1 23

Heat and Mass TransferWärme- und Stoffübertragung ISSN 0947-7411Volume 48Number 2 Heat Mass Transfer (2012) 48:217-226DOI 10.1007/s00231-011-0875-8

A comparison of three adsorptionequations and sensitivity study ofparameter uncertainty effects on adsorptionrefrigeration thermal performanceestimationYongling Zhao, Eric Hu & AntoniBlazewicz

1 23

Your article is protected by copyright and

all rights are held exclusively by Springer-

Verlag. This e-offprint is for personal use only

and shall not be self-archived in electronic

repositories. If you wish to self-archive your

work, please use the accepted author’s

version for posting to your own website or

your institution’s repository. You may further

deposit the accepted author’s version on a

funder’s repository at a funder’s request,

provided it is not made publicly available until

12 months after publication.

ORIGINAL

A comparison of three adsorption equations and sensitivity studyof parameter uncertainty effects on adsorption refrigerationthermal performance estimation

Yongling Zhao • Eric Hu • Antoni Blazewicz

Received: 24 October 2010 / Accepted: 20 July 2011 / Published online: 3 August 2011

� Springer-Verlag 2011

Abstract This paper presents isosteric-based adsorption

equilibrium tests of three activated carbon samples with

methanol as an adsorbate. Experimental data was fitted into

Langmuir equation, Freundlich equation and Dubinin-

Astakov (D–A) equation, respectively. The fitted adsorp-

tion equations were compared in terms of agreement with

experimental data. Moreover, equation format’s impacts on

calculation of the coefficient of performance (COP) and

refrigeration capacity of an adsorption refrigeration system

was analyzed. In addition, the sensitivity of each parameter

in each adsorption equation format to the estimation of

cycle’s COP and refrigeration capacity was investigated. It

was found that the D–A equation is the best form for

presenting the adsorptive property of a carbon-methanol

working pair. The D–A equation is recommended for

estimating thermal performance of an adsorption refriger-

ation system because simulation results obtained using the

D–A equation are less sensitive to errors of experimentally

determined D–A equation’s parameters.

List of symbols

x Adsorbate concentration, kg kg-1

T Temperature, K

Tc Condensing temperature, K

Te Evaporating temperature, K

P Adsorption pressure or partial pressure, Pa

Ps Saturation pressure at local temperature, Pa

Qst Isosteric heat of adsorption, kJ/kg

R Gas constant, kJ kg-1K-1

KI0

Adsorption constant, Pa-1

K Adsorption constant

COP Coefficient of performance

x0 Maximum adsorption capacity, kg kg-1

1/n Parameter of Freundlich equation

n Parameter of D–A equation

D Parameter of D–A equation

q� Equilibrium concentration, kg kg-1

q�0 Adsorption capacity, kg kg-1

h Surface coverage of the micropore

Qr Refrigeration capacity, kJ

Lo Latent heat of vaporation, kJ kg-1

cr Specific heat capacity, kJ kg-1 K-1

Mac Mass of activated carbon, kg

1 Introduction

In recent years, the solid adsorption refrigeration technique

has attracted extensive interest and research [1–3] as a

result of a series benefits it offers, such as low energy

consumption, environmental-friendliness, quiet operation

etc. For an adsorption refrigeration system, the selection of

the working pair (i.e., adsorbent and adsorbate) is crucial

because the thermal performance of the system largely

depends on the adsorptive properties of the working pair

employed. Therefore, obtaining the accurate adsorptive

property of the working pair and choosing a suitable

adsorption equation is essential for design calculation and

thermal performance prediction.

Traditionally, the adsorptive property of an adsorbent

and an adsorbate pair is normally determined experimen-

tally using the isotherm and isobar method [4, 5]. However,

neither method is efficient and precise because these

experiments are normally conducted at a series of constant

Y. Zhao � E. Hu (&) � A. Blazewicz

School of Mechanical Engineering, The University of Adelaide,

North Terrace, Adelaide, SA 5005, Australia

e-mail: eric.hu@adelaide.edu.au

123

Heat Mass Transfer (2012) 48:217–226

DOI 10.1007/s00231-011-0875-8

Author's personal copy

temperatures or pressures that do not cover the entire

temperature and pressure range of sorption to be utilized in

practice. The isosteric-based method [6] could directly test

typical isosteric lines within the range to be used in a real

adsorption refrigeration cycle. Therefore, the isosteric-

based method is a very convenient and efficient approach

that can be used to obtain the adsorptive property of a

working pair for design calculation purposes.

