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Characterization of the microporosity of chromia- and titania-pillared montmorillonites differing in pillar density.
Microporous and Mesoporous Materials 37 (2000) 187–200 www.elsevier.nl/locate/micromeso
Characterization of the microporosity of chromia- and titaniapillared montmorillonites differing in pillar density. I. Adsorption of nitrogen Mikhail Sychev a, *, Tatjana Shubina a, Michal Rozwadowski b, A.P.B. Sommen c, V.H.J. De Beer c, Rutger A. van Santen c a National Technical University of Ukraine ‘Kiev Polytechnic Institute’, Faculty of Chemical Technology, TNV, 252056 Kiev, pr. Peremogy 37, Ukraine b Faculty of Chemistry, Nicholas Copernicus University, 87–100 Torun, Gagarina 7, Poland c Schuit Institute of Catalysis, Eindhoven University of Technology, PO Box 513, 5600 MB Eindhoven, The Netherlands Received 29 March 1999; received in revised form 6 October 1999; accepted for publication 8 October 1999
Abstract The microporosity of chromia- and titania-pillared clays differing in pillar density has been explored. Nitrogen adsorption data determined at very low relative pressures were used. These data were analyzed by means of the a s method and the BET, Langmuir, Dubinin–Radushkevich and Dubinin–Stoeckli approaches. The applicability of these methods for determination of the PILCs’ microporosity was studied. The surface area calculated by the a method s can be considered as a total surface area of the materials studied. The BET method underestimates, whereas the Langmuir approach overestimates, the total surface area of these solids. The Dubinin–Radushkevich method can be applied only to characterize textural features of PILCs exhibiting homogeneously distributed narrow micropores (<0.7–1.0 nm width). The same holds for the Dubinin–Stoeckli relation. The method developed by Zhu et al. is useful for the determination of the porous structure of PILCs having a significant contribution of supermicropores (0.7–2.0 nm width). A good agreement between the total micropore volume of the materials studied and that obtained from the a method was found. All the methods applied demonstrated that these solids possess micropores over a s broad pore-size range. Chromia-pillared montmorillonites contain a significant amount of ultramicropores (<0.7 nm width), whereas titania-pillared clays show an important contribution of supermicropores. An alteration of the pillar density can provide a family of pillared clays that differ in the surface area, micropore volume, and micropore size distribution. © 2000 Elsevier Science B.V. All rights reserved. Keywords: Chromia-pillared clays; Microporosity analysis; Nitrogen adsorption; Titania-pillared clays
* Corresponding author. Tel.: +380-44-441-1279; fax: +380-44-274-2004. E-mail address: [email protected] (M. Sychev) 1387-1811/00/$ - see front matter © 2000 Elsevier Science B.V. All rights reserved. PII: S1 3 8 7 -1 8 1 1 ( 9 9 ) 0 0 26 5 - 6
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1. Introduction Intercalation of smectite clays via exchange of cations located in their interlayer space with hydroxy-metal polycations, followed by a thermal treatment, is an effective approach to modulate them with the purpose to obtain adsorbents, catalyst supports or catalysts [1,2]. The materials thus prepared are referred to as pillared interlayered clays (PILCs). The amount of an incorporated phase can be changed by varying the cation exchange capacity (CEC ) of the host clay mineral. In turn, it is possible to adjust the CEC by means of the Hoffmann–Klemen effect [3], the essence of which consists of migration of some cations with small ionic radii (Li, Co, Ni) to vacant octahedral sites in the clay layers upon heating. Alumina-, zirconiaand chromia-pillared clays differing in pillar density were prepared using clays with a reduced CEC [4–7]. It can be concluded from the literature that the materials considered in the present study exhibit promising catalytic properties [8–17]. Montmorillonite pillared with chromia displays a high catalytic activity for cyclohexene dehydrogenation [8], hydrocracking of n-decane [9], and toluene disproportionation [10]. Its sulfide form is an active and stable catalyst for both thiophene hydrodesulfurization and butene hydrogenation [11]. Titania-pillared montmorillonite is known to have a high thermal stability and attractive catalytic properties [12–14]. This material exhibits a high reactivity in photodegradation of compounds such as 2-propanol, some carboxylic acids, dichloromethane, and chloroform [12–14]. Modification of Ti-PILC with Pd, Cu or V resulted in active and selective catalysts for the hydrogenation of butenonitriles [15], reduction of NO by hydrocarbons and by ammonia [16 ] as well as for the oxidative dehydrogenation of propane [17]. 1.1. Theoretical considerations on micropore analysis The purpose of this section is to review briefly the most commonly used approaches dealing with the characterization of pillared clay microporosity.
