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High-temperature superconducting (HTS) magnets have found wide applications in high-field settings owing to their high current capabilities. Typically, these magnets are powered by high-current power supplies via current leads, which can complicate insulation between cryogenic and room temperature environments. However, new developments in flux pumps for HTS magnets have enabled charging of kA levels of current without power supplies. By combining flux pumps with HTS persistent current operation, it is possible to achieve accurate flux modulation and eliminate the need for power supplies and current leads. In this study, we report on a novel feedback-controlled flux modulation for HTS magnets in persistent current operations. This flux modulation is based on a flux pump mechanism that generates a DC voltage across the charging superconductor by applying a current higher than its critical current. With closed-loop feedback control, our flux modulation can achieve precise injection and reduction of HTS magnet current in increments of 0.5 A. This technology can lead to stable magnetic fields in HTS magnet designs. We anticipate that this work will enable future magnets to operate in a stable persistent current mode within a closed cryogenic chamber, significantly reducing the footprint and power demand of HTS magnets and opening up new opportunities for their applications.

This article introduces the potential use of superconductivity in cryo-electrified aircraft as the aviation industry and governments move toward zero-emissions environmental targets. It outlines the different electrical insulating materials and discusses potential advantages and disadvantages for cryogenic superconducting applications.

This paper studies the magnetization mechanism of a hybrid high temperature superconducting (HTS) trapped field magnet. To address the size limitation of traditional HTS bulk materials, hybridization between HTS-stacked ring magnets and HTS bulks is proposed here. A jointless HTS-stacked ring magnet is used to increase the trapped field area for HTS bulks. A hybrid HTS magnet with 90 mm in length and 60 mm in width was tested to provide a trapped field of 7.35 T in a field cooling magnetization. The paper focuses mainly on understanding the novel magnetization mechanism of this hybrid HTS trapped field magnet. A numerical model based on homogenized H formulation was used to compare with experimental results, and a good match was found. Our experimental and numerical study of the electromagnetic interaction between the HTS-stacked ring magnet and the HTS bulks reveals that there are two magnetization stages, and the magnetization speed differs in these two stages by a sing criterion: whether the HTS-stacked ring magnet is fully penetrated or not. This study confirms that hybridization helps to build large HTS trapped field magnets.

Wind energy is seen as one of the main pillars of renewable energy. However, the intermittent nature of these sources still poses as a major challenge. Moreover, sensitivity to grid faults and response to load changes are also main concerns.Superconducting devices have been introduced to solve grid faults and energy storage problems associated with renewable energy sources. Nevertheless, the cost of superconducting materials was still a major drawback for their application in power grids.In this paper, a novel power electronics circuit is used to connect the superconducting magnetic energy storage (SMES) to a DC system based on a doubly fed induction generator wind turbine. The proposed system merges energy storage function and the fault current limiting function into one device which is referred to as SMES-FCL in this paper.The role played by the SMES-FCL is studied under various scenarios that may affect the whole system. The study of the system is carried in MATLAB/SIMULINK where the system is simulated in standalone and grid-connected modes. In the end, the proposed SMES-FCL control circuit is tested in a small-scale DC system experimentally.

Saccharomyces cerevisiae is an attractive chassis for the production of medium-chain fatty acids, but the toxic effect of these compounds often prevents further improvements in titer, yield, and productivity. To address this issue, Lem3 and Sfk1 were identified from adaptive laboratory evolution mutant strains as membrane asymmetry regulators. Co-overexpression of Lem3 and Sfk1 [Lem3(M)-Sfk1(H) strain] through promoter engineering remodeled the membrane phospholipid distribution, leading to an increased accumulation of phosphatidylethanolamine in the inner leaflet of the plasma membrane. As a result, membrane potential and integrity were increased by 131.5% and 29.2%, respectively; meanwhile, the final OD600 in the presence of hexanoic acid, octanoic acid, and decanoic acid was improved by 79.6%, 73.4%, and 57.7%, respectively. In summary, this study shows that membrane asymmetry engineering offers an efficient strategy to enhance medium-chain fatty acids tolerance in S. cerevisiae, thus generating a robust industrial strain for producing high-value biofuels.

The multi-beam sounding system achieves ultra-wide coverage and high-resolution measurement. Its significantly increased data density has great advantages in accurately depicting the topography of the seabed. However, this requires processing large amounts of data. A preprocessing method that performs in real time automatically identifies outliers in multi-beam bathymetry data, and provides corresponding bathymetry estimates, is able to provide a lot of effective information for the post-processing to improve the data processing efficiency and ensure data quality. In this work, we propose a quality factor (QF) forecasting error (QE) for detecting outliers and forecasting depth in multi-beam bathymetry data. On the basis of the existing QF model for a seabed detection method, and under the assumption of smooth seafloor terrain, we use the QF to select a suitable seabed detection method and eliminate the sounding points that correspond to poor echo characteristics. The uncertainty inferred by the QF is used as the initial parameter for Kalman filter estimation and the depth-value prediction model is formulated. The sounding sequence is sorted by the median value by using the sliding window method. After a second fitting and Kalman filtering, the depth of each point is predicted. A QF model based on forecasting errors is adopted to simplify and unify the outlier detection standards. The selection rules of window length and detection threshold are deeply studied on the basis of simulations performed in this work. For appropriate parameters, the proposed algorithm shows good detection capability for impulse anomalies, cluster anomalies and seabed topography undulations. In addition, the proposed method gives smooth depth-prediction values. Simulation results and analysis show that the proposed algorithm further detects outliers in depth sequences on the basis of the QF and forecasts the sounding points in real time. The QE threshold based on the relative depth is easy to select and is suitable for different sounding systems. This provides effective outlier detection information for post-processing.