On the other hand, in recent years the manufacturing

method (activation method) of activated carbons has

changed extensively, which has resulted in changes in

adsorptive properties of activated carbons. An increasing

number of new categories of activated carbons are now

available on the market and several new types have been

used in research [7]. Critoph and Hu et al. studied the

adsorptive properties of several types of charcoals in 1988

and 1992 [4, 8]. However, research into the adsorptive

properties of new activated carbons is limited. Therefore,

study of the adsorptive properties of these new activated

carbons is necessary and meaningful.

However, once the experimental data of equilibrium tests

have been obtained, the adsorption equation presenting the

data best still needs to be determined. In the area of

adsorption equation formats, Langmuir equation, Freundlich

equation and D–A equation are the dominant ones employed

in current design calculation and various mathematical

modelling. Freundlich equation was proposed as an empiri-

cal equation and is currently widely adopted in adsorption

equilibrium modelling of the solid adsorption system [9–11].

Compared to Freundlich equation, Langmuir equation is a

semi-empirical formula in which monolayer surface

adsorption assumption was introduced and is now popularly

employed in thermal performance estimation of the silica

gel-water adsorption chiller and desalination system

[12–14]. The D–A equation was proposed on the basis of

carbonaceous substance and volume filling theory [15], which

is currently the dominant adsorption equation used for car-

bonaceous adsorbent adsorption system [16–18]. Compared

to Freundlich and Langmuir equations, D–A equation has

three parameters, which may contribute to a better agreement

with experimental data due to stronger adjustment.

In this paper, the isosteric adsorption experimental data

of three activated carbon samples (207C, 207EA and

WS-480, which are from Calgon carbon Corporation) with

methanol as an adsorbate were fitted into three formats

(Langmuir, Freundlich and D–A equations), respectively to

compare their agreement. The calculation of COP and

refrigeration capacity based on each format was conducted

to assess the difference when the same activated carbon

and methanol were used as working pair in a practical

adsorption refrigeration system. Furthermore, the sensitiv-

ity of each parameter in each format to thermal perfor-

mance estimation was studied.

2 Experimental setup and testing procedure

The test rig was set up at Shanghai Jiao Tong University

(SJTU), which was modified from the test rig employed in

the study in the literature [6]. Compared to the original test

rig, connections of the current test rig were modified and

vacuum valves were used to better maintain vacuum. A

pressure transducer ranging from zero kPa to 50 kPa with a

precision of 50 Pa replaced one with a precision of 100 Pa.

In addition, four-wired PT1000 temperature sensors and an

electronic balance with a precision of 0.01 g were used for

pressure and weight measurement. The schematic diagram

of the experimental rig is shown in Fig. 1.

The principle of the isosteric-based adsorption equilib-

rium testing method is that the amount of adsorbed

adsorbate remains nearly unchanged once the adsorbent

was separated from the bulk of adsorbate after reaching

adsorption equilibrium. Procedures therefore include the

following major steps:

1. Degassed the system and then isolated the system by

closing V3. Opened V1 and V2 to initialize adsorption,

which was kept for twelve hours in order to reach

adsorption equilibrium.

2. Closed V1 and conduced measurement of the P–T-x

correlation of the isosteric line.

3. Measured the pressure in the generator using a

pressure transducer when pressure reached equilib-

rium. By setting a series of adsorbent temperatures

(through controlling temperature of water bath), cor-

responding equilibrium pressures was obtained. In

order to avoid condensation on the inner surface of the

Fig. 1 Schematic diagram of the testing system

218 Heat Mass Transfer (2012) 48:217–226

123

Author's personal copy

tube, tube connecting to the generator was wrapped

with heating wire, which was used to keep the tube

temperature equal to that of water bath.

