American Journal of Chemistry and Applications 2015; 2(2): 44-49

Published online March 10, 2015 (http://www.openscienceonline.com/journal/ajca)

The Optimization of Effective Parameters to the Synthesis of Pd-Supported on Activated Carbon for N-Debenzylation of Hexabenzylhexaazaisowurtzitane Using Response Surface Methodology

Yadollah Bayat*, Mona Molaei, Fatemeh Hajighasemali

Department of Chemistry, School of Chemistry and Chemical Engineering, Malek-Ashtar University of Technology, Tehran, Iran

Email address

Y_bayat@mut.ac.ir (Y. Bayat)

To cite this article Yadollah Bayat, Mona Molaei, Fatemeh Hajighasemali. The Optimization of Effective Parameters to the Synthesis of Pd-Supported on

Activated Carbon for N-Debenzylation of Hexabenzylhexaazaisowurtzitane Using Response Surface Methodology. American Journal of

Chemistry and Applications. Vol. 2, No. 2, 2015, pp. 44-49.

Abstract

Tetraacetyldibenzylhexaazaisowurtzitane (TADB) has been synthesized via N-debenzylation reaction of

hexabenzylhexaazaisowurtzitane (HBIW) over Pd/C. Herein, we optimized condition of synthesis of Pd(OH)2 supported on

activated carbon by using design of experiment. The fractional factorial design method was performed in the first step to screen

important factors. Then, response surface methodology using a three-factor five-level central composite design was applied in

the final step. The yield of TADB was promoted to 75% by using Pd (OH)2 supported on activated carbon synthesized in the

optimized condition (14.57% Pd, pH: 9.61 and time of adsorption: 1.1 hour).

Keywords

N-debenzylation, HBIW, Activated Carbon, Supported Catalyst, DoE, Isowurtezitane, CL-20

1. Introduction

Hexanitrohexaazaisowurtzitane (HNIW) commonly

known as CL-20 is one of a high energetic symmetric caged

nitamine. The presence of six Nitro groups attached to

nitrogen atoms (N1-N6) on the high pressure structure of CL-

20 makes this compound as a rich source of energy. In

comparing to other energetic nitramines such as HMX and

RDX, the crystals of HNIW exhibits higher density

(2.044gcm-3

for ε-CL-20), heat of formation (454 kJmol-1

)

and oxygen balance (-11%). Therefore, it has been proposed

as a component of both explosive and propellant [1-4].

Hexabenzylhexaazaisowurtzitane (HBIW) is the first

precursor in the industrial production of HNIW which is

achieved by condensation of benzylamine with glyoxal. Then,

catalytic reductive N-debenzylation and acetylation of HBIW

with H2, Pd/C, Ac2O in presence of PhBr as a co-catalyst

gives tetraacetyldibenzylhexaazaisowurtzitane (TADB) in

high yield, which is then nitrolyzed to obtain HNIW [5].

However, Pd catalyst is not reusable in this way [6]. In

addition, it is highly expensive that has its drawbacks for the

industrial scale. Many efforts to non-hydrogenolysis

synthesis of CL-20 has been investigated, such as; oxidative

debenzylation by potassium permanganate [7], CAN [8].

Even by changing the first material to

hexaallylhexaazaisowurtzitane and then one pot reaction to

the synthesis of CL-20 [9]. Nevertheless, all of these ways

suffer from low yields, collapse of isowurtzitane cage or

benzoelated by-products that resist removing more than with

benzylic substitutions. Furthermore, all attempts to direct

synthesis of CL-20 from HBIW has been unsuccessfully so

far [10-13].

A variety of methods for reducing N-debenzylation have

been reported, including using Pd-adsorbed on carbon

nanotubes, functioned nano-SiO2, Al2O3, TiO2 and activated

Carbone [15]. According to the literatures, activated carbon

or activated charcoal is an efficient support for catalytic

reactions. It has remarkable adsorption properties due to the

porous nature of carbon, which its pore size can be controlled.

The low cost, easy to recovery of Pd by incineration and

American Journal of Chemistry and Applications 2015; 2(2): 44-49 45

resistance to acidic or basic conditions is the other

advantages of activated-carbon as a support. Nevertheless,

the dispersity and distribution of palladium onto activated

carbon influences the effectiveness of this catalyst. It was

previously reported that TADB was not generated by

reductive debenzylation of HBIW in percent of Pd complexes

or Pd(OAc)2 [14] which suggests that the heterogeneous

catalytic system is required. Some of palladium-based

catalyst has been studied in the hydrodebenzylation of HBIW.

