QCon London: Mastering long-running processes in modern architectures
Project reprt
1. CSIR - National Metallurgical Laboratory
(Council of Scientific and Industrial Research)
Jamshedpur, Jharkhand
Summer Project Report
On
“Evaluation of Process conditions for Magnesium Production
from Dolomite Ore Using CALPHAD Method”
(13th May-2013 to 21th June-2013)
Under the Guidance of:
Mr. Madan Mohanasundaram
Scientist
MEF Division
NML – Jamshedpur
Submitted by:
Rakesh Kumar Singh
MSME Department
MANIT- Bhopal
2. CERTIFICATE
This is to certify that Mr. RAKESH KUMAR SINGH B.Tech. Final Year of
Material Science & Metallurgical Engineering, Maulana Azad National Institute of
Technology, Bhopal, has done a summer project entitled, “Evaluation of Process
conditions for Magnesium Production from Dolomite Ore Using CALPHAD
Method” submitted at National Metallurgical Laboratory – Jamshedpur, is a
record of an original work done by me under the guidance of Mr. Madan
Mohanasundaram, Scientist, Metal Extraction and Forming Division (MEF),
NML –Jamshedpur, during the period 13th May-2013 to 21th June-2013 and this
summer project work has not been submitted for the award of any other Degree or
Diploma / Associate ship / fellowship and similar project if any.
RAKESH KUMAR SINGH
Project Guide
Date: - 21th June-2013
~2~
3. ACKNOWLEDGEMENT
First of all I am thankful of my project guide Mr. Madan Mohanasundaram
under whose guideline I was able to complete my project. I am whole heartedly
thankful to him for giving me his valuable time & attention & for providing me a
systematic way for completing my project in time.
I would like to express my sincere thanks to Mr. K.L. Hansda (Training CoOrdinate) at CSIR -National Metallurgical Laboratory, Jamshedpur, India for
arranging vocational Industrial project at their esteemed organization.
My first experience of Industrial/R&D project has been successfully complete,
thanks to the support staff of many friends & colleagues with gratitude. I wish to
acknowledge all of them. However, I wish to make special mention of the
following.
RAKESH KUMAR SINGH
~3~
4. ABSTRACT
Extraction of metals is depending upon their ore processing, better route of
processing and freezing the better process condition. So, the purpose of this project
is to analyze the best process condition for extraction process for Magnesium
production by Magnotherm Method using CALPHAD. In this project, the
Dolomite ore along with Ferro-Silicon, Bauxite & Lime for observing the efficient
production of Magnesium. A computational thermodynamic analysis was
completed on a variety of slag compositions and reaction temperatures. All
available thermodynamic and phase diagram data for these systems were collected
and used to determine three key factors: (1) Efficient amount of Magnesium
Vapors (2) Aggressiveness of the slag (3) Fraction of solid in the bulk slag.
~4~
5. Table of Content
Chapter 1:- Literature Review
1. Introduction of Magnesium
1.1.
1.2.
Thermal Properties…………………………………………………………….8
Mechanical Properties…………………………………………………………8
2. Magnesium Extraction
2.1.
Pidgeon Process……………………………………………………………….9
2.2.
Dow Process………………………………………………………………….10
2.3.
NML Process………………………………………………………………...10
2.4.
Magnotherm Process…………………………………………………………10
2.5.
Magnola Process……………………………………………………………..11
3. Thermodynamics
3.1.
Zeroth Law…………………………………………………………………..11
3.2.
First Law of Thermodynamics……………………………………………….11
3.3.
Heat capacity…………………………………………………………………12
3.4.
Heat Balanced………………………………………………………………..13
3.5.
Mass Balance………………………………………………………………...13
3.6.
Second Law of Thermodynamics……………………………………………14
3.7.
Gibbs Free Energy…………………………………………………………...14
3.8.
Helmholtz Free Energy……………………………………………………....15
3.9.
Third Law of Thermodynamics……………………………………………...15
3.10. Gibbs Energy Minimization……………………………………………….…15
4. FactSage
4.1.
Info………………………………………………………………………….18
4.2.
Databases…………………………………………………………………....18
4.3.
Calculate…………………………………………………………………….19
4.4.
Manipulate…………………………………………………………………..20
Chapter 2:- Experimental Detail
1. Methodology………………………………………………………………..22
Chapter 3:- Results & Discussions…………………………………....26
Chapter 4:- Conclusions…………………………………………..……..39
Chapter 5:- Future work…………………………………………..…….40
Chapter 6:- References……………………………………………………41
~5~
6. List of the Figures
Fig No.
1.1
2.1
2.2
2.3
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
3.10
Figures
FactSage Menu
The Main Menu of Mixture Module
The Main Menu of Equilib Module
The Main Menu of Phase Diagram: Last system
Magnesium amount at constant Temperature
Magnesium amount at constant Pressure
Effect of MgO at Binary Phase Diagram
Effect of Al2O3 at Binary Phase Diagram
Effect of SiO2 at Binary Phase Diagram
Effect of CaO at Binary Phase Diagram
Liquidus Projected Ternary Phase Diagram at MgO = 3gm
Liquidus Projected Ternary Phase Diagram at MgO = 4.5gm
Liquidus Projected Ternary Phase Diagram at MgO = 6gm
Liquidus Projected Ternary Phase Diagram at MgO = 8gm
~6~
Page No.
17
23
23
25
28
29
31
32
33
34
35
36
36
37
7. List of Tables
Table No.
