensitivityand selectivity of formaldehyde was further established by in-situ gas chromatography mass spec-trometry (GC–MS). This work would provide a reliable new HCHO gas sensor which could be usedfor monitoring and forewarning the emission of HCHO for a better protection and improvement ofour environment

Signal enhancement with stacked magnets for high-resolution radio frequency glow discharge mass spectrometry

A method for signal enhancement utilizing stacked magnets was introduced into high-resolution radio frequency glow discharge-mass spectrometry (rf-GD-MS) for significantly improved analysis of inorganic materials. Compared to the block magnet, the stacked magnets method was able to achieve 50−59% signal enhancement for typical elements in Y2O3, BSO, and BTN samples. The results indicated that signal was enhanced as the increase of discharge pressure from 1.3 to 8.0 mPa, the increase of rf-power from 10 to 50 W with a frequency of 13.56 MHz, the decrease of sample thickness, and the increase of number of stacked magnets. The possible mechanism for the signal enhancement was further probed using the software “Mechanical APDL (ANSYS) 14.0”. It was found that the distinct oscillated magnetic field distribution from the stacked magnets was responsible for signal enhancement, which could extend the movement trajectories of electrons and increase the collisions between the electrons and neutral particles to increase the ionization efficiency. Two NIST samples were used for the validation of the method, and the results suggested that relative errors were within 13% and detection limit for six transverse stacked magnets could reach as low as 0.0082 μg g−1. Additionally, the stability of the method was also studied. RSD within 15% of the elements in three nonconducting samples could be obtained during the sputtering process. Together, the results showed that the signal enhancement method with stacked magnets could offer great promises in providing a sensitive, stable, and facile solution for analyzing the nonconducting materials

Larmor precession: observation and utilization for boosting the signal intensity of radio frequency glow discharge mass spectrometry

A novel magnet array system was constructed to use Larmor precession for boosting the signal intensity of rf-GD-MS. The enhancement mechanism with four magnet array devices of single block magnet and 2×2, 3×2, and 3×4 magnet arrays was simulated and studied by COMSOL Multiphysics Software 5.4.0 (COMSOL) to determine if the electrons in the discharge plasma could perform Larmor precession along the direction perpendicular to the magnetic field. Induced by Larmor precession, inelastic collisions between the primary electrons and sample produced numerous secondary electrons and further improved the ionization efficiency. Moreover, the fuzzy synthetic evaluation result predicted that the device with 3×2 magnet array would display the greatest enhancement effect among the four devices. Based on these theoretical studies, a magnet array system with four magnet array devices was fabricated and utilized for studies of two scintillation crystals BGO and PWO. The observations indicated that the signal intensities obtained for 209Bi and 208Pb with the magnet array system were 630-3600 times of that obtained without magnet, and were enhanced by a factor of 1.5-2.8 compared with a previously reported stacked magnetic device. Two NIST samples were used to validate the method, and the results suggested that relative errors were less than 10% and the lowest detection limit for the 3×2 magnet array could reach 0.0032μg•g−1. Furthermore, the magnet array enhancement system with Larmor precession offers an efficient and sensitive approach for the direct analysis of non-conducting materials

Sources of nitrate in a heavily nitrogen pollution bay in Beibu Gulf, as identified using stable isotopes