It seems that the activity of Pd on activated carbon depend on

the accessibility of the large HBIW molecule to the active

centers located in the pores of activated carbon. Considering

these results, the size of pores, amount and dispersity of

palladium are the key factors in the final yield of TADB [6].

As a part of our research program, we focused on

optimizing conditions for preparation of palladium supported

on activated carbon, which synthesized by the deposition -

precipitation method according to literature [16-20]. In this

regard, we used design of experiment (DoE) method [21] to

optimize five factors affecting on the catalyst utility

including (i) pH, (ii) adsorption time, (iii) adsorption

temperature, (iv) the percent of palladium consumption and

(v) precipitation time which then used in the synthesis of

TADB from HBIW procedure (Scheme 1).

Scheme 1. Synthesis of tetraacetyldibenzylhexaazaisowurtzitane (TADB)

2. Experimental

2.1. Chemicals

The chemical reagent PdCl2 was purchased from Aldrich

Chemical Co. Activated carbon was purchased from Merck

Co [activated carbon Code K40597583]. Deionized water

was used to prepare the solutions. HBIW was prepared

following a previously reported procedure and data were in

accordance with the literature. All other chemicals used were

C.P. grade. Pore volume and surface area of activated carbon

were determined by ChemicalsBEL (Brunauer-Emminett-

Teller) Japan BELSORP-mini II. Transmission electron

microscope (TEM) observation was performed on a Philips

S4160 at the accelerating voltage of 100kV. FE-SEM (field

emission scanning electron microscope) images were

obtained on a Hitachi S-1460 field emission scanning

electron microscope using accelerated voltage of 15kV.

Melting points were measured with an Electro thermal 9100

apparatus.

2.2. Preparation of Pd (OH) 2/C Catalysts

Carbon-supported Pd catalyst was prepared by a

conventional deposition-precipitation method. Typically, an

appropriate amount of PdCl2 (for preparation of 5-15% Pd/C)

dissolved in 100mL of 5% HCl to form H2PdCl4 aqueous

solution. Then 1 g of activated carbon was added to the

solution and stirred for 1 to 5 hours at the temperature

ranging from 25 to 80 ˚C which were set according to DoE

method. Afterward, the temperature was reduced below 50˚C

and the pH value of solution adjusted between 8-11 by 20%

CaCO3 solution which added to the mixture drop wise.

Finally, the catalyst was filtered after 16 hours, washed with

distilled water and dried in a vacuum oven.

2.3. Hydrogenolysis Reaction of HBIW

Catalytic debenzylation of HBIW was done in a stainless

steel reactor (2 L capacity) equipped with a mechanical

stirrer and a hydrogen gas supply system.

All experiments were done with a mixture of 10 g HBIW

in 100 mL DMF and 0.5 g synthesized Pd catalysts. 0.45 mL

bromobanzene was added to the reaction mixture as co-

catalyst. Then, 15 mL of acetic anhydride (Ac2O) as an

acetylating agent was added to the mixture. During the

reaction, pressure and temperature of hydrogenolysis reaction

were kept at 4bar and 40°C. These reactions were done in 4

hours. At the end of the experiment, the catalyst and the

product (TADB) were filtered and filtration washed with

acetone. TADB was extracted with hot acetic acid and

precipitated with methanol at 0˚C. The melting point of all

production was 318-321˚C and shown one spot in TLC with

different solvents.

3. Results and Discussion

3.1. Analysis of Experiments

Initially, optimization of the reaction condition in

preparation of TADB from HBIW was done with the aid of

two-level factorial design of Deasign-Expert®soft. These

designs help to screen many factors to discover the vital few

and how they interact. Moreover, the experiment results,

analyze by Doe method to achieve three objectives [22-24]:

• To estimate the best or optimal conditions for a product

or a process

• To estimate the contribution of each factor

• To estimate the results under optimal conditions

Optimal conditions obtain by studying the main effects of

each factor.

Table 1. Minimum and maximum levels of factors in the screening stage of

the first phase of the experiment designed.

levels Factors

+1 -1

15 5 Palladium (%)

5 1 Adsorption time

11 8 pH

80 25 Adsorption temperature

80 25 Precipitation temperature

In the first step, five factors, including (i) pH, (ii)

adsorption time, (iii) adsorption temperature, (iv) the percent

of palladium consumption and (v) precipitation temperature

were considered. The full factorial design requires 2k runs for

46 Yadollah Bayat et al.: The Optimization of Effective Parameters to the Synthesis of Pd-Supported on Activated Carbon for

N-Debenzylation of Hexabenzylhexaazaisowurtzitane Using Response Surface Methodology

k factors, although we performed eight runs arranged in 25-2

fractional factorial design. Only eight runs were necessary

instead of 25=32 runs required by full factorial design [25-29].