4. Measured the mass of the generator and compared with

initial mass of generator to get mass variation and then

the amount of methanol adsorbed, i.e. concentration x,

was obtained.

5. Repeated step1 to step 4 to get various isosters and

corresponding temperature and pressure values by

setting appropriate temperatures of two water baths for

adsorption equilibrium.

6. Experimental data of tested three samples is listed in

Table 1.

3 Adsorption equations

(a) Langmuir equation

Langmuir equation was proposed based on a uniform

surface adsorption assumption and deemed one monolayer

adsorption generated on a uniform surface. The basic form

of the Langmuir equations is expressed in Eq. 1.

h ¼ KP=ð1þ KPÞ ð1Þ

where h ¼ q�=q�0

� �represents the surface coverage of the

micropore, K is an adsorption constant while P is the

partial pressure [5]. When the concentration is low, one

practical working form of the Langmuir equation can be

derived with Henry’s law and vant Hott equation, which is

expressed as follows:

x ¼ P � KI0 exp

Qst

RT

� �ð2Þ

where x is the concentration of adsorbed adsorbate; P is

adsorption pressure; KI0is the adsorption constant; Qst is

adsorption heat; R is gas constant and T is the temperature

of adsorbent.KI0 and Qst are two parameters normally

determined by experiments.

(b) Freundlich equation

Freundlich equation is an empirical equation but still

enjoys considerable accuracy in describing physical

adsorption within the range where the adsorbate concen-

tration is relatively high. For solid–vapor adsorption, Fre-

undlich equation can be given as [19]:

Table 1 Experimental data of

adsorption equilibrium tests

on samples 207C, 207EA

and WS-480

207C 207EA WS-480

x (kg/kg) T �C P (Pa) x (kg/kg) T �C P (Pa) x (kg/kg) T �C P (Pa)

0.13 19.8 4,500 0.24 19.9 4,050 0.22 29.7 8,520

0.13 29.7 7,500 0.24 29.8 6,650 0.22 39.9 14,050

0.13 39.9 11,900 0.24 39.9 10,700 0.22 44.8 18,150

0.13 49.8 19,250 0.24 49.6 17,600 0.22 49.7 22,950

0.13 59.9 30,350 0.24 59.8 26,400 0.22 54.8 28,800

0.11 19.6 3,250 0.20 29.7 4,450 0.19 29.8 5,850

0.11 29.8 4,950 0.20 39.8 7,300 0.19 39.9 10,050

0.11 39.9 8,050 0.20 49.7 12,450 0.19 49.7 16,900

0.11 49.7 13,350 0.20 59.8 18,750 0.19 54.9 21,300

0.11 59.8 20,300 0.20 69.6 26,500 0.19 59.7 26,600

0.08 39.6 4,150 0.17 39.6 5,750 0.15 34.9 4,900

0.08 49.5 7,900 0.17 49.8 8,950 0.15 44.7 8,500

0.08 59.7 12,250 0.17 59.9 13,600 0.15 54.8 14,050

0.08 69.8 17,500 0.17 69.5 20,750 0.15 59.9 18,200

0.08 79.7 27,050 0.17 79.9 29,350 0.15 64.9 22,700

0.06 49.5 4,450 0.11 49.6 4,150 0.09 39.6 3,450

0.06 59.8 6,900 0.11 59.7 7,950 0.09 49.8 5,700

0.06 69.8 10,650 0.11 69.6 10,200 0.09 59.7 9,650

0.06 79.9 18,550 0.11 79.8 17,250 0.09 64.5 12,950

0.06 89.8 28,500 0.11 89.9 24,250 0.09 69.7 15,500

0.04 49.8 3,250 0.06 54.7 3,550 0.05 49.8 3,000

0.04 59.7 5,050 0.06 59.8 4,850 0.05 59.6 5,050

0.04 69.9 7,250 0.06 69.7 6,800 0.05 69.7 8,600

0.04 79.7 10,300 0.06 79.9 9,250 0.05 79.8 13,800

0.04 89.7 16,350 0.06 89.9 14,500 0.05 89.9 20,450

Heat Mass Transfer (2012) 48:217–226 219

123

Author's personal copy

x ¼ x0

P

Ps

� �1=n

ð3Þ

where x0 is theoretical maximum adsorption capacity; Ps

and P are saturation pressure of adsorbate and system

adsorption pressure respectively. 1/n is model parameter. x0

and n are two parameters determined by experiments.

