Performance and durability of broadband antireflection coatings for thin film CdTe solar cells

Light reflection from the glass surface of a photovoltaic (PV) module is a significant source of energy loss for all types of PV devices. The reflection at the glass and air interface accounts for 4% of the total energy. Single layer antireflection coatings with sufficiently low refractive index have been used, such as those using magnesium fluoride or porous silica, but these are only effective over a narrow range of wavelengths. In this paper, the authors report on the design, deposition, and testing of multilayer broadband antireflection coatings. These coatings reduce the weighted average reflection over the wavelength range used by thin film CdTe devices to just 1.22%, resulting in a 3.6% relative increase in device efficiency. The authors have used multilayer stacks consisting of silica and zirconia layers deposited using reactive magnetron sputtering. Details of the stack design, sputter deposition process parameters, and the optical and microstructural properties of the layers are provided. Antireflection coatings on glass exposed to the outdoors must not degrade over the lifetime of the module. A comprehensive set of accelerated environmental durability tests has been carried out in accordance with IEC 61646 PV qualification tests. The durability tests confirmed no damage to the coatings or performance drop as a result of thermal cycling or damp heat. All attempts to perform pull tests resulted in either adhesive or substrate failure, with no damage to the coating itself. The coatings also passed acid attack tests. Scratch resistance, abrasion resistance, and adhesion tests have also been conducted. The optical performance of the coatings was monitored during these tests, and the coatings were visually inspected for any sign of mechanical failure. These tests provide confidence that broadband antireflection coatings are highly durable and will maintain their performance over the lifetime of the solar module. All dielectric metal-oxide multilayer coatings have better optical performance and superior durability compared with alternative single layer porous sol–gel coatings. Thin film CdTe devices are particularly problematic because the antireflection coating is applied to one side of the glass, while device layers are deposited directly on to the opposite glass surface in the superstrate configuration. In thin film CdTe production, the glass is exposed to high temperature processes during the absorber deposition and the cadmium chloride activation treatment. If glass precoated with a broadband antireflection coating is to be used, then the coating must withstand temperatures of up to 550 C. Surprisingly, our studies have shown that multilayer silica/zirconia antireflection coatings on soda lime glass remain unaffected by temperatures reaching 600 C, at which point mild crazing is observed. This is an important observation, demonstrating that low cost glass, which is preprocessed with a broadband antireflection coating, is directly useable in thin film CdTe module production

3D Finite Element Modelling of Cutting Forces in Drilling Fibre Metal Laminates and Experimental Hole Quality Analysis

Machining Glass fibre aluminium reinforced epoxy (GLARE) is cumbersome due to distinctively different mechanical and thermal properties of its constituents, which makes it challenging to achieve damage-free holes with the acceptable surface quality. The proposed work focuses on the study of the machinability of thin (~2.5 mm) GLARE laminate. Drilling trials were conducted to analyse the effect of feed rate and spindle speed on the cutting forces and hole quality. The resulting hole quality metrics (surface roughness, hole size, circularity error, burr formation and delamination) were assessed using surface profilometry and optical scanning techniques. A three dimensional (3D) finite-element (FE) model of drilling GLARE laminate was also developed using ABAQUS/Explicit to help understand the mechanism of drilling GLARE. The homogenised ply-level response of GLARE laminate was considered in the FE model to predict cutting forces in the drilling process

The influence of anisotropy in numerical modelling of orthogonal cutting of cortical bone

Cutting operations in bone are involved in surgical treatments in orthopaedics and traumatology. The importance of guaranteeing the absence of damage in the living workpiece is equivalent in this case to ensuring surface quality. The knowledge in this field is really far from the expertise in industrial cutting of mechanical components. Modeling of bone cutting is a challenge strongly dependent on the accurate modeling of mechanical behaviour of the bone. This paper focuses on modeling of orthogonal cutting of cortical bone. The intrinsic anisotropic nature of the cortical bone that makes it comparable to a composite material is taken into account. The influence of anisotropy is analysed comparing this behaviour with an isotropic approach. It is shown that both chip morphology and temperature are affected by the anisotropy of the cortical bone that acts as a workpiece.The authors acknowledge the financial support for the work to the Ministry of Economy and Competitiveness of Spain under the Project DPI2011-25999 and DPI2013-46643-R.Santiuste, C.; Rodríguez Millán, M.; Giner Maravilla, E.; Miguélez, H. (2014). The influence of anisotropy in numerical modelling of orthogonal cutting of cortical bone. Composite Structures. 116:423-431. doi:10.1016/j.compstruct.2014.05.031S42343111

Predicting the sentiment in sentences based on words: An exploratory study on ANEW and ANET

Current practices for sentiment prediction from text mostly involve words-in-a-bag approach that utilize techniques such as support vector machines or naive Bayes. In this study, ANET (Affective Norms for English Text) sentence ratings of pleasure and arousal are compared with ANEW (Affective Norms for English Words) word ratings using regression and single layer neural networks. The sentences in ANET are decomposed into their words to obtain valence and arousal ratings from ANEW. A stop list is formed for non-words as well as words that are not found in ANEW. Then we studied whether the sentence sentiment reflected in terms of valence and arousal can be predicted from the sentiment of words in the sentence. Using linear regression, we found that approximately 35% of the variance in ANET valence and arousal ratings can be explained by ANEW valence and arousal ratings. Furthermore, Pearson correlation coefficient for ANEW and ANET ratings are similar for both valence and arousal, and close to 0.6. We also trained neural networks to investigate if non-linear approximations improved prediction of sentence sentiments from the constituent words. Out of several feedforward neural network configurations, a network with 200 hidden layer nodes turned out to be capable of identifying sentence sentiments accurately: the words' valence and arousal values explained 88 % of the variance in the sentences' valence ratings and 91 % of the variance in the sentences' arousal ratings. This preliminary study indicates that a proper choice of neural network might be adequate to estimate sentiments of sentences from sentiments of words