Non-contact immobilization of macromolecules, cells, and other bioparticles plays an important role in life science and clinical diagnostics. State of the art acoustofluidics typically treat bio-particles in a multi-wavelength range due to the scale limitations of the established ultrasound field. Here, the theory and method of spatiotemporal modulation of the multiple physical fields for SAW microfluidics is proposed. We report several selective acoustofluidic devices that allow trapping and heating bio-particles in a wavelength scale. We also show that the temperature field of a droplet on the path of a travelling surface wave can be regulated by modulating the heat source distribution and thermal conduction inside the target. Through proof-of-concept experiments, the proposed acoustofluidic devices show potential applications in on-chip biological and chemical analyses, where localized handing and heating is required.

Thermal error has an adverse effect on the operating accuracy of the machine tool. Therefore, reducing the thermal error is very important to improve the machining accuracy. In this paper, in order to realize real-time compensation, taking a three-axis machine tool as an example and a method for robust modeling and predicting thermally induced positional error is proposed. First of all, the number of temperature measuring points required in thermal error’s model was reduced based on the rough set theory, which greatly reduced variable searching and modeling time. Then through grey relation theory, systematic analysis of the similarity degree between thermal error and temperature data was carried out to select sensitive temperature measuring points. which eliminated the coupling problems. The thermal error prediction model of LSTM（ Long Short Term Memory） neural network is established by using temperature change and error data as input samples. The results show that the prediction accuracy of the proposed thermally induced position error model is reliable.

The vibration and noise of transformer core under DC bias are studied in this paper. Firstly, the 30ZH120 silicon steel sheet is tested for B-H and B-λ. The test results in electromagnetic and magnetostrictive characteristics of electrical steel sheet under different DC bias conditions are given. Secondly, based on the Preisach model, the hysteresis model of electrical steel sheet under DC bias is derived. This model is based on the classical Preisach model and describes the influence of DC component on hysteresis model. Thirdly, the vibration and noise of transformer under DC bias are simulated by FEM. The calculation results under different DC bias conditions are obtained. Finally, the vibration noise of transformer is studied experimentally, and the accuracy of simulation results is verified. This work supplements the derivation of Preisach model under DC bias and provides a basis for designers to understand the vibration and noise characteristics of transformer under DC bias.

To increase the areal density in heat assisted magnetic recording (HAMR), a split pole head with integrated nano coil was investigated using numerical simulations. The unique head design realized a preferable head field distribution. LLG micromagnetic recording simulations showed that the head field distribution was effective at reducing the transition curvature.

The classical Jiles-Atherton model is a typical magnetic hysteresis model. However, there are some deviations between actual magnetization curve and the modeled one, especially in the case of unsaturated magnetization curve which is important as a factor the increases hysteresis loss in actual components of electromagnetic equipment. The hybrid modified Jiles-Atherton model is proposed to avoid such deviations. In this paper, we applied the HJA model to symmetric and asymmetric magnetic hysteresis loops. And, Ni, which has stable composition and magnetic properties, is adopts as the material.

As a result, it is shown that the symmetric and asymmetric hysteresis loops of Ni under several applied magnetic field conditions can be expressed by HJA model with good accuracy. And this result also shows that the HJA model could be applied to describing hysteresis loops of various materials.