adsorption kinetics and modeling of cu(ii) ion sorption from aqueous solution by mercaptoacetic acid...

8/11/2019 ADSORPTION KINETICS AND MODELING OF CU(II) ION SORPTION FROM AQUEOUS SOLUTION BY MERCAPTOACETIC

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ISSN: 1573-4377

ADSORPTION KINETICS AND MODELING OF CU(II) ION

SORPTION FROM AQUEOUS SOLUTION BY MERCAPTOACETIC

ACID MODIFIED CASSAVA (MANIHOT SCULENTA CRANZ)

WASTES

A.A. Augustine*, B.D. Orike and A.D Edidiong

Department of Pure and Industrial Chemistry, University of Port Harcourt, P. M. B. 5323,Choba Port Harcourt, Nigeria.

ABSTRACT

The rate of removal of Cu(II) ions from aqueous solution by mercaptoacetic acid modified

cassava wastes (0.5MCF and 1.0MCF) was studied in batch conditions. The rate of sorptionof copper was rapid initially within 5-15 minutes and reached a maximum in 30 minutes.

Kinetic modeling analysis of the Elovich, pseudo-first order, pseudo-second order,intraparticle diffusion, mass transfer and intraparticle diffusivity equations using the linear

coefficient of determination r2 values showed that the pseudo-second order equation was the

most appropriate model for the description of Cu(II) transport. Thus the sorption of Cu(II)ion can be said to follow a pseudo-second order model, with chemical sorption as its ratelimiting step. The initial adsorption rate values were: 2.94 x 10-1 and 2.60 x 10-1 mg.g-

1.min-1 for 0.5MCF and 1.0MCF adsorbents respectively.

KEYWORDS:

Copper, kinetic modeling, sorption, cassava waste, mercaptoacetic acid.

INTRODUCTION

The increased level of environmental contamination as a consequence of industrial

development is posing a very serious problem to the global environment. Industrial processfor extracting metals or, more generally, all processes involving metals in their productive

cycle generate significant heavy metal cations [1]. Mine drainage, metal industries, refining,electroplating, dye and leather industries, domestic effluents, land fill leachate, and

agricultural run off all generate wastewater that contain heavy metal ions [2]

The presence of these heavy metals in the environment has led to a number of environmentalproblems. Since most of these heavy metal are non-degradable into nontoxic end products,


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Augustine et al. EJEAFChe, 6 (4), 2007. [2221-2234]

2222

their concentrations in effluents must therefore be reduced to acceptable levels before

discharging them into the environment. Otherwise these metal ions could pose threats topublic health and or affect the aesthetic quality of potable water. According to World Health

Organisation (WHO), the metals of most immediate concern are chromium, copper, zinc,iron, cadmium and lead [3].

Since copper is a widely used material, there are many actual or potential sources of copperpollution. Copper is used in Jewelry, paints, pharmaceutical products, wood preservatives,pigments, metal works, petroleum refinery, motor vehicle and aircraft plating and finishing.

Also copper may be found as a contaminant in food, especially shellfish, liver, mushroom,nuts and chocolate. In addition, any processing method or container using copper material

may contaminate the product, such as food, water or drink [4].

Copper is essential to human life and is required for various biological processes, but like allheavy metals, is potentially toxic as well [5].

In order to solve the problems of heavy metal pollution in the ecosystem, it is important to

bring pragmatic solutions to the issue. There are several methods for treatment of metalcontaminated effluents such as precipitation, ion exchange, membrane processes and

adsorption. Since the selection of wastewater treatment methods is based on theconcentration of waste and the cost of treatment, adsorption is often the method of choice for

removal of heavy metals from wastewater [6].

Furthermore, to enhance the cost effectiveness of the adsorption process for heavy metaltreatment, various agricultural by-products have been developed as low-cost sorbents.

