Introduction of a Novel Two-Dimensional Equation of State to Predict Gas Equilibrium Adsorption in Highly-Nonideal Systems

Rahimi, Abdolazim; Talaie, Mohamad Reza

doi:10.22108/gpj.2018.100147.1004

Introduction of a Novel Two-Dimensional Equation of State to Predict Gas Equilibrium Adsorption in Highly-Nonideal Systems

Authors

¹ Department of Chemical Engineering, College of Engineering, University of Isfahan, Isfahan, Iran

² Department of Chemical Engineering, College of Engineering, University of Isfahan, Isfahan, Iran Department of Chemical Engineering, School of Chemical, Petroleum and Gas Engineering, Shiraz University, Shiraz, Iran

10.22108/gpj.2018.100147.1004

Abstract

Abstract
The accurate calculations of adsorption equilibrium for multicomponent gas systems are of great importance in many applications. In this paper, five two-dimensional equations of state 2D-EOS, i.e. Van der Waals, Eyring, Zhou-Ghasem-Robinson, Soave-Redlich-Kwong and Peng-Robinson, were examined to find out their abilities to predict adsorption equilibrium for pure and multi-component gas adsorption systems. Also, a new 2D-EOS named Rahimi-Talaie (RT) was developed for accurately predicting adsorption equilibrium of the gas mixtures having highly non-ideal behavior. The pure parameters of all these equations were obtained by fitting 2D-EOS into pure gas-adsorption equilibrium data, and then the mixture parameters were calculated by recommended mixing rules. It was concluded that all equations were capable of accurately predicting pure adsorption equilibrium. However, among the six above-mentioned 2D-EOSs, RT was more successful to provide more accurate prediction of gas-mixture adsorption equilibrium, especially for the mixture showing azeotrope behavior.

Keywords

20.1001.1.23223251.2017.5.2.2.7

Full Text

Introduction

The prediction of adsorption equilibrium plays a crucial part in an adsorption bed design. One of the most important approaches to calculate gas adsorption equilibrium is using two-dimensional equations of state. Many attempts have been made to develop two-dimensional equations of state and apply them to perform gas adsorption equilibrium calculations. Hill (1946) described a systematic thermodynamic treatment for mobile and monolayer adsorption of gas mixtures on homogeneous surfaces. They defined a surface fugacity for each component and they have utilized Van der Waals (VDW) EOS to predict adsorption equilibrium for binary gas mixtures [1]. Payne et al. (1968) derived a two-dimensional equation of state from the Hirschfelder-Eyring modification of VDW and applied it to predict high pressure adsorption equilibrium of pure and mixed hydrocarbons on charcoal [2]. Friederich and Mullins (1972) have used VDW to predict adsorption equilibrium of a mixture of hydrocarbons on carbon black [3]. Patrekiejew et al. (1977) have developed the two-dimensional forms of Eyring, Redlich-Kwong (RK) and Peng-Robinson (PR) EOSs using statistical mechanics [4]. Konno et al. (1985) have obtained an isotherm equation by modifying PR EOS [5]. Zhou (1994) introduced a general two-dimensional equation of state (ZGR) and derived the fugacity equations to describe the adsorbed phase for adsorption from gas mixtures [6]. The results of ZGR has been compared with those of multicomponent Langmuir model and ideal solution theory and found out that ZGR produced better results in multicomponent gas adsorption systems. Zheng et al. (1998) proposed a modified two-dimensional VDW EOS model for the prediction of multicomponent gas adsorption isotherms from corresponding single-component adsorption equilibrium data. Then, they employed this equation to predict adsorption isotherms of CO–CO₂ mixtures and CO₂–N₂ mixtures on Cu(I)–NaY zeolite [7]. Pan (2004) applied 2D EOS of ZGR and PR using new mixing rules to predict the adsorption of pure gas and several binary mixtures of gases on a carbon bed utilizing. A new computational algorithm has been developed for this purpose [8]. Fitzgerald et al. (2005) employed 2D-EOS of ZGR to predict the adsorption of a mixture of gases on wet Tiffany coal [9]. In that work, a modified form of Van der Waals equation was developed by adding a new term. The four key parameters of this equation were obtained based on fitting to adsorption equilibrium data of pure gases using nonlinear regression method. In addition, the results of this equation are compared with those of VDW, Eyring, ZGR, SRK and PR for adsorption equilibrium of several pure and binary systems. The main objective of the present study is to compare the results obtained by two-dimensional EOS of VDW, Eyring, ZGR, SRK and PR in predicting equilibrium adsorption of pure gases and the mixtures of gases. The sets of experimental data on pure and mixture gas adsorption found in literature were introduced in tables 2 and 3. Also, it was intended to develop a powerful 2D-EOS which is capable of producing more accurate results for predicting equilibrium adsorption of highly non-ideal gas mixtures.