One of the main problems in the characterization of porous materials, including PILCs, is the determination of their surface area, micropore volume and pore size distribution, which plays an essential role in their application as catalysts or adsorbents. Several methods have been developed to deduce the pore structure of microporous solids from adsorption isotherms. Owing to their simplicity and the importance of the information generated, the t, a and Dubinin–Radushkevich methods are s often used [18–23]. The first two methods are based on the comparison of adsorption data obtained for the material to be tested with adsorption on a non-porous sample (reference isotherm). They assumed that at relative pressures above a certain value, the micropores are completely filled, and only the adsorption on the external surface influences the isotherm [22]. When the adsorbed volume at each experimental point is plotted against the statistical thickness, t, a linear relation between the adsorbed volume and the t values can be obtained [24]. The estimation of t should be based on the reference isotherm, which yields the same BET constant (C ) as that of the material BET tested. However, C of the external surface of a BET microporous solid is rather difficult to determine [25]. As was demonstrated previously [25], the choice of the standard t function and the part of the V–t curve used for linear fitting may drastically affect the values of the external surface and micropore volume. The strong influence of the chemical composition of the surface on the evolution of t as a function of P/P was evidenced [25]. To avoid 0 the above complications, Sing [26 ] introduced and developed the a method in which the normalized s adsorption, a (=n/n ), is derived from the isos 0.4 therm of a reference material by using the amount adsorbed at a relative pressure of 0.4 (n ) as the 0.4 normalization factor. The adsorption in micropores can be interpreted using the thermodynamic Dubinin–Radushkevich (DR) equation [23] that holds for a variety of adsorption systems. This equation is based on the assumption that adsorbed molecules exhibit an adsorption potential, A, that governs the fractional pore filling. The DR equation is expressed by V /V =exp[−(A/bE )2], a 0 0
(1)
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with V , V , E and b being the amount of adsorpa 0 0 tion at equilibrium pressure, P, the micropore volume, the characteristic adsorption energy, and the affinity coefficient characterizing the adsorbate, respectively. The term ‘adsorption potential’ (A) was introduced by Polanyi, and it corresponds to the change of a molar free energy caused by the change of a vapor pressure [22]:
tion of the pore width from experimental isotherms [22]). This relation is used for transformation of the characteristic adsorption energy to the half-width of the slit-shaped micropores. A Gaussian distribution of these pore widths is given by
A=RT ln(P /P)=−DG, (2) 0 with DG and R being the differential free energy of adsorption and the universal gas constant, respectively. The total heterogeneity, i.e. the sum of the structural and surface heterogeneities of an adsorbent, is usually characterized by a distribution function (X ) of the adsorption potential and may be evaluated by means of the condensation approximation method [27] as
with d and x being the dispersion of the Gaussian distribution and the value of the pore half-width [22], respectively. The micropore size distribution can be derived from the relationship dV /dx vs. x. a The calculation using this method has been widely applied to a great number of carbonaceous adsorbents giving reasonable results [22]. Horvath and Kawazoe described a method for calculating the effective micropore volume distribution of slit-shaped pores [29]. They took into account the interaction between adsorbent and adsorptive using the interaction parameter that depends on their nature. It was established that in the case of materials containing pores with a width less than 1.0 nm, the results determined by this method are in good agreement with the data obtained by other approaches [2,30]. For zeolites having small pores, as well as for alumina-pillared clays with a free space (interlayer free spacing) of 0.7–0.8 nm, the H–K approach gives reasonable pore size distributions [2,30]. However, for materials having a significant fraction of supermicropores, the data obtained by this method were found to be unrealistic [30,31]. Recently, Zhu et al. [30,31] proposed a method using the low-pressure part of the adsorption isotherm for determination of the micropore size distribution of PILCs. The authors assume that the relative pressure at which micropores of each type are completely filled depends on the number of nitrogen layers that can be accommodated. Consequently, the micropore range can be subdivided into five pore groups as a function of the nitrogen monolayers that they can be adsorb. The N adsorption isotherm is replotted as log(P/P ) 2 0 vs. the ratio of the nitrogen volume adsorbed at each relative pressure to the total volume adsorbed. The curve thus obtained contains steps that are
