Research Progress in the Preparation of High Silicon Steel Thin Strip by Near Net Shaping

The latest research progress in the preparation of 6.5%Si steel thin strip by the single-roller spinning method and the high silicon steel thin strip by the strip cast-rolling method are described in this paper.The microstructure and properties of high silicon steel thin strip with different production process-

UV-light-assisted synthesis of CeB_(6)@Ag nano-trees for SERS application

The conventional methods of using surfactants to synthesize noble metal nanoparticles usually introduce residues on the surface,which inevitably decreases nanoparticles’ surface enhanced Raman scattering(SERS) performance.Herein,we propose a surfactant-free and feasible approach of preparing cerium hexaboride-Ag nano-trees hybrids(CeB_(6)@Ag nano-trees) as the SERS substrate.First,the CeB_(6)was synthesized by a one-pot ionothermal method.Secondly,the CeB_(6)powder and silver nitrate were dispersed in an aqueous solution.Thereafter,the Ag+was reduced by the UV-light assisted photoreaction and deposited on the surface of the CeB_(6).The SERS performance of the CeB_(6)@Ag nano-trees was evaluated by using the Rhodamine 6 G as the Raman reporter.It shows that CeB_(6)@Ag nano-trees exhibit good SERS sensitivity with the enhancement factor of 2.45 × 10^(7) and detection limit of 10^(-10) mol/L.Moreover,uniformity evaluation of the SERS signal intensity on the substrate also shows that relatively good relative standard deviation values of 12.6%(Raman peak@612 cm^(-1)) and 14.1%(Raman peak@1652 cm^(-1))can be achieved.Finally,finite element simulation evidences that excellent SERS performance of the CeB_(6)@Ag nano-trees is produced by the strong coupled localized surface plasmon resonance generated under the Raman laser irradiation.

GPU-BASED FLUID SIMULATION WITH FAST COLLISION DETECTION ON BOUNDARIES

In this paper,we present a method for fluid simulation based on smoothed particle hydrodynamic(SPH)with fast collision detection on boundaries on GPU.The major goal of our algorithm is to get a fast SPH simulation and rendering on GPU.Additionally,our algorithm has the following three features:At first,to make the SPH method GPU-friendly,we introduce a spatial hash method for neighbor search.After sorting the particles based on their grid index,neighbor search can be done quickly on GPU.Second,we propose a fast particle-boundary collision detection method.By precomputing the distance field of scene boundaries,collision detection’s computing cost arrived as O(n),which is much faster than the traditional way.Third,we propose a pipeline with fine-detail surface reconstruction,and progressive photon mapping working on GPU.We experiment our algorithm on different situations and particle numbers of scenes,and find out that our method gets good results.Our experimental data shows that we can simulate 100K particles,and up to 1000K particles scene at a rate of approximately 2 times per second.