1.1
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
3.10
3.11
3.12
3.13
Table
Magnesium Ores
Magnesium Yield at Different ratio of Raw Material
Magnesium Amount at changing amount of Fe-Si
Magnesium Amount at changing amount of Bauxite
Effect of Lime Addition
Feed Requirement
Effect of MgO at the slag
Effect of Al2O3 at the slag
Effect of SiO2 at the slag
Effect of CaO at the slag
Effect of the MgO at the Viscosity of slag
Effect of the Al2O3 at the Viscosity of slag
Effect of the SiO2 at the Viscosity of slag
Effect of the CaO at the Viscosity of slag
~7~
Page No.
9
26
27
27
30
30
31
33
34
37
37
38
38
38
8. Chapter 1:- Literature Review
1. Introduction of Magnesium:
Magnesium is the lightest of all the engineering materials known and has good ductility,
better noise and vibration damping characteristics than Aluminium and excellent cast
ability. Alloying magnesium with Aluminium, manganese, rare earths, thorium, zinc or
zirconium increases the strength to weight ratio making them important materials for
applications where weight reduction is important, and where it is imperative to reduce
inertial forces. It has good shielding ability for Electromagnetic Interface Frequency &
Radio Frequency Interface.
[1]
Magnesium is placed in Rare earth metal group with Mg. It has Hexagonal Closed
Pack crystal structure & paramagnetic behavior at the room temperature. The density of
Mg is 1.738 gm-cm-3 (room temperature) & twining effect occurs across the (1013)
planes. Here are some properties of Mg as followings:1.1 Thermal Properties:-
The melting point of pure Magnesium under atmospheric pressure is 650±1
o [1]
C which is increases with increasing the pressure.
The boiling point of pure Magnesium under atmospheric pressure is 1090
o [1]
C .
Thermal Expansion of pure Magnesium at the room temperature is 24.8 µmm-1-K-1. [1]
The Specific Heat Capacity (Cp) at the room temperature is 1.025 kJ/kg.K. [1]
The latent heat of Fusion & Vaporization (∆L) is 360 to 377 kJ/kg & 5150 to
5400 kJ/kg respectively. [1]
The Heat of combustion (∆H) of pure Magnesium under atmospheric pressure
is 24900 to 25200 kJ/kg. [1]
1.2 Mechanical properties:-
The Tensile Strength and Compressive Strength of cast rod (1/2 in.
diameter) of pure Magnesium is 90 MPa and 21 MPa respectively. [1]
The Hardness of the same sample is 16 (HRE) & 30 (HB). [1]
Magnesium has dynamic viscosity of liquid is 1.23 mPa.s at 650 oC and 1.13
mPa.s at 700 oC. [1]
~8~
9. 2. Magnesium Extraction:Ores and Minerals of the Magnesium are described below with the fair percentage
of magnesium present:- [2]
Name
Composition
Molecular Weight
Percentage Mg
Magnesite
MgCO3
84
29
Dolomite
MgCO3-CaCO3
184
13
Brucite
Mg(OH)2
58
42
Carnalite
MgCl2-KCl-6H2O
278
9
Kieserite
MgSO4-H2O
138
17
Serpentino
Mg3Si2O7
240
30
Enstatite
MgSiO3
100
24
Olivine
Mg2SiO4
140
34
Kainite
MgSO4-KCl-3H2O
249
10
Table: 1.1:- Magnesium Ores
Out of the above Ores; Magnesite, Dolomite & Brucite easily available in our country.
There are some extraction processes for the magnesium from its ores is following:
2.1 Pidgeon Process:The Pidgeon process involved essentially solid – state reactions. During the Pidgeon
Process, the following distinct stages are observed:1. The initial reaction takes place between ferrosilicon and CaO to produce a liquid
Ca-Si-Fe alloy, which permeates the briquette and forms a metallic network. This
reaction takes place rapidly at around 1000 oC and is mildly exothermic.
~9~
10. 2. Magnesium vapours are produced at the temperature 1550 oC by the reduction of
MgO by the Ca-Si-Fe alloy. At this stage, the pressure builds up rapidly, slowly
down the rate of reaction. The subsequent reaction rate is governed by the rate at
which magnesium can escape from the briquettes[4].
MgO (c) + Si (c)
Mg (g) + SiO (g)
PSiO at 1550 K = 3.26 * 10-1mm Hg
2SiO (g) + 2CaO (c)
2CaO-SiO2 (c) + Si (c)
-3
PSiO at 1550 K = 8.24*10 mm Hg
2.2.
………...(i)
………...(ii)
Dow Process:The Dow Process is generally applied for extraction of Magnesium from Sea
water. In this process first we add lime for thickening then mix with 10% HCl.
The final product contaminated with the magnesium oxide by which Mg
production occurs by the Electrolysis process[2].
MgCl2.6H2O = MgO + 2HCl + 5H2O
………...(iii)
In the Electrolysis Process, there is large amount of Flux required in electrolyte
composition for maintain fluidity and increases the density of bath. There are steel
wall of the cell use as the cathode and graphite anode are employed.
2.3.
NML Process:The raw material for Magnesium Production is Dolomite, Ferro –Silicon (75%80%), Fluorspar. Dolomite is calcined in the temperature range 950-1100 oC[2].
The calcined dolomite and the ferrosilicon are first ground and then mixed with
1% fluorspar. Then make briquette of that mix charged in the Tubular retorts and
create vacuum. Magnesium is distilled from the charge and then condensed on a
removable sleeve at the cold end of retorts.
2.4.
Magnotherm Process:-
A Magnotherm Process is essentially a ferrosilicon Reduction process similar to the
Pidgeon process, except that it is carried out at a temperature of 1500 oC [2]and the
bath is maintained in a molten state by the addition of alumina to form a molten slag.
~ 10 ~
11. 2.5.
