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Abstract  

A variety of isoconversional and model fitting approaches, all of which use multiple heating schedules, are used to analyze selected data from the ICTAC kinetics and lifetime projects as well as additional simulated data sets created for this work. The objective is to compare the accuracy and suitability of various approaches for various types of chemical reactions. The various simulated data sets show that model fitting and isoconversional methods have comparable reliability for extrapolation outside the range of calibration. First, there is as much variability in prediction for various isoconversional methods as there is between isoconversional methods as a group and different plausible explicit models. Of the three isoconversional models investigated, the Friedman method is usually the most accurate. This is particularly true for energetic materials that have a drop in apparent activation energy in the latter stages of reaction, which leads to a delayed onset of rapid autocatalysis at lower temperatures. It is difficult to determine a priori whether isoconversional or model fitting approaches will give more accurate predictions. The greatest reliability is attained by using both the isoconversional and model fitting approaches on a combination of isothermal and constant heating rate data.

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Isoconversional vs. Model fitting methods

A case study of crystallization kinetics of a Fe-based metallic glass

Journal of Thermal Analysis and Calorimetry
Authors:
A. Pratap
,
T. Lilly Shanker Rao
,
K. Lad
, and
Heena Dhurandhar

Abstract  

The crystallization of metallic glasses has been studied quite extensively using differential scanning calorimetry (DSC) technique. Most methods rely on isokinetic hypothesis for the kinetic analysis of crystallization for which the choice of a reliable model is very important. Due to inherent uncertainty in the determination of kinetic parameters, the model-free isoconversional analytical techniques were proposed. However, these isoconversional methods are scarcely used for metallic glasses. In the present work, the crystallization kinetics of Fe67Co18B14Si1 metallic glass through both isoconversional and isokinetic methods has been investigated and attention has been focused on the relative applicability of the two methods.

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Some transition metal nitrate complexes with hexamethylenetetramine

Part LV. Preparation, X-ray crystallography and thermal decomposition

Journal of Thermal Analysis and Calorimetry
Authors:
G. Singh
,
B. Baranwal
,
I. Kapoor
,
D. Kumar
,
C. Singh
, and
R. Fröhlich

Abstract  

Three hexamethylenetetramine (HMTA) metal nitrate complexes such as [M(H2O)4(H2O-HMTA)2](NO3)·4H2O (where M=Co, Ni and Zn) have been prepared and characterized by X-ray crystallography. Their thermal decomposition have been studied by using dynamic, isothermal thermogravimery (TG) and differential thermal analysis (DTA). Kinetics of thermal decomposition was undertaken by applying model-fitting as well as isoconversional methods. The possible pathways of thermolysis have also been proposed. Ignition delay measurements have been carried out to investigate the response of these complexes under condition of rapid heating.

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Abstract  

The non-isothermal decomposition process of the powder sample of palladium acetylacetonate [Pd(acac)2] was investigated by thermogravimetric (TG) and the X-ray diffraction (XRD) techniques. Model-free isoconversional method of Tang, applied to the investigated decomposition process, yield practically constant apparent activation energy in the range of 0.05≤α≤0.95. It was established, that the Coats-Redfern (CR) method gives several statistically equivalent reaction models, but only for the phase-boundary reaction models (R2 and R3), the calculated value of the apparent activation energy (E) is nearest to the values of E obtained by the Tang’s and Kissinger’s methods. The apparent activation energy value obtained by the IKP method (132.4 kJ mol−1) displays a good agreement with the value of E obtained using the model-free analysis (130.3 kJ mol−1). The artificial isokinetic relationship (aIKR) was used for the numerical reconstruction of the experimental integral model function, g(α). It was established that the numerically reconstructed experimental function follows R3 reaction model in the range of α, taken from model-free analysis. Generally, decomposition process of Pd(acac)2 starts with initial nucleation which was characterized by rapid onset of an acceleratory reaction without presence of induction period.

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on their thermal stability. Although, kinetic studies of thermal degradation using various model-fitting and model-free methods are available [ 11 – 20 ], inconsistencies among results obtained from these two methodologies have also been reported [ 21

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Journal of Thermal Analysis and Calorimetry
Authors:
Gurdip Singh
,
A. K. Shrimal
,
Inder Pal Singh Kapoor
,
Chandra Prakash Singh
,
Dinesh Kumar
, and
Manan S. Mudi

earlier study, we report here, the preparation, characterization, and thermolysis of transition metal perchlorate complexes with 1,6-diaminohexane ligand. Kinetics of thermolysis has been evaluated using isothermal TG by model-fitting and isoconversional

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thermogravimetric curves since the shape of these curves is a function of reaction kinetics. For this purpose, several model-fitting (a reaction model has to be chosen) and model-free (does not require a reaction model) kinetic calculation methods were developed

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Journal of Thermal Analysis and Calorimetry
Authors:
V. M. Abdul Mujeeb
,
K. Muraleedharan
,
M. P. Kannan
, and
T. Ganga Devi

α versus t curves for the thermal decomposition of all samples of KBrO 3 at all temperatures studied Model fitting method The α versus t data in the range α = 0.05–0.95 of the isothermal

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Thermal decomposition kinetics of potassium iodate

Part I. The effect of particle size on the rate and kinetics of decomposition

Journal of Thermal Analysis and Calorimetry
Author:
K. Muraleedharan

particle size ranges: a 63–75, b 75–90, c 106–125 and d 125–150 μm Model-fitting method The α − t data in the range α = 0.05–0.95 of the isothermal decomposition of all

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analysis consisted of descriptive statistics, twin correlations, univariate model-fitting, and bivariate G x E model-fitting analyses. To estimate genetic influences on GA and PS, MZ and DZ twin correlations were computed and univariate model-fitting

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