(c) D–A equation

D–A equation was proposed based on carbonaceous

substances and modified from Dubinin-Radushkevich

(D–R) equation which established volume filling theory.

Compared to Langmuir and Freundlich equations, D–A

equation is more popular on physical micropores adsorp-

tion and its format can be given as below [4].

x ¼ x0 exp �D T lnPs

P

� �n� �ð4Þ

where D is a constant that is determined by the adsorbent

microstructure and n is a parameter introduced to achieve a

better fit with experimental data. x0, D and n are three

parameters normally determined by experiments.

4 Equation fitting

Experimental data were processed in a Matlab environment

to fix the parameters of three adsorption equation formats,

respectively. The specific working form of the Langmuir

equation was used for curving fitting and sensitivity study.

This specific working form was chosen because this work

attempts to experimentally confirm the failure of the

working forming at high concentration condition. More-

over, this work attempts to point out the dramatic sensi-

tivity of parameters of the working form.

With respect to curve fitting method, multiple linear

regression technique was used to determine the parameters

of the Langmuir format. Simple linear regression was

employed to determine parameters of Freundlich and D–A

Formats. Parameters of each sample in three different

formats were determined and shown in Table 2.

5 Results discussions

5.1 Equations’ agreement

The parameters in three equations that were found by fit-

ting experimental data into Eqs. 2, 3 and 4, are listed in

Table 2. The corresponding P–T–x diagrams of three

samples plotted with experimental data and isosteric lines

plotted from determined equations are presented from

Figs. 2, 3 and 4.

The values of R2 in Table 2 indicate that D–A format

enjoys the best agreement with experimental data while

Langmuir format has a relative poor agreement. From three

groups of figures, it’s not difficult to see two features of

those three adsorption equations. One is that Langmuir

equation only agrees well with experimental data in the

range of mediate and low concentration. The other is that

Freundlich equation drops its precision when the concen-

tration (x) decreases, which agrees with the tendency dis-

covered on silica gel-water working pair [19]. However, it

is still accurate for design calculation purposes since in

most cases the adsorption refrigeration system doesn’t

reach the extremely low concentration zone.

5.2 Format impact on COP and refrigeration capacity

When designing a carbon methanol refrigeration system,

estimating the refrigeration capacity and the system COP is

essential. However, for a given working pair and the

adsorption equilibrium test data, using a different adsorp-

tion equation format may result in a huge difference.

Figures 5 and 6 show the refrigeration capacity and COP,

respectively calculated using the three adsorption equation

formats based on tested three activated carbon samples.

Detailed thermodynamic analysis and calculation method

of ideal refrigeration capacity Qr and COP of a basic

adsorption refrigeration system can be found from litera-

ture [8]. In the studied base-case, the system is assumed to

work under the conditions that the condensing temperature

and evaporating temperature are 30�C and -5�C, respec-

tively. The adsorbent bed finally reaches the temperature of

the heat source and the highest heat source temperature is

assumed below 120�C for the consideration of avoiding

methanol decomposition [20].

Figure 5 shows the refrigeration capacity calculated

with different adsorption equations on each sample.

Parameters used in the numerical calculation are listed in

Table 3. Figure 5a, b, c clearly show that refrigeration

capacity Qr calculated from D–A format always achieve

the highest values for each tested samples while those

calculated from Langmuir format always have the lowest

values in the temperature range 85–120�C. Moreover, in

the typical working temperature range, the difference of Qr

calculated from D–A and Freundlich format is significant,

almost reaching 200% for each sample at the temperature

85�C. Therefore, from the view of design calculation, these

adsorption formats need to be treated carefully.