These include: groundnut husk [7], shea butter seed husk [8], wild cocoyam [9], palmkernel fibre [10] and fluted pumpkin [II]

In this study, an agricultural by-product, cassava waste in its chemically modified formwhich is obtained from the processing of cassava tuber (Manihot sculenta cranz) a staplefood in Nigeria will be used to remove Cu(II) ions from aqueous solution. Interest in this

work will be on the kinetics of Cu(II) ion removal. This is because sorption kinetics is animportant parameter in wastewater treatment. Since sorption kinetics can be used to predict

the rate of pollutant removal from aqueous solutions in the design of appropriate sorptiontreatment plants [12]. The different kinetic models that will be used to analyse the kinetic

data for Cu(II) ion sorption are, pseudo-first order [13], the pseudo-second order [14],Elovich [15-16], mass transfer [17], intra-particle diffusion [18-19] and intra-particle

diffusivity [20].

MATERIALS AND METHODSAdsorbent

Cassava fibre waste obtained from the processing of cassava into the staple food garri wasobtained from a cassava processing mill in a village near Port Harcourt, Rivers State,

Nigeria. The cassava fibre waste was airdried and ground using a wiley mill grinder. Thepowdered cassava fibre was washed with deionized water and wet sieved through a set of

sieves (106 and 105m) and airdried.


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Dissolutions

All reagents used for sorption studies were of analytical reagent grade. 1000mg/L ofCopper(II) ion stock solution [CuS04.5H20] (BDH) was prepared by diluting a known mass

in doubly distilled-deionized water in a 1000cm3 volumetric flask and made up to mark.From the stock solution 30mgL-1 working solutions of Cu(II) ions were prepared by serial

dilution.

Adsorbent Activation and Chemical Modification

The sieved cassava fibre waste was soaked in excess 0.3M trioxonitrate (v) acid (HNO3)

solution for 24 hours. It was later filtered airdried and sieved through the mesh sieves. Thepowdered cassava fibre waste was then divided into two portions (1 and 2) each weighing

20g. The first portion 1 was soaked in excess 0.5M mercaptoacetic acid solution, whileportion 2 was also soaked in excess solution of 1.0M mercaptoacetic acid according to the

procedure described in [13]. The two mixtures were later filtered after 24 hours, air driedand labeled as 0.5MCF and 1.0MCF for the 0.5M and 1.0M mercaptoacetic acid modified

cassava fibre waste respectively.

Experimental ProcedureKinetic sorption studies were carried out using 100ml of Cu(II) ion solutions of initial

concentration 30mg/dm3. The metal ion solutions were measured into different labeledconical flasks containing 1.0g of each adsorbent (0.5MCF and 1.0MCF). The different

flasks were corked and uniformly agitated in a EFL-MK3 shaker at a speed of 25 rpm at atemperature of 280C and pH of 5.0 for 5 minutes. The experimental set up was thereafter

repeated for various other time intervals of 10, 15, 20, 25 and 30 minutes. Also kineticinfinity sorption (!) was also carried out for 24 hours. At the end of each contact time, the

content of each flask was filtered using a whatman No. 41 filter paper. The concentration of(Cu(II) ion in each filtrate was determined using a Buck scientific flame atomic absorption

spectrophotometer (FAAS) model 200A.

Data analysis

The metal sorption capacity (qt) of the mercaptoacetic modified cassava fibre wastes was

calculated from the relationship [22] in eqn (1):

qt =

c i " c t( )Ms (1)

Also, the percentage of Cu(II) ions removed (%RE) from the aqueous solution by each ofthe two adsorbents (0.5MCF and 1.0MCF) was calculated using eqn (2):

%RE=c

i" c

t( )c

i

#100

(2)

Whereas the fraction of Cu(II) ions removed by the two adsorbents was determined from therelationship [23].


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YT=

ci" c

t( )c

i" c

e( ) (3)

where qt is the metal sorption capacity of the adsorbent (mg/g), Ci is the initial metal ionconcentration (mg/L), Ctis the metal ion concentration in solution at time t (mg/L), Y tis the

fraction of the metal adsorbed at time t, Ms is the weight of the adsorbent (g), V is thevolume of the metal ion solution used for sorption (dm3) and Ceis the concentration of metal

ion, when sorption is completed, ie infinity sorption [ C"= Ce]

Kinetic Modeling

The study of sorption kinetics describes the adsorbate uptake rate and evidently this ratecontrols the residence time of adsorbate at the solid liquid interface [3]).

