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.

Uv-Vis Spectrum Analysis Of Heavy Metal Detection

MOHAMAD SOFI BIN OMAR, MOHAMAD SOFI (2011) Uv-Vis Spectrum Analysis Of Heavy Metal Detection. Universiti Teknologi Petronas, Sri Iskandar,Tronoh,Perak. (Unpublished)

Download (648kB) | Preview


UV-Vis spectroscopy is routinely used in the quantitative determination of solutions of transition metal ions and highly conjugated compounds. One of its applications is to find the molar absorptivity of different kind of heavy metals ions. Using molar absorptivity, concentration of heavy metals ions can be deduced based on the established calibration curve. This calibration curve first need to be constructed by repeatedly analyzed it UV-Vis spectrum analysis of the concerned ion with controlled concentration. The plot between known concentration and its corresponding absorptivity is used as a calibration curve to predict the unknown concentration of samples based on it absorptivity. The aim of this project is to study several different type of relationship between the Uv-vis spectroscopy absorptivity and heavy metals ion concentration. Conventionally, the relationship between absorptivity intensity variable and it corresponding concentration are all assume as linear. Heavy metals on the other hand show non-linear correlation and when the calibration curve wrongly adapts same construction method, it gives high errors. From three tested model fitted, experiment show that quadratic model is the most suited model to explain the relationship. Apart from the relationship between variable, this project also investigates a multipoint predictor to improve the calibration accuracy. We apply multivariate analysis to the several data extracted from various location of uv-vis spectrum and transform it to single most accurate predictor variable. Partial Least Square Regression (PLSR) analysis proven superior both in prediction of sample concentration and the degree of line fitting to the point compared to Principle Component Regression (PCR) analysis method. PLSR is capable in providing lowest error when linear regression calibration curve are required. Apart from those two factors, the project also uncovers several key factors in helping to improve the accuracy, one of the factor consist of the properties of raw data extraction decision. Different location of point extraction location and different number of point required vary by the transformation method used, but in most occasion, highest peak and second highest peak in spectrum show better potential for both single point raw data and multiple point extracted for preprocessing. Preprocessing step is another factor that supports the improvement of the calibration curve. Instead using the intensity of absorptivity in a wavelength spectrum, different between chosen two points is used as a raw data. Overall, the best calibration curve is the combination of preprocessing step and quadratic model fit.

Item Type: Final Year Project
Subject: T Technology > TP Chemical technology
Divisions: ?? sch_che ??
Depositing User: Users 5 not found.
Date Deposited: 11 Jan 2012 12:23
Last Modified: 25 Jan 2017 09:42
URI: http://utpedia.utp.edu.my/id/eprint/382

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...