From Fig. 6, it is not difficult to see the variation of

system COP calculated using different formats. Generally,

D–A format gives the highest COP values. The difference

among the COP values calculated at a given heat source

temperature can be quite significant. For instance, there is

an almost 170% absolute difference between results from

220 Heat Mass Transfer (2012) 48:217–226

123

Author's personal copy

D–A and Freundlich equation when the values are nearly

stable. Besides the difference in COP values, the minimum

heating source temperature required to run the refrigeration

cycle calculated from those three adsorption equations

varies considerably. The minimum temperatures calculated

from D–A equation and Freundlich equation don’t vary

much for each carbon sample while that calculated from

Langmuir equation are quite different for different carbon

samples.

5.3 Parameters’ sensitivity

It is inevitable that some errors may be generated during

the experiments and when fitting experimental data to

isotherm equations, which will produce errors in the

parameters of each isotherm equations. Therefore, a sen-

sitivity analysis of each parameter in the three isotherm

equations to the system COP and refrigeration capacity has

been conducted to reveal how tolerant the calculated sys-

tem performance is to errors in parameters when each

isotherm is used. The scenario used is that of activated

carbon 207C and methanol as a working pair in a refrig-

eration system that is operated with heating source at

100�C and condensing temperature at 30�C to generate

evaporating temperature of -5�C. In order to study

parameters’ sensitivity to system’s refrigeration capacity

Qr and COP, up to ± 10% errors are assumed for each

parameter to be caused by the experiment and data pro-

cessing. Figures 7 and 9 show the results of the sensitivity

study.

Figure 7 shows that for Langmuir equation, error in the

parameter Qst has a significant impact on refrigeration

output and system COP while parameter KI0 only has a

relative slight effect. When KI0 has 10% error, the impact

on the values of refrigeration power output or system COP

is in a similar range, i.e., approximately 10 and 5%,

respectively. However, the impact of the error in Qst is

huge. When the error in Qst is ?1%, the variation of cal-

culated COP and refrigeration output is about 5–10%. If the

error in Qst was up to 10%, variation in calculated refrig-

eration output could be as high as 340% while the variation

in calculated COP could be about 55%. Moreover, positive

error in Qst could affect Qr more significantly compared to

that caused by negative error.

For Freundlich equation, errors in both the parameters

(i.e., x0 and n) apparently have little influence in the cal-

culations of refrigeration output Qr and system COP as

shown in Fig. 8. Figure 8 shows that the calculated values

of Qr and COP are less sensitive to parameter n than to

parameter x0.

In D–A equation, parameter n is more sensitive to the

calculations of Qr and COP as shown in Fig. 9. A -10%

error in the parameter n could lead to about -48 and -34%

deviations in refrigeration output Qr and system COP,

respectively. Figure 9 also shows that the calculated values

of Qr and COP is less sensitive to errors of parameters x0

and D.

6 Conclusions

The experimental data of isosteric-based adsorption equi-

librium testing for three activated carbon and methanol

were fitted into three classical adsorption equations. The

parameters in the three equations were found and their

sensitivities to the calculations of system performance i.e.,

system COP and refrigeration capacity were studied.

The following conclusions can be drawn from the study:

1. D–A equation is the most suitable format to present the

adsorptive properties of the tested activated carbon/

methanol working pairs, in terms of its agreement with

experimental data. Two factors may contribute to the

superiority of D–A equation for presenting adsorptive

property of activated carbon/methanol working pairs.