The kinetics of Cu(II) ion sorption on the two mercaptoacetic acid modified cassava

adsorbents was analysed using different kinetic models, these include: the pseudo-first order[13],pseudo-second order [14],Elovich [15-16],mass transfer [17],intraparticle diffusion

[18-19], and intraparticle diffusivity [20].

The Pseudo-First Order Equation

The pseudo-first order equation [13], is generally expressed as:

dqt

dt=k

1q

e " qt( ) (4)

Where qeand qtare the sorption capacities at equilibrium and at time t, respectively (mgg-1

)

and K1 is the rate constant of pseudo-first order sorption (Lmin

-1). After integration and

applying boundary conditions t = 0 to t = t and qt = 0 to qt = qt, the integrated form of

equation (4) becomes:

log(qe " qt) =logqe " k1t (5)

When the values of log (qe qt) were linearly correlated with t, the plot of log (qe - qt) versus

t will give a linear relationship from which k1and qecan be determined from the slope andintercept of the graph respectively.

The Pseudo- Second Order Equation

The pseudo-second order chemisorption kinetic equation [14] is expressed as eqn 6:

dqt

dt=k

2 qe " qt( )

2

(6)


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Where qeand qtare the sorption capacity at equilibrium and at time t, (mgg-1

) respectively

and K2 is the rate constant of the pseudo-second order sorption (g.mg-1

. min-1

). For theboundary conditions t = 0 to t = t and qt = 0 to qt = qt, the integrated form of eqn (6)

becomes:

1

qe " qt=

1

qe+k

2

t (7)

Which is the integrated rate law for a pseudo-second order reaction. Eqn (7) can berearranged to obtained:

qt =1

1

k2qe

2+

t

qe

(8)

Which has a linear form:

1

qt=

1

k2qe

2+

t

qe (9)

Where h (mg.g-1

. min-1

) can be regarded as the initial sorption rate as qt/t!0 hence

h= K2qe2 (10)

Furthermore eqn(9) can be written as:t

qt=

1

h+

t

qe (11)

If the pseudo-second order kinetics is applicable to the experimental data, the plot of t/q tversus t of eqn (II) should give a linear relationship from which qe, k and h can be

determined from the slope and intercept of the plot respectively.

The Elovich Kinetic EquationThe Elovich equation [15-16] is generally expressed as:

dqt

dt="e#$qt (12)

Where qt is the sorption capacity at time t (mgg-1), ! is the initial adsorption rate (mg.g

-1.min-1) and, #is the desorption constant (mg.g-1.min-1) during any one experiment.

To simplify the Elovich equation [15] assumed ! # t > > 1 and by applying boundary

conditions qt = 0 at t = 0 and qt= qt and t = t, [16] eqn (14) becomes:


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1

qt

=

ln("#)

#+

ln t

#q (13)

Thus, if a plot of qtversus ln t is linearly correlated, the constants !and #can be computed

from the slope and intercept of the graph.

Mass Transfer Equation

The mass transfer equation [17] is generally expressed as:

co" c

t= De

Kot (14)

Where Cois the initial metal ion concentration (mg.dm-3

), Ctis the metal ion concentrationat time t, t is the shaking time (mins), D is a fitting parameter, Kois the adsorption constant

which is related to the mass transfer adsorption coefficient, Ko = KM, where Mis the massof the adsorbent (g).

A linearised form of eqn (14) is:

ln(co" c

t) = lnD+ K

ot (15)

If the sorption of Cu(II) ions on the two adsorbent is depicted by the mass transfer model,

then a plot of ln (Co Ct) versus time should give a linear relationship from where theconstants lnD and Kocan be determined from the slope and intercept of the plot respectively.

