One of the major challenges towards controlling the transfer of electrical and mechanical properties of nanotubes into nanocomposites is the lack of adequate measurement systems to quantify the variations in bulk properties while the nanotubes were used as the reinforcement material. In this study, we conducted one-way analysis of variance (ANOVA) on thickness and conductivity measurements. By analyzing the data collected from both experienced and inexperienced operators, we found some operation details users might overlook that resulted in variations, since conductivity measurements of CNT thin films are very sensitive to thickness measurements. In addition, we demonstrated how issues in measurements damaged samples and limited the number of replications resulting in large variations in the electrical conductivity measurement results. Based on this study, we proposed a faster, more reliable approach to measure the thickness of CNT thin films that operators can follow to make these measurement processes less dependent on operator skills.
Many healthcare institutions are interested in reducing costs and in maintaining a good quality of care. The operating room department is typically one of the most costly units in a hospital. Hospital managers are always interested in finding effective ways of using operating rooms to minimize operating costs. In this research, we study the operating room scheduling problem. We consider the use of a weekly surgery schedule with an open scheduling strategy that takes into account the availabilities of surgeons and operating rooms. The objective is to minimize the total operating cost while maximizing the utilization of the operating rooms but also minimizing overtime use. A revised mathematical model is proposed that can provide optimal solutions for a surgery size up to 110 surgical cases. Next, two modified heuristics, based on the earliest due date (EDD) and longest processing time (LPT) rules, are proposed to quickly find feasible solutions to the studied problem. Finally, an artificial bee colony (ABC) algorithm that incorporates the initial solutions, a recovery scheme, local search schemes, and an elitism strategy is proposed. The computational results show that, for a surgery size between 40 and 100 surgical cases, the ABC algorithm found optimal solutions to all of the tested problems. For surgery sizes larger than 110 surgical cases, the ABC algorithm performed significantly better than the two proposed heuristics. The computational results indicate that the proposed ABC is promising and capable of solving large problems.
A process for continuously monitoring the ultrasonic dispersion process of carbon nanotubes (CNTs) was discovered by integrating dynamic light scattering (DLS) and UV-vis spectroscopy. Through a continuous flow approach adapted to the dispersion system, the CNT suspension could be quantitatively characterized in real time. By continuously monitoring and identifying the evolution of mean particle size distribution and transparency of CNT suspension, the effective dispersion parameters and dispersion quality was quantified. Two types of MWNTs of different diameters and lengths were studied. For longer MWNTs with smaller diameters, the dispersion process achieved at a steady 100 nm of agglomerate size with 40 min of sonication. For shorter and large diameter and less entangled MWNTs, after 60 min of sonication, an agglomerate size of 100 nm was achieved, yet the stability decrease. The results show the potential ability of the system to optimize nanoparticle dispersion process for inline dispersion quality control.
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