Development of RT 2D EOS

The following general 2D EOS can be developed from three-dimensional equations of state (3D EOS) [10]:


	(1)

Where π, A, T, R and w are spreading pressure, surface area of the adsorbent, absolute temperature, universal gas constant and the material amount adsorbed per mass of adsorbent. α and β are two parameters of this equations. Applying different values of U, W and m, which are mentioned in table 1, one can generate different types of 2D-EOSs.

Table 1. The values of W, U and m for generating different types of EOSs.

w	U	m	2D-EOS
0	0	0	VDW
0	0		Eyring
0	0		ZGR
0	1	1	SRK
-2	1	1	P-R

VW equation can be obtained by using the following equation for :

(2)

In the right-hand side of the above equation, the first and second terms show repulsive and attractive energy of adsorption. By investigating equilibrium adsorption of different systems employing VDW, It was revealed that repulsive term is under-predicted and the attractive term is over-predicted overall. Thus, in order to modify these terms, the following corrections were added to the right-hand side of equation 32:


	(3)
	(4)

Where λ is an additional parameter of the new 2D EOS. Using these two terms, the best results were obtained amongst the numerous different terms tested. As a result, the following equation was obtained for the term :


	(5)

The main difference between RT and VDW is the addition of the third parameter of λ.

Mixing rule

For RT equation the following common mixing rule were applied [11]:

	(6)
	(7)
	(8)
	(9)
	(10)

Where are mole fractions of the components i and j, and are the binary correction factors which can be determined by fitting the results into mixture experimental data. However, in this study these parameters were set equal to zero. Also α, β and λ are the mixture parameters and α_i, β_i, and λ_i are the pure parameters of the 2D EOS.

Fugacity coefficients in adsorbed phase

The fugacity coefficient relation can be derived using the following thermodynamic equation [11]:


	(11)

Where Z_a is the compressibility factor for two-dimensional adsorbate phase which is defined as follows:

(12)

Where a is defined as:

(13)

Using the above equations the following general relations for mixture fugacity coefficient of the new EOS were found:

(14)

Where Q₁, Q₂ and δ are:

	(15)

(16)
	(17)

The term w_j in the above equations denotes the mass of component j in the adsorbate-phase mixture. It should be differentiated from w_jj which is the mass of component j in the pure adsorbate phase. The fugacity coefficient relations for pure components were obtained by taking i=j=1 in the equations, as follows:


	(18)

Where and w_iiare Fugacity coefficient and the mass of component i in the pure adsorbed phase.

For :	(19)

	(20)
	(21)
For :	(22)
	(23)

Equilibrium calculation for pure-component system

The equilibrium relation for pure component is in the following form:

(24)

Where isfugacity of component i in the pure gas phase. Also, k_i is the henry’s constant for single-component adsorption which is the ratio of at very low pressures (P→0).

Taking logarithm from both sides of equation 24 yields:


	(25)

Substituting the relation for pure component fugacity coefficient in adsorbed phase gives:

(26)

Knowing the values of temperature, pressure and also the parameters of α_i, β_i, k_i and λ_i, one can determine the total amount of the adsorbed phase (w_ii). The fugacity of pure component i in gas phase, , was calculated using 3D PR equation of state.

Determination of optimum parameters

In order to determine single-component parameters,α_i, β_i, k_i and λ_i, the adsorption equilibrium several sets of experimental data found in literature for pure component adsoprtion on a particular adsorbents were used as shown in tables 2 and 3. These parameters were calculated by fitting w_iidetermined by the 2D EOS to the experimental data for the pure systems. Then, using the mixing rules one can find the EOS parameters for a multicomponent system with a given composition.

