Correct interpretation of chemical diagrams requires transforming from one level of representation to another

17 volunteer non-major chemistry students taking an introductory university chemistry course were interviewed about their understanding of a variety of chemical diagrams. All the students' interviewed appreciated that diagrams of laboratory equipment were useful to show how to set up laboratory equipment. However students' ability to explain specific diagrams at either the macroscopic or sub-microscopic level varied greatly. The results highlighted the poor level of understanding that some students had even after completing both exercises and experiments using the diagrams. The connection between the diagrams of the macroscopic level (equipment, chemicals), the sub- microscopic level (molecular) and the symbolic level (equations) was not always considered explicitly by students. The results indicate a need for chemical diagrams to be used carefully and more explicitly to ensure learner understanding. Correspondingly, students need to interpret visual chemical diagrams using meta-visualisation skills linking the various levels of representation, and appreciating the role of the diagrams in explanations need to be developed.

The descriptive and explanatory nature of chemical diagrams does not guarantee understanding

Volunteer non-major chemistry students, taking an introductory university chemistry course (n= 17) were interviewed about their understanding of a variety of chemical diagrams. All the students’ interviewed appreciated that diagrams of laboratory equipment were useful to show how to set up laboratory equipment. However students’ ability to explain specific diagrams at either the macroscopic or sub-microscopic level varied greatly. The results highlighted the poor level of understanding that some students had even after completing both exercises and experiments using the diagrams. The connection between the diagrams of the macroscopic level (equipment), the sub-microscopic level (molecular) and the symbolic level (equations) was not always apparent to students. The results indicate a need for chemical diagrams to be used carefully and more explicitly to ensure the learner understanding.

Energy consumption at the state level: the unit root null hypothesis from Australia

In this paper, our goal is to examine the unit root null hypothesis in energy consumption for Australian states and territory. We consider sectoral energy consumption for Australia and its six states and one territory using time series data for the period 1973-2007. This is the first study that does this. Generally, except for some cases in South Australia, we find strong support that shocks to energy consumption have a temporary effect on energy consumption in Australia. © 2009 Elsevier Ltd. All rights reserved.

Does electricity consumption panel Granger cause GDP? A new global evidence

The goal of this paper is to undertake a panel data investigation of long-run Granger causality between electricity consumption and real GDP for seven panels, which together consist of 93 countries. We use a new panel causality test and find that in the long-run both electricity consumption and real GDP have a bidirectional Granger causality relationship except for the Middle East where causality runs only from GDP to electricity consumption. Finally, for the G6 panel the estimates reveal a negative sign effect, implying that increasing electricity consumption in the six most industrialised nations will reduce GDP. © 2010 Elsevier Ltd. All rights reserved.

Relationship between processing, surface energy and bulk properties of ultrafine silk particles

Silk particles of different sizes and shapes were produced by milling and interactions with a series of polar and non-polar gaseous probes were investigated using an inverse gas chromatography technique. The surface energy of all silk materials is mostly determined by long range dispersive interactions such as van der Waals forces. The surface energy increases and surface energy heterogeneity widens after milling. All samples have amphoteric surfaces and the concentration of acidic groups increases after milling while the surfaces remain predominantly basic. We also examined powder compression and flow behaviours using a rheometer. Increase in surface energy, surface area, and static charges in sub-micron air jet milled particles contributed to their aggregation and therefore improved flowability. However they collapse under large pressures and form highly cohesive powder. Alkaline hydrolysis resulted in more crystalline fibres which on milling produced particles with higher density, lower surface energy and improved flowability. The compressibility, bulk density and cohesion of the powders depend on the surface energy as well as on particle size, surface area, aggregation state and the testing conditions, notably the consolidated and unconsolidated states. The study has helped in understanding how surface energy and flowability of particles can be changed via different fabrication approaches.

Prediction interval-based modelling of polymerization reactor: a new modelling strategy for chemical reactors

Precise and reliable modelling of polymerization reactor is challenging due to its complex reaction mechanism and non-linear nature. Researchers often make several assumptions when deriving theories and developing models for polymerization reactor. Therefore, traditional available models suffer from high prediction error. In contrast, data-driven modelling techniques provide a powerful framework to describe the dynamic behaviour of polymerization reactor. However, the traditional NN prediction performance is significantly dropped in the presence of polymerization process disturbances. Besides, uncertainty effects caused by disturbances present in reactor operation can be properly quantified through construction of prediction intervals (PIs) for model outputs. In this study, we propose and apply a PI-based neural network (PI-NN) model for the free radical polymerization system. This strategy avoids assumptions made in traditional modelling techniques for polymerization reactor system. Lower upper bound estimation (LUBE) method is used to develop PI-NN model for uncertainty quantification. To further improve the quality of model, a new method is proposed for aggregation of upper and lower bounds of PIs obtained from individual PI-NN models. Simulation results reveal that combined PI-NN performance is superior to those individual PI-NN models in terms of PI quality. Besides, constructed PIs are able to properly quantify effects of uncertainties in reactor operation, where these can be later used as part of the control process. © 2014 Taiwan Institute of Chemical Engineers.

Comparison of milling and solution approach for production of silk particles

Silk particles were produced by regenerating from silk solution, and using a milling method. In the regenerated silk particle production, two methods which are reported to render submicron silk particles were selected. Their particle sizes and structures were compared with particles of milling method already developed by us. The volume median average particle sizes (d(0.5)) of regenerated particles were much higher than what was reported previously. In contrast, milling method could produce particles with adjustable particle sizes ranging from micron to submicron level. All the milled particles had advantage of at least 15. °C higher thermal decomposition temperature than regenerated particles. They had silk II structure, and the crystallinity reduced as particle fineness increased, but remained higher than regenerated particles of similar sizes. © 2014 Elsevier B.V.

Development of nanostructured polymeric materials using polymerizable lyotropic liquid crystals.

This thesis was focused on the development of nanostructured polymers for CO2 capture and energy storage applications, using polymerizable lyotropic liquid crystal. A combination of polarized optical microscopy, differential scanning calorimetry and Small-angle x-ray scattering has been used to characterize and understand the structure retention of these systems during photo-polymerization.