Magnola Process:-
In this process first take the raw material from the Asbestos mine then make the Pure
Brine by the acid leaching. The filtrate pure brine dry and produce Magnesium Chloride
which contain the oxide of Magnesium. Then by the Electrolysis Process we can able to
produce the Magnesium.
3. Thermodynamics:For economical Magnesium production, it is essential to calculate the raw material
requirement for the optimized temperature & pressure. Thermodynamics is required to
proceed in the right direction. Computational Thermochemistry based on the Calphad
method is a modern tool that supplies quantitative data to guide the development or the
optimization of materials processing. It enables the calculation of multicomponent phase
diagrams and the tracking of individual compounds, species or slag during Extraction
process in Furnace/Retort. There are some basic laws of thermodynamics which describe
below:
3.1. Zeroth Law:According to Zeroth Law of thermodynamics “Two systems in thermal equilibrium with
a third are in thermal equilibrium with each other”.
3.2.
First law of thermodynamics:-
The first law of thermodynamics is nothing but a statement of the law of conservation of
energy means “Energy cannot be created or destroyed, but it can be converted from one
form to another”.
3.2(a) First Law in Terms of Internal Energy:-
The absorption of heat q increases the internal energy dE of the body by the amount ∂q
and performance of work w by the body decreases its internal energy dE by amount ∂w.
dE = ∂q - ∂w
~ 11 ~
…..(1)
12. 3.2 (b)
First Law in terms of Enthalpy:-
The first law of thermodynamics can be expressed in terms of the enthalpy instead of
energy.
dH = ∂q + VdP
…..(2)
Where,
“d” indicates a differential element of a state function or state property.
“∂” indicates a differential element of some quantity which is not a state function.
3.3.
Heat Capacity:-
The Heat capacity, “C” of a substance is defined as the amount of heat required to raise
its temperature by one degree.
C=
……(3)
Heat Capacity at the constant volume is given by
Cv = (
)v = (
)v
…..{from equation (1) }
Heat Capacity at the constant Pressure is given by
Cp = (
)p= [
(
)
]p
…..{from equation (1) }
Heat Capacity at the constant Pressure is also depending upon the temperature changes of
species which is denoted below in polynomial form:-
Cp (T) = a + bT + cT-2 + dT2
Where,
a, b, c & d are the arbitrary constant which are stored for every species.
~ 12 ~
…….. (4)
13. 3.4.
Heat Balance:-
Heat balanced is depending upon the first law of thermodynamics. In furnace constant
pressure can be created easily than the constant volume, means at constant volume:Heat input = Heat output
(at constant pressure)
∆H = q
Means the enthalpy increases of the system must be equal to the heat lost by the
surroundings. A Heat Balanced may be prepared in which the increases in enthalpy of the
system are tabulated in one column and the losses of the heat by the surroundings are
tabulated in other column. Any lack of balance of the two columns is due to experimental
error.
3.5.
Mass Balance:-
Mass balance for any reactive system is denoted by the below diagram.
In – Out + gen – cons = accumulation [3]
FA 0
Rate o f flow in
FA
R a te of flo w ou t
Sy s tem
GA
Rate o f
g en er atio n /
con su mp t io n
Where,
GA = ∫
V is volume of the system,
rA is total material flow rate in the system
A mass balance for a system is
FAo- FA + GA =
Where,
N is the mass of A inside the system.
~ 13 ~
……… (5)
14. 3.6.
Second Law of Thermodynamics:-
There are two statements as applied to thermodynamics:
1) Heat cannot be transferred from low temperature to high temperature without
aid of external agency. Thus the law states the irreversible nature of
spontaneous heat flow.
2) A spontaneous (non – equilibrium), irreversible change, the entropy (S) of an
isolated system always increases.
∆S = +ve
∆S = Sprod - Sreact
Where
Entropy is a state function which is defines as:
…………(6)
dS =
The standard entropy, So in terms of specific heat:-
So(T) = Sref + ∫
( )
dT
………….(7)
The enthalpy of formation, Ho in terms of specific heat:-
Ho(T) = Href + ∫
( ) dT
…………(8)
Where,
Sref & Href are the entropy and enthalpy of the species at the reference temperature
Tref.
3.7.
Gibbs free energy:-
Gibbs free energy is a state function and acts as a store of non-mechanical work or
energy available to the system for doing non-mechanical work. dG is a measure of the
work obtainable from a reversible, isothermal process occurring at constant pressure and
gives a direct indication of possibility of chemical reaction.
dG = dH – TdS
~ 14 ~
………….(9)
15. 3.8.
Helmholtz Free Energy:-
Helmholtz Free Energy A acts like a store of work or energy available for doing work
(i.e. mechanical work and non- mechanical work together ) for the system , Hence, when
work ∂W is done, A decreases by dA.
dA = dE – TdS
3.9.
…………..(10)
Third Law Of Thermodynamics:-
According the third Law of Thermodynamics “The entropy of any homogeneous
substance, which is in complete internal equilibrium, may be taken as zero at the absolute
zero temperature (i.e., So = 0 at T = 0 K).
The third law of thermodynamics is finding of the Nernst who has given Nernst heat
theorem as following:
dG = dH – TdS
[Since,
(
∆
) p = - ∆S
…..{From equation (9)}
]
Put the value in above equation and differentiate with respect to T at constant pressure at
T=0 K.
(
∆
) p, = (
∆
)p
This means that ∆G and ∆H are not zero at absolute zero but approach zero at absolute
zero, but their curves of ∆G vs. T and ∆H vs. T meet and both have the same slope at
absolute zero.
3.10.