Eutrophication, mainly caused by the oversupply of inorganic nitrogen and phosphate, has increased and become a serious environmental problem in the coastal bays of Beibu Gulf, a newly developing industry and port in South China. However, the sources of nitrate are poorly understood in the gulf. In this study, nitrate dual isotopes (δ15N-NO3- and δ18O-NO3-) and ammonium isotopes (δ15N-NH4+) were measured during the rainy season to identify the nitrate sources and elucidate their biogeochemical processes in Xi Bay, a semi-enclosed bay that is strongly affected by human activities in the Beibu Gulf. The results showed that a high dissolved inorganic nitrogen (DIN, 10.24-99.09 µmol L-1) was observed in Xi Bay, particularly in the bay mouth. The concentrations of DIN in the bay were 1.5 times higher than that in Qinzhou Bay and 1.7 times than that in Tieshangang Bay, which mainly influenced by the intensive human activities (i.e., industrial and port activities). In addition, lower values of δ15N-NO3- and δ18O-NO3- and higher values of δ15N-NH4+ were observed in the upper bay, suggesting that microbial nitrification occurs in the upper bay, which was the dominant nitrate source in the upper bay (39%). In addition to nitrification, external sources, including sewage and manure (33%), soil N (15%) and fertilizer (11%), contributed to the higher nutrients in the upper bay. In the lower bay, severe nitrogen pollution led to a weaker impact of biological processes on isotopic fractionation, although a high Chl a level (average of 7.47 µg L-1) was found in this region. The heavy nitrate pollution in the lower bay mainly originated from sewage and manure (54%), followed by soil N (26%) and fertilizer (17%). The contribution of the nitrate source from atmospheric deposition was relatively low in the bay (<3%). This study suggests that biogeochemical processes have little impact on nitrate dual isotopes under heavy nitrogen pollution, and isotopes are an ideal proxy for tracing nitrogen sources

GeoGauss: Strongly Consistent and Light-Coordinated OLTP for Geo-Replicated SQL Database

Multinational enterprises conduct global business that has a demand for geo-distributed transactional databases. Existing state-of-the-art databases adopt a sharded master-follower replication architecture. However, the single-master serving mode incurs massive cross-region writes from clients, and the sharded architecture requires multiple round-trip acknowledgments (e.g., 2PC) to ensure atomicity for cross-shard transactions. These limitations drive us to seek yet another design choice. In this paper, we propose a strongly consistent OLTP database GeoGauss with full replica multi-master architecture. To efficiently merge the updates from different master nodes, we propose a multi-master OCC that unifies data replication and concurrent transaction processing. By leveraging an epoch-based delta state merge rule and the optimistic asynchronous execution, GeoGauss ensures strong consistency with light-coordinated protocol and allows more concurrency with weak isolation, which are sufficient to meet our needs. Our geo-distributed experimental results show that GeoGauss achieves 7.06X higher throughput and 17.41X lower latency than the state-of-the-art geo-distributed database CockroachDB on the TPC-C benchmark

Covalently introducing sulfur in a thiol-rich metal-organic framework toward advanced lithium-sulfur batteries

The severe shuttle effect and sluggish reaction kinetics have hindered the commercial application of high-energy lithium-sulfur (Li-S) batteries. In this work, a dual-thiol metal-organic framework (MOF) was in situ synthesized on carbon nanotubes, and sulfur was covalently connected to this composite (UiO-66(SH)2@CNT) to form a MOF-sulfur copolymer (S-UiO-66(SH)2@CNT). Benefiting from the strong covalent interaction between thiol groups and sulfur species, the S-UiO-66(SH)2@CNT cathode can retard the shuttle effect and simultaneously strengthen the redox kinetics of polysulfides. As a result, a discharge capacity of 791 mAh g-1 is achieved at a current density of 0.2 C, whereas the S/UiO-66@CNT cathode using the blend of UiO-66@CNT and sulfur as active materials only shows a specific capacity of 670 mAh g-1. Moreover, the S-UiO-66(SH)2@CNT cathode exhibits a higher capacity retention of 93.27 % at 0.5 C during 200 cycles compared with that of the S/UiO-66@CNT cathode (64.94 %). This work will provide significant inspiration for the design of advanced MOFs and cathodes for excellent Li-S batteries

Magnetic enhancement for the analysis of scintillation crystals by radio frequency glow discharge mass spectrometry

