Artificial neural network application in short-term prediction in an oscillating water column

Oscillating Water Column (OWC) is one type of promising wave energy devices due to its obvious advantage over many other wave energy converters: no moving component in sea water. Two types of OWCs (bottom-fixed and floating) have been widely investigated, and the bottom-fixed OWCs have been very successful in several practical applications. Recently, the proposal of massive wave energy production and the availability of wave energy have pushed OWC applications from near-shore to deeper water regions where floating OWCs are a better choice. For an OWC under sea waves, the air flow driving air turbine to generate electricity is a random process. In such a working condition, single design/operation point is nonexistent. To improve energy extraction, and to optimise the performance of the device, a system capable of controlling the air turbine rotation speed is desirable. To achieve that, this paper presents a short-term prediction of the random, process by an artificial neural network (ANN), which can provide near-future information for the control system. In this research, ANN is explored and tuned for a better prediction of the airflow (as well as the device motions for a wide application). It is found that, by carefully constructing ANN platform and optimizing the relevant parameters, ANN is capable of predicting the random process a few steps ahead of the real, time with a good accuracy. More importantly, the tuned ANN works for a large range of different types of random, process.

Fabrication of sub-10 nm lamellar structures by solvent vapour annealing of block copolymers

Fabrication of nanoscale patterns through the bottom-up approach of self-assembly of phase-separated block copolymers (BCP) holds promise for nanoelectronics applications. For lithographic applications, it is useful to vary the morphology of BCPs by monitoring various parameters to make “from lab to fab” a reality. Here I report on the solvent annealing studies of lamellae forming polystyrene-blockpoly( 4-vinylpyridine) (PS-b-P4VP). The high Flory-Huggins parameter (χ = 0.34) of PS-b-P4VP makes it an ideal BCP system for self-assembly and template fabrication in comparison to other BCPs. Different molecular weights of symmetric PS-b-P4VP BCPs forming lamellae patterns were used to produce nanostructured thin films by spin-coating from mixture of toluene and tetrahydrofuran(THF). In particular, the morphology change from micellar structures to well-defined microphase separated arrangements is observed. Solvent annealing provides a better alternative to thermal treatment which often requires long annealing periods. The choice of solvent (single and dual solvent exposure) and the solvent annealing conditions have significant effects on the morphology of films and it was found that a block neutral solvent was required to realize vertically aligned PS and P4VP lamellae. Here, we have followed the formation of microdomain structures with time development at different temperatures by atomic force microscopy (AFM). The highly mobilized chains phase separate quickly due to high Flory-Huggins (χ) parameter. Ultra-small feature size (~10 nm pitch size) nanopatterns were fabricated by using low molecular weight PSb- P4VP (PS and P4VP blocks of 3.3 and 3.1 kg mol-1 respectively). However, due to the low etch contrast between the blocks, pattern transfer of the BCP mask is very challenging. To overcome the etch contrast problem, a novel and simple in-situ hard mask technology is used to fabricate the high aspect ratio silicon nanowires. The lamellar structures formed after self-assembly of phase separated PS-b-P4VP BCPs were used to fabricate iron oxide nanowires which acted as hard mask material to facilitate the pattern transfer into silicon and forming silicon nanostructures. The semiconductor and optical industries have shown significant interest in two dimensional (2D) molybdenum disulphide (MoS2) as a potential device material due to its low band gap and high mobility. However, current methods for its synthesis are not ‘fab’ friendly and require harsh environments and processes. Here, I also report a novel method to prepare MoS2 layered structures via self-assembly of a PS-b-P4VP block copolymer system. The formation of the layered MoS2 was confirmed by XPS, Raman spectroscopy and high resolution transmission electron microscopy.