b82 Final Report

7/28/2019 b82 Final Report

http://slidepdf.com/reader/full/b82-final-report 1/57



1 Executive Summary

Mounting concern regarding the adverse efects associated with anthropogenically produced

greenhouse gasses (GHG) has led governments to introduce binding legislation to limit and re-

duce the rate and magnitude o their emission o GHG, with particular emphasis on CO2. While

there are many ways in which these ambitions could be achieved, so-called carbon capture and

storage (CCS) is considered to be a promising route to attaining a meaningul reduction in CO2

emissions in the near-term. It has been shown that CCS technology is particularly appropriate

or large xed-point emission sources. O these, the ossil-uel based power generation indus-

try produces the lion’s share o total global CO2

emissions. Due to its technological maturity,

operational exibility and its associated low technology risk, post-combustion capture (PCC)

o CO2 via solvent based chemisorption is likely to be the preerred technology option in this

important sector. However, current state-o-the-art PCC techniques have a signicant energy

penalty associated with their operation (OPEX) and due to the scale o the problem, the capital

costs (CAPEX) associated with this technology are oten considered prohibitive. Thus, there

exists a well-recognised imperative or the signicant reduction o both the size o the equip-

ment required (CAPEX) and the cost o solvent regeneration (OPEX). The design o advanced

solvents represents the best opportunity or reducing these costs as it is the solvent that denes

the thermodynamic and kinetic limits o the process. However, conventional approaches to mod-

elling reactive separation processes, due to their heavy reliance on the availability o extensive

experimental data, do not easily lend themselves to reormulation as solvent design problems.

The goals o this project were the development and validation o detailed thermodynamic and

process models relevant to CO2 capture processes. The thermodynamic models have been de-

veloped using the SAFT-VR equation-o-state, and the process models have been implemented

in the gPROMS modelling environment. We have developed a novel technique or modelling the

phase behaviour and thermophysical properties o reactive uid mixtures. Reliable models to

quantiy the phase and chemical equilibrium o mixtures o CO 2 + water + amine-based solvent

have been developed. The solvent molecules considered include ammonia (NH3), methylamine,

ethylamine, propylamine, butylamine, pentylamine, hexylamine, ethanol, monoethanolamine

(MEA), 2-amino-2-methyl-1-propanol (AMP), diethylamine, diethanolamine (DEA), triethy-

lamine, methyldiethylamine (MDEA). The models have been shown to be transerable so that

the behaviour with other similar solvents (e.g. alkylamines or other alkanolamines) can be pre-

dicted in the absence o experimental data. The models obtained are highly accurate, with

average absolute deviations less than 1.5% in saturated vapour pressure and liquid density.

1



Building on this success, we have proposed a new methodology or building accurate, predictive

models o reactive separation processes, using rate-based models and taking advantage o theact that CO2 chemisorption is mass-transer limited in commonly used solvents. The novel

approach that has been developed has a signicantly reduced dependence on experimental data

when compared to other approaches. Further, due to the thermodynamic ramework employed,

the process models are substantially simpler and, in our experience, require no adjustment o

model parameters as process operating conditions are changed or indeed as solvent blends are

changed. We have validated the predictions o our absorber model using pilot plant data ob-

tained rom the International Test Centre in the University o Regina, Canada. This validation

was perormed with solvents with a wide range o reaction kinetics, thus giving condence in our

assumptions and results. The predictions o our desorber model have been validated using using

pilot plant data obtained rom NTNU in Trondheim, Norway. In this way, we have proposed

a new approach or solving integrated solvent and process design problems in the context o

mass-transer limited reactive separation processes.

On the basis o preliminary results in this area, we now have the underpinning tools in place

to design novel solvent blends, by optimising process perormance (e.g., minimising energy con-

sumption given separation targets). By building on other tools developed in the research group

we can also tackle the issue o designing novel solvent molecules. Finally, to achieve a complete

description o the design problem, we need to incorporate oxidation and corrosion models into

our overall process model. All these ofer promising and innovative avenues or urther research.

Finally, rom the work done in this project, results sucient or eight journal papers have

been obtained, o which one has been accepted or publication in Industrial & Engineering

Chemistry Research with the remainder currently in preparation or journal publication and

sixteen conerence presentations, o which eleven were oral presentations, have been given.

2



Contents

1 Executive Summary 1

2 Introduction 5

2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.2 Chemistry and thermophysical property methods . . . . . . . . . . . . . . . . . . 6

2.3 Approaches to modelling reactive separation systems . . . . . . . . . . . . . . . . 8

2.3.1 Equilibrium vs. rate-based models . . . . . . . . . . . . . . . . . . . . . . 8

2.3.2 Selection o a mass transer model . . . . . . . . . . . . . . . . . . . . . . 8

3 Results and Discussion 9

3.1 Thermodynamic modelling o reactive uid mixtures with SAFT-VR . . . . . . . 9

3.1.1 Ammonia based mixtures . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3.1.2 Monoethanolamine based mixtures . . . . . . . . . . . . . . . . . . . . . . 14

3.1.3 2-Amino-2-methyl-1-propanol based mixtures . . . . . . . . . . . . . . . . 17

3.1.4 Overview o incorporation o chemical reactions within the SAFT approach 19

3.2 Process modelling and validation . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

3.2.1 Model development and validation . . . . . . . . . . . . . . . . . . . . . . 19

3.2.2 Initial solvent design study . . . . . . . . . . . . . . . . . . . . . . . . . . 21

4 Conclusions 22

5 Proposed work for a subsequent programme 23

3



6 Publications arising from the project 23

Bibliography27

4



2 Introduction

2.1 Background

Due to their energy density, proven resource base and established inrastructure or their ex-

ploitation and distribution, it is well accepted that energy derived rom ossil uels will continue

to play an important role in supplying the worlds energy [1]. At the same time, concerns sur-

rounding climate change due to anthropogenic emissions o CO2 have resulted in a number o

initiatives to reduce CO2 emissions [2]. So-called carbon capture and storage (CCS) technologies

are accepted as being a promising route to a near-term meaningul reduction in CO 2 emissions.

The power generation sector is the largest stationary point source o CO2 emissions [3] and one

o most viable technologies or CO2 capture rom power stations is post-combustion absorption

o CO2 with chemical solvents [4].

The current state-o-the-art technology is solvent scrubbing with amine based solvents [5]. How-

ever, this process is highly energy intensive, in particular it requires a signicant amount o

energy or solvent regeneration [6]. Thereore, there exists a strong imperative to reduce the

energy penalty associated with CO2 capture [7]. In order to achieve these goals, the selection

and design o the solvent or solvent blend to be used is o upmost importance. Specically, itis desirable that the energy penalty associated with solvent regeneration be decreased, the rate

o reaction be increased and that the CO2 loading capacity can be increased [7]. Thereore, this

problem may be ormulated as a solvent design problem, where proposed solvents and solvent

blends can be evaluated using appropriate perormance indices. Process perormance indices

help to quantiy the overall solvent efect on the operation o the process. This leads to a tight

integration o process operation and solvent selection, and provides a rational basis or solvent

design [8].

Typically, in modelling systems with reactive separation, one either uses a sophisticated, compu-tationally intensive methodology, such as in the work o Kucka et al. [9] or simplied enhancement

actor concepts, such as in the work o van Swaaij et al. [10]. However, enhancement actors are

exact only in a ew special limiting cases, and typically approximations to describe more realistic

scenarios are employed [11,12]. Moreover both approaches rely on experimental data to provide

inormation on reaction kinetics and mass transer. These data are unavailable in the context

o novel solvents. Finally, in solvent design problems, there exists the paradoxical requirement

to reduce as much as possible the computational complexity o the process model, while con-

currently retaining accuracy in model predictions in order that the results o any optimisation

5



studies are as robust as possible [8].

In this project, we have developed a new methodology or the design and assessment o novel

solvent blends or uid separation processes. Our approach is completely general and is equally

applicable to both physical and chemical based separation processes with no change in model

complexity, provided that the process is not kinetically limited. We use the statistical associating

uid theory or potentials o variable range (SAFT-VR) [13, 14] both to account or the non-

idealities that are observed in aqueous mixtures o amines and also to represent the key reactions

that are present in this system, thereby simpliying the description o the chemical reactions at

the level o the process model. Thus, the only experimental data required or assessing solvent

blends are binary mixture vapour-liquid equilibria data, which are typically abundant, and arerelatively easy to measure i they are not available, as opposed to detailed inormation on the

kinetics and rate equations which are required in the usual approach. We propose that this

approach provides a suitable platorm or the solution o solvent design problems or complex

and reacting uid systems.

