DynamicStudyofVSAandTSAProcessesforVOCs...

Research ArticleDynamic Study of VSA and TSA Processes for VOCsRemoval from Air

Rawnak Talmoudi 1 Amna AbdelJaoued1 and Mohamed Hachemi Chahbani12

1Laboratoire de Recherche Genie des procedes et systemes industriels Ecole Nationale drsquoIngenieurs de Gabes Universite de GabesGabes Tunisia2Institut Superieur des Sciences Appliquees et de Technologie de Gabes Rue Omar Ibn Elkhattab Zrig Gabes 6029 Tunisia

Correspondence should be addressed to Rawnak Talmoudi talmoudirawnakhotmailcom

Received 26 April 2018 Revised 3 August 2018 Accepted 4 September 2018 Published 24 September 2018

Academic Editor Doraiswami Ramkrishna

Copyright copy 2018 Rawnak Talmoudi et al )is is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

Volatile organic compounds are air pollutants that necessitate to be eliminated for health and environment concerns In thepresent paper two VOCs that is dichloromethane and acetone are recovered by adsorption on activated carbon from a nitrogengas stream Experimental adsorption isotherms of the two VOCs are determined at three different temperatures 298 313 and323K by the dynamic column breakthrough method )e dynamic mathematical model succeeds to predict satisfactorily theexperimental breakthrough curves for pure VOCs and different binary mixtures for various conditions )us the validateddynamic mathematical model has been used as a simulation tool for optimization purposes of VSA and TSA processes in order toachieve the highest performances under the given constraints )e effects of the adsorption step duration the vacuum pressureand the desorption temperature on the recovery of dichloromethane and acetone have been studied A recovery of 100 of the twoVOCs could be attained However the adsorption step duration should be determined precisely so as not to affect the recovery andalter the quality of air being purified due to the breakthrough of VOCs )e vacuum pressure and the desorption temperatureshould be carefully chosen in order to both reduce the energy consumption and shorten the purge step duration Regeneration byhot nitrogen stream seems to be more efficient than regeneration by reducing pressure

1 Introduction

Volatile organic compounds (VOCs) constitute a heteroge-neous group of substances with different physical andchemical behaviours including alkanes ketones aromaticsparaffins olefins alcohols ethers esters and halogenated andsulfur hydrocarbons [1 2] VOCs are emitted from chemicalindustry gaseous effluents oil sands process food industriespaint industries and petrochemical industries [2]

Dichloromethane acetone and ethyl formate are widelyused in the oil sands process for the extraction of the bi-tumen from the oil sands [3] After the separation of bi-tumen these VOCs should be recovered to avoid seriouseffects on human health and environment

Tropospheric ozone is not emitted into the air but ac-tually formed in the atmosphere through a photochemicalprocess for which VOCs play a significant role VOCs in the

air react with oxides of nitrogen NOx in the presence ofsunlight to form ozone Tropospheric ozone has to be dis-tinguished from ozone in the stratosphere which is part ofwhat is commonly referred to as the ldquoozone layerrdquo helping toblock the sunrsquos ultraviolet radiation Unfortunately mostVOCs produce ozone which inhabits the troposphereTroposphere or ground level ozone is a harmful photo-chemical oxidant that significantly contributes to the for-mation of smog It is regularly measured as an indicator ofsmog levels in the atmosphere Preventive measures shouldbe taken to avoid serious problems for those with asthmaand respiratory conditions for days when ozone level is highOzone concentrations of even 008 ppm contributed to lungdisease and pulmonary function deterioration in children)ere is evidence that prolonged exposure to ozone causespermanent damage to lung tissue and interferes with thefunctioning of the immune system Other consequences of

HindawiInternational Journal of Chemical EngineeringVolume 2018 Article ID 2316827 15 pageshttpsdoiorg10115520182316827

excessive ozone levels can include damage to the ecosystemincluding the retardation of plant growth and crop yields [4]

Being a precursor of photochemical oxidants eye irritantand a suspected toxicant of respiratory gastrointestinal andnervous system acetone may have detrimental effects onhuman health and environment [5] Human studies haveobserved associations between occupational exposure todichloromethane and increased risk for several specificcancers including brain cancer liver and biliary tract cancernon-Hodgkin lymphoma and multiple myeloma [6]

Results from experimental studies in humans indicatethat acute neurobehavioral deficits measured for exampleby psychomotor tasks tests of hand-eye coordination visualevoked response changes and auditory vigilance may occurat concentrations gt200 ppm with 4ndash8 hr of exposure [7]

As a result the control of dichloromethane acetone andany VOC exhausts in ambient air is considered imperative

)ere are several methods used to reduce the VOCs suchas absorption adsorption incineration catalytic oxidationbiological treatment ionization photocatalysis Adsorptiononto activated carbon is a highly efficient and relativelyinexpensive technique employed for the removal and re-covery of VOCs from air [8ndash11]

)e most known cyclic adsorption operation is pressureswing adsorption (PSA) [12 13] vacuum swing adsorption(VSA) and temperature swing adsorption (TSA) [14 15])e difference between these processes is their adsorptionand regeneration mode In TSA processes the temperaturechanges in each step with the low temperature upon ad-sorption and the high temperature in regeneration )e PSAtechnique depends on the pressure where the adsorptionstep is carried out at the high pressure and the regenerationoperation is at atmospheric pressure

Many studies of PSA TSA and VSA have been widelyinvestigated for recovery of VOCs from polluted air streams[16ndash18] )ere are more papers dealing with dichloro-methane [19 20] than acetone [21] Each VOC is treatedseparately and works dealing with mixtures of the two VOCsare lacking in the literature In general these works are justlimited to the experimental determination of breakthroughcurves and experiments of regeneration the cyclic steadystate is not considered Furthermore the models used forsimulation often use simplifying assumptions such as neg-ligible pressure drop isothermal conditions

It has to be noted that the adsorption step of VOCs hasbeen widely studied in the literature for different objectives(selection of the appropriate adsorbent effect of operatingconditions) However the regeneration step has been rarelyinvestigated despite its importance for the performance ofthe whole process Regeneration could be done by reducingthe pressure or increasing the temperature Regeneration iscrucial so as to ensure that the adsorption process remainsattractive in comparison with other processes It has a no-table effect on the duration of the total cycle and henceaffects the size and the number of beds of the purificationinstallation

)e principal aim of this work is to design an adsorptionbased separation process (Vacuum Swing Adsorption andtemperature swing adsorption) for recovering two VOCs

that is dichloromethane and acetone used extensively inoil sands process )e design of the process involves ex-perimental determination of equilibrium isotherms of thetwo VOCs on a commercial activated carbon using thedynamic column breakthrough method and the realizationof a simulation tool )e validated simulation tool con-sidering minimum simplifying assumptions is to be usedfor testing the technical feasibility and optimizing the VSAand TSA process through varying the operating parame-ters Results of simulations should give elements of re-sponses concerning the most appropriate process to beused for the present case that is the capture of acetone anddichloromethane

2 Experiments

)e adsorbent used is a commercial activated carbon sup-plied by CECA (Communaute Europeenne pour le Charbonet lrsquoAcier) it is of plant origin and precisely of maritime pine

)e apparent density and the BET Surface are 250 kgmiddotm3

and 1706m2middotgminus1 respectively)e specific surface area of theadsorbent is determined by measuring a N2 isotherm at 77Kusing an ASAP 2020 apparatus from Micromeritics )especific surface area is calculated according to the BETmethod [22]

)e measurements of pure species adsorption equilib-rium isotherms and breakthrough curves of pure compo-nents and binary mixtures of VOCs vapors are performedwith a dynamic adsorption unit

Figure 1 shows the experimental setup used VOCs at theliquid state (a pure component or a binary mixture) areinjected by one or two syringe pumps in the vaporizationcolumn At the exit of the column the liquid is completelyvaporized

A continuous nitrogen gas stream (inert gas) fixed bya mass flow controller (Brooks Instruments) is introduced inthe unit Nitrogen is then mixed with the VOCs vaporexiting the vaporization column before entering the ad-sorption column at a superficial velocity of 017mmiddotsminus1 )eamount of activated carbon packed in the column is 2 gExperiments are carried out at atmospheric pressure anda temperature of 25degC )e column is made of stainless steeland has a height of 10 cm and an internal diameter of 1 cm)e temperature of experiments is controlled by a thermo-static enclosure Pure components isotherms are determinedfor concentrations ranging from 500 to 12000 ppm on ac-tivated carbon at atmospheric pressure and at three tem-peratures 298K 313K and 323K Breakthrough curves forsingle solvent vapor of dichloromethane and acetone arecarried out at 298K 313K and 323K under atmosphericpressure Concentrations of solvent vapors at the inlet of thebed are set from 500 to 12000 ppm