The Intraparticle Diffusision ModelThe intra-article diffusion [18-19] model is expressed as eqn: 16:

R =Kidta (16)

Where R is the percent Cu(II) ions adsorbed, t is the contact time, a is the adsorption

mechanism, kidis the intra-particle diffusion rate constant (min-1

). Kidmay be taken as a ratefactor that is percent Cu

2+adsorbed per unit time [22]

A linear form of eqn 16 is:

logR = logKid+ a log t (17)

The plot of log R versus log t (eqn 17) should give a linear relationship from where the

constants a and Kid can be determined from the slope and intercept of the plot,respectively.


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Fig. 1: Percentage removal of Cu2+

with time for different adsorbents

15

16

17

18

19

20

21

22

23

24

25

0 5 10 15 20 25 30 35

Time(mins)

%Remo

val

O.5MCF 1.0MCF

Fig.2: Cu2+ Sorption capacity(qt) variation with contact time for

adsorbents

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0 5 10 15 20 25 30 35

Time(mins)

Sorption

cap

acity(mg/g)

0.5MCF 1.0MCF

The cassava waste adsorbent contains abundant cellulosic units including a matrix of: OH-,

COO-, CN- and NH2 functional groups that take part in metal ion binding [28]. Also, duringchemical modification process the thiol (SH) was incorporated onto the cassava waste using

mercaptoacetic acid, thereby increasing the concentration of surface active sites on theadsorbent matrix.

Fig.3: Time -dependence of the fraction of adsorption of Cu2+for various

adsorbents

0.4

0.45

0.5

0.55

0.6

0.65

0.7

2 2.5 3 3.5 4 4.5 5 5.5 6

T1/2.min1/2

Yt

0.5MCF 1.0MCF

Figure 3 depicts the time-dependence of the fraction of adsorption of Cu(II) ions on the twoadsorbents. It can been seen from the figure that as T1/2 increases, the rate fraction of

adsorption (Yt) also increases. This indicates that with passage of time, a higher fraction ofthe Cu(II) ions migrates from the bulk solution through the adsorbent boundary layer onto

the active sites of the adsorbent and is adsorbed. This enhanced sorption of the metal ionwith increase in agitation time may be due to the decrease in boundary layer resistance tomass transfer in the bulk solution and an increase in kinetic energy of the hydrated metal ion

[29].


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Kinetic Modeling of Cu2+ Sorption

Many attempts have been made to formulate a general expression describing the kinetics of

sorption on solid surfaces for liquid-solid phase sorption on solid systems. This has led tothe existence of a series of kinetic equations that are used to model metal ion transport onto

adsorbent surfaces

Modeling of kinetic data is fundamental for the industrial application of sorption since itgives information for comparison among different biomaterials under different operational

conditions for designing and optimizing operational conditions for pollutant removal fromwastewater systems. [30].

In order to investigate the mechanism of sorption of copper by the modified cassava wastes

and the potential rate-controlling steps, such as mass transport and chemical reactions,kinetic models were used to model the transport of copper. The different kinetic models

used were, pseudo-first order, pseudo second order, Elovich, intra-particle diffusion, masstransfer, and intra-particle diffusivity.

Fig.4: Pseudo-first order kinetics of Cu2+

on different adsorbents

-0.50

-0.45

-0.40

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0 5 10 15 20 25 30 35

Time(mins)

log(qe-qt)

0.5MCF 1.0MCF

Fig.5:Pseudo-second order kinetics of Cu2+

on different adsorbents

0

10

20

30

40

50

0 5 10 15 20 25 30 35

Time(mins)

t/qt

0.5MCF 1.0MCF

The pseudo-first order plot of Cu2+ on the cassava waste adsorbents is illustrated in Figure

4. From the plot the pseudo-first order rate constant, K1 and the sorption capacity, qe werecomputed from the slope and intercept of the plot and presented in Table 1. It can be seen

that the values of the pseudo-first order rate constant increased with chemical modification.While the sorption capacity, qe values decreased with chemical modification. Figure 5

depicts the plot of t/qt versus contact time for the pseudo-second order equation for sorptionof Cu(II) ions. From the plot the values of the pseudo-second rate constant K2, the initial

adsorption rate h and the sorption capacity qe computed from the slope and intercept arepresented in Table 2. It can be seen that the values of K2 and h decreased with chemical

modification, while the sorption capacity qe, increased with chemical modification.


