Nanoparticle Synthesis: Reduced Agglomeration through Electric-Field Enhanced Flame Synthesis
|Reporting in Journal of Nanoparticle Research, Zhao and colleagues describe a technique to model charged species behavior by electrostatic manipulation that provides additional time/temperature histories beyond flow transport measurements.|
Reviewed by James Krajewski, DuPont
- Zhao, H., X. Liu, and S.D. Tse, "Control of nanoparticle size and agglomeration through electric-field-enhanced flame synthesis," J Nanopart Res (2008) 10:907–923, August 2008. DOI: 10.1007/s11051-007-9330-7
Decreasing nanoparticle agglomeration and controlling particle size are two important parameters of any large-scale nanoparticle manufacturing process, especially with products based on particle/matrix dispersions, nanocomposite uniformity, complete precursor reactivity/sintering, and functionalized/coated nanoparticles. Reporting in Journal of Nanoparticle Research, Zhao and colleagues describe a technique to model charged species behavior by electrostatic manipulation that provides additional time/temperature histories beyond flow transport measurements. This system is based on flame synthesis (extensively cited in the literature) but has an axi-symmetric stagnation point flame that maintains a one–dimensional flow field geometry creating no ionic wind thus isolating the electrophoretic effect when manipulating particle residence time.
Flame synthesis of an organometallic in a uniform electric field between the burner and the cooled substrate creates an electrophoretic effect which aids the thermophoretic effect in transporting the titania or alumina (particles examined in this study) faster to the cooled substrate. This reduces residence time which decreases the particle size, surface area and aggregation rate. This work builds on other work and models the gas-phase flame structure, particle transport and aerosol fluid dynamics through characterization by laser induced fluorescence, dynamic light scattering, x-ray diffraction, SEM and TGA and compares the experimental data with computational modeling.
This model used by Zhao et al. focuses on the axial gas flame structure, using appropriate boundary conditions and examines the gas-phase and surface kinetic flow-chemistry as well as the transport of the precursor and reaction products between the burner and the substrate. Particle growth is discussed with a monodispersed growth dynamic model and a simplified sectional model which allows for generating a particle size distribution.
The monodispersed model, considers particle collision rates, diffusion of particles, coalescing time and the driving force for sintering. By making some valid assumptions about precursor decay (instantaneous), critical size of nucleated nanoparticle (1nm) and that particle velocity is the same as the gas-phase (at point of nucleation), the authors demonstrate a close correlation between experiment and the model. The sectional model was carried out for coagulation with sections defined for volumes with diameters of 1nm to 300nm, using equations for population balance and average surface area, which are solved considering precursor decomposition, homogeneous particle nucleation, coagulation, coalescence and surface growth. This opens up the possibility of using the model for understanding nucleation and particle growth for large scale flame synthesis of non-agglomerated nanoparticles with complex structures.
Particle nucleation and growth are determined by the gas-phase time/temperature history. Typically larger tracer particles are used in particle image and laser Doppler velocimetry where the velocity is extracted through the Mie scattering technique. In this work, Zhao probes the actual flame structure with laser induced fluorescence to map the gas-phase temperature distributions and the OH radical concentration, a key intermediate of combustion. They determine the material processing flow field by comparing the simulation with the in-situ measurements.
Flame characteristics and precursor reactivity as measured with and without electric fields, show good agreement between the model computations and experimental data. With the substrate biased negatively, the hydrodynamic diameters of the aggregates decrease due to shorter residence times (positively biased substrate produces the opposite effect). High electrical fields produce larger aggregates due to charging of the smaller particles by the highly negatively-biased substrate. So electric field polarity and magnitude of the voltage are key size parameters, with coagulation and coalescence being the main particle growth mechanisms. Metastable phases can be synthesized such as anatase which is easily formed at low temperatures due to its fast crystallization kinetics, even though rutile is thermodynamically more stable. Alumina can also be formed in this manner with residence time controlling the size of the aggregates under electrical bias.
This study models the interaction of a uniform electric field with gas phase kinetics to reduce particle size and aggregation rate of a nanoparticle population. This work shows some of the issues in addressing nanoparticle interactions and further work needs to be done to understand the many large scale nanoparticle manufacturing challenges.
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