Mechanical, thermal and colorimetric properties of LLDPE coloured with a blue nanopigment and conventional blue pigments

Purpose – This research deals with a new kind of nanopigment, obtained from the combination of organic dyes and layered nanoclays, that the authors call nanoclay-colorant pigment (NCP). Whilst they have already been employed in inks and coatings, to date these nanopigments have not been used as pigments for polymers. The existing lack of knowledge surrounding them must be redressed in order to bridge the gap between current academic studies and commercial exploitation. Therefore, the main purpose of this paper is to examine the hitherto unknown aspects of the NCP, which relate specifically to their applicability as a new type of colorant for polymers. Design/methodology/approach – A blue NCP has been prepared at the laboratory according to the patented method of synthesis (patent WO0104216), using methylene blue and montmorillonite nanoclay. It has then been applied to a thermoplastic polymer (linear low-density polyethylene – LLDPE) to obtain a coloured sample. Furthermore, samples with the same polymer but using conventional blue colorants have been prepared under the same processing conditions. The mechanical, thermal and colorimetric properties of these materials have been compared. Findings – The thermal stability of the sample coloured with NCP is reduced to some extent, while the mechanical strength is slightly increased. Moreover, this sample has better colour performance than the conventionally pigmented samples. Originality/value – In this paper, a blue NCP has been synthesised and successfully employed with polyethylene and the obtained sample shows better colour performance than polyethylene with conventional pigments.

3D Hand Pose Estimation with Neural Networks

We propose the design of a real-time system to recognize and interprethand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose will be segmented, characterized and track using growing neural gas (GNG) structure. The capacity of the system to obtain information with a high degree of freedom allows the encoding of many gestures and a very accurate motion capture. The use of hand pose models combined with motion information provide with GNG permits to deal with the problem of the hand motion representation. A natural interface applied to a virtual mirrorwriting system and to a system to estimate hand pose will be designed to demonstrate the validity of the system.