Gibbs Energy Minimization:-
The minimization algorithm determines internally the best set of independent system
components that it should use during the minimization procedure. So each phase
constituent is composed of one or more system components. At equilibrium the
chemical potential µ of each system component at each phase is equal:
~ 15 ~
16. μ = μ = μ …
Equilibrium of a closed thermodynamic system is established if its Gibbs energy at
constant temperature and pressure has reached its minimum:
G’ (T, p, ) ≤ G (T, p, ni)
Gibbs energy of the system of one or more phases is then given as[3]:
G=∑ ∑
(μ
+
)
……….. (10)
The minimum value of Gibbs energy is found so that the masses of the system
components remain constant (mass balance constraints):
bj = ∑ ∑
………… (11)
Where,
bj is the molar amount of the system component j,
ni is the molar amount of the constituent i in phase α,
aij is the stoichiometric coefficient of the system component j in constituent i.
There are several software/database packages with applications in materials science.
These packages all contain large critically evaluated databases for thousands of
compounds and hundreds of solution phases, as well as user interfaces of varying degrees
of user-friendliness[6]:
HSC Chemistry
MTS-NPL
Thermo-Calc
Thermodata
FactSage
This is a complete database because all the other thermodynamic properties (H, Cp, µ,
etc.) can be calculated by taking the appropriate derivatives of the G functions. For a
given set of constraints (such as temperature, total pressure and total mass of each
element) the software calculates the equilibrium conditions by minimizing the total
Gibbs energy of the system. This is mathematically equivalent to solving all the
equilibrium constant equations simultaneously.
~ 16 ~
17. 4. FactSage:FactSage was introduced in 2001 as the fusion of the FACT-Win and ChemSage
thermochemical packages[6]. The FactSage package runs on a PC operating under
Microsoft Windows and consists of a series of information, database, calculation and
manipulation modules that enable one to access and manipulate pure substances and
solution databases. The software calculates the equilibrium conditions by minimizing the
total Gibbs energy of the system for given a set of constraints.
Fig.1.1 FactSage Menu
The FactSage package runs on a PC operating under Microsoft Windows the FactSage
Menu (Fig.1) offers access to the various modules of the package. The modules are
grouped into four categories:
1. Info
2. Databases
3. Calculate
4. Manipulate
~ 17 ~
18. 4.1.
Info:-
The General module provides slide shows (Microsoft Power Point and Adobe PDF
presentations) of all the modules as well as database documentation. The module also
includes information on the FactSage Family of Products and Services. These products
include[6]:
ChemApp
- The thermochemical teaching package based on FactSage
Applications.
- The thermochemistry library dynamically linked for software
ChemSheet
- The spreadsheet tool for process simulation.
SimuSage
- The component library for rapid process modeling.
CSFAP
- ChemSage File Administrator Program.
OLI Systems
- FactSage Interface: the link to the OLI aqueous databanks.
METSIM
- FactSage Link for coupled chemical process simulation.
FactSage-Teach
4.2.
Databases:-
In FactSage there are two types of thermochemical databases – compound (pure
substances) databases and solution databases. Compound databases contain data for
stoichiometric compounds (of fixed composition) giving the properties as functions of
T and P. Solution databases contain parameters of models giving the properties of
solution phases as functions of composition as well as of T and P. The
Documentation, View Data, Compound and Solution modules permit one to list
and manipulate the database files.
4.2.(a) Documentation:Introducing extensive documentation and displaying calculated phase diagrams of
different compositions of material at particular Temperature, Pressure range.
~ 18 ~
19. 4.2.(b)
View Data:-
In this module enter the E-L-E-M-E-N-T or Compound or All with selecting the database
type, which we wish to view in the database. We can able to get the entire database [i.e.
Cp (T), H (T), G (T), S (T)] at different phase in the Temperature range.
4.2.(c)
Solution & Compound:-
In these modules create the private compound & solution database which is not present
database. These compound/solution got by the experimental data for any chemical
reaction process. Once when we find the new compound/solution which is not present in
the database, input here in the define group as present in database.
4.3.
Calculate:-
There is Reaction, Predom, EpH, Equilib, Phase Diagram and Optisage modules to
calculate the different data require for the compositions.
4.3.(a) Reaction Module:The Reaction module calculates changes in extensive thermochemical properties (H, G,
V, S, and Cp) & potential (volts) relative to the H2(g)/2H [+] standard reference electrode
for a single species, a mixture of species or for a Chemical Reaction.
4.3.(b) Predom Module:The Predom module one can calculate and plot isothermal predominance area diagrams
for one-, two- or three-metal systems using data retrieved from the compound databases.
4.3.(c)
EpH Module:-
The EpH module is similar to the Predom module and permits one to generate Eh vs. pH
(Pourbaix) diagrams for one, two or three-metal systems using data retrieved from the
compound databases that also include infinitely dilute aqueous data.
~ 19 ~
20. 4.3.(d) Equilib Module:The Equilib module is the Gibbs energy minimization workhorse of FactSage and offers
great flexibility in the way the calculations may be performed. Equilib calculates the
concentrations of chemical species with a wide variety of tabular and graphical output
modes when specified elements or compounds react or partially react to reach a state of
chemical equilibrium under a large range of constraints. Equilib accesses both compound
and solution databases.
4.3.(e) Phase Diagram Module:The Phase Diagram module used to generate various types of phase diagrams for
systems containing stoichiometric phases as well as solution phases, and any number of
system components where the axes can be various combinations of T, P, V, composition,
activity, chemical potential, etc. The Phase Diagram module accesses the compound and
solution databases. The graphical output of the Phase Diagram module is handled by the
Figure module.
