Optimization of interior roller burnishing process for improving surface quality

Improving the surface characteristics of roller burnishing processes is one of effective approaches to decrease the machining costs and time. This paper systematically investigates the nonlinear relationships between machining parameters and surface characteristics, including surface roughness (R_a), surface hardness (H), and hardness depth (HD) of the interior roller burnishing using response surface method (RSM) model. Three process parameters considered include spindle speed S, feed rate F, and burnishing depth D. A set of physical experiments was carried out with AISI 1045 steel on a computer numerical control (CNC) milling machine using the roller burnishing tool. The target of the current complex optimization is to enhance the surface hardness and hardness depth, while the surface roughness is considered as the constraint. Finally, an evolutionary algorithm entitled archive-based micro genetic algorithm (AMGA) was used to generate a set of feasible optimal solutions and determine the best machining conditions. The results show that an appropriate trade-off solution can be drawn with regard to the low surface roughness and high the surface hardness as well as hardness depth. Furthermore, the integration of RSM model and AMGA can be considered as a powerful approach for modeling and optimizing interior roller burnishing processes.     

Recent Advances on 3D Printing Technique for Thermal‐Related Applications

Advances in ink formulation and printing techniques make producing material systems with new and versatile characteristics and functionalities possible. Additive manufacturing or 3D printing enables fabricating complex structures at a faster production rate using different types of materials for various applications. Recently, 3D printing methods are being studied for thermal‐related applications. In this paper, the authors review recent progress of materials and printing techniques for thermal application devices using composite materials.

     

Facile synthesis of CsPbBr3/PbSe composite clusters

In this work, CsPbBr₃ and PbSe nanocomposites were synthesized to protect perovskite material from self-enlargement during reaction. UV absorption and photoluminescence (PL) spectra indicate that the addition of Se into CsPbBr₃ quantum dots modified the electronic structure of CsPbBr₃, increasing the band gap from 2.38 to 2.48 eV as the Cs:Se ratio increased to 1:3. Thus, the emission color of CsPbBr₃ perovskite quantum dots was modified from green to blue by increasing the Se ratio in composites. According to X-ray diffraction patterns, the structure of CsPbBr₃ quantum dots changed from cubic to orthorhombic due to the introduction of PbSe at the surface. Transmission electron microscopy and X-ray photoemission spectroscopy confirmed that the atomic distribution in CsPbBr₃/PbSe composite clusters is uniform and the composite materials were well formed. The PL intensity of a CsPbBr₃/PbSe sample with a 1:1 Cs:Se ratio maintained 50% of its initial intensity after keeping the sample for 81 h in air, while the PL intensity of CsPbBr₃ reduced to 20% of its initial intensity. Therefore, it is considered that low amounts of Se could improve the stability of CsPbBr₃ quantum dots.     

Algorithm for the extraction of page-formatted binary digital data

We present an algorithm for fast and reliable extraction of page-formatted binary digital data. The advantages of the algorithm include a low raw bit-error rate, fast extraction speed, the use of a simple and density-efficient coding scheme, and large tolerance to a change of the signal-to-noise ratio. We used this algorithm to analyze shot-noise-limited binary data that had large interpage and intrapage intensity variations and obtained an improvement in the bit-error rate of 3-4 orders of magnitude compared with that in a single-threshold-detection scheme. Implications of our results for the development of high-speed, high-density holographic memories are discussed.     

An efficient microfluidic sorter: implementation of double meandering micro striplines for magnetic particles switching

The ability to trap, manipulate, and separate magnetic beads has become one of the key requirements in realizing an integrated magnetic lab-on-chip biosensing system. In this article, we present the design and fabrication of an integrated magneto-fluidic device for sorting magnetic particles with a sorting efficiency of up to 95%. The actuation and manipulation of magnetic beads are realized using microfabricated square meandering current-carrying micro striplines. The current is alternated between two neighboring micro striplines to switch the magnetic beads to either one of the two outlets. We performed a series of parametric study to investigate the effect of applied current, flow rate, and switching frequency on the sorting efficiency. Experimental results reveal that the sorting efficiency is proportional to the square of current applied to the stripline, and decreases with increasing buffer flow rate and switching frequency. Such phenomena agree well with our theoretical analysis and simulation result. The fastest switching rate, which is limited by the microchannel geometry and bead velocity, is 2 Hz.     

Solving the Matrix Differential Riccati Equation: A Lyapunov Equation Approach

In this technical note, we investigate a solution of the matrix differential Riccati equation that plays an important role in the linear quadratic optimal control problem. Unlike many methods in the literature, the approach that we propose employs the negative definite anti-stabilizing solution of the matrix algebraic Riccati equation and the solution of the matrix differential Lyapunov equation. An illustrative numerical example is provided to show the efficiency of our approach.      

A framework for linguistic logic programming

Lawry's label semantics for modeling and computing with linguistic information in natural language provides a clear interpretation of linguistic expressions and thus a transparent model for real‐world applications. Meanwhile, annotated logic programs (ALPs) and its fuzzy extension AFLPs have been developed as an extension of classical logic programs offering a powerful computational framework for handling uncertain and imprecise data within logic programs. This paper proposes annotated linguistic logic programs (ALLPs) that embed Lawry's label semantics into the ALP/AFLP syntax, providing a linguistic logic programming formalism for development of automated reasoning systems involving soft data as vague and imprecise concepts occurring frequently in natural language. The syntax of ALLPs is introduced, and their declarative semantics is studied. The ALLP SLD‐style proof procedure is then defined and proved to be sound and complete with respect to the declarative semantics of ALLPs. © 2010 Wiley Periodicals, Inc.