Four different breakthrough curves of dichloromethaneacetone vapor mixtures at various inlet concentrations3000 ppm1500ppm 2000ppm500 ppm 500 ppm2000 ppmand 750 ppm400 ppm are performed on activated carbon at298K and at atmospheric pressure

)e variation of VOCs concentrations with time atthe exit of the adsorption bed are measured by a Gas

2 International Journal of Chemical Engineering

Chromatograph (CompactGC40 Interscience GAS))combined with a flame ionization detector (FID samplingloop 20 μL sampling from the main stream by vacuumpump) )e sample is transported into chromatographiccolumn which has an inner diameter of 032mm anda length of 10mm and then the sample is separated by theGC column coated with Poraplot Q stationary phase )etime for analysis of the single isotherm adsorption is about3min for both dichloromethane and acetone Breakthroughcurves were obtained by plotting the concentrations of eachVOC at the bed exit over time After each adsorption stepthe feed stream is changed to pure nitrogen so as to re-generate the fixed adsorption bed

3 Mathematical modeling

)e mathematical model for a packed adsorption bed as-suming nonisothermal operation involves mass balances forthe bulk fluid phase mass transfer kinetics gas-phase andsolid phase heat balances and a momentum balance

)e following assumptions are considered

(i) Non isothermal operation(ii) Ideal gas behavior for the gas phase(iii) Constant void fraction and velocity of gas(iv) Radial concentration and temperature gradients

negligible(v) Diffusion and mass transfer within a particle was

described by linear driving force (LDF)(vi) Absence of temperature gradients within the solid

particle

31MassBalance A differential fluid phase mass balance forthe component i is given by the following axially dispersedplug flow equation [23]

minusDz

z2ci

zZ2 +zci

zt+

z υgci1113872 1113873

zZ+

(1minus ε)ε

ρpzqi

zt 0 i 1 2 (1)

)e overall mass balance for the bulk gas is given by

zC

zt+

z υgC1113872 1113873

zZ+

(1minus ε)ε

ρp 1113944

n

i1

zqi

zt 0 (2)

where υg is the interstitial gas velocity ε is the bed voidfraction C is total bulk concentration ρp is the particledensity qi is the adsorbed concentration of component i Z isthe axial co-ordinate and Dz is the axial dispersion co-efficient which can be estimated by [24]

Dz 073Dm + 05dpμi

1 + 97 Dmdpμi1113872 1113873 (3)

where dp is the particle diameter μi is the interstitial velocityand Dm is the molecular diffusivity that can be estimatedfrom the ChapmanndashEnskog equation [25]

32 Momentum Balance )e pressure drop along the bedwas determined from the Ergun equation [23]

zP

zZ 150

(1minus ε)2

ε2d2p

μυg + 175(1minus ε)εdp

ρgυ2g (4)

where μ is the gas mixture viscosity ρg is the gas density anddp is the particle diameter

33 Mass Transfer Kinetics )e mass transfer rate betweenthe gas and solid phases is given the linear driving force(LDF) model represented by the following equations [26]

zqi

zt kiLDF q

lowasti minus qi( 1113857 i 1 2 (5)

where

kiLDF 15Dei

r2p (6)

where kiLDF is the mass transfer coefficient qlowasti is the loadingof component i Dei is the effective diffusivity of componenti and rp is the particle radius

It is common practice to predict mixture isotherms frompure component isotherms )e multicomponent extensionof LangmuirndashFreundlich model of dichloromethane and

4

12

5

6

3

7

GC with FIDanalysis

8

9

Figure 1 Schematic diagram of experimental unit for adsorption of VOCs vapors over activated carbon (1) Feed nitrogen (2) mass flowcontroller (3) pure N2 stream (4) syringe pump (5) evaporator column (6) main stream (7) adsorption column (8) thermostaticenclosure (9) gas chromatography (10) acquisition software

International Journal of Chemical Engineering 3

acetone is used based on parameters obtained from purecomponents )e model is represented by the followingequations [27]

qlowasti qmi

biCi( 1113857k3i

1 + 1113936j bjCj1113872 1113873k3i

i j 1 2 (7)

bi k1i expk2i

T (8)

where qmi is the saturation capacity bi k1i k2i and k3i are theLangmuirndashFreundlich equation parameters for component i

)e fit between experimental data and isothermsequation is calculated according to Equation (9) whichindicated the minimum sum of squares SS at three tem-peratures of pure 2 VOCs

SS() 1113944

T3

Ti

1113944

N

j1qexp i minus qmodi1113872 1113873

2 (9)

where qexp i and qmodi are the experimental and predictedamounts adsorbed respectively T1 to T3 are the three testedtemperatures j is the number of points per isotherm and gascomponent i represents the component (dichloromethaneand acetone) and N is the total number of experimental datapoints

34 Heat Balance for the Gas Phase )e gas-phase energybalance includes convection of energy axial thermal con-duction accumulation of heat gas-solid heat transfer andgas-wall heat transfer )e governing partial differentialequation is as follows [28]

CpgρgzTg

ztminus λL

z2Tg

zZ2 + ρgCpgz υgTg1113872 1113873

zZ+

1minus εε

1113874 1113875ashf Tg minusTs1113872 1113873

+4hw

εbdintTg minusTw1113872 1113873 0

(10)

where Cpg and Cps are the specific heats of the gas and solidphases λL is the effective axial thermal conductivity hf hware the heat transfer coefficient between the gas and theadsorbent and the heat transfer coefficient between the gasand the wall and Tg Ts and Tw are the gas solid and walltemperatures

)e film heat transfer hf is calculated from the followingequation [29]

Nug 2 + 1 1Re06Pr13 (11)

Nug hfdp

kg (12)

Re ρgυgdp

μ (13)

Pr Cpgυg

kg (14)

)e axial heat dispersion λL for each VOC can be es-timated from the following equation [30]

λL DZCpgρg (15)

35 Heat Balance for the Solid Phase )e solid phase energybalance takes into account the transfer of heat over the filmaxial thermal conduction accumulation in solid phase heatgenerated by the adsorption phenomenon )e energybalance equation for the bed can be expressed as in thefollowing equation [28]

minusksz2Ts

zz2 + ρpCpszTs

zt ashf Tg minusTs1113872 1113873 + 1113944

n

i1minusΔHi( 1113857

zqi

zt

(16)

where ks is the effective axial solid phase thermal conduc-tivity as expresses the ratio of the particle external surfacearea to volume and ΔHi is the isosteric heat of adsorption

36 Numerical Solution Aspen Adsorption enables processsimulation and optimization for a wide range of industrialgas adsorption processes It permits to choose from variousgeometries to complete process simulation tasks such asvacuum swing adsorption modeling Modeling includesa wide range of kinetic models including lumped resistancemicromacropore and general rate It uses a wide range ofstandard equilibrium models for pure and multicomponentgases It also uses a highly configurable energy balance toaccount for nonisothermal behavior conduction heat lossand wall effects

)us the set of aforementioned partial differentialequations relative to mass heat and momentum balancestogether with the appropriate initial and boundary condi-tions to fully describe the adsorption process are numeri-cally solved by Aspen Adsorption software )e set of partialdifferential equations change according to assumptionsconsidered

37 VSA and TSA Simulation After the determination ofneeded data to be used in simulations (adsorption isothermsand mass transfer coefficients for dichloromethane andacetone) VSA and TSA processes were designed to evaluatethe feasibility of acetone and dichloromethane recoveryfrom polluted air with activated carbon

371 Four-Step VSA Cycle )e 4-step VSA cycle consid-ered consists of four steps adsorption (I) countercurrentevacuation (II) countercurrent purge (III) and cocurrentpressurization with feed (IV) A schematic diagram of a one-bed VSA cycle is indicated in Figure 2(a)

In step I a continuous feed gas (VOCs +N2) is in-troduced at atmospheric pressure )e desorption step of


VSA cycle consists of steps II and III In the evacuation stepmoles of VOCs adsorbed are removed from the bed bydecreasing the bed pressure from 1 atm to 05 atm In thepurge step pure nitrogen is used to regenerate the bed ata pressure of 05 atm During step IV the pressure in thecolumn increases from 05 atm to the atmospheric pressurethe bed being pressurized by a mixture of VOCs and N2)ebed is initially filled with pure nitrogen )e duration of theadsorption step is chosen so as not to allow VOCs tobreakthrough )e purge step is stopped when the entireadsorbed amount is cleared from the adsorption bed

372Cree-Step TSA Cycle )e cycle step sequence for TSAincludes adsorption (I) heating (II) and cooling (III) steps)e schematic diagram of TSA process is illustrated inFigure 2(b)

