Influence of acoustic cavitation on the controlled ultrasonic dispersion of carbon nanotubes.

Ultrasonication is the most widely used technique for the dispersion of a range of nanomaterials, but the intrinsic mechanism which leads to stable solutions is poorly understood with procedures quoted in the literature typically specifying only extrinsic parameters such as nominal electrical input power and exposure time. Here we present new insights into the dispersion mechanism of a representative nanomaterial, single-walled carbon nanotubes (SW-CNTs), using a novel up-scalable sonoreactor and an in situ technique for the measurement of acoustic cavitation activity during ultrasonication. We distinguish between stable cavitation, which leads to chemical modification of the surface of the CNTs, and inertial cavitation, which favors CNT exfoliation and length reduction. Efficient dispersion of CNTs in aqueous solution is found to be dominated by mechanical forces generated via inertial cavitation, which in turn depends critically on surfactant concentration. This study highlights that careful measurement and control of cavitation rather than blind application of input power is essential in the large volume production of nanomaterial dispersions with tailored properties

End-to-end deep graph convolutional neural network approach for intentional islanding in power systems considering load-generation balance

Intentional islanding is a corrective procedure that aims to protect the stability of the power system during an emergency, by dividing the grid into several partitions and isolating the elements that would cause cascading failures. This paper proposes a deep learning method to solve the problem of intentional islanding in an end-to-end manner. Two types of loss functions are examined for the graph partitioning task, and a loss function is added on the deep learning model, aiming to minimise the load-generation imbalance in the formed islands. In addition, the proposed solution incorporates a technique for merging the independent buses to their nearest neighbour in case there are isolated buses after the clusterisation, improving the final result in cases of large and complex systems. Several experiments demonstrate that the introduced deep learning method provides effective clustering results for intentional islanding, managing to keep the power imbalance low and creating stable islands. Finally, the proposed method is dynamic, relying on real-time system conditions to calculate the result

Predicting the optoelectronic properties of nanowire films based on control of length polydispersity

We demonstrate that the optoelectronic properties of percolating thin films of silver nanowires (AgNWs) are predominantly dependent upon the length distribution of the constituent AgNWs. A generalized expression is derived to describe the dependence of both sheet resistance and optical transmission on this distribution. We experimentally validate the relationship using ultrasonication to controllably vary the length distribution. These results have major implications where nanowire-based films are a desirable material for transparent conductor applications; in particular when application specific performance criteria must be met. It is of particular interest to have a simple method to generalize the properties of bulk films from an understanding of the base material, as this will speed up the optimisation process. It is anticipated that these results may aid in the adoption of nanowire films in industry, for applications such as touch sensors or photovoltaic electrode structures

Ultrasound assisted dispersal of a copper nanopowder for electroless copper activation

This paper describes the ultrasound assisted dispersal of a low wt./vol.% copper nanopowder mixture and determines the optimum conditions for de-agglomeration. A commercially available powder was added to propan-2-ol and dispersed using a magnetic stirrer, a high frequency 850 kHz ultrasonic cell, a standard 40 kHz bath and a 20 kHz ultrasonic probe. The particle size of the powder was characterized using dynamic light scattering (DLS). Z-Average diameters (mean cluster size based on the intensity of scattered light) and intensity, volume and number size distributions were monitored as a function of time and energy input. Low frequency ultrasound was found to be more effective than high frequency ultrasound at de-agglomerating the powder and dispersion with a 20 kHz ultrasonic probe was found to be very effective at breaking apart large agglomerates containing weakly bound clusters of nanoparticles. In general, the breakage of nanoclusters was found to be a factor of ultrasonic intensity, the higher the intensity the greater the de-agglomeration and typically micron sized clusters were reduced to sub 100 nm particles in less than 30 min using optimum conditions. However, there came a point at which the forces generated by ultrasonic cavitation were either insufficient to overcome the cohesive bonds between smaller aggregates or at very high intensities decoupling between the tip and solution occurred. Absorption spectroscopy indicated a copper core structure with a thin oxide shell and the catalytic performance of this dispersion was demonstrated by drop coating onto substrates and subsequent electroless copper metallization. This relatively inexpensive catalytic suspension has the potential to replace precious metal based colloids used in electronics manufacturing

Influence of acoustic cavitation on the controlled ultrasonic dispersion of carbon nanotubes.

Ultrasonication is the most widely used technique for the dispersion of a range of nanomaterials, but the intrinsic mechanism which leads to stable solutions is poorly understood with procedures quoted in the literature typically specifying only extrinsic parameters such as nominal electrical input power and exposure time. Here we present new insights into the dispersion mechanism of a representative nanomaterial, single-walled carbon nanotubes (SW-CNTs), using a novel up-scalable sonoreactor and an in situ technique for the measurement of acoustic cavitation activity during ultrasonication. We distinguish between stable cavitation, which leads to chemical modification of the surface of the CNTs, and inertial cavitation, which favors CNT exfoliation and length reduction. Efficient dispersion of CNTs in aqueous solution is found to be dominated by mechanical forces generated via inertial cavitation, which in turn depends critically on surfactant concentration. This study highlights that careful measurement and control of cavitation rather than blind application of input power is essential in the large volume production of nanomaterial dispersions with tailored properties