alexa Predicting the Burning Rate of Thermally Thin Nylon Using TGA (Thermo Gravity Analysis) and DSC (Differential Scanning Calorimeter)

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Predicting the Burning Rate of Thermally Thin Nylon Using TGA (Thermo Gravity Analysis) and DSC (Differential Scanning Calorimeter)

Sarat Ganti*
University of Petroleum and Energy Studies, Visakhapatnam, Andhra Pradesh, India
*Corresponding Author: Sarat Ganti, University of Petroleum and Energy Studies, Visakhapatnam, Andhra Pradesh, India, Email: [email protected]

Received Date: May 02, 2018 / Accepted Date: Jun 15, 2018 / Published Date: Jun 22, 2018

Abstract

Given the importance of thermally thin materials in minimizing the fire accidents different properties of Nylon added with montmorillonite (MMT) clay of 5% (thermally thin) are examined in this paper. A simple first order reaction model is considered to minimize the number of unknown parameters. Different Kinetic, Physical, and thermodynamic properties are obtained from DSC and TGA data and are compared for both thermally thick and thin rubbers thereby, proving the importance of thermally thin Nylon.

Keywords: Thermo gravity analysis; Differential scanning calorimeter; Arrhenius equation; Cone calorimeter

Introduction

Thermally thin materials have been an engaging area to be debated in the field of fire safety. Given the increase in wide range of application for polymers, upgrading the properties of the polymers by adding nanoparticles has been hitting the trends in the current scenario. Nylon finds its usage from machine parts to cooking wares. From Plastic fasteners to fabric and due to this wholesome range of applications polymer Nylon has been considered as basis for our study [1].

Nylon a thermally thick material is added with montmorillonite (MMT) clay of 5% which turns it in to a thermally thin material. There is huge contrast in the behaviours of Nylon and Nylon added with montmorillonite (MMT) clay. The addition of montmorillonite (MMT) clay leads to reduction in the rate of burning due to the formation of thermal insulation layer [2]. This also leads to the increase in clearance time in case of fire [3]. Flashovers are the critical component which might lead to catastrophic accidents and the addition of MMT reduces it [4].

Experimental

In the TGA analysis the amount of material lost is obtained with respect to temperature. The specific heat and the heat of decomposition are calculated from the TGA and DSC data. And from the correlations a wide range of physical properties can be obtained. In this paper a simple first order model is considered the reason being, the increase in order of the reaction the unknown parameters get increased leading to the complexity in the model and in order to curb this menace a simple first order reaction has been considered [5].

The parameters to be considered in the Arrhenius equation are the activation energy (Ea) and the pre-exponential factor/frequency factor (K0). The pre-exponential factor/frequency factor (K0) is dependent on the rate of heating. And the activation energy (Ea) depends on the amount of conversion (Xa) [6].

In this paper the burning behaviour of the thermally thin materials is predicted and the required data for the formulation of the model is obtained by DSC and TGA analysis and a comparison is laid down for both type materials (thermally thick and thermally thin) and also the importance of amount of clay added is also discussed.

Thermogravity analysis

The main aim of TGA is to find the kinetic parameters and TGA curve is obtained by depicting the graph between change in change in weight in mg (Y-axis) and temperature in °C (X-axis) [6].

A sample TGA curve has been depicted below (Figure 1):

international-journal-waste-resources-curve

Figure 1: TGA curve.

Calculation of TGA curve theoretically

Let image be a fraction which is reacting in the given time t.

The change in X with respect to time is a function of X with a rate constant k which is dependent on temperature.

image(1)

Here, K is the rate constant, X is the fraction reacted, and t is the time.

Consider Arrhenius equation (6) as,

image(2)

Here, K0 is the pre exponential factor Ea is the activation energy, and T is the temperature.

Consider the following equation for constant linear heating rate (7) as,

image (3)

Using equation (1), (2), and (3) we get the form,

image(4)

Rearrange equation (4) to get the form as follows:

image (5)

Analysing equation (5) we get to know that the f (X) determines the shape of the curve and in order to know f (X) we need to consider the decomposition theory of the sample under consideration.