Equilibrium calculation for a multi-component system

The equilibrium relations used in equilibrium adsorption calculations of a multi-component system are:

(27)

Where N_C is the number of components. Knowing temperature, pressure and composition one can determine gas-phase composition {y_i} and adsorbed –phase composition {w_i}. Determining the multi-component parameters of α, β and λ using the mixing rules one can calculate (using equation 14) and , which is the fugacity of component i in the gas-phase mixture (using 3-D PR). Substituting these values into the set of equilibrium relations (equation 27), the following system of Nc equations for N_C variables which are the amount of each component in adsorbed mixture (w_i) was obtained:

(28)

Solving the above using the iterative Newton numerical method equations one can determine the mass of each component in the adsorbed mixture (w_i).

Result and Discussion

The adsorption equilibrium data predicted by new 2-D EOS (RT) were compared to the ones collected from literature. In order to conduct equilibrium calculations for a multi-component system, the parameters of single component adsorption of all respective constituents are required. It means that a set of adsorption equilibrium data for a multi-component system on a specific adsorbent cannot be employed until the single-component equilibrium data of all components on that particular adsorbent are available. These data are necessary to find the single-component parameters. This fact created a huge restriction on the adsorption equilibrium data released in literature. In this regard, the appropriate sets of data were collected by an extensive literature survey. In this study, 24 sets of pure-component data containing 441 equilibrium points and 15 sets of binary data comprising 175 equilibrium points were used to compare the performances of different 2-D EOSs. Table 4 compares the predictions of various 2-D EOSs with each other and reported their respective relative average deviations (%RAD) which are defined as:

(29)

Where and are the calculated and experimental amount of adsorbed phase of pure component i respectively.

Table 2. The comparison of relative average deviations in predicting single-component adsorption equilibrium data using various 2-D EOSs.

*Ref*	T(K)	Adsorbate	Adsorbent	*%RAD*						NP	System
*Ref*	T(K)	Adsorbate	Adsorbent	R-T	P-R	SRK	ZGR	EYRING	VDW	NP	System
[12]	298.15	i-C₄H₁₀	13X	2.88	2.92	2.94	2.84	2.86	2.90	16	1
[12]	298.15	C₂H₄	13X	3.61	4.69	4.75	4.08	4.55	5.04	30	2
[12]	323.15	i-C₄H₁₀	13X	1.48	1.47	1.48	1.67	1.59	1.48	16	3
[12]	323.15	C₂H₄	13X	2.77	2.67	2.66	2.99	2.77	2.70	25	4
[12]	298.15	C₂H₆	13X	1.97	3.46	3.32	4.61	2.32	2.92	31	5
[12]	323.15	C₂H₆	13X	2.63	2.77	2.67	3.00	1.75	2.47	20	6
[12]	298.15	CO₂	13X	2.69	4.84	5.06	4.11	4.87	5.44	20	7
[12]	323.15	CO₂	13X	2.69	2.56	2.56	3.00	2.77	2.65	17	8
[13]	300	CH₄	13X	0.54	0.52	0.53	4.07	1.95	0.54	18	9
[13]	300	C₃H₈	13X	1.83	1.86	1.74	2.36	1.74	2.57	15	10
[13]	300	CH₄	5A	4.00	3.94	3.95	4.63	3.94	3.95	18	11
[13]	300	C₂H₆	5A	0.82	1.23	1.18	2.26	1.21	0.91	15	12
[13]	300	C₃H₈	5A	5.58	5.74	5.65	5.23	5.34	6.13	12	13
[14]	293	CO₂	13X	2.11	1.98	2.44	2.20	2.59	3.81	38	14
[14]	293	C₂H₆	13X	0.55	1.64	1.43	2.90	1.28	0.76	30	15
[15]	423	C₃H₈	4A	2.37	1.99	2.15	6.67	4.35	2.44	5	16
[15]	423	C₃H₆	4A	2.99	3.01	3	3.21	3.06	2.99	20	17
[15]	473	C₃H₈	4A	2.25	2.24	2.24	2.50	2.12	2.25	5	18
[15]	473	C₃H₆	4A	2.70	2.78	2.76	3.68	3.06	2.71	18	19
[16]	298	O₂	10X	0.51	0.50	0.50	0.59	0.53	0.50	19	20
[16]	298	N₂	10X	0.26	0.33	0.34	0.25	0.30	0.35	19	21
[17]	298	CH₄	Norit R1	.49	1.64	1.82	3.12	0.60	2.04	12	22
[17]	298	N₂	Norit R1	.69	0.76	0.79	5.18	2.03	.84	10	23
[17]	298	CO₂	Norit R1	1.63	2.87	3.07	3.28	1.58	3.36	12	24
----	----	----	----	2.09	2.51	2.54	3.14	2.47	2.67	441	TOTALL

