Sharif Digital Repository

The current study presents a supercritical synthesis of magnetite-reduced graphene oxide (M-RGO) in methanol media, in which Fe3O4 nanoparticles are simultaneously formed, surface modified and decorated on the surface of the reduced graphene oxide. Simulations using density functional theory, which were performed using the M06-2x/cc-pVDZ level of theory, indicate that upon adsorption of a Fe3O4 cluster on the graphene, the overall charge on the graphene surface becomes about -0.0236e, indicating charge transfer from the Fe3O4 cluster to the graphene surface. Instrumental and chemical analyses exhibited the formation of strong bonds between Fe3O4 and graphene, through C-O-Fe and C-Fe bridges.... 

For many years, computer designers benefitted from Moore's law and Dennard scaling to significantly improve the speed of single-core processors. The failure of Dennard scaling pushed the computer industry toward homogenous multicore processors for the performance improvement to continue without significant increase in power consumption. Unfortunately, even homogeneous multicore processors cannot offer the level of energy efficiency required to operate all the cores at the same time in today's and especially tomorrow's technologies. As a result of lack of energy efficiency, not all the cores in a multicore processor can be functional at the same time. This phenomenon is referred to as dark... 

Many applications, including big-data server applications, frequently encounter data misses. Consequently, they lose significant performance potential. Fortunately, data accesses of many of these applications follow temporal correlations, which means data accesses repeat over time. Temporal correlations occur because applications usually consist of loops, and hence, the sequence of instructions that constitute the body of a loop repeats many times, leading to data access repetition. Temporal data prefetchers take advantage of temporal correlation to predict and prefetch future memory accesses. In this chapter, we introduce the concept of temporal prefetching and present two instances of... 

Many applications extensively use data objects with a regular and fixed layout, which leads to the recurrence of access patterns over memory regions. Spatial data prefetching techniques exploit this phenomenon to prefetch future memory references and hide their long latency. Spatial prefetchers are particularly of interest because they usually only need a small storage budget. In this chapter, we introduce the concept of spatial prefetching and present two instances of spatial data prefetchers, SMS and VLDP. © 2021 Elsevier Inc  

Many applications, including big-data server applications, frequently encounter data misses. Consequently, they lose significant performance potential. Fortunately, data accesses of many of these applications follow temporal correlations, which means data accesses repeat over time. Temporal correlations occur because applications usually consist of loops, and hence, the sequence of instructions that constitute the body of a loop repeats many times, leading to data access repetition. Temporal data prefetchers take advantage of temporal correlation to predict and prefetch future memory accesses. In this chapter, we introduce the concept of temporal prefetching and present two instances of... 

Many applications extensively use data objects with a regular and fixed layout, which leads to the recurrence of access patterns over memory regions. Spatial data prefetching techniques exploit this phenomenon to prefetch future memory references and hide their long latency. Spatial prefetchers are particularly of interest because they usually only need a small storage budget. In this chapter, we introduce the concept of spatial prefetching and present two instances of spatial data prefetchers, SMS and VLDP. © 2022 Elsevier Inc  

In many cases, multiple-fault diagnosis of plant-wide systems based on steady-state data is impossible. To solve this problem, a new diagnosis strategy based on neural networks has been proposed. In the suggested framework, the neural network is used as the diagnoser trained by a hybrid set of steady and dynamic characteristic data of the system. The dynamic characteristic data include overshoot and undershoot values of measured variables and their corresponding occurrence times. To evaluate its performance, the proposed scheme was used in the diagnosis of the concurrent faults of the Tennessee Eastman (TE) process. Various combinations of concurrent faults were considered in this... 

In this paper, the fuzzy system has been used for fault detection and diagnosis of a yeast fermentation bioreactor based on measurements corrupted by noise. In one case, parameters of membership functions are selected in a conventional manner. In another case, using certainty factors between normal and faulty conditions the optimal values of these parameters have been obtained through the genetic algorithm. These two cases are compared based on their performances in fault diagnosis of a yeast fermentation bioreactor for three different conditions. The simulation results indicate that the fuzzy-genetic system is superior in multiple fault detection for the conditions where the minimum and... 

Magnetite nanoparticles with a size distribution of 15-21 nm were synthesized and decorated onto surface of graphene oxide by ultrasound assisted precipitation. Size and size distribution of the obtained M-GO hybrid were appreciably finer than the hybrids prepared by stirring method. M-GO is a superparamagnetic material with saturation magnetization of 31 emu g-1. The Langevin equation was successfully applied for estimation of size of Fe3O4 nanoparticles in M-GO hybrid, with maximum error of 17.5%. The study put forward a formation mechanism for M-GO, based on instrumental analyses. Adsorption isotherms of Sr2+ and Co2+ ions, which were fitted by Langmuir monolayer... 

A novel microspherical adsorbent for the removal of uranium from aqueous solutions was developed by immobilizing of natural bentonite in the polymeric matrix of calcium alginate. Different uptake properties of the prepared microspheres were examined using batch, stirred and column methods. The adsorbent showed high affinity toward uranium ions, especially at pHs above 3. Major uptake mechanisms included ion exchange, chelating of the (UO2)2+ ions to the -OH groups of alginate, and surface complexation with bentonite. Surprisingly, the capacity of microspheres was higher than both its constituents, revealing that a synergetic effect occurs. Adsorption kinetics was controlled by slow chemical...