2.2 Chemistry and thermophysical property methods

The reactive nature o mixtures o amines in aqueous solution with CO2 is well known; there is alarge body o experimental and theoretical work in place detailing the mechanisms and rates o

these reactions [15–20]. Moreover, they have been presented several times in the literature, and

as such they will not be described in detail here. It suces to say that the principle reactions

o interest are the ormation o carbamate

Carbamate ormation : CO2 + 2RNH2 [RNHCO−

2 + RNH+3 ] (1)

and the subsequent reversion o carbamate to bicarbonate,

Carbamate reversion : RNHCO−

2 + H2O RNH2 + HCO−

3 , (2)

where it can be seen that the overall stoichiometry o the reaction is such that each molecule o

CO2 is eventually associated with two amine molecules; the carbamate and protonated amine

can be considered as a tightly bound ion pair (denoted by the square brackets) particularly at

higher temperatures. In addition to these chemical reactions, there are also the ionic speciation

6



equilibria o the CO2+H2O and aqueous amine mixtures to consider [21]. The chemical reac-

tions and ionic speciation that occur in these mixtures strongly inuences the phase behaviouro the system, and ailure to adequately account or these interactions results in highly erro-

neous predictions [22–24]. Typically, in order to account or the non-idealities o this mixture a

quasichemical-based [25–28] lattice model o the liquid phase such as the electrolyte nonrandom

two liquid (eNRTL) model o Chen et al. [29,30] (a modication o the NRTL model o Renon

and Prausnitz [31]) is used, as in the work o Kucka et al. [9]. However, lattice models are

inapplicable to the gas phase, and consequently, another theory must be used to describe its

phase behaviour. Oten, cubic equations-o-state, like the Soave-Redlich-Kwong [32] equation

are used to describe the gas phase as in Kucka et al. [9], or sometimes the gas phase is treated

as ideal as in the work o Kvamsdal et al. [33] or Ziaii et al. [34].

Others, such as Gabrielsen et al. [35] and Aboudheir et al. [36] have developed their own cor-

relations using a Henry’s law type description o the phase behaviour, modied to incorporate

the efect o the reactions on the vapour pressure o each component. Some o these models

have been subsequently successully incorporated in process models o CO2 absorption sys-

tems [37, 38]. These correlations are typically very simple in mathematical orm, and are very

easy to use. However, their predictive ability is limited, and any attempt to use them outside

the region in which the correlation was developed can result in highly aphysical predictions.

The development and implementation o accurate process models requires extensive calculation

o the physical properties associated with the system. Thus, the ability to calculate and, more

importantly, accurately and reliably predict the phase behaviour and thermophysical properties

o complex, multicomponent systems is o paramount importance to developing robust process

models. In this way, accurate physical property predictions can be considered the raw materials

o optimal process design [39]. The implementation o a multistage nonequilibrium model in-

volves the repeated calculation o interacial compositions (phase equilibria) and the enthalpies

o the bulk gas and liquid phases requiring the calculation o both pure component and mixtureenthalpies. As these quantities are themselves used again and again throughout the model in the

energy balance and rate equations, their accurate calculation is o vital importance to the accu-

racy o the the model as a whole. Further, many o the correlations used in typical engineering

design require the calculation o quantities such as liquid interacial tension, enthalpy o vapori-

sation, heat capacity, gas and liquid densities. The ability to accurately calculate these quantities

in a predictive way with SAFT-VR will remove existing restrictions on exploring with condence

the diferent operating regimes and also allow more condence in solvent design activities. We

have used the SAFT-VR [13,14,40,41] equation o state (EOS) to calculate the thermodynamic

7



properties and uid phase equilibria o our system as it has previously been shown to model

complex associating and reactive mixtures successully or a wide range o conditions.

2.3 Approaches to modelling reactive separation systems

2.3.1 Equilibrium vs. rate-based models

Most types o gas-liquid contactors can be considered as a cascade o segments or stages which

are related to one another through mass and energy balance equations [42]. In gure 14, diferent

model approaches representing diferent complexities concerning the description o mass transerand chemical reaction are presented. The simplest model is the classical equilibrium stage model

which assumes that the streams leaving a given stage are in equilibrium, with no reactions and

innitely ast mass transport within the single stage [42]. As mass and heat transer are rate

processes that are driven by gradients o chemical potential and temperature, equilibrium is

rarely attained and thus traditional “equilibrium stage models + eciency actor” approaches

are inadequate or the description o chemisorption processes. In increasing the complexity o

the model, we can choose to include some details o the reaction kinetics while maintaining the

concept o the equilibrium stage [43].

For a model to be both rigorous and predictive, the efect o simultaneous heat and mass transer,

the efect o chemical reactions and their coupled efects on the physical properties and phase

behaviour o the system must be included in the model. Mass transer in multicomponent

mixtures is more complicated than in binary systems because o the possible coupling between

the individual concentration gradients. Phenomena such as reverse difusion (difusion o a

species against its own concentration gradient) or osmotic difusion (difusion o a species even

though no concentration gradient or that species exists) are possible in multicomponent systems

but not in binary mixtures. One o the interesting consequences o these interaction efects is

that the individual point eciencies o diferent species are not constrained to lie between zero

and one. Instead, they may be ound anywhere in the range rom −∞ to +∞ [44]. It is not

possible to predict these phenomena with “equilibrium stage” models.

2.3.2 Selection of a mass transfer model

For reactive systems with a “ast” chemical reaction, i.e., where the process is not limited by

the reaction kinetics, the two-lm model has been extensively used as the mass transer model

8



o choice almost since its inception by Lewis and Whitman in 1924 [45] and its subsequent

renement by Hatta in 1932 [46]. See or example the journal papers o [33, 42, 44,47–50] andreerences therein or details. Also, it has been shown [51] that that the selection o the lm

model can be justied on the basis o the value o Ha, the Hatta number [52,53]. It has been

shown that systems characterised by a “rapid” chemical reaction, such as the absorption o acid

gases, where the chemical reaction can be considered to occur only in the liquid lm, the liquid

holdup is not important and the rate o absorption will be large i the efective interacial area

and the individual mass transer coecients and are large. This is called the physical kinetic

regime and is characterised by the condition:

Ha > 3 (3)

The Hatta, Ha, number may be dened as [54]:

Ha =N i

N Physi

(4)

This is the ratio o absorption with reaction, N i, to that without reaction, N Physi . Ha has

diferent unctional orms depending on the nature o the reaction occurring (1st order 2nd etc).

As long as the condition in equation (3) is satised, the system will be well represented by the

two-lm model.

3 Results and Discussion

This section is presented in three successive parts. First, some key results o the thermo-

dynamic modelling activities o this project are presented. This section is divided into three

distinct sections wherein the results o the work on NH3, MEA and AMP mixtures are presented.

Subsequently, the results o our process model development and validation work are presented.

Finally we present the results o our initial solvent design work.

3.1 Thermodynamic modelling o reactive fuid mixtures with SAFT-VR

In the SAFT-VR approach a molecule i is modelled as a homonuclear chain o mii bonded square-

well segments o hard-core diameter σii. The square-well interactions are urther characterised

9



by a well depth εii and a range λii. In addition, a number o of-centre, square-well association

sites are used to mediate the association interactions. The sites are placed at a distance r∗

d = 0.25rom the centre o a segment and the cut-of range between a site a on a segment i and a site

b on a segment j is denoted by r∗cab,ij = rcab,ij /σij. These two parameters dene the volume

K ab,ij available or site-site bonding [55]. When two sites are within a distance o rc;ab,ij they

interact with a well depth εHBab,ij. The sites are commonly labelled as e or H , representing either

an electronegative atom (or its lone-pairs o electrons) or the hydrogen atoms in a molecule,

respectively; only e-H bonding is allowed. In all the models considered in this paper one e site

is allocated or each electron lone-pair and one H site or each hydrogen atom.

In order to model the mixtures, a number o unlike intermolecular potential parameters also needto be specied. The arithmetic mean is used to obtain size-related intermolecular parameters,

so that the unlike contact diameter between two molecules i and j is given by

σij =σii + σ jj

2, (5)

the unlike square-well range by

λij =

λiiσii + λ jjσ jj

σii + σ jj , (6)

and the unlike bonding volume by

K ab,ij =

K

1/3ab,ii + K

1/3ab,j j

2

3. (7)

These parameters are not readjusted at any point. The unlike dispersion and hydrogen bonding

energetic parameters are dened in terms o the geometric mean o the like interactions and a

correction actor, so that the unlike dispersion energy between two components i and j is given

by

εij = (1 − kij)√

εiiε jj , (8)

and the unlike hydrogen bonding energy between two sites a and b is given by

εHBab,ij = (1 − kHB

ab,ij)

εHBab,iiε

HBab,jj. (9)

10



The adjustable parameters kij and kHBab,ij are determined by comparison to mixture experimental

data.

In reporting the perormance o our models, we use the average absolute deviations AAD. For

the pure components, we use three descriptors o the quality o the t: an overall percentage

AAD,

%AAD =100

N P + N ρ

N P i=1

P Expv,i (T i)− P Calcv,i (T i; θ)

P Expv,i (T i)

+

N ρ j=1

ρExpl,j (T j)− ρCalcl,j (T j ; θ)

ρExpl,j (T j)

, (10)

and separate percentage AADs or vapour pressure and liquid density,

%AAD P =100

N P

N P i=1

P Expv,i (T i)− P Calcv,i (T i; θ)

P Expv,i (T i)

, (11)

%AAD ρl =100

N ρ

N ρi=1

ρExpv,i (T i)− ρCalcv,i (T i; θ)

ρExpv,i (T i)

. (12)

In the case o the mixtures, we report either the error in the calculated equilibrium pressure o the mixture, at a given temperature and liquid composition given by

%AAD P =100

N P

N P i=1

P Expi (T, xIi)− P Calci (T, ρI, xI

i; θ, φ)

P Expi (T, xIi)

, (13)

or the error in the calculated equilibrium temperature at given pressures and liquid compositions

%AAD T = 100N T

N T i=1

T

Exp

i (P i, x

I

i)− T

Calc

i (P i, ρ

I

, x

I

i; θ, φ)T Expi (P i, xI

i)

