In recent years, observed focus greatly on gold nanoparticles synthesis due to its unique properties and tremendous applicability. In most of these researches, the citrate reduction method has been adopted. The aim of this study was to prepare and optimize monodisperse ultrafine particles by addition of reducing agent to gold salt, as a result of seed mediated growth mechanism. In this research, gold nanoparticles suspension (G) was prepared by traditional standard Turkevich method and optimized by studying different variables such as reactants concentrations, preparation temperature and stirring rate on controlling size and uniformity of nanoparticles through preparing twenty formulas (G1-G20). Subsequently, the selected formula that prepared from the best tested condition was further optimized by preparing it using inverse method via the addition of gold salt to the reducing agent in opposite to the previous traditional method (G21). The optimized gold nanoparticles were characterized by SEM, EDX, TEM and zeta potential. The obtained results indicated that (G21) with reactants concentrations of 0.5mM and 10mM for HAuCl4.3H2O and trisodium citrate dihydrate respectively, 65°C of preparation temperature and 1500rpm of stirring rate was chosen as an optimized formula according to AFM provided gold nanoparticles with smoother surface, smaller size (average 8.75nm) with more uniform size distribution (7.32%) as well as short over all preparation time (27minutes). In addition to that all results of SEM, EDX and TEM indicated uniform spherical shape with zeta potential of -47.87. In conclusion, inversed method is promising for the preparation of gold nanoparticles with high monodispersity.
RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2
Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent
The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
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