X(A)=−dH(A)/dA,
(3)
with H being the relative adsorption. The intercept of the linear part with the lower slope of the plot lnV vs. ln2(P /P) yields the 0 micropore volume. The micropore filling of a system with a distribution of pore sizes can be described by the sum of the contributions from individual pore groups that are characterized by their own pore volume, V , and adsorption energy i E . Adsorption on microporous solids having two i kinds of micropores can be described by a twoterm DR equation [18,22], expressed as: V=V exp[−(R2T2 ln2(P /P)/E2 ]+V 1 0 1 2 ×exp[−(R2T2 ln2(P /P)/E2 ] (4) 0 2 The Dubinin–Stoeckli (DS) relation [28] describes an empirical relationship between the characteristic adsorption energy (E ) and the 0 average half-width of the slit-shaped micropores (x ) 0 E =k/x , (5) 0 0 where k=13.03–1.53×10−5E3.5 0 A constant value of 10 or 12 is used for x (the 0 constant 10 is more appropriate for the determina-
dV /dx =[V /d(2p)1/2)] exp[−(x −x)2/2d2], a 0 0 0 (6)
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thermodynamically related to the filling of pores of a certain size. The derivative of this curve, dV/d log(P/P ), clearly exhibits the position of 0 these steps. By locating the main maxima, the pore-size range can be correlated with a certain P/P range. 0 For pillared clays, however, the methods reviewed above yield different micropore volumes. The present paper deals with the characterization of the microporosity of pillared montmorillonites differing in pillar density via the nitrogen adsorption. An attempt is also made to analyze the applicability of different methods for distinguishing the microporosity of these PILCs.
2. Experimental 2.1. Materials Preparation conditions were chosen as to obtain samples with different microporosities. The starting material was a purified Oglanlinsky bentonite (CIS) [7]. Its monoionic Li form, which contains 0.85 mequiv. g−1, of exchangeable Li+, was prepared following the technique described elsewhere [32]. Portions of this cationic form were calcined at 408 and 423 K for 24 h. A small amount of each was then exchanged with NH+ to allow 4 determination of the CEC by the micro-Kjeldahl method. A fraction of the air-dried and calcined Li-form containing particles smaller than 2 mm (collected by sedimentation) was used for pillaring. Since the calcined clay does not swell fully in water, an acetone–aqueous suspension was applied for the pillaring. The preparation method of Cr-PILCs was similar to that proposed by Tzou and Pinnavaia [8]. The pillaring reagent containing Cr oligomers was formed by heating a 1.0 mol dm−3 solution of Cr(NO ) and Na CO at 368 K for 36 h. Prior to 33 2 3 this operation, the base was gradually added to the vigorously stirred Cr(NO ) solution at room 33 temperature so that the molar concentration ratio of hydroxide to the Cr ion was equal to 2.0. The aqueous or acetone–aqueous suspension of the host clay (1.0 wt%) was added slowly to the vigorously stirred pillaring reagent (50 mmol Cr3+ per
mequiv. clay) at 313 K, and the mixture was stirred for 1.5 h. Titania-pillared clays were prepared following the procedure of Yamanaka et al. [33]. Ti isopropoxide was added dropwise in an inert atmosphere to a vigorously stirred 1 mol dm−3 HCl solution. The molar ratio of acid to alkoxide was equal to four. The resulting slurry was peptized by further stirring at 298 K for 3 h. Next, the obtained sol was mixed with an acetone–aqueous suspension of the cationic form of montmorillonite. The amount of titania sol used for pillaring was such that the molar TiO /clay CEC ratio was 40. Then, the 2 mixture was kept at 298 K for 3 h under continuous stirring. After completion of the pillaring reaction, both chromia- and titania-pillared clays were separated by centrifugation, washed 10-fold with de-ionized water (i.e. the Ti-PMs were Cl−-free as checked by AgNO ) air-dried in a thin layer at 295 K, and 3 heat-treated in a He flow at 473 K for 5 h. The samples synthesized are referred to as Cr- or Ti-PM(0.85), -PM(0.40) and -PM(0.28), where the numbers in parentheses indicate the CEC of the parent material. The amount of Cr and Ti incorporated in the montmorillonite was determined by atomic-absorption spectroscopy (AAS ) with a Perkin Elmer 3030 spectrometer using the Li metaborate method [7]. 2.2. Nitrogen adsorption N adsorption experiments were performed at 2 liquid-nitrogen temperature (77 K ), using a Micromeritics ASAP 2010 apparatus (a static volumetric technique). Prior to the determination of an adsorption isotherm, a sample (approximately 0.25 g) was outgassed at 473 K for 5 h under a residual pressure lower than 10−4 mbar. The pressure was measured with an accuracy of ±0.25%. For the a -plots, the adsorption isotherm of s Na-montmorillonite calcined at 973 K was used as a reference.