During the adsorption step a gas mixture with 3000 ppmdichloromethane1500 ppm acetone is fed to the bed at 298Kand atmospheric pressure During the heating stepdichloromethane and acetone are desorbed from the bed byincreasing the column temperature up to 443K using a hotnitrogen stream )e direct heating with hot inert gas facil-itates the thermal and concentration swing for removal of thetwo VOCs During the cooling step the temperature of thebed is decreased with the aid of inert nitrogen stream at 298Kwhich comes in direct contact with the activated carbon

373 VSA and TSA Performance )e platform of AspenAdsorption is widely used in the industry by engineers tooptimize and simulate a wide range of PSA TSA VSA andother variants of these with a wide range of solid adsorbentsAspen Adsorption can be used for adsorption process designand can reduce significantly time and cost of laboratory andpilot plant trials)is is themajor benefit of simulation works)e software gives the user the freedom to configure theprocess to improve the plant operations in order to determinethe effect of various variables on plant performance

Using Aspen Adsorption software VSA and TSA cycleruns are performed for a binary VOCs mixture ofdichloromethaneacetone (gas inlet concentrations 3000 ppm1500 ppm) at 298K and atmospheric pressure using activatedcarbon

)e mathematical modeling of each step of the VSA andTSA cycles are performed by the same equations describedin Section 3

)e performance of the VSA and TSA processes isanalyzed through the obtained values for the recovery ofdichloromethane and acetone and this parameter is definedas the amount of the VOCs (dichloromethane and acetone)recovered during the regeneration step divided by the totalamount of VOCs used during the feed step Equations (17)and (18) are used to calculate the recovery for each VOCcomponent at cyclic steady state conditions [31]

For the VSA process the regeneration step includesevacuation and purge steps and the feed step comprisesadsorption and pressurization steps

Recovery() 1113938II0 ciυ|zL dt + 1113938

III0 ciυ|zL dt

1113938I0 ciυ|z0 dt + 1113938

IV0 ciυ|z0 dt

(17)

For the TSA process the regeneration step is the heatingstep and the feed step is the adsorption step

Recovery() 1113938II0 ciυ|zL dt

1113938I0 ciυ|z0 dt

(18)

4 Results and Discussion

41 Adsorption Equilibrium Isotherms Reliable adsorptionequilibrium isotherms are key elements in the design of anadsorption separation process )e dynamic column break-through method could be used safely for obtaining single-component equilibrium isotherm data It is used herein toderive the equilibrium isotherms of dichloromethane andacetone on activated carbon )e experimental setup andanalysis required for this method were previously described)e equilibrium results for these gases at atmospheric pres-sure and at three different temperatures are presented

)e dynamic column method of measuring single-component isotherm data involves monitoring a series ofbreakthrough curves in a column packed with the adsorbent

Various feed concentrations of the adsorbable compo-nent in an inert carrier are normally used in order to obtainthe isotherm over a large range of concentrations From thebreakthrough curves the adsorbed amount of VOCs for that

Cycle Adsorption Evacuation Purge Pressurization2 VOCs

(dichloromethane andacetone) + N2

2 VOCs(dichloromethane and

acetone) + N2

100 N2mdashFeed

(a)

Cycle

Feed

Adsorption Heating Cooling2 VOCs


100 N2100 N2

(b)

Figure 2 Schematic diagram and sequence of cycle steps in the operation of (a) 1-bed4-step VSA cycle (b) 1-bed3-step TSA cycle for 2VOCs removal


particular operating conditions in equilibrium with gasphase can be deduced according to the following equation

qlowasti

Qfeed

mad1113946

tf

oCo minusC(t)( 1113857dt (19)

where Co and C(t) are the gas-phase concentration of VOCat the inlet and outlet of the column respectively mad is themass of the activated carbon sample Qfeed is the gas flowrate and tf is the adsorption end time

In the latter equation the amounts of VOC in the in-terparticle and in the intraparticle voids per adsorbent massare not considered because they are negligible in comparisonwith the adsorbed amount qlowasti

Figures 3 and 4 show the experimental results relative tothe adsorption equilibrium of pure dichloromethane andacetone on activated carbon at three temperatures (298 313and 323K)

For each experimental isotherm fitted curves obtainedwith the LangmuirndashFreundlich model are represented )efigures show a good agreement between the values given bythe two-parameter (bi and qmi) model and the experimentaldata for the two VOCs at each temperature )e expressionsof parameters bi and qmi in function of temperatureaccording to Equations (6) and (7) are obtained by fitting)e ki parameters for dichloromethane and acetone aregiven in Table 1

42 Breakthrough Curves )e experimental breakthroughcurves for pure solvents vapors of dichloromethane andacetone were determined at different temperatures and inletconcentrations

Figures 5(a) 5(b) and 5(c) show a comparison betweenbreakthrough curves obtained experimentally and by sim-ulation using Aspen Adsorption software for dichloro-methane at atmospheric pressure and for the temperatures298 313 and 323K respectively Inlet concentrationschosen were 500 1000 2000 4000 8000 and 12000 ppm Itshould be mentioned that these breakthrough curves werepreviously used to determine the equilibrium isotherms ofdichloromethane at the different temperatures

Figures 6(a) 6(b) and 6(c) give experimental and the-oretical breakthrough curves of acetone for the sameconditions

It has to be noted that the dynamic mathematical modelsucceeds to predict satisfactorily the experimental data forthe different conditions )is confirms the validity of themathematical model along with the assumptions considered)e mass transfer coefficients kLDF used in the linear drivingmodel for dichloromethane and acetone are assessed byadjusting simulation results to experimental breakthroughcurves )e kinetic parameters (kLDF) obtained for the twoVOCs for adsorption on activated carbon are given inTable 2 )e kLDF value retained corresponds to the mini-mum sum of squares (SS) considering the different break-through curves obtained for the different concentrations(similar to Equation (9))

Figures 7(a) 7(b) 7(c) and 7(d) give breakthroughcurves of binary mixtures of dichloromethane and acetone

on activated carbon for various feed compositions(3000 ppm1500 ppm 2000 ppm500 ppm 500 ppm2000 ppm and 750 ppm400 ppm) at atmospheric pressureand 298K Whatever the composition of the binary mixturedichloromethane is the first compound to breakthrough Asexpected the results corroborate the ability of activatedcarbon to separate the dichloromethane and acetone froma nitrogen stream For simulations the same values of masstransfer coefficients determined previously for pure VOCswere used Although experimental measurements can becarried out they are laborious and time-consuming so it is

0

05

1

15

2

25

3

35

4

0 2000 4000 6000 8000 10000 12000

Adso

rben

t loa

ding

q (m

olK

g)

Concentration (ppmv)

323K

313K

298K

Figure 3 Adsorption isotherms of dichloromethane on activatedcarbon at 298 313 and 323K and at atmospheric pressuresymbols experimental adsorption data solid lines curves fittingsusing extended LangmuirndashFreundlich model

0

1

2

3

4

5

6

0 2000 4000 6000 8000 10000 12000Concentration (ppmv)

323K

313K

298KAd

sorb

ent l

oadi

ng q

(mol

Kg)

Figure 4 Adsorption isotherms of acetone on activated carbon at298 313 and 323K and at atmospheric pressure symbols ex-perimental adsorption data solid lines curves fittings using ex-tended LangmuirndashFreundlich model

Table 1 LangmuirndashFreundlich extended isotherm parameters forthe adsorption of VOCs vapors on activated carbon

Dichloromethane Acetoneqmi (kmolkg) 00051 00044K1 (bar) 0017 0014K2 (K) 32355 416574K3 (minus) 076 082


common practice to predict mixture isotherms from purecomponent isotherms Several models for predicting mixtureisotherms from pure component data have been used themulticomponent LangmuirndashFreundlich model has been usedto predict mixture isotherms herein From Figure 7 one cannote that there is a good agreement between experimental andsimulation results for the different binary mixtures )us thedynamicmathematical model has been validated and could beused safely as a useful tool for optimization purposes of PSAor VSA processes in order to obtain highest achievableperformances under the given constraints It is worthwhile tonote that the dynamic mathematical model could simulateany multicomponent gaseous mixture (more than two)provided that the adsorption equilibrium isotherms of thedifferent components are available

43 VSA Performance )e VSA performance will beassessed via process simulation which is a useful toolallowing time and money savings )e accuracy of simu-lations will depend of course on themathematical modelingand in particular on the validity of assumptions consideredFor the present case the model considered permits to ac-count for all the main mechanisms involved in the process ofadsorption it involves the mass momentum and energybalances that govern the process taking into account theaxial mixing and mass transfer resistances )e resultingmodel which is a system of coupled algebraic and partialdifferential equations over time and space domains is nu-merically solved by Aspen Adsorption software As indicatedpreviously the performance of the VSA process will beevaluated according to product recovery