, (14)

and, i available, the error in the composition o the other equilibrium (vapour or liquid) phase

at each T i or P i and phase I composition. As mole ractions are constrained to be between zero

and one, an absolute measure o error is more appropriate,

AAD xII =1

N x

N x

i=1xII,Expi − xII,Calc

i

. (15)

11



3.1.1 Ammonia based mixtures

Pure ammonia

Following the general scheme described in section 3.1, NH3 is modelled as a single spherical

segment. This is what one would expect as a model NH3 and the spatial density plots presented

by Thompson et al. [56] lend urther credence to this view. The hydrogen bonding interactions

in NH3 are mediated by the inclusion o our of-centre association sites. A our-site model is

physically intuitive, and is consistent with the traditional physical chemistry molecular-orbital

view o ammonia and it is also consistent with the view o water or which there is abundant

simulation and experimental data, as presented by Clark et al. [57]. The our-site model is asym-metric, with one e site to represent the lone pair o electrons on the nitrogen atom and three

H sites to represent the three hydrogen atoms. When modelling NH3, only e - H interactions

are permitted. A nal model o NH3 is selected based on its ability to simultaneously correlate

vapour-liquid equilibria and predict the interacial-tension, γ , and the enthalpy o vapourisa-

tion, ΔH fg o the NH3 molecule. As ΔH fg is a second derivative property o the Helmholtz

ree energy, this constitutes a very severe test o our model. Further, this analysis o γ is help-

ul in establishing that we have the correct partitioning between the enthalpic and entropic

contributions to the ree energy, as rom

dAσ = −SdT σ − P dV σ + γdA+nci

μidni (16)

it can be seen that

dAσ

dT

V σ,A ,ni

= −S σ

The results o this investigation are shown in gures 1, 2, 3a and 3b respectively. The AAD as

dened by equation (10) or the NH3 model was 1.48% in saturated vapour pressure and liquid

density. We consistently use this rationale to discriminate between molecular models or other

components considered in this work.

Aqueous ammonia mixtures

The modelling o binary mixtures o NH3 + H2O is interesting both rom a practical and scientic

standpoint. The academic interest stems primarily rom the act that aqueous solutions o NH3

12



signicantly disassociate in water. In this work, we treat this dissociation without explicitly

treating the electrolytes, thus simpliying the model. In solutions with signicant dissociation,there will be signicant deviation rom Henrys law. This is signicant as a ailure to adequately

account or these interactions between NH3 adn H2O will result in a erroneous prediction o

vapour pressures [24]. From a more practical perspective, there has been a great deal o recent

interest in using NH3 as an alternative solvent with which to capture CO2. Obviously, beore

NH3 can be deployed in practice, a detailed knowledge o the phase behaviour o aqueous NH 3

mixtures and also the liquid phase behaviour o aqueous NH3 + CO2 mixtures is essential.

The NH3 + H2 mixture is a mixture o two associating uids o similar molecular weight, it

is completely miscible and does not exhibit azeotropy. One would thereore expect the unlikeinteractions in the system to be close to ideal. Consequently, the standard Lorentz-Berthelot

(LB) [58] combining rules should be an appropriate choice in this case. Unlike binary interaction

parameters were estimated by comparison with experimental data rom the triple-point, T t o

H2O to the critical point, T c o NH3. This estimation was perormed using the gPROMS sotware

package [59]. A sample o graphical results are provided in gure 4. The accuracy o this model

as dened by equation (13) and (14) is 1.857% in temperature and pressure and 0.026 in mole

raction as dened by equation (15). This mixture exhibits both positive and negative deviations

rom Raoult’s law as well as extensive ionic speciation, and it is gratiying to see this eature

reproduced with our model.

Ammonia ternary mixtures

The immediate industrial relevance o this work is in the arena o amine based CO2 capture

rom the ue gasses o ossil uel red power plants, so one obvious application o these results

is in the modelling, simulation and optimisation o such processes. Recently, there has been

a signicant amount o industrial interest in NH3 based CO2 capture processes [60–63], and

accurate thermophysical models o this system are necessary or the development o accurate

and predictive process models. However, the complexity associated with modelling this mixture

is compounded by the act that it is reactive, as opposed to simply associating. In modelling

the NH3+H2O+CO2 mixture, SAFT-VR intermolecular parameters describing the NH3+CO2

interactions were obtained using the experimental data presented by Goppert et al. [64].

Maurer [22] notes that i one is using a chemical-theory to calculate the phase equilibrium

o the reacting NH3+H2O+CO2 mixture, there are - in principle - 72 temperature dependent

binary interaction parameters which must be determined. It is unrealistic to assume that these

parameters can be determined by comparison with experimental VLE data, and as a result

13



sensitivity analyses must be perormed, and parameters o minor importance either estimated

or ignored. This urther level o approximation in the approach inevitably reduces the accuracyand predictivity o the models. In the SAFT approach, only ve temperature-independent

binary-interaction parameters are required, and reliable values or these parameters can be

obtained by tting to binary mixture VLE data. O these, only two need be determined by

comparison to ternary VLE data. A sample o calculation results at conditions relevant to CCS

processes are presented in gures 5 and 6. We note that the unlike interaction parameters or the

NH3+CO2+H2O mixture were tted to the data shown in gure 5, while the results presented

in gure 6 are predictions. Our simple, physical models predict the phase behaviour o this

complex mixture very accurately - the models developed or this mixture correlate and predict

the liquid phase CO2 loading to within 0.02.

3.1.2 Monoethanolamine based mixtures

In this section, a brie description o the development o a detailed SAFT-VR model o mo-

noethanolamine (MEA) is presented. In a recent publication [65], we describe in detail the

development o the SAFT-VR models o H2O, MEA and CO2, and readers are reerred here and

to reerences therein or a complete description o the methods employed in the development o

SAFT-VR molecular models.

Pure monoethanolamine

Here we present a model o MEA that explicitly considers that the hydroxyl – hydroxyl interac-

tion, the amine – amine interaction, the hydroxyl electron lone-pair – amine hydrogen and the

hydroxyl hydrogen – amine electron lone-pair interactions all have diferent hydrogen bond en-

ergies. Inevitably, this increases the number o intermolecular parameters required to model the

multiunctional nature o MEA, but one can exploit the molecular nature o the SAFT theory

to reduce the number o intermolecular parameters that have to be determined by transerringparameters rom other molecules with the same unctional groups: SAFT-VR models o ethanol

and ethylamine. In this way, we present a general methodology or the development o accurate,

predictive models o complex, multiunctional, associating molecules, and their mixtures with

other associating uids.

The model o MEA is characterised by twelve parameters: mMEA , σMEA , εMEA , λMEA,

εHBeH,MEA, rc;eH,MEA, εHBe∗H ∗,MEA, rc;e∗H ∗,MEA, εHBeH ∗,MEA, rc;eH ∗,MEA, εHBe∗H,MEA and rc;e∗H,MEA,

which results in a parameter estimation problem o much higher dimensionality than is usual

14



in SAFT-VR studies o associating systems. At this point, we take advantage o the physical

basis and transerability o parameters in SAFT (see or example the studies reported in re-erences [66, 67]) and propose to transer the association parameters describing the interaction

between the hydroxyl groups o the MEA molecules (represented by the e−H site-site interac-

tion: εHBeH,MEA, rc;eH,MEA) rom those obtained in a separate study or ethanol. Similarly, the

parameters related to the interaction between the amine groups o MEA (represented by the

e∗-H ∗ site-site interaction: εHBe∗H ∗,MEA, rc;e∗H ∗,MEA) are determined rom a separate study or

ethylamine. When these parameters or ethanol and ethylamine are transerred or the corre-

sponding interactions in MEA, the only association interactions that remain to be specied or

the MEA molecule are those or the cross amine-hydroxyl group association interactions. These

are represented by e∗-H and e-H ∗ site-site interactions characterised by εHBe∗H,MEA, rc;e∗H,MEA,

εHBeH ∗,MEA and rc;eH ∗,MEA. To reduce urther the number o parameters, we set the value o

the range o the association potential or the e-H ∗ and e∗-H interactions to be the same such

that rc;eH ∗,MEA=rc;e∗H,MEA. The %AAD (equation (10)) is not improved by using two diferent

values or rc;eH ∗,MEA and rc;e∗H,MEA. The proposed procedure has allowed us to reduce the

number o parameters to six (σMEA , εMEA , λMEA, εHBeH ∗,MEA, εHBe∗H,MEA and rc;eH ∗,MEA), no

more than or other SAFT-VR models.

The perormance o the nal model o MEA can be seen in gures 1 and 2. The predictions

obtained or the enthalpy and the surace tension (gures 8 and 9) in particular are in excellent

agreement with the experimental data [68–71]. It is striking to see how the set o selected

molecular parameters is able to quantitatively predict the surace tension values over a wide

range o temperatures and pressures. The AAD as dened by equation (10) or the MEA model

was 2.41% in saturated vapour pressure and liquid density. These results give added condence

in the adequacy o the model developed or the complex MEA molecule.

Aqueous MEA mixtures

A mixture o MEA and H2O modelled using the asymmetric model o MEA presented above

requires the determination o three adjustable unlike energy interaction parameters: the hy-

drogen bonding energy between water and the hydroxyl (εHBeH,MEA−H 2O

= εHBHe,MEA−H 2O

) and

amine (εHBe∗H,MEA−H 2O

= εHBH ∗e,MEA−H 2O

) groups o MEA, and the unlike dispersion interactions

between MEA and water εMEA−H 2O. In order to reduce the number o mixture parameters,

a transerable approach is proposed. The hydrogen-bonding interaction between the hydroxyl

group o MEA and water is transerred rom that o a mixture o ethanol and water and, simi-

larly, the hydrogen-bonding interaction between the amine group and water is transerred rom

15



a study o ethylamine and water.