Decomposition theory [7]

Assumptions:

1. The materials under consideration when decomposed forms a perfect two phase mixture of solid-fuel (a) and char (c) [1].

2. The char formed does not shrink in its volume thereby allowing us to consider the same volume as the initial sample [8].

3. As the for majority of the materials the order of the thermal decomposition lies in between the range of 0.5 and 1.5 we consider it to be a first order reaction [9].

Char Fraction (CX): Ratio of final mass to the initial mass of the sample under consideration [5]. Applying conservation of mass for the sample when heated,

The rate of mass lost with respect time (t) is equal to the rate of fuelgas mass coming out.

image (6)

Here, mg is the mass rate of fuel gas.

From the assumptions (2) and (3) the equation for the first order reaction is,

image(7)

Here, V is the volume (considered as constant according to assumption 1) and ρa is the density image.

Equation (7) is modifies as,

image(8)

image(9)

Decomposition Reaction Stoichiometry leads to,

image

Integration on both sides leads to,

image(10)

Using the equation for the fraction reacted and equation (10) we get,

image (11)

Using equation (11), (9), and (8) we get,

image (12)

Substituting the equation (12) in equation (2) we obtain,

image(13)

Equation (13) is the required for TGA. In equation (13) the parameters frequency factor and activation energy are to be obtained.

Results and Discussion

Determination of kinetic parameters [3]

In order to determine the kinetic parameters apply log on both sides of the equation (13) as follows:

image(14)

Compare equation (14) with the form Y = mX +c

Here, m is the slope image and c is the intercept image.

Plotting the graph between image on Y axis and image on X axis.

Obtaining the value of image is difficult as it involves complex derivations and hence, image needed to be modified.

image(15)

image(16)

Applying the required parameters the following values are obtained (Table 1) [10].

Parameters Activation energy (J/mol) Pre-exponential energy* 10-14
Thermally Thin Material 223 2.1
Thermally Thick Material 223 1.5

Table 1: Kinetic parameters.

DSC

This chapter consists of obtaining the values of Heat of decomposition and heat of melting for thermally thick and thin materials using differential scanning calorimeter [11].

Introduction

In Differential scanning calorimeter two materials namely sample under study (Nylon and Nylon+5% MMT clay) and the reference material are placed and basing on the difference in heat absorbing and releasing nature the difference in behaviours, and various parameters such as the extent of the chemical reaction taking place are obtained [12].

Heat of decomposition [12]

For different heating rates the heat of decomposition is obtained for Nylon and Nylon+5% MMT clay.

For Nylon (Thermally thick material) (Table 2).

Heating Tate (°C/min) Heat of Decomposition (kJ/kg)
5 388

Table 2: Thermally thick material.

For Nylon+5% Clay (Thermally thin material) (Table 3).

Heating Rate (°C/min) Heat of Decomposition (kJ/kg)
2 557
5 618
10 522

Table 3: Thermally thin material.

Heat of melting [10]

For the heating rate at 5°C/min the heat of melting for both the materials has been obtained (Table 4).

Heating rate (°C/min) Heat of decomposition (kJ/kg)
5 35, 73 (Thermally Thin Material)
5 32 (Thermally Thick Material)
5 35 (Thermally Thick Material)

*Data obtained from thesis paper of Kim-Predicting the Burning of polymers.

Table 4: Heat of melting.

Conclusion

From the TGA analysis the we obtained that the activation energy for both the materials is same which means both the materials require the same amount of energy to cross the energy barrier. However, the pre exponential factor is less for thermally thin material.

From the DSC analysis we can infer that the thermally thin materials rate of burning is low which can be cited as a major advantage and also for the same amount of rate of heating the heat of melting and heat of decomposition of the thermally thin material is less which indicates the superiority of the thermally thin materials over thick materials in fire protection.

References

Citation: Ganti S (2018) Predicting the Burning Rate of Thermally Thin Nylon Using TGA (Thermo Gravity Analysis) and DSC (Differential Scanning Calorimeter). Int J Waste Resour 8: 343. DOI: 10.4172/2252-5211.1000343

Copyright: © 2018 Ganti S. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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