3. Results At low relative pressures, the N adsorption– 2 desorption isotherms of the Cr-PM preparations
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Fig. 1. Nitrogen adsorption isotherms at low relative pressures: (A) (1) Cr-PM(0.85), (2) Cr-PM(0.40), (3) Cr-PM(0.28) and (B) (1) Ti-PM(0.85), (2) Ti-PM(0.40), (3) Ti-PM(0.28).
are close to Type I of the IUPAC classification [34]. The results are similar to those reported by us earlier [7,11,35]. For the Ti-PM materials, the adsorption isotherms are rather a combination of Type I and Type IV. All isotherms show that the pillared clays are essentially microporous with some mesoporosity [33,35]. The N adsorption isotherms obtained at very 2 low pressures are shown in Fig. 1. According to Gil et al. [21], their shape indicates the presence of two groups of micropores differing in size. One group is filled with N at lower relative pressures, 2 approximately up to p/p =1.5 10−4, and can be 0 classified as ultramicropores (<0.7 nm width). The other group is filled at higher relative pressures, and can be considered as supermicropores (0.7– 2.0 nm width) [22]. The abundance of both pore groups depends on the nature of the intercalated
species (see Fig. 1). In the case of the Ti-PM materials, the fraction of ultramicropores is somewhat smaller compared to that of Cr-PMs. In parallel, herewith, the contribution of such pores tends to decrease with a reduced pillar concentration. Also, the results presented in Table 1 demonstrate that the specific total pore volume (V ) derived from the adsorption isotherms, except t for the Cr-PM(0.28) sample containing a small fraction of incompletely pillared clay [7], increases with decreasing pillar population. Fig. 2 shows the a -plots derived from the N s 2 adsorption isotherms. Each a -plot exhibits a plas teau with an insignificant slope, and can be extrapolated to the origin. For the Cr-PM samples, the lowest a values part of these plots do not accus rately fit the extrapolation due to an upward swing. This kind of deviation in the a -plot has been s
Table 1 Specific surface areas and specific total pore volume (V ) for chromia and titania pillared claysa t Sample
Cr ( Ti) content (mol kg−1)
S Langmuir (m2 g−1)
Correlation coefficient
S BET (m2 g−1)
Correlation coefficient
S a (m2 g−1)
Sa ext (m2 g−1)
V t (ml g−1)
Cr-PM(0.85) Cr-PM(0.40) Cr-PM(0.28) Ti-PM(0.85) Ti-PM(0.40) Ti-PM(0.28)
5.10 3.11 1.72 5.69 2.68 1.87
363 324 285 440 402 356
0.9999 0.9999 0.9999 0.9990 0.9985 0.9976
308 285 210 290 287 254
0.9989 0.9992 0.9995 0.9997 0.9999 0.9999
366 301 225 332 298 267
21 35 42 46 54 75
0.191 0.233 0.227 0.210 0.274 0.302
a V : determined from N adsorption isotherm at P/P =0.995. S : total and Sa external surface areas were derived from a -plot. t 2 0 a ext s
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Fig. 2. a -plots of chromia and titania PILCs. s
designated as the filling swing, suggesting the presence of ultramicropores [22]. In the case of the Ti-PM materials, the a -plots exhibit the condensas tion swing corresponding to the filling of supermicropores [22]. The N adsorption isotherms were analyzed by 2 means of the BET and Langmuir approaches and the a method. The two former methods were s applied for P/P values between 0.05 and 0.25, i.e. 0 within the range used by Remy et al. [25]. The results are compiled in Table 1. In the case of the Cr-PM materials, the adsorption isotherms give a good fit on both the Langmuir and BET equations, although the latter method shows a lower correlation coefficient. For the BET equation, an improvement in the correlation coefficient with a decrease of the pillar density is observed. The application of the Langmuir equation to the adsorption isotherms of the Ti-PM samples leads to less favorable correlation coefficients. A much better fit is obtained when the BET equation is used ( Table 1). For all materials studied, the S is larger Langmuir than the S . Table 1 also contains the surface BET areas calculated from a -plots via the slope of the s
extrapolation line passing through the origin [22]. Except for Cr-PM(0.85), the a method gives s surface area values in between S and S . Langmuir BET In addition, the external surface areas obtained from the a -plots increased with the pillar density s reduction (see Table 1). Fig. 3 shows the relative errors between the experimental points obtained from the BET (Cr-PM ) and Langmuir ( Ti-PM ) plots, and the slope determined by a linear regression. As can be seen, in the case of the chromia pillared clays [Fig. 3(A)], a relative error of about 5% is found for an experimental point at a low relative pressure. This is almost more than fivefold higher than the maximum relative error derived from the isotherm of the non-porous reference material (Na-montmorillonite calcined at 973 K ) measured under the same experimental conditions. The noticeable curvature of the Langmuir plots observed for the Ti-PM samples [Fig. 3(B)], together with the low correlation coefficients ( Table 1), indicates that this approach is not suitable for the determination of the surface area of these materials. Fig. 4 compares the surface area calculated by
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Fig. 3. Difference between the experimental points (X ) and those determined from the straight line obtained by linear regression i (C ) expressed in% of C for: (A) BET Eq. (1) Cr-PM(0.85), (2) Cr-PM(0.40), (3) Cr-PM(0.28) and (B) Langmuir Eq. (1) i i Ti-PM(0.85), (2) Ti-PM(0.40), (3) Ti-PM(0.28).