In gure 10, three isotherms o the vapour-liquid equilibrium or MEA+H2O at T = 298.15,

343.15, 364.15 K are presented; the adequacy o the description can be clearly seen rom the

gure. The continuous lines represent calculations perormed with the asymmetric model o

MEA and the dashed lines represent calculations perormed with the symmetric model. The

accuracy o the models in describing the MEA+H2O mixture is %AAD=2.03% in temperature

and pressure and AAD=0.024 in vapour phase composition when using the asymmetric model

o MEA and %AAD=4.39% in temperature and pressure and AAD=0.008 in vapour phase

composition when using the symmetric model o MEA.

MEA ternary mixtures

Armed with the molecular models or pure component and binary mixtures developed in the

previous sections, we now come to a main goal o our work: the accurate representation o the

uid phase behaviour o carbon dioxide in aqueous MEA. Numerous studies o the thermophys-

ical properties o the MEA+CO2+H2O mixture have been reported to date. There are also a

substantial number o correlations which describe the vapour-liquid equilibria o this system.

The majority o these expressions are however applicable only over a limited range o composi-

tions and/or temperature and pressure. Outside the recommended range, these expressions are

typically inapplicable and are thereore o limited use in the design and optimisation o novel

processes incorporating these components. One major advantage o the SAFT approach is that

the parameters used in the models are temperature and pressure independent and thus there

is in principle no region in the uid range beyond description (with due caution taken in the

critical and near-critical regions). A caveat, however, in the context o the MEA+CO2+H2O

system, is that our models do not ully capture the various reaction mechanisms (we ocus on

the ormation o carbamate), so that use o the model ar outside the region where the models

are developed may not be reliable (e.g., in the limit o low water concentration).

In modelling MEA + CO2 + H2O, we examine data over a temperature range rom 298.15K to

373.15K, a pressure range rom 0.001MPa to 10MPa, and a liquid phase CO2 concentration o

0.01 ≤ xCO2≤ 0.12 [72–74]. We have used the data at 313 K to estimate the MEA–CO2 associ-

ation energy εHBe∗α,MEA−CO2

using the gPROMS sotware package [59] assuming that εMEA−CO2

is given by the Berthelot rule, i.e., kMEA−CO2= 0.0. Using these parameters we are able to

obtain and excellent description o the ternary system at these conditions and excellent quanti-

tative predictions o the ternary phase behaviour at 333 K and 335 K, with an AAD over the

three isotherms o 0.010 in liquid mole raction o CO2, or MEA represented as the asymmetric

16



model. This level o accuracy is in line with that presented in other contributions, or example

the recent work o Faramazi et al. [21]. We note that, unlike the many correlations that arecurrently available, our model captures the behaviour o the data over the entire composition

range or which data is available.

The results o our SAFT-VR calculations or the phase equilibrium o MEA+CO2+H2O are

summarised in gure 11. As can be seen, a complex, non-linear behaviour is seen or the partial

pressure o CO2 o the coexisting gas phase as a unction o the liquid phase CO2 mole raction

(the latter is a direct measure o the extent o absorption o CO2 in the amine solvent). This

behaviour is due to a complex system o competing interactions, and it is very encouraging to

see this behaviour reproduced so accurately with our simple physical models o the chemicalassociation. From gure 11, one can also see that, though the various correlations can be used

to provide a good description o the absorption, their use is not appropriate over wide ranges

o conditions. Further, in gure 11a we compare the results o using both the symmetric and

asymmetric models o MEA to predict the phase behaviour o this mixture. It can be seen that

while the asymmetric model ully captures the complex uid phase behaviour, the symmetric

model does not. This is because a ully symmetric model o MEA misrepresents the stoichiometry

o the corresponding reactions o this system, and results in a vapour phase consisting almost

entirely o water. Finally, we have ound that the inclusion o nitrogen (an essentially inert gas,

chemically speaking) in our SAFT-VR description does not modiy the phase behaviour o the

liquid phase appreciably. This accurate representation o the uid phase behaviour o MEA

+ CO2 + H2O (+N2) within our SAFT-VR platorm is o paramount importance or use in a

detailed description o the CO2 capture process. Again, our models predict the phase behaviour

o this complex mixture very accurately - the models developed or this mixture correlate and

predict the liquid phase CO2 mole raction with an accuracy o 0.0165 o CO2 mole raction in

the liquid phase.

3.1.3 2-Amino-2-methyl-1-propanol based mixtures

Following the results o our study o MEA, we proceed to build models o 2-amino-2-methyl-1-

propanol (AMP). Apart rom MEA, AMP is one o the most studied alkanolamine alternatives

or CO2 capture. This is because it is the sterically hindered orm o MEA, and thereore

diferences between the properties o AMP and MEA can unambiguously be ascribed to steric

efects. Given the results o the MEA work, we have a clear direction as to how to model AMP.

17



Pure AMP

A detailed model o AMP has been developed, preserving the molecular detail o the molecule

by once again considering an asymmetric model o this compound. In order to reduce model

complexity, all association parameters required to describe AMP are transerred rom the MEA

model. This is a reasonable decision, as both molecules are primary alkanolamines, and this is

consistent to group contribution approaches. Thus, AMP is modelled as having an aspect ratio

o 2.29, with the same association scheme as MEA. Again, results o the models developed or

AMP are presented in gures 1 and 2. The AAD as dened by equation (10) or the AMP model

was 0.29% in saturated vapour pressure and liquid density.

Aqueous AMP mixtures

Again, ollowing the MEA mixture modelling, we transer binary interaction parameters de-

scribing the unlike interactions between AMP and H2O rom the work on MEA. In this case,

an excellent description o the binary vapour-liquid equilibria is obtained without adjusting any

binary interaction parameters. The accuracy o this model as dened by equation (13) and (14)

is 0.42% in temperature and pressure and 0.006 in mole raction as dened by equation (15).

The transerable nature o the parameters developed to describe these complex mixtures is a

testament to the adequacy o our models and the rigourous physical basis o the SAFT approach.

Results o this work are provided in gure 12.

AMP ternary mixtures

Once again, it is necessary to develop models o AMP+CO2+H2O. We do this in a similar manner

to the MEA work. Results are presented in gure 13. We note that this is a prediction, with the

unlike interaction parameters describing the AMP+CO2 interactions having been obtained rom

a separate data set at T = 313.15K. This is a highly complex system, with numerous compenting

interactions, and a high accuracy is achieved with relatively simple physical interpretations o

these interactions that nevertheless account or the complex, non-linear behaviour o this system.

Again, our models predict the phase behaviour o this complex mixture very accurately - the

models developed or this mixture correlate and predict the liquid phase CO2 mole raction with

an accuracy o 0.02 o CO2 mole raction in the liquid phase.

18



3.1.4 Overview of incorporation of chemical reactions within the SAFT approach

We incorporate a description o the many interactions between the uid components at the level

o the thermodynamic model, using the SAFT ormalism to simultaneously mediate the efect

o the physical and chemical interactions in the uid. This approach acilitates a consistent,

physically based description o the numerous, competing interactions in both the gas and liquid

phases, giving ull consideration to all aspects o the non-ideality o this mixture. Moreover,

the SAFT approach allows implicit consideration o reaction products, i.e., when compounds

A and B react to orm a product C , the product is described in the SAFT-VR model as an

A-B dimer, possessed o thermophysical properties which are dened by the unlike interaction

parameters o components A and B. This both simplies the mass and energy balance equations

in the process model (i.e., there are no generation terms in these balance equations), and also

removes the requirement or an explicit description o the properties o the reaction products.

Finally, because reactions are incorporated in the physical description o the uid, we no longer

need to use enhancement actor concepts to describe the efects o chemical reaction on the

process behaviour. We are thereore no longer constrained by the availability o experimental

data on the rate equations in reacting systems. This constitutes a major advantage in modelling

systems comprising novel solvents where these experimental data are not available. A caveat to

this approach is that it may not be appropriate in systems which are not limited by the kineticso the chemical reaction occurring.

3.2 Process modelling and validation

3.2.1 Model development and validation

The model described in this section has been implemented using the commercial sotware package

gPROMS [59] using a SAFT-VR Foreign Object [75].

Reactive separation processes are highly studied, but some signicant challenges remain in de-

veloping predictive models o these processes. Principally, conventional models developed or

these processes require a large amount o experimental data to describe the efects o both the

physical interactions and chemical reactions on process behaviour. Further, so-called enhance-

ment actors are typically used to describe the accelerating efect o the reactions on the mass

transer. However, these expressions are theoretically exact only in a ew limiting cases, and

typically simplications or approximations are used in practice. Moreover, enhancement actor

19



expressions themselves require a lot o experimental inormation pertaining to the rate equations

and reaction kinetics associated with the system at hand. All this conspires to make predictivemodelling and solvent design dicult.

The SAFT-based approach which we have employed in our work signicantly simplies the

modelling o mass-transer limited reactive separation systems. In our model, reaction products

are implicitly considered in the thermodynamic model o the uid, as opposed to explicitly at the

level o the process model. This means less physicochemical properties are required to describe

the process behaviour. Moreover, there are ewer component balances required, and there are

no generation terms in the mass or energy balance equations. Finally, because o this, there is

no enhancement actor required to describe the efect o the reaction.