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

CC 0

Time (s)

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

(a)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000Time (s)

(b)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000Time (s)

(c)

Figure 5 Breakthrough curves for dichloromethane adsorption on activated carbon at (a) 298K (b) 313 K (c) 323K Symbols experimentaldata Lines LDF model


)e aim of simulations is to test the feasibility of the VSAcycle in removing and recovering dichloromethane andacetone from polluted air with activated carbon and find theoptimal operational parameters in order to provide usefulinformation for future industrial design and application)e

simulation results obtained for a one-bed VSA process arerepresented in this section )e conditions of simulations ofthe VSA cycle are summarized in Table 3

)e following simulation results are relative to a feedwhosecomposition is 3000 and 1500ppm for dichloromethane andacetone respectively )e corresponding simulation results areobtained for the cyclic steady state which is attained after nearly10 cycles Figure 8 shows the pressure history at one end of theadsorption column (closed end for pressurization and evac-uation steps) during one cycle at steady state

)e simulated axial profiles of the adsorbed amount ofdichloromethane and acetone at the end of different steps of

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

CC 0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(a)C

C 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(b)

CC 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(c)

Figure 6 Breakthrough curves for acetone adsorption on activated carbon at (a) 298K (b) 313K (c) 323K Symbols experimental dataLines LDF model

Table 2 Mass transfer coefficients kLDF for VOCs vapors fordichloromethane and acetone

VOC kLDF (sminus1)Dichloromethane 0008Acetone 001


the cycle at steady state are given in Figure 9 One can notethat despite the decrease of pressure from 10 (pressureprevailing at the end of the adsorption step) to 05 atm (valueof pressure at the end of the evacuation step) the axialprofiles of the adsorbed amount of dichloromethane andacetone have decreased slightly In fact mass transfer be-tween solid and gas phases which is controlled by intra-particle diffusion being very slow does not permit the twophases to be in equilibrium given the rapid change inpressure

On the contrary the small amount of dichloromethaneand acetone desorbed during the evacuation step due to thepressure decrease results in a notable increase in the con-centration in the gas phase at the end of this step as can beseen in Figure 10 )e concentration of dichloromethane

and acetone has nearly doubled in the saturated zone of thebed passing from 3000 to 6000 ppm for dichloromethaneand from 1500 to 3000 for acetone If the equilibrium modelwas used instead of the linear driving force model to accountfor intraparticle mass transfer resistances the adsorbedamount of dichloromethane obtained at the end of theevacuation step would have been much lower

)e corresponding axial temperature profiles at the endof adsorption evacuation and purge steps are shown inFigure 11 Once again because of the small amount of VOCsdesorbed during the evacuation step the decrease in tem-perature due to desorption during this step is very slightHowever the difference in temperature between the twoends of the bed could reach a value of 10degC (during the purgestep) As can be seen in Figures 3 and 4 giving the adsorption

0

500

1000

1500

2000

2500

3000

3500

0 2000 4000 6000 8000 10000 12000

C 0 (p

pm)

Time (s)

DichloromethaneAcetone

(a)

C 0 (p

pm)

0

500

1000

1500

2000

2500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)


(b)

C (p

pm)


00

500

1000

1500

2000

2500

1000 2000 3000 4000 5000 6000 7000 8000 9000Time (s)

(c)

C 0 (p

pm)


0100200300400500600700800900

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)

(d)

Figure 7 Breakthrough curves of mixtures of dichloromethane and acetone for different compositions (a) 3000 ppm1500 ppm(b) 2000 ppm500 ppm (c) 500 ppm2000 ppm and (d) 750 ppm400 ppm on activated carbon at 298K and atmospheric pressure Symbolsexperimental data Lines LDF model


equilibrium isotherms of dichloromethane and acetone fordifferent temperatures a deviation of 10degC can have a sig-nificant effect on the adsorbed amount of dichloromethaneand acetone )is demonstrates that incorporating energy

balances in modeling is a judicious choice and hencesimulation results of models dealing with VOCs adsorptionassuming isothermal conditions should be considered witha great precaution

Figure 12 gives histories of dichloromethane and acetoneconcentration at the bed exit during evacuation and purgesteps at cyclic steady state )e concentrations of the twoVOCs diminish gradually from the highest values attained atthe end of the evacuation step until values approaching zeroat the end of purge step )e desorbed VOCs in the outletstream could be pumped to a condenser where they could beseparated from N2 and recovered as a liquid )is processinvolves cooling the outlet stream to a temperature below thedew point of each VOC

Table 3 Adsorbent and bed characteristics and operating con-ditions used in the Aspen Adsorption simulations

Parameter ValueNumber of adsorbent bed 1VOC mixture DichloromethaneacetoneConcentration (ppm) 30001500Bed height (m) 1Bed diameter (m) 02Packing density (kgmiddotmminus3) 250Particle diameter (mm) 1Interparticle voidage ε 04Void of pellets εp 036ΔHdichloromethane (kJmol) minus40ΔHacetone (kJmol) minus50Dz (m2middotsminus1) 183 10minus3

hf (Wmiddotmminus2middotKminus1) 56λL (Wmiddotmminus2middotKminus1) 48Feed flow rate (molmin) 20Purge flow rate (molmin) 12Tads (K) 298VSA cycleAdsorption pressure (atm) 1Desorption pressure (atm) 05tad (s) 9000tevac (s) 60tpg (s) 40000tPR (s) 80Cycle time (s) 49140TSA cycleAdsorption pressure (atm) 1Tdes (K) 443tad (s) 9000theat (s) 7600tcool (s) 5500Cycle time (s) 22100

0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV

Figure 8 Pressure history of the adsorption column during onecycle for a VOCs mixture of dichloromethaneacetone(3000 ppm1500 ppm)

002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption

End of evacuationEnd of adsorption End of purge

End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)

Figure 9 Simulated axial profiles of the adsorbed amount ofdichloromethane and acetone at the end of different steps of the cycleat steady state Solid lines dichloromethane and dotted lines acetone

End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0

Figure 10 Simulated axial concentration profiles of dichloro-methane and acetone at the end of different steps of the cycle atsteady state Solid lines dichloromethane and dotted lines acetone


)e improvement of the performance of the VSA cycle isachieved through the optimization of the operating pa-rameters one among these parameters is the adsorption steptime Figure 13 gives the variation of recovery ofdichloromethane and acetone with the adsorption stepduration tad All the operating parameters of the VSA cycleare kept unchanged except for tad Detailed operatingconditions and cycle parameters are given in Table 3According to simulation results it is clear that the VSA unitcan recover completely the two VOCs (100 of dichloro-methane and acetone) for tad equal to 9000 s For this value

of tad only pure N2 exits the bed the two VOCs are totallyretained Adsorbed VOCs are then totally desorbed duringthe subsequent steps (evacuation and purge) thus permit-ting to get a recovery of 100)e recovery of the two VOCsdecreases then gradually when tad increases )is can beexplained by the fact that the two VOCs break through uponsaturation of the bed if tad exceeds 9000 s as shown inFigure 14 giving the change with the adsorption step time ofthe maximum concentration of the two VOCs attained at theoutlet of the column at cyclic steady state )e amount ofVOCs exiting the bed during the adsorption step constitutesa loss and causes a decrease in recovery )e adsorption stepduration should be determined precisely so as not to affectthe recovery and alter the quality of air being purified due tothe breakthrough of VOCs

)e vacuum pressure is also amajor operating parameterin the VSA process and affects significantly its performanceIt has to be noted that more than 70 of the power con-sumption of the VSA cycle is attributed to the vacuum pump[32] )us the evacuation pressure has a tremendous effecton the energy performance of the process and its choiceshould be optimized so as to lower the power consumptionof the system If the vacuum pressure chosen is too low thepower consumption becomes too high On the contrary ifthe vacuum pressure selected is not low enough the du-ration of the purge step will be too long )is depends ofcourse on the shape of the adsorption isotherm )e greaterthe slope of the adsorption isotherm the greater the effect ofthe decrease in pressure on the process performance

Figure 15 shows the variation of purge step time withvacuum pressure For the different simulations the N2molarflow rate is maintained constant (12molmn) and the du-ration of the purge step is chosen so as to obtain a recovery of100 for dichloromethane and acetone )e other param-eters are maintained unchanged (as indicated in Table 3)For Pdes 1 atm the VSA cycle is only composed of two stepsat the same pressure adsorption and purge and there is no

292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL

End of adsorptionEnd of evacuationEnd of purge

Figure 11 Axial Temperature profiles at the end of different stepsof the cycle at steady state

0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)


Figure 12 Histories of dichloromethane and acetone concentra-tion at the bed exit during evacuation and purge steps at cyclicsteady state