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Table 1: Kinetic constants for pseudo-first order Equation.

Adsorbent k1(L.min-1) qe(mg.g

-1)

0.5MCF 1.15 X 10-2 1.973

1.0MCF 1.17 X 10-2 1.676

Table 2: Kinetic parameters for pseudo-second order Equation.

Adsorbent qe (mg.g-1) k2(g.mg

-1. min

-1) h (mg.g-1. min-1)

0.5MCF 0.669 6.56 X 10-1 2.94 X 10-1

1.0MCF 0.703 5.25 X 10-1 2.60 X 10-1

Table 3: Kinetic constants for Elovich Equation

Adsorbent "(mg.g-1

. min-1

) #(mg.g-1

.min-1

)

0.5MCF 6.48 X 10-2

15.822

1.0MCF 7.40 X 10-2 13.900

The Elovich equation plot for Cu(II) ion sorption is shown in Figure 6. Table 3 shows the

constants of the Elovich equation !the initial adsorption rate and #the desorption capacitythat were obtained from the slope and intercept of the Elovich plot. It can be seen that the

initial adsorption rate increased with chemical modification. While the desorption constantdecreased with chemical modification. Since adsorption and desorption are interrelated in

surface transport, it can be said that there exist an inverse relationship between ! and #aspresented in Table 3.

Fig.6: Elovich sorption model for Cu2+

on different a dsorbents

0.50

0.52

0.54

0.56

0.58

0.60

0.62

0.64

0.66

0.68

2.00 2.20 2.40 2.60 2.80 3.00 3.20 3.40 3.60

ln time

qt(mg/g)

0.5MCF 1.0MCF

Fig. 7:Intraparticle Diffusion kinetics for Cu2+sorption onto different

1.2

1.22

1.24

1.26

1.28

1.3

1.32

1.34

1.36

0.6 0.8 1 1.2 1.4 1.6

Log T

LogR

0.5MCF 1.0MCF

Figure 7 shows the plot of Log R (percent removal) versus Log T for the description of the

intra-particle diffusion kinetics of Cu(II) removal. The computed values of the constants,the intra-particle diffusion constant (Kid) and the adsorption mechanism (a) are presented in

Table 4. The values show that both constants increased with chemical modification. Themass transfer plot of ln (Co-Ct) versus time is seen in Figure 8. The fitting parameter (ln D)

that is a measure of the apparent distribution ratio, the adsorption constant Ko and the mass


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transfer adsorption coefficient Km values were computed from the slope and intercept and

are presented in Table 5. From the table it can be seen that the values of lnD, Ko and Kmincreased with chemical modification. The increase in the value of lnD, which is a measure

of the apparent distribution ratio of the Cu(II) ion between the bulk solution and theadsorbent surface portrays that as chemical modification of the adsorbent increases a higher

concentration of the Cu(II) ions are transported from the bulk solution onto the active sites

of the adsorbent particles.

Table 4: Kinetic parameters for Intra-particle Diffusion Equation

Adsorbent Kid(min-1

) A

0.5MCF 14.01 1.09 X 10-1

1.0MCF 14.41 1.10 X 10-1

Table 5: Kinetic constants for mass transfer Equation

Adsorption lnD Ko(min-1) km(g.L

-1.min-1)

0.5MCF

1.604

7.0 X 10-3

3.50 X 10-3

1.0MCF 1.610 9.1 X 10-3 4.55 X 10-3

The intra-particle diffusivity equation for the description of the sorption of Cu(II) ions from

the aqueous solution onto the surface of the cassava waste adsorbents (0.5MCF and1.0MCF) is shown in Figure 9. From the slope and intercept of the plot, the values of the

initial sorption rate K1 and the boundary layer thickness, Xi were computed and presented inTable 6. Examination of Table 6 shows that the values of the initial sorption rate increased

with chemical modification, while that of the boundary layer thickness decreased withchemical modification. Thus it can be said that there is a decrease in boundary layer

thickness (Xi) between the bulk solution and the adsorbent particle as the initial adsorptionrate (K1) of Cu(II) ion increases. Hence there is said to exist an inverse relationship

between, the initial sorption rate k1 and the boundary layer thickness, Xi which leads to theobserved pattern of Cu(II) ion sorption from the intra-particle diffusivity equation.

