Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

A Novel QSPR Model for the Prediction of the Ionic Liquid Toxicities towards Green Algae {Pseudokirchneriella SubcapUata)

Abdul Rahman, Nora Aziela (2012) A Novel QSPR Model for the Prediction of the Ionic Liquid Toxicities towards Green Algae {Pseudokirchneriella SubcapUata). Universiti Teknologi PETRONAS. (Unpublished)

[img] PDF
Download (1MB)


Ionic Liquid (IL) are defined as the salt that melting point temperatures are lower than the boiling point of water. ILs can also be called as green solvent due to their undetectable vapor pressure hence can emit no volatile organic compounds. However, many ILs are found to be harmful and toxic to human and environment. Therefore, the toxicity studies of ILs become of great importance. The early study in determining toxicity of ILs was by using experimental works. However, ILs present in a very large combination of cations and anions that synthesized in the market and thousands are added every year which exceed the capacity of experimental works. Besides, experimental works are time consuming, require high cost and can kills aquatic organism. Therefore, Quantitative Structure Activity Relationship (QSAR) models are the best approach to overcome the above matter since QSAR approach is suitable to be used for huge number of chemical in a rational and effective manner. This study aims to develop a QSAR model to predict the toxicities of ILs towards one of green algae which is Pseudokirchneriella subcapitata (P. subcapitata), previously known as Selenastrum capricornutum. The dataset constructed by gathering 61 effective concentrations (EC50) values of various ILs towards P. subcapitata from published literature before they being fragmented according to their cations, anions, and alkyl groups. The prediction model will then develop using QSAR approach employing multiple linear regressions (MLR) with polynomial model that will be coded using MATLAB software. To the best of our knowledge, there is no previous model developed based on combination of these two models towards P. subcapitata. The proposed model indicates that the model is capable of predicting the IL toxicities accurately, where R > 100% with an average absolute deviation error 0%. The model has the potential to be used as an alternative to experimental measurement in the determination of EC50 values for a wide range of ILs towards P. subcapitata. In addition, it can be one of the important references for industrial people who deal with ILs.

Item Type: Final Year Project
Academic Subject : Academic Department - Chemical Engineering - Reactor Technology
Subject: T Technology > TP Chemical technology
Divisions: Engineering > Chemical
Depositing User: Users 2053 not found.
Date Deposited: 24 Oct 2013 10:12
Last Modified: 25 Jan 2017 09:40
URI: http://utpedia.utp.edu.my/id/eprint/9621

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...