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Biomass-derived carbon materials have received a surge of scientific attention to develop lightweight and broadband microwave absorbers. Herein, rodlike porous carbon materials derived from cotton have been fabricated with uniformly dispersed CoFe2O4 nanoparticles via facile and scalable process. The combination of magnetic particles and carbonaceous material is advantageous to realize the magnetic-dielectric synergistic effect which could effectively promote the dissipation of incident waves, giving rise to an optimal reflection loss value of –48.2 dB over a qualified bandwidth (4.8 GHz) at 2.5 mm. The cotton-derived carbon rods with conductive network not only act as a supporter to carry the CoFe2O4 nanoparticles, but also provide massive heterointerfaces to facilitate the interfacial polarization. In consideration of the renewable and abundant resource of cotton, the as-prepared CoFe2O4/C composites would meet the increasing demand of lightweight and highly efficient microwave absorbers.

A running compressor generates a huge amount of data every day. Some of the data contains useful information that allows the user to determine in advance whether the machine will fail or not. Forecasting in advance cannot only avoid the huge loss caused by unnecessary downtime but also ensure the safety of staff. The main tasks of compressor condition monitoring include data acquisition, data preprocessing, data analysis, alarm module, response strategy analysis, etc. Prediction is one of the tasks of condition monitoring. This paper mainly studies the performance of different time prediction models on the running data produced by a centrifugal compressor. In the data preprocessing part, this paper uses Bayesian wavelet denoising and probabilistic principal component analysis methods proposed by the research group to remove the useless parts in the data. In the part of time series model, the prediction performance of LSTM, GRU and ARIMA on the same dataset is compared. The comparative results indicate that since the dataset is non-stationary, the LSTM and GRU outperform the statistical ARIMA model.

As an efficient global optimization method to deal with expensive black-box functions, Bayesian optimization (BO) has great potential in the field of turbomachinery component design. It can relieve the complexity, long cycle, and excessive dependence on experience of the design process. A core of Bayesian optimization is acquisition functions which aim to guide the search to efficiently find the optimum. An excellent acquisition function can greatly improve the performance of the algorithm. The well-known acquisition function, upper confidence bound (UCB), in Bayesian optimization achieves the balance between local exploitation and global exploration through an explicit trade-off coefficient. The trade-off coefficient is a key to the quality of UCB-based Bayesian optimization. Currently, this coefficient is either manually specified according to some criterion or sampled from a specific distribution. Due to the lack of a comparative study on existing trade-off strategies, this paper attempts to comprehensively analyse and highlight the impact of various trade-off strategies on the performance of UCB-based BO algorithm through eleven numerical examples and two turbomachinery design cases. The comparative results indicate that the proper trade-off is key for the optimization quality, and the strategy of looping through a trade-off set shows superiority in our numerical experiments.

In this paper, we introduce a novel and simple method to fabricate a preconcentrator based on the ion concentration polarization phenomenon (ICP). Using a three-dimensional printed layer, the microchannels could be easily integrated with an ion exchange membrane which plays the role of the nanoporous junction needed for ICP. To demonstrate the preconcentration ability of the devices, we conducted experiments with negatively charged fluorescein sodium and positively charged rhodamine 6G. As a result, the negatively charged sample could be preconcentrated more than 18 fold by using a cation exchange membrane. The positively charged sample could be preconcentrated more than 40 fold by using an anion exchange membrane. This preconcentrator with a simple fabrication process could be implemented in various microfluidic systems for biochemical assays.

We have observed light emission with a luminance of 3.5 cd m−2 from a diamond:Ce thin-film electroluminescence device at an applied voltage of 150 V. The electroluminescence spectrum at room temperature shows main peaks centred at 454 and 490 nm, which are attributed to isolated emission centres of Ce3+ ions.