4.3.(f) OptiSage Module:The OptiSage Module is used to generate a consistent set of Gibbs energy parameters
from a given set of experimental data using known Gibbs energy data from wellestablished phases of a particular chemical system. The assessor (user of OptiSage) has
to use his best judgment as to which of the known parameters should remain fixed, which
sets of parameters need refinement in the optimization and which new parameters have to
be introduced, especially when assessing data for non-ideal solutions.
.
4.4.
Manipulate:-
It consist Results, Mixture, Fact-XML, Figure, Viscosity, Reset & Quit module which
are not directly use in FactSage. There are mainly use first five modules for examine the
data and phase diagram etc. which described below:-
~ 20 ~
21. 4.4.(a) Results Module:The Results module generates graphs from the output of complex equilibrium
calculations performed with Equilib Results (Equi*.Res) files. Depending upon the
selected axis variable(s) it may be necessary to specify in addition to the variable itself a
species or phase to which this variable is related.
4.4.(b) Mixture Module:Use Mixture to edit mixtures and streams for input to Equilib. The mixture module use
in making the mixture of the elements or compounds which are act as the reactants in the
reaction process. In the stream module is use to take the mixture of the product gasses as
and use them as a reactants which is very much helpful in recycling of heat/energy in the
chemical process.
4.4.(c)
Fact-XML:-
The Fact-XML is an add-in to the Equilib program that enables you to edit the results of
a calculation and save customized outputs as templates. There is no limitation to the
number of templates. In this module we can change the unit, activity of species, graph
setup and draw etc.
4.4.(d) Figure Module:Use of Figure to Manipulate, edit and plot figure and phase diagrams already calculated
by FactSage. Graphical output from calculation modules such as Reaction, Predom,
Equilib or Phase Diagram can be Post-viewed and edited using the Figure module.
4.4.(e) Viscosity Module:The viscosity module for single-phase, liquid slags and glasses has been developed. It is
distinct from other viscosity models in that it directly relates the viscosity to the structure
of the melt, and the structure in turn is calculated from the thermodynamic description of
the melt using the Modified Quasichemical Model.
~ 21 ~
22. Chapter 2:- Experimental Detail
5. Methodology:1. Extraction of magnesium get by the raw material Dolomite, Ferro-Silicon &
Bauxite with the following compositions (in Wt. %):-
Ferro – Silicon:Si
Fe
Al
Ca
=
=
=
=
70.10 %
27.19%
2.02%
0.53 %
Calcined Bauxite:Al2O3
CaO
SiO2
Fe (T)
=
=
=
=
87.34%
1.35%
4.66%
3.5%
MgO
CaO
SiO2
Al2O3
Fe2O3
Na
K
=
=
=
=
=
=
=
20.80%
29.87%
0.54%
1.12%
1.24%
0.12%
0.04%
Dolomite Ore (Dolo-3):-
2. By using the Mixture Module in FactSage, make mixture of Ferro-Silicon,
Calcined Bauxite & Dolomite ore. Its to be mentioned mention that compositions
are in mass percent unit and not in the “mole”. Save those mixtures for further
process as shown in below fig:
~ 22 ~
23. Fig 2.1:- The Main Menu of Mixture Module[6]
3. Import all the mixture in the Equilib Module in different weight ratio of FerroSilicon, Calcined Bauxite & Dolomite ore. Then calculate the weight of
Magnesium vapours at the specific temperature and pressure. Be sure that the
mass unit in the Equilib module should not in “Mole”.
Fig: 2.2:- The Main Menu of Equilib Module[6]
24. 4. The effective mass of magnesium is depend upon the minimum Gibbs Free
Energy for the above mixture reaction at the specific temperature and pressure by
the below formula:
Pure Condensed Phases
G=
∑ ni (
+ RT ln Pi ) + ∑ ni
+ ∑ ni (
+ RT ln Xi + RT lnγi)
Ideal Gas
+ ∑ ni (
Solution - 1
+ RT ln Xi + RT ln γi) ……
[6]
……(12)
Solution - 2
Where,
ni : Moles
Pi : Gas Partial Pressure
Xi : Mole Fraction
γi : Activity Coefficient
: Standard Molar Gibbs Energy
Since,
Pi=Mg =
* PTotal
5. When we get the best process condition for Magnesium Production from these
raw materials. Then add the Lime at that process condition and observed the
influence of lime at the production of Magnesium.
6. Then by using the Phase Diagram Module for components of slag ( i. e. MgO,
CaO, Al2O3 & SiO2 ) draw the binary phase diagram keep constant amount of two
components for looking the effect of other two components on slag formation
temperature & Calcium Silicate + slag temperature by which it’ll easy to
determine the Low melting temperature of slag economically, Make sure about
the below condition[8]:-
= 1.8 but for the furnace process this ratio can be use the
range of 2.2- 2.4
= 0.26 but for the furnace process this ration can be use the range of
0.30– 0.33
…………. (iv)
Slag components weight percentage should be in the following range:
CaO
SiO2
Al2O3
MgO
=
=
=
=
~ 24 ~
54-58%
23-28%
11-15%
3-8%
25. 7. Draw the Liquidus projection Ternary Phase Diagram of the slag components
CaO, Al2O3 & SiO2 at the range of the MgO amount (3-8 wt. %) and the
temperature range (1400oC – 1800oC) for looking the Liquidus area shrinkage
and growing with the MgO amount And Temperature by superimpose all
diagrams.
0.026136 atm
Fig 2.3:- The menu of Phase Diagram: Last system
8. For low viscosity of the slag use the Viscosity module, in which keep different
slag composition ratio of the MgO, CaO, Al2O3 & SiO2 components with keep in
mind above ratio and slag components amount at the temperature range 1400oC –
1700oC.
9. Finally with keep in mind Low slag Viscosity, Low Slag melting Temperature &
optimum temperature and Pressure, determine the amount of raw material.