In order or us to have condence in the predictions o our model, we must ensure that it predicts

accurately temperature and composition proles along the length o the column, rather than

simply the conditions at the outlet o the column [76]. Thereore, we validate the predictions o

both our absorber and desorber models using published pilot plant data. To test the robustness

o the assumption o reaction equilibrium, we assess the adequacy o our model against both

MEA and AMP solvents, i.e., solvents which are considered to have both ‘ast” and “slow”

kinetics. Finally, we note that no adjustable parameters are used in the process model. The

results presented in this section are predictions.

For the absorber model presented in this paper, the required input to the model, in addition

to the column geometry and packing characteristics, the inlet gas phase pressure, temperature,

owrate and composition and the inlet liquid temperature, owrate and composition. The

validation o the proposed absorber model is perormed by comparison o the model predictions

with experimental data presented by Tontiwachwuthikul et al. [49] or the data presented or

runs T22 and T26. The results presented in gure 17 were obtained using an MEA solvent and

those results presented in gure 17 were obtained using an AMP based solvent solution. The

results o these investigations are shown in gures 16 - 17. These data were chosen as they have

previously been independently reproduced by other workers [9,37]. Good agreement is observed

between the measured and simulated column proles, particularly in light o the simplicity o

the proposed model. The accuracy o the predictions o our absorber model are in line with

other contributions in the literature. We emphasise the act that no enhancement actors were

used in this work, nor were any kinetic data (rate constants, reaction enthalpies etc) required.

Moreover, no retuning o model parameters or correlations was required in switching between

MEA and AMP solvents. On this basis, we consider that we have provided rigorous validation

20



o our assumptions, and that our model is robust. Consequently, we propose that this model

is a suitable initial point or the construction o a platorm or the solution o solvent designproblems in reactive separation systems.

In the case o the desorber model, in addition to the column geometry and packing character-

istics, the required inputs are the inlet liquid owrate, temperature, pressure and composition.

The inlet steam owrate and pressure are assigned in the model, and may be used to either

provide a given amount o energy to the system, or achieve a given temperature in the reboiler.

Finally, the cooling water owrate, inlet temperature and permissible temperature rise are as-

signed in order to speciy a desired condensate temperature or a given condenser duty. The

validation o the proposed desorber model is perormed by comparison o the model predictionso the liquid phase temperature prole with experimental data presented by Tobiesen et al. [77].

The predicted liquid phase temperature proles in the desorber column are in reasonably good

agreement with the experimental data and show the same linear temperature prole as the

temperature proles presented by Tobiesen et al. [77]. Some results or this process presented

in gure 18. In order to validate the energetic aspects o our desorber model, we compare the

reboiler duty and the extent o solvent regeneration obtained by supplying steam to the reboiler

in order to obtain a desired reboiler temperature. In order to obtain the experimental reboiler

temperature set point o 119.5oC, the model required that 10.5kW o energy be supplied which

achieved a lean loading o 0.25 moles o CO2 per mole o amine. These results compare well

with the reported values o 9.6kW to obtain a lean loading o 0.24 moles o CO 2 per mole o

amine. It is noted that due to the elevated temperatures at which the solvent regeneration

process operates, the assumption o reaction equilibrium is well accepted here. On this basis,

we consider the desorption process to be adequately validated and that we now have a suitable

platorm or carrying out process perormance indexed solvent design studies.

3.2.2 Initial solvent design study

Solvent blends, particularly those including sterically hindered compounds, are considered to be

an attractive approach to developing solvents or CO2 capture. Recently, blends o AMP (a slow

amine) and NH3 have been shown to be particularly promising when compared to a standard

30wt% MEA solvent [78,79]. Specically, this blend was presented as having reaction kinetics as

ast as an MEA solvent, but with a signicantly superior capacity or absorbing CO2. A 30wt%

AMP + 5wt% NH3 blend, denoted 30:5, has been suggested as promising. Our objective is to

use the proposed model to identiy an improved blend. To this end, we ormulate an objective

21



unction as ollows:

f Obj = AyCO2+ ByRNH 2 + LCp (17)

where A, B are weights, with A=6,000 and B=8,500; yCO2is the outlet mole raction o CO2

in the ue gas, yRNH 2 is the total outlet mole raction o amine in the ue gas (i.e., the sum

o the mole ractions o AMP and NH3); L is the ow rate o the rich solvent stream leaving

the absorption column in units o kmol/s; C p is the heat capacity o that stream in units o

kJ/kmol.K. The rst term is related to the emission o CO2 to the atmosphere, the second to

the emission o amine, and the third to the regeneration cost expressed in terms o the totalheat capacity o the rich solvent stream. A solvent design problem has been solved on the basis

o the proposed objective unction using the inlet temperature, T , and composition, xNH 3 and

xAMP o the lean solvent stream and the owrate L as design variables. The constraints include

a minimum water content o 50wt% or the lean solvent, to avoid corrosion problems due to the

presence o AMP. The results o the optimisation are compared to the best perormance that

can be achieved with the 30:5 blend, and are presented in gure 19. The optimal solvent blend

has an increased AMP content and a decreased NH3 content, a greater solvent ow rate, and a

reduced inlet temperature. Its perormance in terms o separation efectiveness is similar to that

o MEA: the mole raction o CO2 in the ue gas (yCO2) is 0.004 or MEA and 0.009 with the

optimal blend. Given these promising results, a more realistic objective unction must now be

developed, to account in more detail or the compromise between absorption efectiveness and

regeneration cost and to incorporate additional costs such as cooling the solvent to the desired

inlet temperature.

4 Conclusions

In this project, we have developed detailed molecular thermodynamic models or a range o

compounds o relevance to CO2 capture applications rom coal-red power-stations. These

thermodynamic models have been incorporated in a rigorous process model o a CO2 capture

process, whose perormance has been validated using published pilot plant data or a range

o solvents and operating conditions. Finally, some preliminary solvent design work has been

completed, with blends o AMP and NH3 having been identied as promising solvents or CO2

capture. A signicant part o this work has been the development o a novel approach or

22



modelling reactive separation processes, which makes the solution o solvent design problems or

theses systems much more tractable.

5 Proposed work or a subsequent programme

The models developed in this project have accurately accounted or uid phase reactions in the

case where there was only one reaction to consider, i.e., that between the amine and the CO2.

However, in real operations, it is possible that there will be multiple acidic components in a ue

gas, e.g., H2S and/or SOx. It would be o interest to investigate the suitability o the techniques

developed in this work to date to dealing with processes involving multiple, parallel reactions.

Further, an area which is now ready or investigation is detailed solvent design activities, using

a perormance index linked to the perormance o the entire CO2 capture process. It is possi-

ble to identiy solvent blends that minimise energy consumption or other objective unctions.

Additional research could also lead to the computer-aided design o novel solvent molecules.

However, one property which is currently beyond the reach o our models is the susceptibility

o amines to oxidative and other degradation. It is suggested that any rational solvent design

procedure should accurately account or this phenomenon. It would thereore be o interest to

develop a detailed, mechanistic understanding o the processes leading to solvent degradation,

and incorporate this in uture, process perormance indexed solvent design activities.

6 Publications arising rom the project

The ollowing conerence presentations and journal papers have been produced as a result o the

work done in this project.

Journal articles:

N. Mac Dowell, F. Llovell, C. S. Adjiman, G. Jackson, A. Galindo “Modelling the phase be-

haviour o the CO2 + H2O + MEA mixture using transerable parameters with the SAFT-VR

approach”, Accepted, Industrial and Engineering Chemistry Research, 2009

23



N. Mac Dowell, F. Llovell, A. Galindo, C. S. Adjiman, G. Jackson “Modelling the phase be-

haviour o CO2 +H2O + RNH2 mixtures with the SAFT-VR approach: a platorm or solventdesign”, To be submitted to Journal o Physical Chemistry B

F. Llovell, N. Mac Dowell, A. Galindo, F. Blas, G. Jackson “Study and prediction o interacial

properties o complex binary mixtures by means o a density unctional theory based on the

SAFT-VR equation o state”, To be submitted to Fluid Phase Equilibria

N. Mac Dowell, A. Galindo, C. S. Adjiman, G. Jackson “Modelling and design o MEA-based

CO2 capture processes: Combining advanced thermodynamics and rate-based models”, To be

submitted to Chemical Engineering Science

N. Mac Dowell, A. Galindo, C. S. Adjiman, G. Jackson “Modelling and design o AMP-based

CO2 capture processes: Combining advanced thermodynamics and rate-based models”, For sub-

mission to Energy and Fuels, In preparation

N. Mac Dowell, A. Galindo, C. S. Adjiman, G. Jackson “An integrated process and solvent

design platorm or CO2 capture rom low pressure gas”, For submission to AIChE Journal, In

preparation

N. Mac Dowell, F. Llovell, A. Galindo, C. S. Adjiman, G. Jackson “On the modelling o multi-

unctional molecules using transerable parameters with the SAFT-VR approach”, For submis-

sion to Fluid Phase Equilibria, In preparation

N. Mac Dowell, A. Galindo, C. S. Adjiman, G. Jackson, Buchard, A. P, Williams, C., Hallett,

J., Welton, T. and P. Fennell, “An overview o carbon capture technologies: State o the art

and uture perspectives”, To be submitted to Energy and Environmental Science

Conference presentations:

N. Mac Dowell, C. S. Adjiman, A. Galindo, G. Jackson,“Towards integrated solvent and process

24



design in amine-based processes or post-combustion CO2 capture” (talk), The International