96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)


Figure 13 Recovery of dichloromethane and acetone with theadsorption step duration


pressure change For the case being studied decreasing Pdesleads to a substantial decrease in the duration of the step Infact the purge step time is divided by 10 when the vacuumpressure goes from 1 to 01 atm For Pdes 01 atm 16000 sare sufficient to regenerate the bed while 160000 s arenecessary for Pdes 1 atm As expected the vacuum level hasan appreciable effect on the VSA performance However thechoice of the vacuum pressure has an impact on energyconsumption depending on the value of the vacuum pres-sure and also on the duration of the purge step )e higherthe vacuum pressure the shorter the duration of the purgestep but the higher the energy consumption A compromisemust be found between the energy consumption and theduration of the step )e total amount of gas used to purgethe adsorber which is proportional to the duration of thepurge step given that its molar flow rate at the bed inlet isconstant increases with vacuum pressure)e amount of N2

consumed for desorbing the bed increases notably with thevacuum pressure it varies from 3 to 32 kmol when vacuumpressure increases from 01 to 1 atm respectively )evacuum pressure should be carefully chosen in order to bothreduce the energy consumption and shorten the purge stepduration

44 TSA Performance )is section deals with the TSAprocess for the recovery of the same VOCs )e detailedcycle conditions are presented in Table 3 Simulationscarried out show that cyclic steady state of the process isreached after approximately 12 cycles

Figure 16 shows the dichloromethane and acetoneconcentration history at the column outlet during theheating step )e evolution with time of gas temperature atthe exit of the bed for one cycle at cyclic steady state is givenin Figure 17

As can be seen from Figure 16 the increase of the bedtemperature due to heating results in a more rapid re-generation of the bed in comparison with the VSA processIn the case being studied it appears clearly that an increasein temperature during the regeneration step is more efficientthan a decrease of pressure Compared to the concentrationsobtained for a VSA process much higher concentrations ofdichloromethane and acetone are obtained (approximately32000 (6000 for VSA) and 12000 (3000 for VSA) ppm resp))is shows that the desorbed amount of the two VOCs ismore sensitive to a variation of temperature than to a var-iation of pressure

During the heating step the concentration waves of the 2VOCs and temperature wave propagate together through thecolumn In terms of desorption the higher temperature isthe weaker the van der Waals forces between VOCs and thesurface of activated carbon becomes which leads to anincreasing regeneration at high desorption temperatureSince desorption temperature is the most important factorconcerning the performance of the regeneration step theeffects of this operating parameter on recovery are in-vestigated for the TSA process Figure 18 shows the variationof the heating step duration versus desorption temperatureFor the various simulations the hot nitrogen stream used inthe heating step is maintained constant (12molmin) and thenecessary duration of this step is optimized to totally recoverthe 2 VOCs (100 recovery) Also all the operating pa-rameters of the 3-step TSA cycle (as indicated in Table 3) arekept unchanged except for Tdes and theat

When desorption temperature increases from 403 to443K the purge duration decreases from 8600 to 7600 s)ecorresponding N2 amount consumed for the regeneration ofthe column decreases slightly from 172 to 152 kmol )esevalues are much lower than those obtained for the VSAprocess

)e simulation results obtained for the VSA and TSAprocesses show that it is possible to achieve highdichloromethane and acetone recovery (a value of 100 forthe 2 VOCs could be obtained)

For the VSA process it has been shown that the durationof the regeneration step for a 100 recovery of the two

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)

Figure 15 Variation of purge step time with vacuum pressure formixtures dichloromethaneacetone vapor at 3000 ppm1500 ppmexposure concentration

Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)


Figure 14 Maximum concentration of dichloromethane and ac-etone at the end the adsorption step for different


VOCs varies from 20000 to 160000 s for desorption pres-sures varying from 01 to 1 atm (Figure 15) For the TSAprocess the regeneration step durations vary from 8600 to7600 s when the desorption temperature changes from 403to 443K at a pressure of 1 atm )us there is a substantialdecrease in the total duration of the TSA cycle compared to

the VSA cycle Regeneration by hot nitrogen stream seems tobe more efficient than regeneration by reducing pressure

5 Conclusion

Volatile organic compounds are air pollutants that should beremoved to avoid serious effects on human health andenvironment A particular interest has been given to therecovery of dichloromethane and acetone used as solvents inoil sands process for extraction of bitumen Experimentaladsorption isotherms of the two VOCs are determined atthree different temperatures by the dynamic columnbreakthrough method )e developed simulation modelusing Aspen Adsorption software has been used successfullyto predict the experimental breakthrough curves for pureVOCs and different binary mixtures for various conditions)e mass transfer coefficients kLDF used in the linear drivingmodel for dichloromethane and acetone are assessed byadjusting simulation results to experimental breakthroughcurves )e validated simulation model has been used foroptimizing vacuum and temperature swing adsorptionprocesses so as to achieve the highest performances Em-phasis has been given to the effect of many operating pa-rameters that is the adsorption step duration the vacuumpressure and the desorption temperature on the recovery ofdichloromethane and acetone It has been shown that a re-covery of 100 of the two VOCs could be attained Howeverthe adsorption step duration should be determined preciselyso as not to affect the recovery and alter the quality of airbeing purified due to the breakthrough of VOCs )evacuum pressure and the desorption temperature should becarefully chosen in order to both reduce the energy con-sumption and shorten the purge step duration It has to benoted that regeneration by hot nitrogen stream is moreefficient than regeneration by reducing pressure

Nomenclature

as Express the ratio of the particle externalsurface area to volume m2middotmminus3

B LangmuirndashFreundlich equation parameterC Concentration of the VOC molmiddotmminus3Cps Heat capacity of the adsorbent Jmiddotkgminus1middotKminus1CO Initial inlet concentration ppmCpg Gas heat capacity Jmiddotkgminus1middotKminus1Dp Particle diameter mdint Column internal diameter mDe Effective diffusivity of the VOC m2middotsminus1Dz Axial dispersion coefficient m2middotsminus1

k1 k2 k3 LangmuirndashFreundlich equation parameterkLDF Mass transfer coefficient sminus1Kg Gas thermal conductivity Wmiddotmminus1middotKminus1ks Effective axial solid phase thermal

conductivity Wmiddotmminus2middotKminus1hf Film heat transfer Wmiddotmminus2middotKminus1L Bed height mmad Mass of the sample of activated carbon in the

bed gQ Average adsorbed concentration molmiddotkgminus1

7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)

Figure 18 Variations of heat duration step versus desorptiontemperature

295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III

Figure 16 Gas temperature history along the bed during one cycle

0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)


Figure 17 Concentration of dichloromethane and acetone profilesat the column outlet during the heating step


qlowast Equilibrium adsorption concentrationmolmiddotkgminus1

Qm Adsorption capacity of the amount molmiddotkgminus1Rp Particle radius mP Pressure PaPad Feed pressure in adsorption step atmPdes Vacuum pressure in evacuation and purge

step atm_Qfeed Molar flow molmiddotminminus1_Qpg Molar flow of purge step molmiddotminminus1t Time stf Adsorption end time mintad Adsorption step time stcool Cool step time stevac Evacuation step time stheat Heat step time stpg Purge step time stPR Pressurization step time sT Temperature KTad Adsorption temperature KTdes Desorption temperature KZ Axial co-ordinate along the bed mυg Interstitial velocity mmiddotsminus1


ρg Gas density kgmiddotmminus3ρp Particle density kgmiddotmminus3ε Void fractionεp Void of pelletsmicro Dynamic viscosity PamiddotsλL Axial heat dispersion Wmiddotmminus2middotKminus1ΔH Isosteric heat of adsorption Jmiddotmolminus1I ComponentJ ComponentI II III VI Step numbers

Data Availability

)e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

)e authors declare that they have no conflicts of interest

References

[1] F I Khan and A K Ghosal ldquoRemoval of volatile organiccompounds from polluted airrdquo Journal of Loss Prevention inthe Process Industries vol 13 no 6 pp 527ndash45 2000

[2] I K Shah P Pre and B J Alappat ldquoEffect of thermal re-generation of spent activated carbon on volatile organiccompound adsorption performancesrdquo Journal of the TaiwanInstitute of Chemical Engineers vol 45 no 4 pp 1733ndash17382014

[3] J Read D Whiteoak and S Bitumen Ce Shell BitumenHandbook )omas Telford Publishers London UK 5thedition 2003

[4] J Sundell ldquoOn the history of indoor air quality and healthrdquoIndoor Air vol 14 no s7 pp 51ndash58 2004

[5] T Dobre O C Parvulescu A Jacquemet and V A IonldquoAdsorption and thermal desorption of volatile organiccompounds in a fixed bedmdashexperimental and modellingrdquoChemical Engineering Communications vol 203 no 12pp 1554ndash1561 2016