~ 25 ~
26. Chapter 3:- Results & Discussions
1. Take amount of the raw materials in different weight Ratio at Temperature range
1500oC-1700oC & Pressure 10mm – 30mm Hg.
1.1.
Keep Calcined Bauxite & Ferro –Silicon Amount constant, increase the
amount of Dolomite (Dolo-3).
Ratio ( Dolo-3:Bauxite:Ferro-Silicon)
(x100 gm.)
Magnesium Yield (wt. %) at
1600
4.68
1.59
0.06
9.69
5.12
2.84
9.11
6.96
6.19
1600
10.13
8.30
7.37
11.27
10.22
9.01
13.14
11.01
10.28
1600
13.13
12.13
11.36
13.51
13.11
12.57
1500
13.91
13.31
12.84
1600
14.37
13.89
13.51
1700
14.64
14.34
14.08
1500
14.43
13.98
13.67
1600
14.75
14.38
14.13
1700
14.93
14.66
14.47
1500
13.93
13.45
13.07
1600
14.16
13.94
13.77
1700
14.29
14.12
13.99
1500
12.45
12.13
11.88
1600
12.72
12.56
12.42
1700
7:1:1
0.05
1700
6:1:1
0.29
1500
5:1:1
1.58
1700
4:1:1
30mm Hg
1500
3:1:1
20mm Hg
1700
2:1:1
10mm Hg
1500
1:1:1
Temperature
(oC)
12.80
12.74
12.68
Table: 3.1:- Magnesium Yield at different ratio of Raw
~ 26 ~
27. Magnesium Yield (Wt. %) is economically maximum for the ratio 5:1:1 but Amount of
Magnesium (gm.) is economically maximum at the ratio 6:1:1. So, it has been decided to
choose the latter Ratio for the further procedure from above table.
1.2.
Increase amount of Ferro –Silicon from 100gm to 130gm at constant
Dolomite & Bauxite amount.
Ratio ( Dolo-3:Bauxite:FerroSilicon)
Temperature(oC)
Magnesium amount(gm.)
118.43
115.42
113.42
1600
120.52
117.99
116.27
121.63
119.73
118.39
1500
122.98
119.59
117.31
1600
125.33
122.53
120.59
1700
126.49
124.30
122.75
1500
125.89
122.26
119.73
1600
128.48
125.50
123.37
1700
6:1:1.3
30 mm
1700
6:1:1.2
20 mm
1500
6:1:1.1
10 mm
129.77
127.54
125.87
Table: 3.2:- Magnesium Amount at changing the amount of Ferro-Silicon
Since, we know that the Ferro-Silicon provide the Si which increase the reactant
concentration by which reaction proceed forward that’s why magnesium amount
increases as shown in reaction (i).
1.3.
Increase the Amount of Calcined Bauxite at Ratio 6:1:1.3 with keeping the
constant amount of Dolomite & Ferro-Silicon.
Ratio ( Dolo-3:Bauxite:Ferro-Silicon)
Temperature(oC)
Magnesium amount(gm.)
10 mm
30 mm
1500
121.84
117.19
114.03
1600
125.43
121.85
107.27
1700
6:1.5:1.3
20 mm
127.48
124.91
122.97
Table: 3.3:- Magnesium Amount at changing the amount of Bauxite
~ 27 ~
28. Means for the efficient production of Magnesium, the Optimum ratio of Dolo-3: Calcined
Bauxite: Ferro-Silicon should be in 6:1:1.3.
2. Take the Magnesium amount at the optimum ratio of raw material at pressure
range 10 mm-30 mm Hg at constant temperature range 1500oC-1700oC.
131
1550 oC
130.1064
129.6144
130
129
128.7744
1600 oC
128.1456
128
127.5888
1700 oC
127.8216
127.08
126.9408
125.688
127
Magnesium Amount (gm)
1650 oC
128.856
125.7144
126.0864
126
1500 oC
126.9168
125.9016
125
126.108
124.98
124.5528
124
123.9984
124.1784
123.528
123
122.904
122.3544
122
121.7856
121
120.9696
120
119.7528
119
118
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Pressure (mm Hg)
Fig: 3.1:- Magnesium amount at constant Temperature
3. Take the Magnesium amount at the optimum ratio of raw material at constant
pressure range 10 mm-30 mm at temperature range 1500oC-1700oC.
~ 28 ~
30. Lime
0
10
20
30
40
50
Addition(gm.)
125.50 126.41 127.36 128.24 129.08 129.89
Magnesium
amount (gm.)
Solid Slag (wt.
13.816 16.95
19.91
22.67
25.24
27.58
%)
1.003
0.99
0.977
0.962
Viscosity (poise) 1.024 1.014
Table: 3.4:- Effect of Lime Addition
60
70
80
130.65
131.37
132.04
29.7
31.57
33.19
0.945
0.928
0.909
When we add lime then from Reaction (ii), we observe that Partial Pressure of SiO is
Low than Reaction (i) that’s why the Magnesium production increases.