Table 3. The comparison of relative average deviations in predicting multi-component adsorption equilibrium data using various 2-D EOSs.

Quantities	P (KPa)	T (K)	Adsorbent	Adsorbate	NAME

wi	137.8	298.15	13X Zeolite	i-C₄H₁₀(1)-C₂H₄(2)	A
w
wi	137.8	323.15	13X Zeolite	i-C₄H₁₀(1)-C₂H₄(2)	B
w
wi	137.8	298.15	13X Zeolite	i-C₄H₁₀(1)-C₂H₆(2)	C
w
wi	137.8	323.15	13X Zeolite	i-C₄H₁₀(1)-C₂H₆(2)	D
w
wi	137.8	298.15	13X Zeolite	C₂H₄(1)-CO₂(2)	E
w
wi	137.8	323.15	13X Zeolite	C₂H₄(1)-CO₂(2)	F
w
wi	345	300	13X Zeolite	CH₄(1)-C₃H₈(2)	G
w
wi	345	300	5A Zeolite	CH₄(1)-C₂H₆(2)	H
w
wi	345	300	5A Zeolite	C₂H₆(1)-C₃H₈(2)	I
w
wi	101.3	293	13X Zeolite	CO₂ (1)-C₂H₆(2)	J
w
wi	84.61-98.41	423	4A Zeolite	C₃H₆(1)-C₃H₈(2)	K
w
wi	102.93-118.99	473	4A Zeolite	C₃H₆(1)-C₃H₈(2)	L
w
wi	6.38-28.65	298	10X Zeolite	O₂(1)-N₂(2)	M
w
w_i	151-5975	298	Activated carbon	CH₄(1)-N₂(2)	N
w
w_i	98-5916	298	Activated carbon	CH₄(1)-CO₂(2)	O
w
wi	OVERALL
w

ref	NP	R-T	PR	SRK	ZGR	Eyring	VDW
ref	NP	*%RAD*
[12]	10	5.69	19.77	22.25	22.70	23.35	24.65
[12]	10	2.20	3.21	3.54	3.50	3.70	3.86
[12]	8	5.24	9.80	16.99	10.30	9.25	8.28
[12]	8	2.52	4.32	3.71	4.29	4.62	3.97
[12]	10	32.21	49.51	44.03	38.16	36.54	37.43
[12]	10	6.07	6.69	6.79	6.77	6.38	6.38
[12]	7	22.51	34.24	33.24	30.04	29.81	31.57
[12]	7	5.39	4.03	3.97	4.86	4.03	4.25
[12]	6	12.70	20.57	15.36	9.67	10.24	11.51
[12]	6	1.06	8.03	5.82	3.18	4.00	5.72
[12]	5	8.64	17.13	14.06	18.84	8.87	9.04
[12]	5	1.25	5.75	4.20	1.24	1.55	3.00
[13]	8	26.95	50.97	50.91	18.45	26.67	43.94
[13]	8	3.41	1.90	1.71	3.88	2.99	1.68
[13]	27	14	14.77	14.18	13.45	13.71	13.90
[13]	27	6.04	8.35	7.64	6.06	6.24	6.62
[13]	16	22.32	19.88	20.72	21.40	21.33	20.21
[13]	16	6.72	7.22	6.99	6.94	6.99	6.90
[14]	6	10.25	49.31	40.4	7.23	10.09	9.90
[14]	6	1.81	14.21	9.31	4.19	5.030	5.09
[15]	7	11.18	11.52	9.25	14.13	12.20	11.37
[15]	7	2.32	4.06	3.15	2.77	2.64	2.88
[15]	6	10.85	8.98	9.46	14.82	12.50	10.89
[15]	6	2.97	3.80	3.45	3.99	3.44	3.26
[16]	11	10.08	10.79	11.27	6.92	33.64	11.19
[16]	11	2.34	4.01	3.49	9.43	18.85	1.74
[17]	24	9.51	10.60	10.56	8.37	10.46	16.64
[17]	24	3.69	6.16	4.54	5.78	4.12	3.72
[17]	24	18.33	20.44	20.11	18.72	18.13	22.66
[17]	24	2.82	6.14	4.66	3.55	2.64	3.50
	175	15.04	20.79	20.22	16.36	18.22	19.10
	175	3.87	6.11	5.17	5.13	5.37	4.44