The starting point of optimization was the reproduction of

the results of Nielsen et al [30]. The low (-1) and high (+1)

levels of each factor determined are shown Table1.

The eight experiment design and its yield of reactions are

brought in Table 2.

The experimental data were statistically analyzed and the

significance of effects was checked by analysis of variance

test (ANOVA). The results are shown in the ANOVA table

(Table 3). The first column of this table is the numerical

value of the sum of squares which the larger value indicates

the greater impact factor. A, B and BC factors have the

highest value.

Table 2. The results of the first phase of the experiment designed.

run Pd (%) Ads. Time pH Prc.Temp(˚C) Ads.Temp (˚C) Yields (%)

1 5 1 11 80 25 32

2 15 1 11 25 80 52

3 15 5 11 80 80 38

4 15 5 8 80 25 58

5 5 5 8 25 80 43

6 15 1 8 25 25 52

7 5 1 8 80 80 32

8 5 5 11 25 25 24

Table 3. ANOVA table calculated for the first phase.

Source Sum of squares df Mean squares F- Value P-value Prob > F

Model 978.5 4 244.625 47.73171 0.0048 significant

A-Pd% 595.125 1 595.125 116.122 0.0017

B-Ads. Time 3.125 1 3.125 0.609756 0.4918

C-pH 190.125 1 190.125 37.09756 0.0089

BC 190.125 1 190.125 37.09756 0.0089

Residual 15.375 3 5.125 37.09756 0.0089

Cor Total 993.875 7

F-value is the measurement of distance between individual

distributions (Mean Square of X / Mean Square of Error) as

is clear in Table 3; the effect of A factor is greater than the

other factors. If the sum of squares divided by the df, the

numerical values of the mean squares are calculated. A good

model is able to predict the maximum variance of data

distribution.

The P - value represents the probability of error. The first

phase of the ANOVA (Table 3) shows that only 0.48%

probability of error is due to noise. P-values with amounts of

less than 0.05 indicates the reliability of the model. In

addition, it proves that the clauses A, C and BC are

significant factors (which approved by equation1suggested

by software). The normal probability curve shows the impact

of each factor. As you can see in Figure 1, the factors with

the farther distances of the normal line are the most effective

factors. Here, the factors A, C and BC have a greater effect.

The factor with the positive effect are on the right and ones

with negative effect are on the left. The factors with positive

effect reflect that by increasing of this variable, the rate of

product will grow up. However, the BC and C factors with

negative effects suggest that by reducing these factors the

yield of reaction will increase. According to the data of the

normal probability curve and the result of ANOVA table, the

effect of temperature of precipitation and temperature of

adsorption was not considerable factors.

Yield (%) =+41. 38+8.63 * A-0.63 * B-4.88 * C-4.87 * B * C

equation 1

Figure 1. Normal probability curve in the first phase of experiment.

Table 4. Selected levels for experimental design (coded values).

+2 +1 0 -1 -2 factors

15 13.54 10 6.46 5 A: palladium (%)

5 4.41 3 1.59 1 B: adsorption time(h)

11 10.56 9.50 8.44 8 C: pH

RSM (response surface methodology) using a three-factor,

five-level CCD (central composite design (Kennedy and

Krouse 1999)) was applied for optimizing the reaction of

three screened variables (A, B, C) to enhance TADB yield.

The three different parameters chosen as main variables,

including A; (Pd%), B (adsorption time) and C (pH) are

presented in Table 4, whereas the low, middle and high value

of each variable was designated as -2, -1, 0, 1, 2 respectively.

American Journal of Chemistry and Applications 2015; 2(2): 44-49 47

After determination of the experimental design levels, 14

runs of experiments were designed by the CCD method. The

catalyst was synthesized under defined conditions and its

effects on the conversion reaction of HBIW to TADB were

checked in the reactor. The matrix of 14 designed

experiments and its consequences are listed in Table 5.

Then the results were analyzed by ANOVA with various

models provided by software. Among these models, the

quadratic model was considered as the most appropriate

model. The results of the ANOVA are presented in Table 6.

The sum of squares of C factor is more than the other factors

(it has the highest impact). The F-value parameter of C factor

is in the highest amount which reflects the importance of this

factor. Lack of fit was insignificant which confirmed that the

model was suitable for this experiment.

Table 5. The second phase of experimental design using a CCD.