One is that D–A equation was proposed based on the

theory of volume filling of micropores (TVFM), which

is more realistic compared to monolayer adsorption

Table 2 Determined parameters of each adsorption equation formations

Carbon sample Format Determined parameters R2

207C Langmuir – KI0 ¼ 5:68� 10�6 Qst ¼ 1007:30 0.9272

207EA Langmuir – KI0 ¼ 7:12� 10�6 Qst ¼ 1040:90 0.9558

WS-480 Langmuir – KI0 ¼ 7:87� 10�7 Qst ¼ 1196:30 0.9323

207C Freundlich x0 ¼ 0:25 – n ¼ 1:65 0.9777

207EA Freundlich x0 ¼ 0:54 – n ¼ 1:47 0.9723

WS-480 Freundlich x0 ¼ 0:43 – n ¼ 1:39 0.9641

207C D–A x0 ¼ 0:15 D ¼ 9:67� 10�6 n ¼ 1:72 0.9901

207EA D–A x0 ¼ 0:28 D ¼ 8:45� 10�7 n ¼ 2:08 0.9865

WS-480 D–A x0 ¼ 0:27 D ¼ 9:08� 10�6 n ¼ 1:78 0.9942

Heat Mass Transfer (2012) 48:217–226 221

123

Author's personal copy

Fig. 2 Comparison between experimental data (markers) of sample

207C and corresponding isosteric lines (solid lines) plotted with

determined adsorption equations: (a) Langmuir equation, (b) Freund-

lich equation and (c) D–A equation

Fig. 3 Comparison between experimental data (markers) of sample

207EA and corresponding isosteric lines (solid lines) plotted with

determined adsorption equations: (a) Langmuir equation, (b) Freund-

lich equation and (c) D–A equation

222 Heat Mass Transfer (2012) 48:217–226

123

Author's personal copy

Fig. 4 Comparison between experimental data (markers) of sample

WS-480 and corresponding isosteric lines (solid lines) plotted with

determined adsorption equations: (a) Langmuir equation, (b) Freund-

lich equation and (c) D–A equation

Fig. 5 Qr versus heat source temperature calculated with Langmuir,

Freundlich and D–A equations, respectively: (a) Sample 207C,

(b) Sample 207EA and (c) Sample WS-480

Heat Mass Transfer (2012) 48:217–226 223

123

Author's personal copy

assumed by Langmuir equation. The other factor is

that D–A equation was just proposed based on

carbonaceous substances.

2. Freundlich equation is still in a good agreement with

experimental data, except in the area with a relatively

low concentration. This feature is similar to the finding

reported by Xia et al. [6]. One factor contributing to

the failure in low concentration is experimental errors,

because in this circumstance the errors of measuring

charged methanol become considerable.

3. Langmuir equation is not suitable to present the

adsorptive properties of the tested activated carbon/

Fig. 6 COP versus heat source temperature calculated with Lang-

muir, Freundlich and D–A equations respectively: (a) Sample 207C,

(b) Sample 207EA and (c) Sample WS-480

Table 3 Parameters used in thermal performance estimation

Symbol Value Unit Symbol Value Unit

Tc 30 �C Cr 2.53 kJ/kg K

Te -5 �C Mac 1 kg

L0 1,120 kJ/kg

Fig. 7 Impact on Qr and COP of a base-case cycle caused by error of

parameters KI0 and Qst of Langmuir equation: (a) refrigeration

capacity Qr and (b) refrigeration COP

224 Heat Mass Transfer (2012) 48:217–226

123

Author's personal copy

methanol working pair because it has the least

agreement with experimental data. However, when

the concentration is low, this working form of the

Langmuir equation enjoys a relatively good agreement

with experimental data. This is because the working

form of the Langmuir equation was derived with

Henry’s law, which should work better when the

adsorbate concentration is low. The present work

experimentally confirmed this theoretical point.

4. In the Langmuir equation, any error in the process of

experiment and data processing would cause huge vari-

ation in the system performance calculations. No matter

what working pairs are used, great effort is necessary to

determine the parameters accurately in Langmuir

equation, especially the Qst, otherwise the system

performance calculations would suffer considerably.

5. Freundlich isotherm format and D–A isotherm format

are recommended for carbon methanol adsorption

refrigeration system thermal performance calculations

since errors of their parameters have less impact on

calculation. However, the parameter n still needs to be

determined carefully in Freundlich and D–A equation

formats, especially in the D–A format.

Acknowledgments The tests were carried out in the Institute of

Refrigeration and Cryogenics at Shanghai Jiao Tong University

(SJTU). Special appreciation goes to Prof. R.Z. Wang for access to

their lab, and we would also like to extend our gratitude to Dr. T.X. Li

and L.X. Gong for their help in setting up the test rig.

