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Understanding bottom-up continuous hydrothermal synthesis of nanoparticles using empirical measurement and computational simulation
Authors:José Sierra-Pallares  Thomas Huddle  Juan García-Serna  Esther Alonso  Fidel Mato  Igor Shvets  Olaf Luebben  María José Cocero  Edward Lester
Affiliation:1.Fluids Engineering Group Energy and Fluid Mechanics Engineering Department,University of Valladolid,Valladolid,Spain;2.Advanced Materials Research Group,the University of Nottingham,University Park, Nottingham,UK;3.High Pressure Processes Group, Department of Chemical Engineering and Environmental Technology,University of Valladolid,Valladolid,Spain;4.School of Physics,Trinity College Dublin, College green,Dublin 2,Ireland
Abstract:Continuous hydrothermal synthesis was highlighted in a recent review as an enabling technology for the production of nanoparticles. In recent years, it has been shown to be a suitable reaction medium for the synthesis of a wide range of nanomaterials. Many single and complex nanomaterials such as metals, metal oxides, doped oxides, carbonates, sulfides, hydroxides, phosphates, and metal organic frameworks can be formed using continuous hydrothermal synthesis techniques. This work presents a methodology to characterize continuous hydrothermal flow systems both experimentally and numerically, and to determine the scalability of a counter current supercritical water reactor for the large scale production (>1,000 T·year–1) of nanomaterials. Experiments were performed using a purpose-built continuous flow rig, featuring an injection loop on a metal salt feed line, which allowed the injection of a chromophoric tracer. At the system outlet, the tracer was detected using UV/Vis absorption, which could be used to measure the residence time distribution within the reactor volume. Computational fluid dynamics (CFD) calculations were also conducted using a modeled geometry to represent the experimental apparatus. The performance of the CFD model was tested against experimental data, verifying that the CFD model accurately predicted the nucleation and growth of the nanomaterials inside the reactor.
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