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ERC

AGGLONANOCOAT Report Summary

Project ID: 279632
Funded under: FP7-IDEAS-ERC
Country: Netherlands

Final Report Summary - AGGLONANOCOAT (The interplay between agglomeration and coating of nanoparticles in the gas phase)

Core-shell nanoparticles and other nanostructured particles have high potential in several practical applications, such as catalysis and energy conversion and storage. However, a hurdle in their utilisation is that typically large amounts of such materials are required. Gas-phase coating using atomic layer deposition (ALD, a variant of chemical vapour deposition) can be used to provide the surface of a particle with either an ultrathin conformal coating or a decoration of nanoclusters. ALD has its roots in experiments made in the Soviet Union in the 1960s and in Finland in the 1970s, but it only started to attract substantial attention in the 1990s. Up to now, the majority of work reported in literature is aimed at coating stagnant substrates such as wafers. However, when applied to nanoparticles suspended in a gas flow (a so-called fluidized bed), ALD offers an attractive way of producing nanostructured particles.

It was already shown previously that ALD can be applied to particles in a fluidized bed at ~1 mbar. This pressure was thought to be critical for the removal of by-products. However, we have shown that with ALD at atmospheric pressure still excellent coatings can be achieved. The operation at 1 atmosphere simplifies the equipment design, and facilities scale-up. Both by modelling and experiments, we have demonstrated that properly designed ALD processes show a reactant utilization of >95%: much more efficient than most other processes to created nanostructured materials. In case of heat-sensitive substrates, coating at room temperature is even possible for specific precursors, but in that case precise dosing of the precursor is crucial.

We have developed a reactor design (the pneumatic transport reactor) that can produce coated particles in a continuous manner; this is attractive since various branches of industry prefer continuous production over batchwise processes. Finally, we have demonstrated that noble metal clusters can be deposited on graphene platelets in a very controlled manner.

Detailed knowledge of the physical aspects of the agglomeration of fluidized nanoparticles is crucial to optimize the coating process. It was already reported that these agglomerates have a fractal structure. We have shown that these agglomerates cannot be characterized by a single fractal dimension; we demonstrated the existence of three fractal scaling regimes using in-situ two characterisation techniques: Spin Echo Small Angle Neutron Scattering for the length scales <20 micron and video imaging for the length scales >40 micron. This knowledge is important to understand and model the reactant diffusion inside the agglomerates. Moreover, we have demonstrated the present of long-term transients in the fluidization of nanoparticles. Using discrete element modelling, we have studied the influence of particle properties and operating conditions on the agglomerate dynamics.
We have already applied our approach for making nanostructured particles to a range of fields. We have made a very active photocatalyst by very well dispersing platinum nanoclusterson the surface of titania nanoparticles. Using ALD, we have also coated quantum-dot films which changes their stability from hours to more than months. The life-time of Li-ion batteries has been increases by a factor five. We are currently also investigating the use of ALD in the synthesis of radio-active isotopes for medical applications. We have shown that ALD can be applied to a range of substrates, from paper to graphene platelets.

In summary, the work in this project is an important steps towards a detailed understanding of the coating of (nano)particles using ALD, both regarding the ALD chemistry and the physics of the particle interaction. We are applying the obtained knowledge for the synthesis of novel, nanostructured materials than can be deployed in various fields. The obtained insight can be used to optimize these synthesis approaches.

Reported by

TECHNISCHE UNIVERSITEIT DELFT
Netherlands
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