Conerence on Coal Science and Technology (ICCST), 28th

- 31st

August 2007, NottinghamUniversity, Nottingham, UK

N. Mac Dowell, C. S. Adjiman, A. Galindo, G. Jackson,“Thermodynamic modelling o amine

solvents” (poster), Thermodynamics 2007, 26th-28th September 2007, IFP, Rueil-Malmaison,

Paris, France

N. Mac Dowell, C. S. Adjiman, A. Galindo, G. Jackson,“Improvements in amine ue gas scrub-

bing systems or coal red power stations” (talk), British Coal Utilisation Research Association,

Coal Research Forum (BCURA CRF) 4th June, 2008, Imperial College London, London, UK

N. Mac Dowell, C. S. Adjiman, A. Galindo, G. Jackson,“Modelling CO 2 capture in amine sol-

vents with an advanced association model: Process optimisation and a platorm or solvent

design” (talk), American Institute or Chemical Engineers (AIChE) 2008 Annual meeting, 16 th-

21st November 2008, Philadelphia, USA

N. Mac Dowell, C. S. Adjiman, A. Galindo, G. Jackson,“Amine ue gas scrubbing systems:

Integrating advanced thermodynamic modelling with sophisticated process simulation - an opti-

misation platorm” (poster), UK Carbon Capture and Storage Consortium (UKCCSC) meeting,

24th November 2008, IMechE, London, UK

N. Mac Dowell, C. S. Adjiman, A. Galindo, G. Jackson,“Advanced thermodynamic and process

modelling: Integration or amine scrubbing in post-combustion CO2 capture” (poster), Impe-

rial/Nature virtual conerence on Climate Change and CO2 Storage, Dec. 3, 2008, Available

rom Nature Precedings http://dx.doi.org/10.1038/npre.2008.2638.1 (2008)

N. Mac Dowell, C. S. Adjiman, A. Galindo, G. Jackson,“Model based optimisation o a mul-

ticomponent chemisorption process or CO2 capture: A solvent design platorm” (talk), The

5th Trondheim Conerence on CO2 Capture, Transport and Storage, 16-17 June, 2009, NTNU,

Trondheim, Norway

25





N. Mac Dowell, A. Galindo, G. Jackson, C. S. Adjiman,“The integrated design o solvent blends

and separation processes or CO2 capture rom ue gases” (talk), PPEPPD-12, Properties andPhase Equilibria or Product and Process Design, May 16th - 21st, 2010, Suzhou, Jiangsu, China

F. Llovell, N. Mac Dowell, G. Jackson, A. Galindo, F. J. Blas “Fundamentals, development

and application o DFT theories to a SAFT-type equation o state or the prediction o intera-

cial phenomena in complex mixtures” (talk), PPEPPD-12, Properties and Phase Equilibria or

Product and Process Design, May 16th - 21st, 2010, Suzhou, Jiangsu, China

27



Reerences

[1] Meeting the energy challenge A white paper on energy. Technical report, Department o

Trade and Industry, May 2007. www.berr.gov.uk/les/le39387.pd.

[2] IPPC. Intergovernmental panel on climate change, third assessment report. Technical re-

port, IPCC, 2001.

[3] B. Metz, O. Davidson, H. C. de Coninck, M. Loos, and L. A. Meyer. IPCC, 2006: IPCC

Special Report o Carbon Dioxide Capture and Storage. Prepared by Working Group

III o the Intergovernmental Panel on Climate Change . Cambridge University Press,

Cambridge, United Kingdom and New York, NY, USA, 2005.

[4] J. H. St Clair and W. F. Simister. Process to recover CO2 rom us gas gets rst large scale

tryout in Texas. Oil Gas J., 6:109–113, 1983.

[5] A. B. Rao and E. S. Rubin. A technical, economic and enviromental assessment o amine-

based CO2 capture technology or power plant greenhouse gas control. Environ. Sci.

Technol., 36(20):4467–4475, 2002.

[6] G. Astarita, D. W. Savage, and A. Biso. Gas Treating With Chemical Solvents . John Wiley

and Sons, New York, 1983.

[7] A. M. Wolsky, E. J. Daniels, and B. J. Jody. CO2 capture rom the ue gas o conventionalossil uel red power plants. Environ. Prog., 13:214–219, 1994.

[8] A. Giovanoglou, J. Barlatier, C. S. Adjiman, E. N. Pistokopoulos, and J. L. Cordiner.

Optimal solvent design or batch separation based on economic perormance. AIChE J.,

49(12):3095–3109, 2003.

[9] L. Kucka, I. Muller, E. Y. Kenig, and A. Gorak. On the modelling and simulation o sour

gas absorption by aqueous amine solutions. Chem. Eng. Sci., 58(16):3571–3578, 2003.

[10] W. P. M. van Swaaij and G. F. Versteeg. Mass transer accompanied with complex reversible

chemical reactions in gas-liquid systems: An overview. Chem. Eng. Sci., 47(13–14):3181–

3195, 1992.

[11] W. J. DeCoursey. Enhancement actors or gas absorption with reversible reaction. Chem.

Eng. Sci., 37(10):1483–1489, 1982.

[12] W. J. DeCoursey and R. W. Thring. Efects o unequal difusivities on enhancement actors

or reversible and irreversible reaction. Chem. Eng. Sci., 44(8):1715–1721, 1989.

[13] A. Gil-Villegas, A. Galindo, P.J. Whitehead, S.J. Mills, and G Jackson. Statistical asso-

ciating uid theory or chain molecules with attractive potentials o variable range. J.

28



Chem. Phys., 106(10), 1997.

[14] A. Galindo, L.A. Davies, Gil-Villegas, and G. Jackson. The thermodynamics o mixtures

and the corresponding mixing rules in the SAFT-VR approach or potentials o variable

range. Mol. Phys., 93(2):241–252, 1998.

[15] G. Astarita. Mass Transer With Chemical Reaction . Elsevier, London, 1967.

[16] H. Hikita, S. Asai, H. Ishikawa, and M. Honda. The kinetics o reactions o carbon diox-

ide with monoethanolamine, diethanolamine and triethanolamine by a rapid mixing

method. Chem. Eng. J., 13(1):7–12, 1977.

[17] P. V. Danckwerts. The reaction o CO2 with ethanolamines. Chem. Eng. Sci., 34(4):443–

446, 1979.

[18] S. S. Laddha and P. V. Danckwerts. Reaction o CO2 with ethanolamines: kinetics rom

gas-absorption. Chem. Eng. Sci., 3(36):479–482, 1981.

[19] D.E. Penny and T.J. Ritter. Kinetic study o the reactions between carbon dioxide and

primary amines. J. Chem. Soc., Faraday Trans. I., 79:2103–2109, 1983.

[20] P.M.M. Blauwhof, G.F. Versteeg, and W.P.M. van Swaaij. A study on the reaction between

CO2 and alkanolamines in aqueous solutions. Chem. Eng. Sci., 39(2):207–225, 1984.

[21] L. Faramarzi, G. M. Kontogeorgis, K. Thomsen, and E. H. Stenby. Extended UNIQUAC

model or thermodynamic modelling o CO2 absorption in aqueous alkanolamine solu-

tions. Fluid Phase Equilib., 282:121–132, 2009.

[22] G. Maurer. Phase equilibria in chemically reactive systems. Fluid Phase Equilib, 30:337–352,

1986.

[23] G. Maurer. Phase equilibria in chemical reactive uid mixtures. Fluid Phase Equilib, 116:39–

51, 1996.

[24] J.M. Prausnitz, R.N. Lichtenthaler, and E.G. de Azevedo. Molecular thermodynamics o

uid phase equilibria . Prentice Hall, 1999.

[25] E. A. Guggenheim. The statistical mechanics o regular solutions. Proc. R. Soc. Lond.,

Series A, 148(864):304–312, 1935.

[26] E. A. Guggenheim. The statistical mechanics o co-operative assemblies. Proc. R. Soc. Lond.

A, 169(936):134–148, 1938.

[27] G. S. Rushbrooke. A note on Guggenheim’s theory o strictly regular binary liquid mixtures.

Proc. R. Soc. Lond. A, 166(925):296–315, 1938.

29





[41] S. P. Tan, H. Adidharma, and M. Radosz. Recent advances and applications o statistical

associating uid theory. Ind. Eng. Chem. Res., 47(21):8063–8082, 2008.

[42] R. Taylor and R. Krishna. Multicomponent Mass Transer . Wiley, 1993.

[43] E. Y Kenig, R. Schneider, and A Gorak. Reactive absorption: Optimal process design via

optimal modelling. Chem. Eng. Sci., 56(2):343–350, 2001.

[44] R. Krishnamurthy and R. Taylor. A nonequilibrium stage model o multicomponent separa-

tion processes, Part I: Model description and method o solution. AIChE J., 31(3):449–

456, 1985.

[45] W. K. Lewis and W. G. Whitman. Principles o gas absorption. Ind. Eng. Chem.,

16(12):1215–1220, 1924.

[46] S. Hatta. On the absorption velocity o gases by liquids. Technical Reports rom Tohoku

Imperial University , 10:119–135, 1932.

[47] R. E. Treybal. Adiabatic gas absorption and stripping in packed towers. Ind. Eng. Chem.,

61(7):36–41, 1969.

[48] J. D. Pandya. Adiabatic gas absorption and stripping with chemical reaction in packed

towers. Chem. Eng. Commun., 19:343–361, 1982.

