Modeling that leads to the prediction of photocatalytic coatings characterization.

摘要

One of the abundant sources of energy on earth is a solar energy which is the clean and safest energy source. It is also known as universal energy, the most important source of renewable energy available today. On realizing that the light source has a crucial role in daily life, several scientists and researchers from centuries ago have studied to establish photo induced systems and utilized them. Long after the knowledge of thermal energy, photovoltaic energy, and photosynthesis in plants, two prominent scientists, Fujishima and Honda, have discovered the electrochemical photolysis of water with the Titanium dioxide electrode which was reported in "Nature by Analogy" with a natural photosynthesis in 1972. This discovery leads to the development of heterogeneous photocatalysis in various applications including air and water purification treatment and organic synthesis. Since then it has drawn the wide scientific interest of many academicians and commercial industries.;Over the past few decades, the extensive study focused on photocatalysis. Titanium dioxide photocatalysis has been promoted as a leading and emerging green technology for air and water purification systems because of its versatile nature being non-toxic environment friendly, stability to photocorrosion, low cost and potential to function under solar light better than any other artificial light source. It can be exploited for both harvesting solar energy and the destruction of organic and inorganic pollutants, even micro-organisms, in water and air by solar light irradiation.;Recently several researches have been focused on improving the operating efficiency of the photocatalytic process on both the mechanistic aspects and other operating parametric aspects including catalyst concentration load, irradiation time, relative humidity, reaction temperature and many more; however, rate limiting properties still remain elusive. Many issues hindering its application on large scale production still exists. Several chemists and materials scientists focused mainly on the synthesis of more efficient materials and the investigation of degradation mechanism while engineers and computational scientists focused mainly on the development of appropriate models both mathematical and statistical, graphical representations to evaluate the intrinsic kinetics parameters and to build the prediction models that allow the scale up or re-design of efficient large-scale photocatalytic reactors.;The number of raw data points and raw data files collected by sensors during several experiments grows rapidly over a time. With a large number of raw data sets, a tool to handle such a large raw data set is a practical necessity both for visualization and data analysis along with the computing power. With an aim to build the prediction model of the photocatalytic characterization, scientific computing tools NumPy, SciPy, Pandas, and Matplotlib based on the python programming language are used. For graphical analysis and statistical significance, a custom tool was built using the wxPython package.