427157 Multiscale Design of Gas-Phase Synthesis of Nanomaterials

Sunday, November 8, 2015
Exhibit Hall 1 (Salt Palace Convention Center)
Eirini Goudeli, Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland and Sotiris E. Pratsinis, Particle Technology Laboratory, Institute of Process Engineering, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland


Multiscale design of aerosol reactors for synthesis of nanomaterials includes continuum, mesoscale, molecular dynamics (MD) and quantum mechanics models spanning 10 – 15 orders of magnitude in length and time, respectively. Quantum mechanics account for the electronic structure of matter determining the interatomic potentials in MD models for accurate estimation of sintering and crystallization rates. Mesoscale models provide the transport properties and coagulation rate of multi-particle structures while continuum models describe the effect of process variables on product particle size and morphology at various process temperatures and residence times (Buesser and Pratsinis, 2012). Multiscale modeling is introduced in the design of scalable processes for gas-phase synthesis of nanoparticles with closely controlled characteristics.

Fundamental particle properties, like structure and crystallinity are determined from first principles as they affect material performance in a score of applications (e.g. sensors, catalysts, biometerials). More specifically, highly parallelized MD simulations are carried out to monitor dynamic properties and physical mechanisms governing the nanoparticle characteristics that cannot be easily obtained experimentally. Sintering rates and crystallinity dynamics that can be incorporated in mesoscale and continuum models are determined ab initio for gold nanoparticles.

Discrete Element Modeling (DEM) simulations are used to track the detailed structure and size distribution and agglomerate size of fractal-like particles undergoing Brownian coagulation without coalescence, sintering or surface growth (Goudeli et al., 2015). The DEM-obtained mobility size and number-based geometric standard deviation of the mobility radius are compared to Scanning Mobility Particle Sizer (SMPS) and combined Differential Mobility Analyzer (DMA) and Aerosol Particle Mass (APM) measurements as function of the number of primary particles per agglomerate. Particle morphology and structure are quantified by the fractal dimension, Df, and mass-mobility exponent, Dfm, which are related to the cluster optical and transport properties, respectively, from spherical particles to fractal-like agglomerates until they attain their well-known asymptotic structure.

Easy-to-use expressions are extracted that can be readily interfaced with climate dynamics, meteorological models or computational fluid dynamics describing the reactor operation and particle production. For example, the effect of varying particle structure during the formation of fractal-like crystalline TiO2 and amorphous SiO2 is investigated by employing the above DEM-derived Df evolution in a monodisperse continuum model (Kruis et al., 1993) accounting for concurrent coagulation and sintering. Neglecting the evolving particle structure overestimates the hard-agglomerate diameter by up to 25% for TiO2 and 30% for SiO2, especially at high maximum temperatures and cooling rates that hard-aggregates consist of only a few primary particles.

Interfacing the above models that are applicable at multiple length and time scales can facilitate the understanding and scale-up design of aerosol reactors for synthesis of nanoparticles whose properties can be closely controlled during scale-up from laboratory scale to commercial products.


Buesser, B., and Pratsinis, S.E. (2012) Annu. Rev. Chem. Biomol. Eng., 3, 103-127.

Goudeli, E., Eggersdorfer, M.L., and Pratsinis, S.E. (2015) Langmuir 31, 1320-1327.

Kruis, F.E., Kusters, K.A., Pratsinis, S.E., and Scarlett, B. (1993) Aerosol Sci. Technol. 19, 514-526.

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