[49] P. Tontiwachwuthikul, A. Meisen, and Lim C. J. CO2 absorption by NaOH, mo-noethanolamine and 2-amino-2-methyl-1-propanol solutions in a packed column. Chem.

Eng. Sci., 47(2):381–390, 1992.

[50] E.Y. Kenig, R. Schneider, and A. Gorak. Rigorous dynamic modelling o complex reactive

absorption processes. Chem. Eng. Sci., 54(21):5195–5203, 1999.

[51] J. C. Charpentier. Multiphase chemical reactors Volume II - Design methods , chapter Gen-

eral characteristics o multiphase gas-liquid reactors: Hydrodynamics and mass transer,

pages 157–270. Alphen aan den Rijn, The Netherlands, 1981.

[52] A. E. Rodrigues, J. M. Calo, and N. H. Sween, editors. Multiphase Chemical Reactors

Volumne I - Fundamentals . Nato Advanced Study Institutes Series, 1980.

[53] A. E. Rodrigues, J. M. Calo, and N. H. Sween, editors. Multiphase Chemical Reactors

Volumne II - Design Methods . Nato Advanced Study Institutes Series, 1980.

[54] R. B. Bird, W. E. Stewart, and E. N. Lightoot. Transport Phenomena . Wiley, second

edition, 2007.

[55] G. Jackson, W. G. Chapman, and K. E. Gubbins. Phase equilibria o associating uids

spherical molecules with multiple bonding sites. Mol. Phys., 65(1):1–31, 1988.

31



[56] H. Thompson, J.C. Wasse, N.T. Skipper, C.A. Howard, D.T. Bowron, and A.K. Soper. The

structure o polaronic electron cavities in lithium-ammonia solutions. J. Phys.: Condens.Matter , 16:5639–5652, 2004.

[57] G. N. I. Clark, A. J. Haslam, A. Galindo, and G. Jackson. Developing optimal Wertheim-

like models o water or use in statistical associating uid theory (SAFT) and related

approaches. Mol. Phys., 104(22–24), 2006.

[58] J. S. Rowlinson and F. L Swinton. Liquids and Liquid Mixtures . Butterworth - Heinmann,

London, Third edition, 1982.

[59] PSE, 2007. http://www.psenterprise.com/.

[60] K. P. Resnik, J. T. Yeh, and H. W. Pennline. Aqua ammonia process or simultaneous

removal o CO2, SO2 and NOx. Int. J. o Environmental Technology & Management ,

4(1/2):89–104, 2004.

[61] R. Peltier. Alstom’s chilled ammonia CO2 capture process advances toward commercialisa-

tion. Power , 2008. Available rom: www.powermag.com/environmental/Alstoms chilled

ammonia CO2 capture process advances toward commercialization 86 p4.html.

[62] Chilling news or carbon capture. Mod. Power Syst., 26(12):17–18, 2006.

[63] A. C. Larsson. The chilled ammonia process by ALSTOM - Status o development. In The

5 th Trondheim conerence on CO 2 capture, transport and storage , 2009. Available rom:

www.energy.sinte.no/arr/CO2/2009/Presentations/A6-1.pd.

[64] U. Goppert and G. Maurer. Vapour - liquid equilibria in aqueous solutions o ammonia and

carbon dioxide at temperatures between 333 and 393 K and pressures up to 7 MPa.

Fluid Phase Equilib., 41(1–2):153–185, 1988.

[65] N. Mac Dowell, F. Llovell, C. S. Adjiman, G. Jackson, and A. Galindo. Modelling the

uid phase behaviour o carbon dioxide in aqueous solutions o monoethanolamine us-

ing transerable parameters with the SAFT-VR approach. Ind. Eng. Chem. Res. (Ac-

cepted)., 2009.

[66] A. Galindo, P. J. Whitehead, G. Jackson, and A. N. Burgess. Predicting the high-pressure

phase equilibria o water + n-alkanes using a simplied SAFT theory with transerable

intermolecular interaction parameters. J. Phys. Chem., 100(16):6781–6792, 1996.

[67] G. N. I. Clark, A. Galindo, G. Jackson, S. Rogers, and A. N. Burgess. Modeling and un-

derstanding closed-loop liquid-liquid immiscibility in aqueous solutions o poly(ethylene

glycol) using the SAFT-VR approach with transerable parameters. Macromolecules ,

41(17):6582–6595, 2008.

32



[68] D. Hope. Thermophysical data o pure substances. Data Compilation o Fiz Chemie Ger-

many , 1990.

[69] G. Vazquez, E. Alvarez, J. M. Navaza, R. Rendo, and E. Romero. Surace tension o binary

mixtures o water + monoethanolamine and water + 2-amino-2-methyl-1-propanol and

tertiary mixtures o these amines with water rom 25 C to 50 C. J. Chem. Eng. Data ,

42(1):57–59, 1997.

[70] K. Moerke and T. Roscher. Determination o the surace tension o some ethyleneamines.

Leuna protocol , 1982.

[71] G. Liessmann, W. Schmidt, and S. Reifarth. Recommended thermophysical data. Data

compilation o the Saechsische Olefnwerke Boehlen Germany , 1995.

[72] J. I Lee, F. D. Otto, and A. E. Mather. Equilibrium between carbon dioxide and aqueous

monoethanolamine solutions. J. Appl. Biotechnol., 26(10):541–549, 1976.

[73] F. Y Jou, A. E. Mather, and F. D. Otto. The solubility o CO2 in a 30 mass percent

monoethanolamine solution. Can J. Chem. Eng., 73(1):140–147, 1995.

[74] R. Dugas. Pilot plant study o carbon dioxide capture by aqueous monoethanolamine.

Master’s thesis, The University o Texas at Austin, 2006.

[75] N. M. P. Kakalis, A. I. Kakhu, and C. C. Pantelides. Ecient solution o the associationterm equations in the statistical associating uid theory equation o state. Ind. Eng.

Chem. Res., 45(17):6056–6062, 2006.

[76] R. Taylor. (Di)Still modelling ater all these years: A view o the state o the art. Ind. Eng.

Chem. Res., 46(13):4349–4357, 2007.

[77] F. A. Tobiesen, O. Juliussen, and H. F. Svendsen. Experimental validation o a rigorous

desorber model or CO2 postcombustion capture. Chem. Eng. Sci., 63:2641–2656, 2008.

[78] W. J. Choi, B. M. Min, B. H. Shon, J. B. Seo, and K. J. Oh. Characteristics o absorp-

tion/regeneration o CO2-SO2 bunary systems into aqueous AMP+ammonia solutions.

J. Ind. Eng. Chem., 2009. In Press.

[79] W. J. Choi, J. B. Seo, S. Y. Jang, J. H. Jung, and W. J. Oh. Removal characteristics o

CO2 using aqueous AME/AMP solutions in the absorption and regeneration process. J.

Env. Sci., 21:907–913, 2009.

[80] D. A. Fletcher, R. F. McMeeking, and D. Parkin. The United Kingdom Chemical Database

Service. J. Chem. In. Comput. Sci., 36(4):746–749, 1996.

33



[81] D. Silkenbaeumer, B. Rump, and R. N. Lichtenthaler. Solubility o carbon dioxide in aque-

ous solutions o 2-amino-2-methyl-1-propanol and n-methyldiethanolamine and theirmixtures in the temperature range rom 313 to 353 K and pressures up to 2.7 MPa. Ind.

Eng. Chem. Res., 38(8):3133–3141, 1988.

34





7 Contour plot or the relative average absolute deviation (%AAD) o the vapour

pressure and saturated liquid density determined using the SAFT-VR equation o state with the asymmetric model o MEA. At each point on the surace, the dis-

persion εMEA/k and sel-cross-association εHBeH,MEA/k and εHB

e∗H ∗,MEA/k energies

are xed, and the size (σMEA) and range (λMEA) parameters are optimised by

minimising the least-squares objective unction or 376 points between the triple-

point temperature to 90% o the critical point. The optimal model on this surace

corresponds to %AAD P Sat + ρl = 2.41%. Only the relevant section o the entire

parameter space explored is depicted. . . . . . . . . . . . . . . . . . . . . . . . . 45

8 Experimental data (squares) [80] or the enthalpy o vaporisation ΔH vap o MEAcompared with SAFT-VR predictions or the asymmetric model (continuous curve). 46

9 Experimental data (squares) [80] or vapour-liquid interacial tension o MEA

compared with SAFT-VR predictions or the asymmetric model (continuous curve). 47

10 Isotherms o the pressure-composition (P −x) vapour-liquid equilibria o MEA+H2O

compared with SAFT-VR calculations with both the symmetric and asymmetric

models o MEA. The continuous curves are the calculations with the asymmet-

ric model o MEA and the dashed line curves those with the symmetric model

o MEA. Three representative temperatures are shown:, T = 298.15 K; ◦,

T = 343.15 K; ♦, T = 363.15 K. The symbols correspond to the experimen-

tal data [80] and the curves to the corresponding SAFT-VR description. . . . . 48

11 Isothermal projections o the pressure-composition (P x) vapour-liquid equilibria

o the ternary mixture MEA+CO2+H2O compared with SAFT-VR description:

a) T = 313.15 K, b) T = 333.15 K, and c) T = 353.15 K. The thick continu-

ous curves correspond to SAFT-VR calculations with the asymmetric model o

MEA, and the thick dashed curve in a) to SAFT-VR calculations with the sym-metric model o MEA. In all gures, the thin continuous curves corresponds to

a correlation presented by Aboudheir et al. [36] and the thin dashed curve cor-

responds to a correlation presented by Gabrielsen et al. [35] The symbols denote

the experimental data: correspond to the data o Jou and Mather [73]; ♦ and

correspond to the data o Dugas [74]; ◦ correspond to the data o Lee et al. [72] 49