5. Then Feed requirement for the 1 ton Magnesium and the slag composition of
the process with increasing the amount of lime will be following:
Dolomite
ore
(ton)
4.781
4.745
4.711
4.679
4.648
4.619
4.592
4.567
4.544
Calcined
Bauxite
(ton)
0.797
0.791
0.785
0.779
0.775
0.769
0.765
0.761
0.757
FerroSilicon
(ton)
1.036
1.028
1.021
1.014
1.007
1.001
0.995
0.989
0.985
Total
Energy
Amount
Requirement
(ton)
(kWh/ton)
0
6.614
1.4226*10^4
0.079
6.643
1.4336*10^4
0.157
6.674
1.4447*10^4
0.234
6.706
1.4559*10^4
0.309
6.739
1.4674*10^4
0.385
6.774
1.4790*10^4
0.459
6.811
1.491*10^4
0.523
6.84
1.5033*10^4
0.606
6.892
1.5159*10^4
Table: 3.5:- Feed requirement
Lime
(ton)
Slag(ton)
Solid
0.765
0.944
1.115
1.278
1.431
1.575
1.707
1.827
1.935
Liquid
4.771
4.624
4.486
4.358
4.241
4.134
4.04
3.959
3.894
6. Now draw the binary phase diagram between the Temperatures Vs. mass
fraction of slag constituents for observing the Lowest Liq-Slag & Solid Slag
(Ca2SiO4) formation temperature with keep in mind equation (iv).
6.1.
Keep MgO mass fraction in range of 0-0.08 Wt. % with keep the
constant mass fraction of Al2O3 & SiO2, draw the Binary Phase
Diagram.
~ 30 ~
31. Fig: 3.3:- Effect of MgO at Binary Phase Diagram
Take the Solid & Liquid slag temp & Wt. % at different mass fraction of MgO from
above Binary Phase Diagram.
MgO(mass Fraction)
0.05
0.06
0.07
0.08
Solid Slag Temp.
1480.77
1524.62
1560
1590.15
Liquid Slag Temp.
1861.54
1831.08
1791.38
1745.23
Solid slag %
39.85
31.83
23.91
16.03
Liquid slag %
60.15
68.17
76.09
83.97
Table: 3.6:- Effect of the MgO at the slag
From the above data, we observe that as increasing the amount of MgO in slag Solid Slag
temperature increase as decreasing the Liquid Slag temperature. Since as increasing the
MgO in slag decreases the Magnesium amount as in reaction (i). That’s why solid slag
percentage also decreases with increasing the amount of MgO in slag.
~ 31 ~
32. 6.2.
Keep Al2O3 mass fraction in range of 0-0.20 Wt. % with keep the
constant mass fraction of MgO & SiO2, draw the Binary Phase
Diagram.
Fig: 3.4:- Effect of Al2O3 at Binary Phase Diagram
Take the Solid and Liquid Slag wt. % in the slag at the efficient solid slag temperature
at different mass fraction of Al2O3 from above Binary Phase Diagram.
Al2O3(mass Fraction)
.095
.098
.1
.105
Solid Slag Temp.
1652
1502.46
1436.92
1436.92
Liquid Slag Temp.
1748.92
1824.62
1897.54
1906.77
Solid slag %
12.03
31.68
44.69
70.02
Liquid slag %
87.97
68.32
55.31
29.98
Table: 3.7:- Effect of the Al2O3 at the slag
~ 32 ~
33. From the above data we observe that as increasing the amount of Al2O3 in slag decreases
the solid slag temperature but increases the liquid slag temperature. Since alumina in slag
also increases the CaO in slag that’s why solid slag will be increase as in reaction (ii).
6.3.
Keep SiO2 mass fraction in range of 0-0.32 Wt. % with keep the
constant mass fraction of MgO & Al2O3, draw the Binary Phase
Diagram.
Fig: 3.5:- Effect of SiO2 at Binary Phase Diagram
Take the Solid and Liquid Slag wt. % in the slag at the efficient solid slag temperature
at different mass fraction of SiO2 from above Binary Phase Diagram.
SiO2(mass Fraction)
.31
.3
.29
.29
Solid Slag Temp.
1436.92
1436.85
1577.69
1637.69
Liquid Slag Temp.
1832
1791.54
1746.15
1735.38
Solid slag %
58.33
46.79
29.46
12.82
Liquid slag %
41.67
53.21
70.54
87.18
Table: 3.8:- Effect of the SiO2 at the slag
~ 33 ~
34. From the above data we observe that increasing the amount of SiO2 in slag decreases
solid slag temperature with increasing the liquid slag temperature. Since increasing silica
in slag increase the CaO [reaction (iv)] that’s why solid slag will form more as in reaction
(ii).
6.4.
Keep CaO mass fraction in range of 0-0.58 Wt. % with keep the
constant mass fraction of MgO & Al2O3, draw the Binary Phase
Diagram.
Fig: 3.6:- Effect of CaO at Binary Phase Diagram
Take the Solid and Liquid Slag wt. % in the slag at the efficient solid slag temperature at
different mass fraction of CaO from above Binary Phase Diagram.
CaO(mass Fraction)
0.54
0.55
0.56
0.57
Solid Slag Temp.
1662
1524
1437
1481
Liquid Slag Temp.
1786
1853.54
1906.5
1941.33
Solid slag %
16.58
34.91
47.01
53.93
Liquid slag %
83.42
65.09
52.98
46.07
Table: 3.9:- Effect of the CaO at the slag
~ 34 ~
35. As we observe from the above data as increasing the amount of CaO in slag Solid
temperature first decrease then again increase and liquid slag temperature increases. As
increase CaO in slag also increase the silica [reaction(iv)] by which the slag formation
will be more.
7. Draw the ternary phase diagram of slag components Al2O3, SiO2 and CaO at
Magnesium amount range 3gm-8gm and Temperature range 1500 oC – 1700
o
C at constant pressure 20mm Hg for observing the effective Liquidus
Projection with combine effect of slag components:
1800oC
1600oC
1500oC
1700oC
Fig: 3.7:- Liquidus Projected Ternary Phase Diagram at MgO = 3gm
~ 35 ~
37. 1600oC
o
1800 C 1700 C
1500oC
o
Fig: 3.10:- Liquidus Projected Ternary Phase Diagram at MgO = 8gm
8. Now take slag composition of the components at the temperature range for
measuring the viscosity of slag in melts state.