Fig. 4. Evolution of S and S as a function of the Langmuir BET surface area determined by the a method. s
the a method with that derived from the Langmuir s and BET equations. Except for Cr-PM(0.85), the S overestimates, whereas the S underestiLangmuir BET mates, the surface area of pillared clays derived from the a -plots. For the S , the relative s Langmuir overestimation decreases with increasing S . a
As shown recently, using the Dubinin– Radushkevich formalism [23], it is possible to describe the micropore filling and the energetic heterogeneity of various pillared clays [18,21]. Therefore, this method was also applied to characterize the textural properties of our PILC materials. The general features of the DR plots are similar for all preparations. From these plots, two different linear parts can be observed (Fig. 5) and each corresponds to the filling of micropores with different sizes [18,21]. The linearity of those parts tends to decrease with decreasing pillar density, resulting in fewer experimental points that can be fitted ( Fig. 5). As mentioned already, the adsorption on microporous solids with two kinds of micropores has been described by a two-term DR equation. The values of V and E listed in Table 2 are obtained mi i by extrapolation to the ordinate and from the slope of each linear part, respectively (see Fig. 5). V and E were derived from data obtained in m1 1 the low-pressure region, namely log2(P /P)<50, 0 whereas for V and E , data obtained at higher m2 2 relative pressures [log2(P /P)≤4] were taken into 0 account. Since this low-pressure region includes not only the ultramicropores filling, the terms ‘micropores’ and ‘supermicropores’ will be used
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Fig. 5. Dubinin–Radushkevich (DR) plots obtained at high (A and B) and low (C and D) relative pressures: (1) Cr-PM(0.85), (2) Cr-PM(0.40), (3) Cr-PM(0.28) and (4) Ti-PM(0.85), (5) Ti-PM(0.40), (6) Ti-PM(0.28). Table 2 Micropore volumes (V ), specific adsorption energies (E ) derived from DR equation and corresponding correlation coefficients for m i chromia and titania PILCs Sample
V a (ml g−1) m1
E a (kJ mol−1) 1
Correlation coefficient
V b (ml g−1) m2
E b (kJ mol−1) 2
Correlation coefficient
Cr-PM(0.85) Cr-PM(0.40) Cr-PM(0.28) Ti-PM(0.85) Ti-PM(0.40) Ti-PM(0.28)
0.077 0.054 0.042 0.076 0.055 0.042
30.61 30.99 32.89 26.06 26.23 25.25
0.9986 0.9970 0.9956 0.9989 0.9966 0.9953
0.052 0.059 0.057 0.070 0.055 0.048
20.59 16.34 17.15 13.48 15.43 17.29
0.9991 0.9994 0.9990 0.9995 0.9950 0. 9972
a V and E were obtained from low relative pressures [ log2(P /P)]<50. m1 1 0 b V and E were obtained from low relative pressures [ log2(P /P)]<4. m2 2 0
hereunder as a definition of narrow (<0.7–1.0 nm width) and wide (1.0–2.0 nm width) micropores, respectively. The results collected in Table 2 indicate that the specific adsorption energy values E and E depend 1 2 on the nature of the pillared clays. For both Cr-PMs and Ti-PMs, the volumes of micropores
(V ) and supermicropores (V ) are related to the m1 m2 pillar concentration. However, the results reported in Table 2 also show a decrease in correlation coefficients with the reduced pillar concentration, which indicates a lowering of the E and V i mi accuracy. The VDR shown in Table 3 represents the specific mt
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Table 3 Ratios of the volume of the micropores (V ) and the supermicropores over the specific total micropore volume (VDR) derived from m1 mt the DR equation, the specific total micropore volumes (Va ) and (V1 ) obtained from the a method and the method used by Zhu mt mt s et al. [30] Sample
V /VDR m1 mt
V /VDR m2 mt
VDR ml g−1 mt
Va (ml g−1) mt
V1 (ml g−1) mt
Cr-PM(0.85) Cr-PM(0.40) Cr-PM(0.28) Ti-PM(0.85) Ti-PM(0.40) Ti-PM(0.28)