References

1. Critoph RE (2002) Multiple bed regenerative adsorption cycle

using the monolithic carbon-ammonia pair. Appl Therm Eng

22:667–677

Fig. 8 Impact on Qr and COP of a base-case cycle caused by error of

parameters xn and n of Freundlich equation: (a) refrigeration capacity

Qr and (b) refrigeration COP

Fig. 9 Impact on Qr and COP of a base-case cycle caused by error of

parameters x0, n and D of D–A equation: (a) refrigeration capacity Qr

and (b) refrigeration COP

Heat Mass Transfer (2012) 48:217–226 225

123

Author's personal copy

2. Grisel RJH, Smeding SF, Boer RD (2010) Waste heat driven

silica gel/water adsorption cooling in trigeneration. Appl Therm

Eng 30:1039–1046

3. Wang RZ, Oliveira RG (2006) Adsorption refrigeration–an effi-

cient way to make good use of waste heat and solar energy. Prog

Energy Combust Sci 32:424–458

4. Jing H, Exell RHB (1993) Adsorptive properties of activated

charcoal/methanol combinations. Renew Energy 3:567–575

5. Ng KC, Chua HT, Chung CY, Loke CH, Kashiwagi T, Akisawa

A, Saha BB (2001) Experimental investigation of the silica gel-

water adsorption isotherm characteristics. Appl Therm Eng

21:1631–1642

6. Xia ZZ, Chen CJ, Kiplagat JK, Wang RZ, Hu JQ (2008)

Adsorption equilibrium of water on silica gel. J Chem Eng Data

53:2462–2465. doi:10.1021/je800019u

7. Zhao YL, Hu E, Blazewicz A (2010) A non-uniform pressure and

transient boundary condition based dynamic modeling of the

adsorption process of an adsorption refrigeration tube. Appl

Energy. doi:10.1016/j.apenergy.2010.12.062

8. Critoph RE (1988) Performance limitations of adsorption cycles

for solar cooling. Sol Energy 41:21–31

9. Gupta Y, Metchop L, Frantzis A, Phelan PE (2008) Comparative

analysis of thermally activated, environmentally friendly cooling

systems. Energy Convers Manag 49:1091–1097

10. Alam KCA, Saha BB, Kang YT, Akisawa A, Kashiwagi T (2000)

Heat exchanger design effect on the system performance of silica

gel adsorption refrigeration systems. Int J Heat Mass Transf

43:4419–4431

11. Liu Y, Leong KC (2006) Numerical study of a novel cascading

adsorption cycle. Int J Refrig 29:250–259

12. Liu Y, Leong KC (2005) The effect of operating conditions on

the performance of zeolite/water adsorption cooling systems.

Appl Therm Eng 25:1403–1418

13. Wu JW, Biggs MJ, Hu EJ (2010) Thermodynamic analysis of an

adsorption-based desalination cycle. Chem Eng Res Des

88(12):1541–1547

14. Hamamoto Y, Alam KCA, Saha BB, Koyama S, Akisawa A,

Kashiwagi T (2006) Study on adsorption refrigeration cycle uti-

lizing activated carbon fibers. Part 2. Cycle performance evalu-

ation. Int J Refrig 29:315–327

15. Dabrowski A (2001) Adsorption–from theory to practice. Adv

Colloid Interface Sci 93:135–224

16. Fadar AE, Mimet A, Perez-Garcıa M (2009) Modelling and

performance study of a continuous adsorption refrigeration sys-

tem driven by parabolic trough solar collector. Sol Energy

83:850–861

17. Critoph RE, Metcalf SJ (2004) Specific cooling power intensifi-

cation limits in ammonia-carbon adsorption refrigeration sys-

tems. Appl Therm Eng 24:661–678

18. Jing H, Exell RHB (1994) Simulation and sensitivity analysis of

an intermittent solar-powered charcoal/methanol refrigerator.

Renew Energy 4:133–149

19. Gong LX, Wang RZ, Xia ZZ, Chen CJ (2010) Adsorption equi-

librium of water on a composite adsorbent employing lithium

chloride in silica gel. J Chem Eng Data 55:2920–2923. doi:

10.1021/je900993a

20. Hu EJ (1998) A study of thermal decomposition of methanol in

solar powered adsorption refrigeration systems. Sol Energy

62:325–329

226 Heat Mass Transfer (2012) 48:217–226

123

Author's personal copy