8.1.
First keep Magnesium amount constant in the range of 1-8 wt. % and
make different composition of slag.
Slag Compositions (wt. %)
MgO
CaO
Al2O3
SiO2
62.17
8.5
28.33
1
62.94
8.5
26.56
2
61.6
7.4
28
3
57.47
9.5
29.03
4
56.23
8
30.77
5
56
8.53
29.47
6
55.37
8
29.63
7
55.43
8
28.57
8
o
1400 C
2.18
2.012
2.061
2.351
2.41
2.31
2.281
2.173
Viscosity(poise)
1500 oC 1600 oC
1.235
0.744
1.145
0.693
1.173
0.709
1.333
0.803
1.365
0.823
1.314
0.794
1.299
0.786
1.242
0.753
Table: 3.10:- Effect of the MgO at the Viscosity of slag
~ 37 ~
1700 oC
0.472
0.441
0.452
0.51
0.522
0.505
0.501
0.481
38. As the amount of MgO increases (0-8 gm.), the viscosity of slag also increases (0.44-2.41
poise) at constant temperature and decreases with increasing temperature.
8.2.
Now make the compositions of slag components (i. e. Al2O3, SiO2 &
CaO) with observing viscosity of slag at different temperature.
Slag Compositions (wt. %)
MgO
CaO
Al2O3
SiO2
4
56
30
10
4.1
56.1
30.2
9.6
4.2
56.3
30.5
9
4.4
56.5
30.7
8.4
4.5
56.8
30.8
7.9
o
1400 C
2.521
2.504
2.478
2.441
2.403
Viscosity(poise)
1500 oC 1600 oC
1.425
0.857
1.415
0.851
1.402
0.843
1.382
0.831
1.361
0.819
1700 oC
0.543
0.539
0.534
0.527
0.520
Table: 3.11:- Effect of the Al2O3 at the Viscosity of
As the amount of Alumina increases (7.9-10 gm.), the viscosity of slag also increases
(2.521-0.520 poise) at constant temperature and decreases with increasing temperature.
Slag Compositions (wt. %)
MgO
CaO
Al2O3
SiO2
5
55
10
30
5.5
55.5
9.5
29.5
6
56
9
29
6.3
56.2
9.3
28.2
6.4
56.3
9.4
27.9
o
1400 C
2.520
2.406
2.301
2.242
2.219
Viscosity(poise)
1500 oC 1600 oC
1.426
0.858
1.365
0.823
1.309
0.791
1.277
0.773
1.265
0.767
1700 oC
0.544
0.523
0.504
0.493
0.489
Table: 3.12:- Effect of the SiO2 at the Viscosity of slag
As the amount of Silica increases (27.9-30 gm.), the viscosity of slag also increases
(2.520-0.489 poise) at constant temperature and decreases with increasing temperature
Slag Compositions (wt. %)
MgO
CaO
Al2O3
SiO2
5.5
9.5
28.5
56.5
5.8
9.6
29
55.6
6
9.7
29.3
55
6.2
9.8
29.5
54.5
6.3
9.9
29.8
54
o
1400 C
2.291
2.357
2.402
2.435
2.483
Viscosity(poise)
1500 oC 1600 oC
1.303
0.788
1.339
0.809
1.364
0.823
1.382
0.834
1.408
0.849
1700 oC
0.501
0.514
0.523
0.530
0.539
Table: 3.13:- Effect of the CaO at the Viscosity of slag
As the amount of CaO increases (54-56.5 gm.), the viscosity of slag also decreases
(2.483-0.501 poise) at constant temperature and also decreases with increasing
temperature
~ 38 ~
39. Chapter 4:- Conclusions
The process conditions for the production of Magnesium by Magnotherm Process
is evaluated.
The optimum ratio of the raw materials is found to be Dolomite: Bauxite: FerroSilicon: Lime:: 6:1:1.3:0.5.
The optimum range of the operating process conditions are; 1600oC temperature &
20mm Hg Pressure for the given raw material and the feed ratio.
Maintenance of the liquid slag is evaluated through the phase diagrams and the
calculation of the viscosity of the given slag. From the calculations, it is known
that the minimization of silica in the slag and optimized use of the amount of
Magnesia and Alumina leads to the maintenance of the slag in liquid form.
~ 39 ~
40. Chapter 5:- Future work
These studies can further continued in the open system, where continuous
evaluation of the Mg can be obtained, which is an actual situation.
The kinetic study of the rate of dissolution of the ore in the slag bath is an
important parameter for the Mg production.
CFD of the Magnesium reactor is important, as to access the internal process
parameters and its distribution over the entire domain.
~ 40 ~
41. Chapter 6:- References
1. ASM Specialty Handbook, “Magnesium and Magnesium Alloys”.
2. H S Ray, “Extraction of Non Ferrous Metals”.
3. Gaskell, “Introduction to thermodynamics of materials”.
4. J.M Toguri and L.M. Pidgeon, Can. J. Chem. 39, 540 (1961). & O.
Kubaschewski and E. Ll. Evans. “Metallurgical thermochemistry”. Pergamon
Press Ltd., London. 1958.
5. Ursula R. Kattner NIST-Gaithersburg. “Thermodynamic Modeling of
Multicomponent Phase Equilibria”. JOM 49 (12) (1997) 14-19.
6. FactSage® 6.4 Manual.
7. Melissa Marshall and Zi-Kui Liu, “A Computational Thermodynamic Analysis
of Atmospheric Magnesium Production”. TMS (2001)
8. United states Patent 4190434, “Thermal Processes for the Production of
Magnesium”.(14th Jun-1978)
~ 41 ~