RUN Pd (%) Ads.Time pH Yield (%)

1 10 5 9.5 39

2 13.5 4.4 8.4 67

3 10 3 9.5 36

4 10 3 8 59

5 6.5 4.4 10.5 21

6 10 3 9.5 39

7 10 1 9.5 50.3

8 15 3 9.5 58

9 10 3 11 35

10 6.5 1.6 8.4 52

11 13.5 1.6 10.5 61

12 10 3 9.5 43

13 10 3 9.5 37

14 5 3 9.5 34

Table 6. ANOVA table calculated for the second stage.

Source Sum of Squares df Mean Square F Value p-value Prob > F

Model 2158.95 7 308.4214 45.11376 < 0.0001 Significant

A-A 288 1 288 42.12665 0.0006

B-B 209.9263 1 209.9263 30.70657 0.0015

C-C 629.0804 1 629.0804 92.01753 < 0.0001

BC 55.43452 1 55.43452 8.108579 0.0293

A2 108.3137 1 108.3137 15.84338 0.0073

B2 73.60742 1 73.60742 10.76679 0.0168

C2 138.3303 1 138.3303 20.23401 0.0041

Residual 41.01917 6 6.836528

Lack of Fit 12.26917 3 4.089722 0.426754 0.7487 not significant

Pure Error 28.75 3 9.583333

Cor Total

13

Figure 2. parity plot of actual experiments on the results predicted by the

proposed model.

The parity plot of the model is shown in Figure 2. In this

plot if the experimental results entirely matched with

predicted results proposed by the model, the data would place

perfectly on central line of this plot. Equally it is presented,

the predicted values match with the experimental ones. This

outcome indicates that the applicability and reliability of the

equation in representing the reaction over a reach of

experimental conditions with sufficient level of accuracy.

Figure 3. Diagram of three-dimensional interaction of B (Pd adsorption

time of support) and C (pH) on the reaction efficiency.

According to equation modeling software (equation2) and

data resulted from ANOVA table, only BC interaction with

selected models is significantly important. A three-

dimensional graph of the effect of pH on the efficiency of Pd

adsorption time is indicated in Figure 3. As can be

understood, by reducing the adsorption time to 1 hour and

reducing the pH to 8, the product yield has increased. Then,

pH and the Pd adsorption time on the support has affected on

the reaction efficiency by a negative impact (which approved

in equation 2).

48 Yadollah Bayat et al.: The Optimization of Effective Parameters to the Synthesis of Pd-Supported on Activated Carbon for

N-Debenzylation of Hexabenzylhexaazaisowurtzitane Using Response Surface Methodology

Yield (%) =+38. 60+8.49 * A-5.12 * B-8.87 * C-5. 26* B *

C+3. 84 * A2+3. 17* B2+4. 34 * C2 equation 2

The principal objective of the response surface

methodology was the optimization of the factors affecting

response. In order to optimize the reaction process, the

effects of factors were considered in range ± α and the

maximum yields were obtained. Agreeing to this method, the

optimal values obtained were between 73-75% (after three

repetitions) when the amount of Pd, adsorption time and pH

was 14.57%, 1.1 h and 9.61 respectively.

3.2. Characterization of Synthesized

Catalysts

SEM analysis of Pd (OH)2/C revealed that Pd were fully

loaded with well dispersed Pd particles (with an intermediate

size of 5nm) and spherical particles (Figure 4). In addition,

TEM image (the amount of Pd was 14.57%) has shown

homogeneous distribution of Pd particles of activated carbon

(see figure 4 d).

Figure 4. SEM of a: activated carbon b: 6.5% Pd supported on activated carbon and c: 14.57% Pd supported on activated carbon d: TEM of 14.57%Pd

supported on activated carbon

4. Conclusions

In this paper, the optimization process to synthesis of

Pd(OH)2/C on debenzylation reaction of HBIW were

investigated. Determining the experiments condition for the

synthesis of Pd(OH)2/C catalysts were performed by DoE7

software (fractional factorial design in the first step and

central composite design in the final step). Three factors,

including Pd, adsorbent time and pH were identified as

important factors affecting the efficiency of catalysts in the

debenzylation of HBIW to TADB reaction rate.

In conclusion, the quantity of palladium in the synthesis

of catalyst was considered as the most significant factors in

the TADB yield. The DoE method could reduce the number

of experiments that was needed to identify the best condition

for the synthesis of catalyst and in consequence the TADB

reaction rate. The best palladium supported catalyst which

was synthesized (pH: 9.61, adsorption time: 1.1 h, Pd%:

14.57) could promote the reaction rate of hydrogenolysis

debenzylation reaction of HBIW to75% in the total reduced

reaction price.

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