A ring magnet enhancement method was developed and utilized for boosting the signal intensity of the analysis of scintillation crystals by radio frequency glow discharge mass spectrometry (rf-GD-MS). Three scintillation crystals of BGO, LYSO and GGAG were applied to observe the performance of the ring magnet method. The investigations suggested that the signal intensities obtained for 209Bi, 175Lu and 158Gd with the ring magnet were 7810–27 600 times those obtained without a magnet and were enhanced by a factor of 1.9–2.3 compared with the previously reported stacked magnet and array magnet methods. The results also suggested that the signal intensity was enhanced as the rf power increases from 25 W to 70 W (with a frequency of 13.56 MHz) and a sharp rise up to 4.8 MPa and then decreased with the increase of discharge pressure from 2.2 to 8.4 MPa. The validation results with two NIST samples indicated that the relative errors were within 13% and the lowest detection limit could reach as low as 0.0023 μg g−1 (24Mg, with 40 W and 4.8 MPa) for the ring magnet. The enhancement mechanism of this method was further proposed in which electrons could undergo distinct Larmor precession with a ring magnet, which could increase the collisions between the electrons and other particles to increase the ionization efficiency. Moreover, this work not only shed light on the possible enhancement mechanism by the ring magnet but also provided an effective determination method for the artificial crystals

An Intelligent Nonlinear Control Method for the Multistage Electromechanical Servo System

In order to meet the requirements of servo systems, including sensitive and rapid adjustment, high control and motion accuracy, and strong working adaptability, in special application fields, such as high thrust and long travel, an adaptive inversion control method is proposed for the lateral force and other nonlinear factors of multistage electromechanical servo system (MEMSS). The position tracking controller of permanent magnet synchronous motor (PMSM), based on an improved adaptive inversion method, was designed and its stability was analyzed, and the Luenberger load torque observer model of PMSM was established. The EMESS simulation model of an adaptive inversion controller was built using the Simulink platform, and the motor multibody dynamics model was established in ADAMS software. Through the joint simulation of Simulink and ADAMS software, the results of EMESS under adaptive inversion controller and traditional PID controller were compared, and the feasibility and reliability of the designed adaptive inversion controller were verified. Finally, the designed controller was tested based on the experimental platform. The experimental results show that the adaptive inversion controller designed in this paper has better robustness and stability than the traditional PID controller

Electromechanical Actuator Servo Control Technology Based on Active Disturbance Rejection Control

Electromechanical actuators (EMA) are becoming more and more widely used. As the core technology of EMA, servo control technology determines their performance. In this paper, an active disturbance rejection control (ADRC) method with an improved extended state observer (ESO) is proposed to design a cascade controller of EMA based on permanent magnet synchronous motor (PMSM). The mathematical model of PMSM in a two-phase rotating coordinate system is established, then it is decoupled by an id=0 current control method to realize the vector control of the motor. In a three closed-loop vector control system, a PID controller including current loop, speed loop and position loop is designed. To solve the problems caused by measurement noise, the filter link and system are modeled as a whole, and an improved ESO is constructed. On this basis, an ADRC controller of the speed loop and position loop of PMSM is designed and simulated based on Simulink. Based on the physical test platform, a load step test and load disturbance test of ADRC are completed. The results show that, in comparison to the PID method, the ADRC method shortens the response time by 25% on average, and reduces the overshoot by 60% on average. So, it can be concluded that ADRC has good static and dynamic performance, which has a good guiding role for engineering practice

Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16

In this paper, an inter-turn short-circuit fault of a permanent magnet synchronous motor in an electromechanical actuator is analyzed, and a fault diagnosis method based on transfer learning with a VGG16 convolution network is proposed. First, a 2D finite element model of an inter-turn short circuit fault of a permanent magnet synchronous motor was established in ANSOFT Maxwell, and then a simulation experiment analysis was completed. A three-phase current was chosen as a fault characteristic signal. Second, a fault diagnosis method with a VGG16 deep convolutional neural network and based on transfer learning was designed, and the fine tuning of the hyperparameters of the fault diagnosis model was completed by using grid search and cross verification methods. Finally, based on the transfer learning VGG16 model established in this paper, the inter-turn short circuit fault of a permanent magnetic synchronous machine (PMSM) was diagnosed and verified. The experimental results showed that the proposed convolutional network model based on transfer learning can identify faults effectively and accurately, and has a good engineering guidance significance