Table 6: Kinetic parameters for Intra-particle Diffusivity Equation

Adsorbent K1(mg.g

-1.min

-0.5) X1

0.5MCF 3.62 X 10-2 4.29 X 10-1

1.0MCF

4.15 X 10-2

4.22 X 10-1


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Fig.8: Mass transfer kinetic model for Cu2+ on various adsorbents

1.50

1.55

1.60

1.65

1.70

1.75

1.80

1.85

1.90

1.95

2.00

0 5 10 15 20 25 30 35

Time(mins)

ln(Co-C

t)

0.5MCF 1.0MCF

. :I +

0.5

0.52

0.54

0.56

0.58

0.6

0.62

0.64

0.66

0.68

2 2.5 3 3.5 4 4.5 5 5.5 6

T1/2.min1/2

qt

(mg

/g)

0.5MCF 1.0MCF

Coefficient of Determination Analysis

For an appropriate description of the mechanism of Cu(II) ion sorption, it was necessary thatdifferent kinetic models be tested to determine their extent of fitness to the experimental

sorption data. The optimization procedure to be able to select the best fit model requires theselection of an error function in order to evaluate the fit of the kinetic models to the

experimental sorption data. The choice of error function can affect the parameters derived-error functions based primarily on absolute deviation bias of the fit towards high

concentration data and this weighing increases when the square of the deviation is used topenalize extreme errors. The coefficient of determination, r2 was chosen as the error

function for the kinetic model analysis. This is because linear regression implicitlyminimizes the sum of the squares of the errors to determine the equation parameters [31].

Table 7 presents the values of the linear coefficient of determination (r2) values of thedifferent kinetic models used to evaluate the sorption of Cu(II) onto the two modifiedcassava waste adsorbents. Examination of Table 7 shows that the pseudo-second order

kinetic equation had the highest r2 values. Thus this kinetic model was taken as the best fitequation for the description of the mechanism of sorption of Cu(II) ions. In addition,

examination of the sorption capacity values (qe) of the pseudo second order model showsthat the values were in the same range as the experimental sorption capacity values.

Therefore, the sorption of Cu(II) ions from aqueous solution onto the mercaptocacetic acid

modified cassava waste adsorbents was found to follow the pseudo-second order kineticequation. Similar conclusion was also reported for the sorption of some heavy metal ions

onto various adsorbent surfaces [32-35].

Furthermore, the pseudo-second order is based on the assumption that sorption follows asecond order mechanism, with chemsorption as the rate limiting step. So the rate of

occupation of adsorption sites is proportional to the square of the number of unoccupiedsites [4].


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Table 7:Linear coefficient of determination (r2) of kinetic models

Kinetic Model Adsorbent

0.5MCF 1.0MCF

Pseudo-first order 0.9804 0.9514

Pseudo-second order

0.9940

0.9896

Elovich 0.8848 0.8370

Intraparticle diffusion 0.9333 0.8087

Mass transfer 0.8867 0.9726

Intraparticle diffusivity 0.9512 0.9152

CONCLUSION

It appears that majority of sorption kinetic studies reported in literature often use one or two

models to test their data and then conclude on the appropriate model for their work.However, it is the view in this study that metal ion sorption may be described by more than

one kinetic model. Thus it is necessary that several kinetic equations be used to model metalion sorption. A detailed analysis of six kinetic equations were used to investigate the

sorption of Cu(II) ions onto the chemically modified cassava wastes. From the kineticmodel analysis using coefficient of determination, the pseudo-second order model was the

most fitting for the description of Cu(II) ion transport from the bulk solution onto the surfaceof the chemically modified cassava waste adsorbents.

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adsorption kinetics and modeling of cu(ii) ion sorption from aqueous solution by mercaptoacetic acid...

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