As expected, the results obtained by all EOSs are in good agreement with the experimental data for pure-component systems. Adsorption of propane on zeolite 5A using VDW having %RAD of 6.13 is the worst case. This table shows that RT EOS having the total relative average error of 2.09 demonstrates the best performance, while the highest total average error is associated with ZRG having the error of 3.14. Using the optimum values of the single-component parameters (α_i, β_i, k_i and λ_i) obtained through the calculations related to table 4, the multicomponent parameters (α, β and λ) were determined. Table 5 shows the relative average deviations, %RAD (wi) and %RAD(w), of different 2-D EOSs for binary systems. These relative errors were calculated using the following equations:

(30)

(31)

Where N_C is the total number of components and N_p is the total number of equilibrium points in a set of data. The superscript c and e stand for calculated and experimental respectively. w and w_i are total amount of adsorbed phase and the amount of component i in adsorbed phase respectively.

As it is apparent from Table 3, RT equation of state having %RAD (w_i)=15.04 and %RAD(w)=3.87 reveals the best prediction among the others. PR is ranked as the worst having %RAD (w_i)=20.79 and %RAD(w)=6.11. The good prediction of highly-nonideal systems where shows azeotropic behavior is the primary advantage of the new EOS. In order to demonstrate this capability, three sets of experimental data showing highly-nonideal behavior were selected to be compared with the predictions of different EOSs. For each case the single-component parameters and %RAD for various EOSs are shown through the tables. Also, the variation of one component (w_i) and total (w) adsorbed amounts were plotted versus mole fraction of one component. Because of the limitation of the data released in literature on gas adsorption, the following three cases were considered.

Case 1: Adsorption of isobutene-ethylene on zeolite 13X

Table 4. The single-component parameters and %RAD for various EOSs

Adsorbate	2-D-EOS	NP	10^-4α_i	β_i	Ln k_i	λ_i	%AAD	P (KPa)	T (K)	Ref
Iso-butane	VDW	16	-2.286	0.4074	8.554	---	2.90	24-137.84	298.15	[12]
	Eyring	16	-0.0452	0.3680	8.953	---	2.86	24-137.84	298.15
	ZGR	16	1.829	0.3439	9.993	----	2.84	24-137.84	298.15
	SRK	16	-3.782	0.4135	9.069	----	2.94	24-137.84	298.15
	P-R	16	-4.416	0.4104	9.126	----	2.92	24-137.84	298.15
	R-T	16	-1.872	0.3912	8.405	-0.3912	2.88	24-137.84	298.15
Ethylene	VDW	30	-0.4643	0.2362	5.065	----	5.04	24-137.84	298.15	[12]
	Eyring	30	0.6790	0.2093	5.612	----	4.55	24-137.84	298.15
	ZGR	30	1.802	0.1973	6.627	----	4.08	24-137.84	298.15
	SRK	30	-0.6323	0.2405	5.129	----	4.75	24-137.84	298.15
	P-R	30	-0.7564	0.2396	5.157	----	4.69	24-137.84	298.15
	R-T	30	0.3001	0.2559	6.131	2.406	3.61	24-137.84	298.15

Figure 1. The variation of adsorbate mole fraction of isobutene versus gas mole fraction of isobutene.