36





19 Predicted temperature and composition proles or an industrial scale absorption

column a) Liquid phase temperature prole b) Gas phase CO2 concentrationprole c) Liquid phase CO2 loading prole. The continuous curves correspond

to a 30wt% MEA solvent, the dotted curves correspond to a 30wt% AMP +

5wt%NH3 solvent blend and the dashed curves correspond to an optimised solvent

blend comprising 37.7wt% AMP and 1.96wt% NH3 mixture. . . . . . . . . . . . . 56

38





0 0.01 0.02 0.03 0.04 0.05100

200

300

400

500

600

700

800

ρ /mol cm-3

T / K

MEANH

3AMP

Figure 2: Experimental data (squares) [80] or the vapour-liquid coexistence densities, ρ o NH3,

AMP and MEA are compared with the SAFT-VR description or the models o these molecules

(continuous curves)

40



150 200 250 300 350 400 4500

5

10

15

20

25

30

Δ H f g

/ k J m o l - 1

T /K

150 200 250 300 350 400 450

0

20

40

60

80

γ / m N m - 1

T /K

a)

b)

Figure 3: a)Experimental data (squares) [80] or the enthalpy o vapourisation o NH3, ΔH NH 3fg ,

are compared with the SAFT-VR description or the models o these molecules (continuous

curves), b)Experimental data (squares) [80] or the vapour-liquid interacial tension o NH3,

γ NH 3 ,are compared with the SAFT-VR description or the models o these molecules (continuous

curves)

41



0 0.2 0.4 0.6 0.8 10

0.5

1

1.5

2

2.5

3

xH

2O

P / M P a

Figure 4: Isotherms o the pressure-composition (P − x) vapour-liquid equilibria o NH3+H2O

compared with SAFT-VR models o NH3. The symbols correspond to the experimental data at

T =333.15K [80] and the curves to the corresponding SAFT-VR description.

42



0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

1.4

θCO

2

P / M P a

Figure 5: Isothermal projection o the pressure-loading (P − x) vapour-liquid equilibria o the

ternary mixture o NH3+H2O+CO2, where θ is dened as xCO2/xNH 3. The symbols corre-

spond to the experimental data at T =333.15K and mNH 3 = 0.591 [64] and the curves to the

corresponding SAFT-VR description. This data set was used to obtain the NH3+CO2 binary

interaction parameters.

43



0.2 0.4 0.6 0.8 1 1.20

0.2

0.4

0.6

0.8

1

1.2

1.4

θCO

2

P / M P a

Figure 6: Isothermal projections o the pressure-composition (P − x) vapour-liquid equilibria

o the ternary mixture o NH3+H2O+CO2, where θ is dened as xCO2/xNH 3. The symbols

correspond to the experimental data at T =353.15K and mNH 3 = 0.591 [64] and the curves to

the corresponding SAFT-VR description. These results are a prediction, not a correlation.

44



900

1000

1100

1200

1300

200

300

400

500400

450

500

550

600

650

700

εHB

eH*,MEA /k /K

εMEA

/k /K

ε H B

e * H , M E A

/ k / K

%AAD

2

3

4

5

6

7

8

9

10

Figure 7: Contour plot or the relative average absolute deviation (%AAD) o the vapour pres-

sure and saturated liquid density determined using the SAFT-VR equation o state with the

asymmetric model o MEA. At each point on the surace, the dispersion εMEA/k and sel-cross-association εHB

eH,MEA/k and εHBe∗H ∗,MEA/k energies are xed, and the size (σMEA) and range

(λMEA) parameters are optimised by minimising the least-squares objective unction or 376

points between the triple-point temperature to 90% o the critical point. The optimal model on

this surace corresponds to %AAD P Sat + ρl = 2.41%. Only the relevant section o the entire

parameter space explored is depicted.

45



0 200 400 600 8000

200

400

600

800

1000

1200

Δ

H v a p

/ k J k g - 1

T /K

Figure 8: Experimental data (squares) [80] or the enthalpy o vaporisation ΔH vap

o MEA

compared with SAFT-VR predictions or the asymmetric model (continuous curve).

46



200 300 400 500 600 700 8000

10

20

30

40

50

60

γ / m N m - 1

T /K

Figure 9: Experimental data (squares) [80] or vapour-liquid interacial tension o MEA com-

pared with SAFT-VR predictions or the asymmetric model (continuous curve).

47



0 0.2 0.4 0.6 0.8 10

0.02

0.04

0.06

0.08

xH

2O

P / M P a

Figure 10: Isotherms o the pressure-composition (P −x) vapour-liquid equilibria o MEA+H2O

compared with SAFT-VR calculations with both the symmetric and asymmetric models o MEA.

The continuous curves are the calculations with the asymmetric model o MEA and the dashed

line curves those with the symmetric model o MEA. Three representative temperatures are

shown:, T = 298.15 K; ◦, T = 343.15 K; ♦, T = 363.15 K. The symbols correspond to the

experimental data [80] and the curves to the corresponding SAFT-VR description.

48



0 0.02 0.04 0.06 0.08 0.1 0.12 0.1410

-5

100

105

xCO

2

P C O

2 / k P a

0 0.02 0.04 0.06 0.08 0.1 0.1210

-5

100

105

xCO

2

P C O

2 / k P a

0 0.02 0.04 0.06 0.08 0.1 0.12

100

105

xCO

2

P C O

2 / k P a

a)

c)

b)

Figure 11: Isothermal projections o the pressure-composition (P x) vapour-liquid equilibria o

the ternary mixture MEA+CO2+H2O compared with SAFT-VR description: a) T = 313.15 K,

b) T = 333.15 K, and c) T = 353.15 K. The thick continuous curves correspond to SAFT-

VR calculations with the asymmetric model o MEA, and the thick dashed curve in a) to

SAFT-VR calculations with the symmetric model o MEA. In all gures, the thin continuous

curves corresponds to a correlation presented by Aboudheir et al. [36] and the thin dashed

curve corresponds to a correlation presented by Gabrielsen et al. [35] The symbols denote the

experimental data: correspond to the data o Jou and Mather [73]; ♦ and correspond to the

data o Dugas [74]; ◦ correspond to the data o Lee et al. [72]

49





0 0.5 1 1.5 210

-3

10-2

10-1

100

101

102

θCO

2

P / M P a

Figure 13: Ternary VLE calculations or the AMP+CO2+H2O mixture compared with exper-

imental data. The continuous lines correspond to SAFT-VR calculations and the symbols ()

to the experimental data o [81] at a constant temperature o T = 353.15 K

51



Figure 14: Evolution o model complexity, taken rom Kenig et al. [43]

Figure 15: Representation o column stage

52



0 5 10 15 20 25280

290

300

310

320

330

340

T ( K )

Stage

0 5 10 15 20 25

0

0.05

0.1

0.15

0.2

y C O

2

Stage

0 5 10 15 20 250

0.1

0.2

0.3

0.4

0.5

θ C O 2

Stage

c)

a) b)

Figure 16: a) Liquid phase temperature prole or absorber column, b) Gas phase CO2 concen-

tration prole or absorber column, c) Liquid phase CO2 loading prole or absorber column.

The continuous curves correspond to the predictions o our model, and the symbols correspond

to pilot plant data obtained rom run T22 in [49]. Stage 1 corresponds to the top o the column,

and stage 25 to the bottom. An MEA solvent is used.

53



0 5 10 15 20 25280

290

300

310

320

330

340

T ( K )

Stage

0 5 10 15 20 25

0

0.05

0.1

0.15

0.2

y C O

2

Stage

0 5 10 15 20 250

0.1

0.2

0.3

0.4

0.5

θ C O 2

Stage

a) b)

c)

Figure 17: a) Liquid phase temperature prole or absorber column, b) Gas phase CO2 concen-

tration prole or absorber column, c) Liquid phase CO2 loading prole or absorber column.

The continuous curves correspond to the predictions o our model, and the symbols correspond

to pilot plant data obtained rom run T26 in [49]. Stage 1 corresponds to the top o the column,

and stage 25 to the bottom. An AMP solvent is used.

54



0 5 10 15 20 25350

360

370

380

390

400

T ( K )

Stage

Figure 18: Liquid phase temperature prole or NTNU desorber rom [77]. The continuous

curves correspond to the predictions o our model, and the symbols correspond to pilot plantdata. Stage 1 corresponds to the top o the column, and stage 25 to the bottom.An MEA solvent

is used.

55



0 5 10 15 20 25280

300

320

340

360

T ( K )

Stage

0 5 10 15 20 250

0.05

0.1

0.15

0.2

y C O

2

Stage

0 5 10 15 20 250

0.2

0.4

0.6

0.8

θ C O

2

Stage

Figure 19: Predicted temperature and composition proles or an industrial scale absorption

column a) Liquid phase temperature prole b) Gas phase CO2 concentration prole c) Liquid

phase CO2 loading prole The continuous curves correspond to a 30wt% MEA solvent the

Date post:	03-Apr-2018
Category:	Documents
Upload:	vijaya-sarathi-uppala
View:	215 times
Download:	0 times

b82 Final Report

Documents