Effect of antiferromagnetic coupling at interfaces on magnetic properties of Gd/CoFeTaB multilayers

In this work, a multilayer structure composed of Gd and CoFeTaB was prepared by magnetron sputtering, and the effect of annealing temperatures on magnetic properties of the multilayer structure are investigated. The existence of interfacial antiferromagnetic coupling in this system was proved by analysis of microstructure, magnetic characteristics, and magnetic resonance characteristics. The preparation of artificial multilayer antiferromagnetic structure with weak stray fields was demonstrated, which provides a shortcut for spintronics application

Additive Manufacturing of Rare Earth Permanent Magnetic Materials: Research Status and Prospects

With the rapid development of intelligent manufacturing, modern components are accelerating toward being light weight, miniaturized, and complex, which provides a broad space for the application of rare earth permanent magnet materials. As an emerging near-net-shape manufacturing process, additive manufacturing (AM) has a short process flow and significantly reduces material loss and energy consumption, which brings new possibilities and impetus to the development of rare earth permanent magnetic materials. Here, the applications of AM technology in the field of rare earth permanent magnets in recent years are reviewed and prospected, including laser powder bed fusion (LPBF), fused deposition modeling (FDM), and binder jetting (BJ) techniques. Research has found that the magnetic properties of AM Nd-Fe-B magnets can reach or even exceed the traditional bonded magnets. In addition, in situ magnetic field alignment, in situ grain boundary infiltration, and post-processing methods are effective in enhancing the magnetic properties of AM magnets. These results have laid a good foundation for the development of AM rare earth permanent magnets

A GIS-Based Probabilistic Spatial Multicriteria Roof Water Inrush Risk Evaluation Method Considering Decision Makers’ Risk-Coping Attitude

A combination of geographic information system (GIS) and spatial multicriteria decision making (MCDA) in mine water inrush risk evaluation is widely used, but the randomness in the process of index weight determination and the risk-coping attitude of decision makers are not considered in the decision making process. Therefore, this paper proposes a probability-based roof water inrush risk evaluation method (GIS-MCDA) by combining the Monte Carlo analytic hierarchy process (MAHP) and ordered weighted averaging (OWA) operator. This method uses MAHP to determine the weight of the evaluation indicators, reducing the randomness of the analytic hierarchy process (AHP) to determine the weight of the evaluation indicators using the OWA operator to quantify the five risk-coping attitudes of decision makers and incorporate the risk attitude of decision makers into the evaluation process. Taking the Liangshuijing Coal Mine in northern Shaanxi as an example, the application of the GIS-MCDA method showed that the method makes the risk results of roof water inrush more objective and comprehensive and reduces or avoids the risk of decision making due to human subjective tendency change

Study on the application of artificial neural network-based flamelet/progress variable model in supersonic combustion

The flamelet model has the characteristics of high efficiency and physical intuition and has excellent application prospects in supersonic turbulent combustion simulation. Expanding the dimensions of the flamelet model is a potential direction for model development in order to improve its applicability and accuracy, but the accompanying surge in memory is a problem that must be avoided. Therefore, the idea of using the artificial neural network (ANN) model to replace the flamelet database is a feasible exploration currently and has been preliminarily applied in 2D flamelet databases based on central processing unit frameworks. Based on the 3D flamelet database of the flamelet/progress variable (FPV) model, this article studies the strategy of using ANN to replace the flamelet database of the FPV model in a graphics processing unit framework. Due to the significant influence of the progress variable source term and heat release rate on the combustion calculation and the large range of these two parameters, four data processing methods are used to train the parameters separately, and three indicators are used to evaluate the training performance. Subsequently, based on the ANN model using different data processing methods mentioned earlier, calculations are conducted on a hydrogen-fueled supersonic combustion, and the computational accuracy is evaluated. The results indicate that the strategy proposed in this study can screen out artificial neural network replacement models with the same accuracy as the traditional flamelet model

Study on magnetic and electrical properties of CoFeTaBO films with different oxygen content based on two-state model

Amorphous magnetic CoFeTaBO granular films with different oxygen contents are fabricated by using magnetron sputtering. The effect of oxygen contents on magnetic and electrical properties of the amorphous CoFeTaBO granular films are investigated, and a model for the coexistence of two states of oxygen-dependent metallic oxides in the CoFeTaBO film is proposed to explain magnetic and electrical characteristics in amorphous film system. It is expected that our proposed two-state model can provide a new perspective for understanding the physical properties of amorphous magnetic granular film materials