The adsorption characteristics of Co(II) and Mn(II) ions on mesoporous silica SBA15 were investigated. SBA15 was synthesized from the silicate precursor tetraethyl-orthosilicate (TEOS), and it was functionalized with ethylene-diamine-tetra-acetic-acid (EDTA) and N,N-dimethylacetamide (DMAC), which consists of the amine functional groups. It was also characterized by nitrogen adsorptiondesorption analysis, element analysis (EA), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The adsorption capacities of EDTA functionalized SBA15 for Co(II) and DMAC functionalized SBA15 for Mn(II) in a single component system were found to be 10.12 mg/g and 6.8 mg/g, respectively. These values are about 10 times higher than that of assynthesized SBA15. The adsorption isotherms and kinetics data were found to follow the Langmuir adsorption isotherm model and the Pseudosecond order kinetic model (r 2 > 0.99). After the 5 adsorption cycles, over 90% regeneration efficiency was achieved for the functionalized SBA15, which would be applied for recovery of the metals.
In this work, we fabricated MgO-based magnetic tunnel junction (MTJ) samples to observe behavior of resistance variation, and investigated a stochastic behavior model for MTJ resistance from measured real data. We found the relationship between parallel resistance (R P ), anti-parallel resistance (R AP ), and TMR from the measurements. The variation of barrier thickness affects not only resistance but also TMR. This means that broad R AP distribution is caused by R P distribution. In addition, R AP distribution can be reduced by increasing temperature and bias voltage. We developed a macro model that can evaluate resistance distribution based on the stochastic behavior of MTJ resistance variation from only t ox varied. The amount of resistance variation, which is considered with regard to the circuit performance, can be obtained from Δt ox designed by designer. In addition, the impact for operating circumstance such as bias and temperature can be considered by using fit equations.
The resistance distribution of a magnetic tunnel junction (MTJ) shows nonuniformity according to various MTJ parameters. Moreover, this resistance variation leads to write-current density variation, which can cause serious problems when designing peripheral circuits for spin transfer torque magnetoresistance random access memory (STT-MRAM) and commercializing gigabit STT-MRAM. Therefore, a macromodel of MTJ including resistance, tunneling magnetoresistance ratio (TMR), and critical current variations is required for circuit designers to design MRAM peripheral circuits, that can overcome the various effects of the variations, such as write failure and read failure, and realize STT-MRAM. In this study, we investigated a stochastic behavior macromodel of the write current dependence on the MTJ resistance variation. The proposed model can possibly be used to analyze the write current density in relation to the resistance and TMR variations of MTJ with various parameter variations. It can be very helpful for designing STT-MRAM circuits and simulating the operation of STT-MRAM devices considering MTJ variations.
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