[6] G S Cooper C S Scott and A S Bale ldquoInsights fromepidemiology into dichloromethane and cancer riskrdquo In-ternational Journal of Environmental Research and PublicHealth vol 8 no 8 pp 3380ndash3398 2011

[7] P M Bos M J Zeilmaker and J C van Eijkeren ldquoAp-plication of physiologically based pharmacokinetic model-ing in setting acute exposure guideline levels for methylenechloriderdquo Toxicological Sciences vol 91 no 2 pp 576ndash5852006

[8] F Zeinali A A Ghoreyshi and G D Najafpour ldquoAdsorptionof dichloromethane from aqueous phase using granular ac-tivated carbon isotherm and breakthrough curve measur-mentsrdquo Middle-East Journal of Scientific Research vol 5no 4 pp 191ndash198 2010

[9] L Gales A Mendes and C Costa ldquoEquilibrium and heat ofadsorption for organic vapors and activated carbonsrdquoCarbonvol 38 no 7 pp 1083ndash1088 2000

[10] C Long Y Li W Yu and A Li ldquoRemoval of benzene andmethyl ethyl ketone vapor comparison of hypercross linkedpolymeric adsorbent with activated carbonrdquo Journal ofHazardous Materials vol 203-204 pp 251ndash256 2012

[11] L Fournel P Mocho R Brown and P le Cloirec ldquoModelingbreakthrough curves of volatile organic compounds on ac-tivated carbon fibersrdquo Adsorption vol 16 no 3 pp 147ndash1532010

[12] C A Grande ldquoAdvances in pressure swing adsorption for gasseparationrdquo ISRN Chemical Engineering vol 2012 Article ID982934 13 pages 2012

[13] K Rambabu L Muruganandam and S Velu ldquoCFD Simu-lation for separation of carbon dioxide-methane mixture bypressure swing adsorptionrdquo International Journal of ChemicalEngineering vol 2014 Article ID 402756 7 pages 2014

[14] J A Wurzbacher C Gebald and A Steinfeld ldquoSeparation ofCO2 from air by temperature vacuum swing adsorption usingdiamine-functionalized silica gelrdquo Energy amp EnvironmentalScience vol 4 no 9 p 3584 2011

[15] A L Chaffee G P Knowles Z Liang J Zhang P Xiao andP A Webley ldquoCO2 capture by adsorption material andprocess developmentrdquo International Journal of GreenhouseGas Control vol 1 no 1 pp 11ndash18 2007

[16] F Salvador N Martin-Sanchez R Sanchez-HernandezM J Sanchez-Montero and C Izquierdo ldquoRegeneration ofcarbonaceous adsorbents Part I thermal regenerationrdquoMicroporous andMesoporousMaterials vol 202 pp 259ndash2762015

[17] M A Sidheswarana H Destaillats D P Sullivan S CohnandW J Fisk ldquoEnergy efficient indoor VOC air cleaning withactivated carbonfiber (ACF) filtersrdquo Building and Environ-ment vol 47 pp 357ndash367 2011

[18] M J Jeon and Y W Jeon ldquoCharacteristic evaluation of ac-tivated carbon applied to a pilot-scale VSA system to controlVOCsrdquo Process Safety and Environment Protection vol 112pp 327ndash334 2017

[19] A Kane S Giraudet J B Vilmain and P Le Cloirec ldquoIn-tensification of the temperature swing adsorption processwith a heat pump for the recovery of dichloromethanerdquoJournal of Environmental Chemical Engineering vol 3 no 2pp 734ndash743 2015


[20] K S Hwang D K Choi S Y Gong and S Y Cho ldquoAd-sorption and thermal regeneration of methylene chloridevapor on activated carbon bedrdquo Chemical Engineering andProcessing vol 46 pp 1111ndash1123 1998

[21] L Li Z Liu Y Qin Z Sun J Song and L Tang ldquoEstimationof volatile organic compound mass transfer coefficients in thevacuum desorption of acetone from activated carbonrdquoJournal of Chemical amp Engineering Data vol 55 no 11pp 4732ndash4740 2010

[22] S Brunauer P H Emmett and E Teller ldquoAdsorption of gasesin multimolecular layersrdquo Journal of the American ChemicalSociety vol 60 no 2 pp 309ndash319 1938

[23] J A Delgada and A E Rodrigues ldquoAnalysis of the boundaryconditions for the simulation of the pressure equalization stepin PSA cyclesrdquo Chemical Engineering Science vol 63 no 18pp 4452ndash4463 2008

[24] M F Edwards and J F Richardson ldquoGas dispersion in packedbedsrdquo Chemical Engineering Science vol 23 no 2 pp 109ndash123 1968

[25] R B Bird W E Stewart and E N Lightfoot ldquoTransportphenomenardquo AIChE Journal vol 7 no 2 pp 5J-6J 1961

[26] M Lei C Vallires G Grevillot and M A Latifi ldquoModelingand simulation of a thermal swing adsorption process for CO2capture and recoveryrdquo Industrial and Engineering ChemistryResearch vol 52 no 22 pp 7526ndash7533 2013

[27] J Xiao Y Peng P Benard and R Chahine ldquo)ermal effectson breakthrough curves of pressure swing adsorption forhydrogen purificationrdquo International Journal of HydrogenEnergy vol 41 no 19 pp 8236ndash8245 2015

[28] F Rezaei S Subramanian J Kalyanaraman R P LivelyY Kawajiri and M J Realff ldquoModeling of rapid temperatureswing adsorption using hollow fiber sorbentsrdquo ChemicalEngineering Science vol 113 pp 62ndash76 2014

[29] A P D Wasch and G F Froment ldquoHeat transfer in packedbedsrdquo Chemical Engineering Science vol 27 no 3 pp 567ndash576 1972

[30] S Yagi D Kunii and N Wakao ldquoStudies on axial effectivethermal conductivities in packed bedsrdquo AIChE Journal vol 6no 4 pp 543ndash546 1960

[31] K Daeho S Ranjani and T B Lorenz ldquoOptimization ofpressure swing adsorption and fractionated vacuum pressureswing adsorption processes for CO2 capturerdquo Industrial ampEngineering Chemistry Research vol 44 pp 8084ndash8094 2005

[32] J Zhang P A Webley and P Xiao ldquoEffect of process pa-rameters on power requirements of vacuum swing adsorptiontechnology for CO2 capture from flue gasrdquo Energy Conversionand Management vol 49 no 2 pp 346ndash356 2008


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excessive ozone levels can include damage to the ecosystemincluding the retardation of plant growth and crop yields [4]

Being a precursor of photochemical oxidants eye irritantand a suspected toxicant of respiratory gastrointestinal andnervous system acetone may have detrimental effects onhuman health and environment [5] Human studies haveobserved associations between occupational exposure todichloromethane and increased risk for several specificcancers including brain cancer liver and biliary tract cancernon-Hodgkin lymphoma and multiple myeloma [6]

Results from experimental studies in humans indicatethat acute neurobehavioral deficits measured for exampleby psychomotor tasks tests of hand-eye coordination visualevoked response changes and auditory vigilance may occurat concentrations gt200 ppm with 4ndash8 hr of exposure [7]

As a result the control of dichloromethane acetone andany VOC exhausts in ambient air is considered imperative

)ere are several methods used to reduce the VOCs suchas absorption adsorption incineration catalytic oxidationbiological treatment ionization photocatalysis Adsorptiononto activated carbon is a highly efficient and relativelyinexpensive technique employed for the removal and re-covery of VOCs from air [8ndash11]

)e most known cyclic adsorption operation is pressureswing adsorption (PSA) [12 13] vacuum swing adsorption(VSA) and temperature swing adsorption (TSA) [14 15])e difference between these processes is their adsorptionand regeneration mode In TSA processes the temperaturechanges in each step with the low temperature upon ad-sorption and the high temperature in regeneration )e PSAtechnique depends on the pressure where the adsorptionstep is carried out at the high pressure and the regenerationoperation is at atmospheric pressure

Many studies of PSA TSA and VSA have been widelyinvestigated for recovery of VOCs from polluted air streams[16ndash18] )ere are more papers dealing with dichloro-methane [19 20] than acetone [21] Each VOC is treatedseparately and works dealing with mixtures of the two VOCsare lacking in the literature In general these works are justlimited to the experimental determination of breakthroughcurves and experiments of regeneration the cyclic steadystate is not considered Furthermore the models used forsimulation often use simplifying assumptions such as neg-ligible pressure drop isothermal conditions

