Properties and Mechanism of Al/St Bimetal Tube Bonding Produced by Cold Spin-Bonding (CSB) Process

Spin-bonding is a novel tube cladding method for fabrication of bilayer tubes based on flow-forming process. The bimetal Al/St tubular components have extensive application in different industries. In this paper, an Al/St bimetal tube was successfully produced at different thickness reductions from 35 to 65% and mechanical and metallurgical aspects of the joint were investigated. Peeling tests were done to investigate the strength of the bond. The results showed that an increase in the thickness reduction led to a significant increase in the bond strength. Besides, the bonding mechanism between Al as inner tube to St as an outer one resulting from spin-bonding process was investigated. The results showed that an excellent bonding of Al and St tubes could be achieved from this process. The results showed that the bonding process consisted of three stages. First, removal of surface layers resulting in contact between the virgin metals of two bond surfaces and then an unstable bond was formed that stabilized as deformation proceeded. Finally the bond strengthening occurred. The SEM micrographs of the peeled surfaces showed that removing surface films in aluminum and steel in the first stage was based on different mechanisms. Also, SEM back-scatter images of bond interface showed that no intermetallic phases were formed.     

Distributed state estimation from infrequent and delayed measurements in large-scale processes

Effective control and monitoring of a process usually require frequent and delay-free measurements of important process output variables. However, these measurements are often either not available or available infrequently with significant time delays. This article presents a method that allows for improving the performance of distributed state estimators implemented on large-scale manufacturing processes. The method uses a sample state augmentation approach that permits using delayed measurements in distributed state estimation. The method can be used with any state estimator, including unscented Kalman filters, extended Kalman filters, and moving horizon state estimators. The method optimally handles the tradeoff between computational time and estimation accuracy in distributed state estimation implemented using a computer with parallel processors. Its implementation and performance are shown using a few simulated examples.     

An efficient algorithm for community detection in complex weighted networks

Community detection decomposes large-scale, complex networks “optimally” into sets of smaller sub-networks. It finds sub-networks that have the least inter-connections and the most intra-connections. This article presents an efficient community detection algorithm that detects community structures in a weighted network by solving a multi-objective optimization problem. The whale optimization algorithm is extended to enable it to handle multi-objective optimization problems with discrete variables and to solve the problems on parallel processors. To this end, the population's positions are discretized using a transfer function that maps real variables to discrete variables, the initialization steps for the algorithm are modified to prevent generating unrealistic connections between variables, and the updating step of the algorithm is redefined to produce integer numbers. To identify the community configurations that are Pareto optimal, the non-dominated sorting concept is adopted. The proposed algorithm is tested on the Tennessee Eastman process and several benchmark community-detection problems.     

Evaluation of elastic modulus of polymer matrix nanocomposites

A new model to evaluate the elastic modulus of polymer nanocomposites is developed with emphasising on the role of inclusion/matrix interphase. The new model can be applied to polymer nanocomposites reinforced by inclusions with different shapes including spherical, cylindrical, and platelet. After validating the new model using experimental and FEA results, the effects of several parameters such as inclusion shape and modulus, d‐spacing, and matrix properties on the elastic modulus of nanocomposites are investigated. POLYM. COMPOS., 28:405–411, 2007. © 2007 Society of Plastics Engineers     

A small size Ka band six-bit DMTL phase shifter using new design of MEMS switch

Microsystem Technologies - This paper presents a new design of MEMS switch to achieve a six-bit small size and low loss DMTL phase shifter. In the proposed structure two electrodes are added to the...     

Polyethylene glycol as an epoxy modifier with extremely high toughening effect: Formation of nanoblend morphology

The brittle nature of epoxy polymers is one of their main drawbacks, preventing their widespread applications. In this research article, a new modifier with an extremely toughening effect on brittle epoxy was developed. It was found that introducing low‐molecular‐weight polyethylene glycol (PEG) in the low amounts (up to 10%) into epoxy matrix considerably improves the impact and fracture properties of epoxy thermosetting polymer without attenuating its tensile properties. Epoxy/PEG hybrid containing 10% PEG exhibited an impact strength of 56.3 kJ/m² which is 5.7 times greater than that of pristine epoxy. The fracture strength of 7.7 MPa m^1/2 with 540% increase compared to pure epoxy was also observed for the hybrid material. Morphological, chemical, and thermal properties of epoxy/PEG hybrid were studied using scanning electron microscopy, Fourier transform infrared spectrometry, and differential thermal analysis, respectively, to find out the basic reasons behind such a considerable improvement. A new morphology, consisting uniformly dispersed PEG nanoparticles in the epoxy matrix, was observed for the modified hybrid. This unique morphology for epoxy/PEG was named as nanoblend. The results showed that the formation of nanoblend morphology with strong interaction between epoxy and PEG in the blend structure is responsible for epoxy toughness. POLYM. ENG. SCI., 54:1833–1838, 2014. © 2013 Society of Plastics Engineers     

Microfluidic-Assisted CTC Isolation and In Situ Monitoring Using Smart Magnetic Microgels

Capturing rare disease-associated biomarkers from body fluids can offer an early-stage diagnosis of different cancers. Circulating tumor cells (CTCs) are one of the major cancer biomarkers that provide insightful information about the cancer metastasis prognosis and disease progression. The most common clinical solutions for quantifying CTCs rely on the immunomagnetic separation of cells in whole blood. Microfluidic systems that perform magnetic particle separation have reported promising outcomes in this context, however, most of them suffer from limited efficiency due to the low magnetic force generated which is insufficient to trap cells in a defined position within microchannels. In this work, a novel method for making soft micromagnet patterns with optimized geometry and magnetic material is introduced. This technology is integrated into a bilayer microfluidic chip to localize an external magnetic field, consequently enhancing the capture efficiency (CE) of cancer cells labeled with the magnetic nano/hybrid microgels that are developed in the previous work. A combined numerical-experimental strategy is implemented to design the microfluidic device and optimize the capturing efficiency and to maximize the throughput. The proposed design enables high CE and purity of target cells and real-time time on-chip monitoring of their behavior. The strategy introduced in this paper offers a simple and low-cost yet robust opportunity for early-stage diagnosis and monitoring of cancer-associated biomarkers.