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With the proposal and development of the Material Genome Engineering program, artificial intelligence has played a significant role in accelerating the research and development of new materials. In the field of electrical engineering materials, high-throughput experimental and computational methods provide a huge amount of data. It also poses new challenges to how to manage material data scientifically and efficiently. Database technology has become a hot topic for material scientists and engineers. This paper makes a comprehensive overview of the development, demand analysis and application of database technology in the electrical engineering materials, and discusses the existing problems and the future development trend of the database. Compared with many materials, such as energy materials, catalytic materials, biomedical materials, etc., the electrical material database still has a long way to go in the process of database platform construction, management and operation, and practical application. However, driven by governmental support and market demand, the construction of electrical material database will gradually improve and play an important role in the data-driven new materials researches. [ABSTRACT FROM AUTHOR]

Rational water and fertiliser management have an important impact on alfalfa production. This research aimed to explore the effects of water and phosphorus (P) fertiliser on water‐use efficiency (WUE) and phosphorus‐recovery efficiency (PRE) of each cut of alfalfa under drip irrigation and to determine the optimal interaction ratio of water and phosphorus to improve the quality and yield of alfalfa. Different irrigation levels were set, i.e., 5250, 6000 and 6750 m3/ha (referred to as W1, W2, W3, respectively), and P fertiliser levels (0, 50, 100 and 150 kg/ha P2O5 referred to as P0, P1, P2, P3, respectively) were set to determine the hay yield and nutrient quality of each cut of alfalfa under drip irrigation. The hay yield of each cut of alfalfa increased first and then decreased with increased P fertiliser under the same irrigation amount. WUE decreased gradually with an increasing amount of irrigation under the same P application rate. The WUE of alfalfa increased first and then decreased with the increase of P application rate under the same irrigation amount, and WUE was 0.20%–4.75% (2016) and 1.31%–6.22% (2017) higher in the P treatments than in the non‐phosphorus treatments. PRE decreased gradually with increasing P application rate under the same irrigation amount. Therefore, we concluded that moderate irrigation (6000 m3/ha) and P fertiliser (100 kg/ha) optimised WUE, PRE, hay yield and nutrient quality. [ABSTRACT FROM AUTHOR]

The data-driven method has been widely used to mine knowledge from the smart shop floors' production data to guide dynamic scheduling. However, the mined knowledge may be invalid when the production scene changes. In order to address this problem and ensure the validity of the knowledge, this paper studies a data-driven scheduling knowledge life-cycle management (SKLM) method for the smart shop floor. The proposed method includes four phases: knowledge generation, knowledge application, online knowledge evaluation, and knowledge update. Specifically, the extreme learning machine (ELM) is applied to learn knowledge based on the composite scheduling rules. The quality control theory is used to evaluate the quality of scheduling knowledge. And the online sequential ELM (OS-ELM) is adopted to update the knowledge. Knowledge life-cycle management is implemented through the iterative knowledge update. The proposed method is validated on the MIMAC6, which is a simulation model of the semiconductor production line. Experimental results show that the proposed method could improve the effectiveness of scheduling knowledge and further optimize the performance of the smart shop floor. [ABSTRACT FROM AUTHOR]

We analyze the material removal mechanism of abrasive jet polishing (AJP) technology, based on the fluid impact dynamics theory. Combined with the computational fluid dynamics simulation and process experiments, influence functions at different impingement angles are obtained, which are not of a regular Gaussian shape and are unfit for the corrective figuring of optics. The influence function is then optimized to obtain an ideal Gaussian shape by rotating the oblique nozzle, and its stability is validated through a line scanning experiment. The fluctuation of the influence function can be controlled within [+ or -] 5%. Based on this, we build a computed numerically controlled experimental system for AJP, and one flat BK7 optical glass with a diameter of 20 mm is polished. After two iterations of polishing, the peak-to-valley value decreases from 1.43[lambda] ([lambda] = 632.8 nm in this paper) to 0.294[lambda], and the rms value decreases from 0.195[lambda] to 0.029[lambda]. The roughness of this polished surface is within 2 nm. The experimental result indicates that the optimized influence function is suitable for precision optics figuring and polishing. OCIS codes: 220.0220, 220.4610, 220.5450.

Figuring technologies based on intracone and intercone stitching for high-gradient mirrors are discussed. Based on the conventional computer-controlled optics shaping principle, a process model for a single cone with intracone stitching is constructed. With the circular stitching property of the model, a modified Bayesian-based Richardson--Lucy (RL) algorithm is deduced to deconvolute dwell time for single cone. Building on this algorithm, with the introduction of intercone stitching, a process model for a complex cone is built. Then another modified Bayesian-based RL algorithm is deduced to deconvolute the dwell time for a complex cone from the properties of intracone stitching and intercone stitching. With a velocity realization method for dwell time on a spiral path of the cone and the determination criterion of the path parameter, figuring technologies for single and complex cones are presented. Simulation and experiment demonstrate that theories and methods discussed can solve key problems of figuring high-gradient mirrors; the figuring technologies are novel methods for high-gradient mirrors and can be used to figure mirrors finely. [c] 2010 Optical Society of America OCIS codes: 220.0220, 220.4610, 220.5450.