It has to be noted that the adsorption step of VOCs hasbeen widely studied in the literature for different objectives(selection of the appropriate adsorbent effect of operatingconditions) However the regeneration step has been rarelyinvestigated despite its importance for the performance ofthe whole process Regeneration could be done by reducingthe pressure or increasing the temperature Regeneration iscrucial so as to ensure that the adsorption process remainsattractive in comparison with other processes It has a no-table effect on the duration of the total cycle and henceaffects the size and the number of beds of the purificationinstallation

)e principal aim of this work is to design an adsorptionbased separation process (Vacuum Swing Adsorption andtemperature swing adsorption) for recovering two VOCs

that is dichloromethane and acetone used extensively inoil sands process )e design of the process involves ex-perimental determination of equilibrium isotherms of thetwo VOCs on a commercial activated carbon using thedynamic column breakthrough method and the realizationof a simulation tool )e validated simulation tool con-sidering minimum simplifying assumptions is to be usedfor testing the technical feasibility and optimizing the VSAand TSA process through varying the operating parame-ters Results of simulations should give elements of re-sponses concerning the most appropriate process to beused for the present case that is the capture of acetone anddichloromethane

2 Experiments

)e adsorbent used is a commercial activated carbon sup-plied by CECA (Communaute Europeenne pour le Charbonet lrsquoAcier) it is of plant origin and precisely of maritime pine

)e apparent density and the BET Surface are 250 kgmiddotm3

and 1706m2middotgminus1 respectively)e specific surface area of theadsorbent is determined by measuring a N2 isotherm at 77Kusing an ASAP 2020 apparatus from Micromeritics )especific surface area is calculated according to the BETmethod [22]

)e measurements of pure species adsorption equilib-rium isotherms and breakthrough curves of pure compo-nents and binary mixtures of VOCs vapors are performedwith a dynamic adsorption unit

Figure 1 shows the experimental setup used VOCs at theliquid state (a pure component or a binary mixture) areinjected by one or two syringe pumps in the vaporizationcolumn At the exit of the column the liquid is completelyvaporized

A continuous nitrogen gas stream (inert gas) fixed bya mass flow controller (Brooks Instruments) is introduced inthe unit Nitrogen is then mixed with the VOCs vaporexiting the vaporization column before entering the ad-sorption column at a superficial velocity of 017mmiddotsminus1 )eamount of activated carbon packed in the column is 2 gExperiments are carried out at atmospheric pressure anda temperature of 25degC )e column is made of stainless steeland has a height of 10 cm and an internal diameter of 1 cm)e temperature of experiments is controlled by a thermo-static enclosure Pure components isotherms are determinedfor concentrations ranging from 500 to 12000 ppm on ac-tivated carbon at atmospheric pressure and at three tem-peratures 298K 313K and 323K Breakthrough curves forsingle solvent vapor of dichloromethane and acetone arecarried out at 298K 313K and 323K under atmosphericpressure Concentrations of solvent vapors at the inlet of thebed are set from 500 to 12000 ppm

Four different breakthrough curves of dichloromethaneacetone vapor mixtures at various inlet concentrations3000 ppm1500ppm 2000ppm500 ppm 500 ppm2000 ppmand 750 ppm400 ppm are performed on activated carbon at298K and at atmospheric pressure

)e variation of VOCs concentrations with time atthe exit of the adsorption bed are measured by a Gas









particle


minusDz

z2ci

zZ2 +zci

zt+

z υgci1113872 1113873

zZ+

(1minus ε)ε

ρpzqi

zt 0 i 1 2 (1)


zC

zt+

z υgC1113872 1113873

zZ+

(1minus ε)ε

ρp 1113944

n

i1

zqi

zt 0 (2)


Dz 073Dm + 05dpμi

1 + 97 Dmdpμi1113872 1113873 (3)



zP

zZ 150

(1minus ε)2

ε2d2p


ρgυ2g (4)



zqi

zt kiLDF q


where

kiLDF 15Dei

r2p (6)



4

12

5

6

3

7

GC with FIDanalysis

8

9




qlowasti qmi

biCi( 1113857k3i

1 + 1113936j bjCj1113872 1113873k3i

i j 1 2 (7)

bi k1i expk2i

T (8)



SS() 1113944

T3

Ti

1113944

N


2 (9)



CpgρgzTg

ztminus λL

z2Tg

zZ2 + ρgCpgz υgTg1113872 1113873

zZ+

1minus εε

1113874 1113875ashf Tg minusTs1113872 1113873

+4hw


(10)



Nug 2 + 1 1Re06Pr13 (11)

Nug hfdp

kg (12)

Re ρgυgdp

μ (13)

Pr Cpgυg

kg (14)


λL DZCpgρg (15)


minusksz2Ts

zz2 + ρpCpszTs


n


zqi

zt

(16)

















III0 ciυ|zL dt

1113938I0 ciυ|z0 dt + 1113938

IV0 ciυ|z0 dt

(17)



1113938I0 ciυ|z0 dt

(18)








acetone) + N2

100 N2mdashFeed

(a)

Cycle

Feed



100 N2100 N2

(b)




qlowasti

Qfeed

mad1113946

tf












0

05

1

15

2

25

3

35

4

0 2000 4000 6000 8000 10000 12000

Adso

rben

t loa

ding

q (m

olK

g)


323K

313K

298K


0

1

2

3

4

5

6


323K

313K

298KAd

sorb

ent l

oadi

ng q

(mol

Kg)







0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

CC 0

Time (s)

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

(a)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000Time (s)

(b)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000Time (s)

(c)







0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

CC 0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(a)C

C 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(b)

CC 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(c)









0

500

1000

1500

2000

2500

3000

3500

0 2000 4000 6000 8000 10000 12000

C 0 (p

pm)

Time (s)


(a)

C 0 (p

pm)

0

500

1000

1500

2000

2500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)


(b)

C (p

pm)


00

500

1000

1500

2000

2500

1000 2000 3000 4000 5000 6000 7000 8000 9000Time (s)

(c)

C 0 (p

pm)


0100200300400500600700800900

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)

(d)









0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV


002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption


End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)


End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0







292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia









particle


minusDz

z2ci

zZ2 +zci

zt+

z υgci1113872 1113873

zZ+

(1minus ε)ε

ρpzqi

zt 0 i 1 2 (1)


zC

zt+

z υgC1113872 1113873

zZ+

(1minus ε)ε

ρp 1113944

n

i1

zqi

zt 0 (2)


Dz 073Dm + 05dpμi

1 + 97 Dmdpμi1113872 1113873 (3)



zP

zZ 150

(1minus ε)2

ε2d2p


ρgυ2g (4)



zqi

zt kiLDF q


where

kiLDF 15Dei

r2p (6)



4

12

5

6

3

7

GC with FIDanalysis

8

9




qlowasti qmi

biCi( 1113857k3i

1 + 1113936j bjCj1113872 1113873k3i

i j 1 2 (7)

bi k1i expk2i

T (8)



SS() 1113944

T3

Ti

1113944

N


2 (9)



CpgρgzTg

ztminus λL

z2Tg

zZ2 + ρgCpgz υgTg1113872 1113873

zZ+

1minus εε

1113874 1113875ashf Tg minusTs1113872 1113873

+4hw


(10)



Nug 2 + 1 1Re06Pr13 (11)

Nug hfdp

kg (12)

Re ρgυgdp

μ (13)

Pr Cpgυg

kg (14)


λL DZCpgρg (15)


minusksz2Ts

zz2 + ρpCpszTs


n


zqi

zt

(16)

















III0 ciυ|zL dt

1113938I0 ciυ|z0 dt + 1113938

IV0 ciυ|z0 dt

(17)



1113938I0 ciυ|z0 dt

(18)








acetone) + N2

100 N2mdashFeed

(a)

Cycle

Feed



100 N2100 N2

(b)




qlowasti

Qfeed

mad1113946

tf












0

05

1

15

2

25

3

35

4

0 2000 4000 6000 8000 10000 12000

Adso

rben

t loa

ding

q (m

olK

g)


323K

313K

298K


0

1

2

3

4

5

6


323K

313K

298KAd

sorb

ent l

oadi

ng q

(mol

Kg)







0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

CC 0

Time (s)

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

(a)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000Time (s)

(b)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000Time (s)

(c)







0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

CC 0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(a)C

C 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(b)

CC 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(c)









0

500

1000

1500

2000

2500

3000

3500

0 2000 4000 6000 8000 10000 12000

C 0 (p

pm)

Time (s)


(a)

C 0 (p

pm)

0

500

1000

1500

2000

2500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)


(b)

C (p

pm)


00

500

1000

1500

2000

2500

1000 2000 3000 4000 5000 6000 7000 8000 9000Time (s)

(c)

C 0 (p

pm)


0100200300400500600700800900

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)

(d)









0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV


002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption


End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)