Figure 2. the variation of total amount of adsorbate versus gas mole fraction of isobutene.

Case 2: Adsorption of carbon dioxide-ethylene on zeolite 13X

Table 5. The single-component parameters and %RAD for various EOSs

Adsorbate	2-D-EOS	NP	10^-4α_i	β_i	Ln k_i	λ_i	%AAD	P (KPa)	T (K)	Ref
Ethylene	VDW	25	-6.322	0.2108	3.887	---	2.70	67-137.87	323.15	[12]
	Eyring	25	6.527	0.1968	4.375	---	2.77	67-137.87	323.15
	ZGR	25	20.170	0.1942	5.335	----	2.99	67-137.87	323.15
	SRK	25	-7.511	0.2236	3.926	----	2.66	67-137.87	323.15
	P-R	25	-8.822	0.2233	3.951	----	2.67	67-137.87	323.15
	R-T	25	1.497	0.2479	4.210	1.419	2.77	67-137.87	323.15
Carbon dioxide	VDW	17	-8.398	0.0966	4.0477	----	2.65	0.44-137.84	323.15	[12]
	Eyring	17	1.120	0.1180	4.4618	----	2.77	0.44-137.84	323.15
	ZGR	17	11.470	0.1265	5.3763	----	3	0.44-137.84	323.15
	SRK	17	-8.481	0.1333	4.0770	----	2.56	0.44-137.84	323.15
	P-R	17	-9.670	0.1356	4.1082	----	2.56	0.44-137.84	323.15
	R-T	17	-2.571	0.1505	4.2643	1.080	2.69	0.44-137.84	323.15

Figure 3. The variation of adsorbate mole fraction of ethylene versus gas mole fraction of ethylene.

Figure 4. The variation of total amount of adsorbate versus gas mole fraction of ethylene.

Case 3: Adsorption of Nitrogen-oxygen on zeolite 10X

Table 6. The single-component parameters and %RAD for various EOSs

Adsorbate	2-D-EOS	NP	10^-4α_i	β_i	Ln k_i	λ_i	%AAD	P (KPa)	T (K)	Ref
Oxygen	VDW	25	12.6552	0.5593	-1.852	---	0.505	92.9-212.39	273.15	[16]
	Eyring	25	67.6354	0.8062	-1.368	---	0.537	92.9-212.39	273.15
	ZGR	25	128.2308	0.9011	-0.3409	----	0.592	92.9-212.39	273.15
	SRK	25	11.0082	0.4634	-1.855	----	0.504	92.9-212.39	273.15
	P-R	25	10.7484	0.4289	-1.858	----	0.503	92.9-212.39	273.15
	R-T	25	32.0132	0.7882	-1.831	1.244	0.510	92.9-212.39	273.15
Nitrogen	VDW	17	-10.8017	5.00E-05	-0.3447	----	0.351	99.5-212.4	273.15	[16]
	Eyring	17	0.9828	0.1212	0.0285	----	0.307	99.5-212.4	273.15
	ZGR	17	12.3812	0.1370	0.9070	----	0.253	99.5-212.4	273.15
	SRK	17	-9.2520	0.0917	-0.3313	----	0.342	99.5-212.4	273.15
	P-R	17	-9.7411	0.1022	-0.3143	----	0.333	99.5-212.4	273.15
	R-T	17	18.4780	0.4298	0.8526	3.199	0.262	99.5-212.4	273.15

Figure 5. the variation of adsorbate mole fraction of oxygen versus gas mole fraction of oxygen.

Figure 6. The variation of total amount of adsorbate versus gas mole fraction of oxygen.

As it can be seen from figures 1 through 6 for all cases, especially for case 1, the performance of the RT EOS outreaches the rest significantly.

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Introduction of a Novel Two-Dimensional Equation of State to Predict Gas Equilibrium Adsorption in Highly-Nonideal Systems

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Volume 5, Issue 2
December 2017
Pages 1-12

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Volume 5, Issue 2December 2017Pages 1-12

Volume 5, Issue 2
December 2017
Pages 1-12