Send Orders for Reprints to reprints@benthamscience.net Current Nanoscience, 2014, 10, 869-876 869 Correlation Between Size of CoFe 2 O 4 Nanoparticles Determined from Experimental and Calculated Data by Different Mathematical Models Danut Gabriel Cozma a , Daniel Gherca a , Ionut Mihalcea b,c , Constantin Virlan a , Nicoleta Cornei a and Aurel Pui* a a Faculty of Chemistry, “Alexandru Ioan Cuza” from Iasi, University, Carol I Bvd. No. 11, Iasi 700506, Romania; b Unité de Catalyse et Chimie du Solide (UCCS) – UMR CNRS 8181, Université de Lille Nord de France, USTL-ENSCL, Bat C7, BP 90108, 59652 Villeneuve d’Ascq, France; c Institut für Nanotechnologie, Karlsruhe Institute of Technology, Postfach 3840, D-76021 Karlsruhe, Germany Abstract: This study reports the synthesis of CoFe 2 O 4 nanoparticles by coprecipitation method in the presence of Linseed Oil as surfactant. The capping agent was used to stabilize the particles and prevent their agglomeration. The characteriza- tion studies were conducted by in situ X-ray diffraction, transmission electron microscopy, thermal analysis (TG-DTA) and FTIR spectroscopy. The average particle sizes obtained by XRD data were used to obtain a correlation with size of CoFe 2 O 4 nanoparticles determined, using mathematical equations based on different models. The statistical studies show that the cubic model gives a good correlation within the whole temperature range (100 – 850 °C). The result of these in- vestigations was very useful for establishing the optimal calcination temperature. FT-IR spectroscopy and thermogra- vimetric analysis (TG) showed that the core-shell structure type of CoFe 2 O 4 nanoparticles is stable below this annealing temperature. TEM analysis indicates that the CoFe 2 O 4 samples during the calcinations treatment were spherical in shape and uniform in morphology and particles size. Keywords: Infrared spectroscopy, mathematical models, nanoparticles size, powder X-ray diffraction patterns. INTRODUCTION Cobalt ferrite, with a well-known cubic spinel ferrite crystal structure, is considered to be a competitive candidate for a wide area of applications in various fields of catalysis [1], hyperthermia treatment [2], recording device and sensors [3], microwave devices and magnetic ferrofluids technology, magnetic resonance imaging, drug delivery, antitumor and protein separation [4-6]. Among these applications it is well know that synthesis protocols, reaction conditions and post- synthesis processes strongly influence the properties of co- balt ferrite magnetic materials, which have further impact on their different practical uses. Several synthetic methods have been developed for co- balt nanoferrites and these include hydrothermal synthesis [7], emulsion [8], sol-gel template approach [9], coprecipita- tion route [10, 11], combustion [12] and organic thermal decomposition process [13]. Among them, the coprecipita- tion synthetic process is one of the most inexpensive meth- ods to prepare in high-yield cobalt ferrite nanoparticles. Dur- ing this process, the precipitates are produced simultaneously and uniformly dispersed in the solution. The annealed fer- rites at high temperature might have some inconveniences, including agglomeration of the particles, chemical heteroge- neity and uncontrolled growth of particle size. In order to prevent such disadvantages, previous studies have concluded *Address correspondence to this author at the Faculty of Chemistry, Univer- sity “Alexandru Ioan Cuza” from Iasi, Carol I Bvd. No. 11, Iasi 700506, Romania; Tel/Fax: +40 232 2013 13; E-mail: aurel@uaic.ro that surfactant molecules can be employed in a whole syn- thetic process [6, 14-21]. Other studies show that the synthe- sis temperature and subsequent calcinations processes play an important role in controlling the size of the cobalt ferrite, which significantly influence the physical properties of the product [22, 23]. A wide variety of regression models have been devel- oped to evaluate different situations. The regression model consists of a systematic component and a residual compo- nent. The systematic component contains information about the underlying dependencies between a set of predictor vari- ables and a response. The aim of statistical regression analy- sis is to model the mechanisms that produce the systematic component [24]. Statistics models show the degree of corre- lations between the experimental results and the predicted values, which validates the accuracy of the mathematical model [25]. The influence of the calcination temperature on the de- gree of crystallinity, morphology, microstructure and phase purity can be investigated by different techniques, e.g., pow- der X-ray diffraction pattern (PXRD), transmission electron microscopy (TEM), and Fourier transform infrared spectros- copy (FT-IR), respectively [26]. From the literature survey we conclude that there are no studies to correlate the NP’s dimensions with temperature, based on mathematical models. The aim of this study is finding a mathematical model that could best correlate the nanoparticles sizes and to deter- mine the optimal calcination temperature for maintaining the 1575-6786/14 $58.00+.00 © 2014 Bentham Science Publishers Bentham Science Publishers For Personal Use Only Not For Distribution