End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0







292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



qlowasti qmi

biCi( 1113857k3i

1 + 1113936j bjCj1113872 1113873k3i

i j 1 2 (7)

bi k1i expk2i

T (8)



SS() 1113944

T3

Ti

1113944

N


2 (9)



CpgρgzTg

ztminus λL

z2Tg

zZ2 + ρgCpgz υgTg1113872 1113873

zZ+

1minus εε

1113874 1113875ashf Tg minusTs1113872 1113873

+4hw


(10)



Nug 2 + 1 1Re06Pr13 (11)

Nug hfdp

kg (12)

Re ρgυgdp

μ (13)

Pr Cpgυg

kg (14)


λL DZCpgρg (15)


minusksz2Ts

zz2 + ρpCpszTs


n


zqi

zt

(16)

















III0 ciυ|zL dt

1113938I0 ciυ|z0 dt + 1113938

IV0 ciυ|z0 dt

(17)



1113938I0 ciυ|z0 dt

(18)








acetone) + N2

100 N2mdashFeed

(a)

Cycle

Feed



100 N2100 N2

(b)




qlowasti

Qfeed

mad1113946

tf












0

05

1

15

2

25

3

35

4

0 2000 4000 6000 8000 10000 12000

Adso

rben

t loa

ding

q (m

olK

g)


323K

313K

298K


0

1

2

3

4

5

6


323K

313K

298KAd

sorb

ent l

oadi

ng q

(mol

Kg)







0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

CC 0

Time (s)

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

(a)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000Time (s)

(b)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000Time (s)

(c)







0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

CC 0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(a)C

C 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(b)

CC 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(c)









0

500

1000

1500

2000

2500

3000

3500

0 2000 4000 6000 8000 10000 12000

C 0 (p

pm)

Time (s)


(a)

C 0 (p

pm)

0

500

1000

1500

2000

2500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)


(b)

C (p

pm)


00

500

1000

1500

2000

2500

1000 2000 3000 4000 5000 6000 7000 8000 9000Time (s)

(c)

C 0 (p

pm)


0100200300400500600700800900

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)

(d)









0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV


002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption


End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)


End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0







292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia











III0 ciυ|zL dt

1113938I0 ciυ|z0 dt + 1113938

IV0 ciυ|z0 dt

(17)



1113938I0 ciυ|z0 dt

(18)








acetone) + N2

100 N2mdashFeed

(a)

Cycle

Feed



100 N2100 N2

(b)




qlowasti

Qfeed

mad1113946

tf












0

05

1

15

2

25

3

35

4

0 2000 4000 6000 8000 10000 12000

Adso

rben

t loa

ding

q (m

olK

g)


323K

313K

298K


0

1

2

3

4

5

6


323K

313K

298KAd

sorb

ent l

oadi

ng q

(mol

Kg)







0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

CC 0

Time (s)

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

(a)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000Time (s)

(b)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000Time (s)

(c)







0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

CC 0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(a)C

C 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(b)

CC 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(c)









0

500

1000

1500

2000

2500

3000

3500

0 2000 4000 6000 8000 10000 12000

C 0 (p

pm)

Time (s)


(a)

C 0 (p

pm)

0

500

1000

1500

2000

2500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)


(b)

C (p

pm)


00

500

1000

1500

2000

2500

1000 2000 3000 4000 5000 6000 7000 8000 9000Time (s)

(c)

C 0 (p

pm)


0100200300400500600700800900

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)

(d)









0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV


002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption


End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)


End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0







292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



qlowasti

Qfeed

mad1113946

tf












0

05

1

15

2

25

3

35

4

0 2000 4000 6000 8000 10000 12000

Adso

rben

t loa

ding

q (m

olK

g)


323K

313K

298K


0

1

2

3

4

5

6


323K

313K

298KAd

sorb

ent l

oadi

ng q

(mol

Kg)







0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

CC 0

Time (s)

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

(a)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000Time (s)

(b)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000Time (s)

(c)







0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

CC 0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(a)C

C 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(b)

CC 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(c)









0

500

1000

1500

2000

2500

3000

3500

0 2000 4000 6000 8000 10000 12000

C 0 (p

pm)

Time (s)


(a)

C 0 (p

pm)

0

500

1000

1500

2000

2500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)


(b)

C (p

pm)


00

500

1000

1500

2000

2500

1000 2000 3000 4000 5000 6000 7000 8000 9000Time (s)

(c)

C 0 (p

pm)


0100200300400500600700800900

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)

(d)









0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV


002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption


End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)


End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0







292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

CC 0

Time (s)

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

(a)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000 6000 7000Time (s)

(b)

CC 0

500 ppm

1000 ppm4000 ppm 2000 ppm

8000 ppm

12000 ppm

0

02

04

06

08

1

12

0 1000 2000 3000 4000 5000Time (s)

(c)







0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

CC 0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(a)C

C 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(b)

CC 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(c)









0

500

1000

1500

2000

2500

3000

3500

0 2000 4000 6000 8000 10000 12000

C 0 (p

pm)

Time (s)


(a)

C 0 (p

pm)

0

500

1000

1500

2000

2500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)


(b)

C (p

pm)


00

500

1000

1500

2000

2500

1000 2000 3000 4000 5000 6000 7000 8000 9000Time (s)

(c)

C 0 (p

pm)


0100200300400500600700800900

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)

(d)









0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV


002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption


End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)


End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0







292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia






0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

CC 0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(a)C

C 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

1200

0

1300

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(b)

CC 0

0

02

04

06

08

1

12

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1000

0

1100

0

Time (s)

500 ppm

1000 ppm2000 ppm4000 ppm8000 ppm

12000 ppm

(c)









0

500

1000

1500

2000

2500

3000

3500

0 2000 4000 6000 8000 10000 12000

C 0 (p

pm)

Time (s)


(a)

C 0 (p

pm)

0

500

1000

1500

2000

2500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)


(b)

C (p

pm)


00

500

1000

1500

2000

2500

1000 2000 3000 4000 5000 6000 7000 8000 9000Time (s)

(c)

C 0 (p

pm)


0100200300400500600700800900

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)

(d)









0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV


002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption


End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)


End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0







292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia






0

500

1000

1500

2000

2500

3000

3500

0 2000 4000 6000 8000 10000 12000

C 0 (p

pm)

Time (s)


(a)

C 0 (p

pm)

0

500

1000

1500

2000

2500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)


(b)

C (p

pm)


00

500

1000

1500

2000

2500

1000 2000 3000 4000 5000 6000 7000 8000 9000Time (s)

(c)

C 0 (p

pm)


0100200300400500600700800900

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (s)

(d)









0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV


002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption


End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)


End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0







292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia








0

02

04

06

08

1

12

0 10000 20000 30000 40000 50000

Pres

sure

(atm

)

Time (s)

I II III IV


002040608

112141618

2

0 01 02 03 04 05 06 07 08 09 1ZZ0

End of adsorption


End of evacuation

End of purge

Adso

rptio

n ca

paci

ty (m

olK

g)


End of adsorption


End of evacuation

End of purge

0

1000

2000

3000

4000

5000

6000

7000

0 01 02 03 04 05 06 07 08 09 1

Con

cent

ratio

n (p

pm)

ZZ0







292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia






292

294

296

298

300

302

304

0 01 02 03 04 05 06 07 08 09 1

Tem

pera

ture

(K)

ZL



0

1000

2000

3000

4000

5000

6000

7000

1071

81

1121

81

1171

81

1221

81

1271

81

1321

81

1371

81

1421

81

1471

81

Con

cent

ratio

n (p

pm)

Time (s)



96

97

98

99

100

9000 9500 10000 10500 11000 11500 12000

Reco

very

()

Adsorption time (s)













0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia











0

20000

40000

60000

80000

100000

120000

140000

160000

180000

0 01 02 03 04 05 06 07 08 09 1

Purg

e ste

p tim

e (s)

Pdes (atm)


Con

cent

ratio

n of

dic

hlor

omet

hane

(ppm

)

0

002

004

006

008

01

012

014

016

0

20

40

60

80

100

120

140

9000 9500 10000 10500 11000 11500 12000

Con

cent

ratio

n of

acet

one (

ppm

)

Adsorption time (s)






5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




5 Conclusion


Nomenclature






7400

7600

7800

8000

8200

8400

8600

8800

120 130 140 150 160 170 180

Hea

ting

step

time (

s)

Tdes (K)


295

315

335

355

375

395

415

435

455

0 5000 10000 15000 20000

T (K

)

Time (s)

I II III


0

5000

10000

15000

20000

25000

30000

35000

9000 10000 11000 12000 13000 14000 15000 16000 17000

Con

cent

ratio

n (p

pm)

Time (s)









Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia







Data Availability




References





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia


















RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia


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