0.60 0.48 0.42 0.52 0.50 0.47
0.40 0.52 0.58 0.48 0.50 0.53
0.129 0.113 0.099 0.146 0.110 0.090
0.120 0.104 0.087 0.142 0.120 0.101
0.121 0.100 0.088 0.134 0.125 0.096
total volume [21] and is the sum of the two micropore-type volumes V and V . For all m1 m2 preparations, the specific total micropore volume (VDR) tends to decrease with decreasing pillar mt density. From the trends of the V /VDR and V m1 mt m2 /VDR ratios, one can see that this is caused by the mt decreasing contribution of micropores, since the value of the V /VDR ratio continuously decreases, m1 mt while V /VDR increases with decreasing pillar denm2 mt sity ( Table 3). Also compared in this table are the specific total micropore volumes obtained with the DR and a methods and with the approach by s Zhu et al. [30,31]. The functions of the adsorption potential distribution, X(A), derived from Eq. (3) for Cr-PM(0.85), Cr-PM(0.40), and Ti-PM(0.85) are presented in Fig. 6. These PILCs were chosen
because the fit of their adsorption data by the DR equation had the highest correlation coefficients (see Table 2). Distributions with two maxima in the A region from zero up to ca 30 kJ mol−1 were obtained. The positions of these maxima (see numbers added) are different for these materials. The larger A values are related to the micropores of a narrow size, which can be considered as ultramicropores and narrow supermicropores, while the smaller values correspond to the wider micropores, mainly supermicropores [21]. Fig. 7 presents the micropore width distributions for these samples, calculated according to Eq. (6) at a x value of 10. These results show 0 that both the nature of the intercalated species and the pillar density influence these distributions. The same conclusion can be derived from the
Fig. 6. Adsorption potential distributions of chromia and titania PILCs.
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Fig. 7. Micropore width distribution of chromia and titania PILCs determined from the DS equation.
micropore size distributions calculated by the method of Zhu et al. [30,31], shown in Fig. 8. The ultramicropores of the Cr-PMs contribute more significantly to the micropore volume than those of the Ti-PMs (see Fig. 9). For the latter samples, the pore width distributions are shifted to wider supermicropores (see Fig. 8). Pores in the range of 0.71–1.06 nm are observed for all the pillared clays and are created probably by gaps in the faceto-face stacking of collapsed or non-intercalated clay layers [36 ].
4. Discussion The variations of the adsorption isotherm shape at low relative pressures ( Fig. 1) indicate that the microporosity of the samples studied differs. In the case of the chromia-pillared clays, the isotherms are more Type I-like, suggesting a significant contribution of ultramicropores, especially for the sample with maximal pillar density [Cr-PM(0.85)]. However, the Ti-PM materials contain a noticeable amount of supermicropores, as follows from the isotherm shape being a combination of Type I and Type IV ( Fig. 1). The latter
isotherm type is characteristic of a mesoporous solid [34], and was observed earlier by Yamanaka et al. [33] for several titania-pillared clays. Hence, our Ti-PMs also contain some mesopores. For both the Cr-PM and Ti-PM materials, a reduction of the pillar density causes an adsorption decrease at low relative pressures (P/P <1.5×10−4), thus 0 implying that the contribution of ultramicropores to the total microporosity tends to decrease with the reduced pillar density. With the exception of the Cr-PM(0.28) sample, the total pore volume increases systematically with decreasing pillar density ( Table 1). This effect can be ascribed to the increase in lateral pillar distance, leading to the development of a total sorption capacity of the pore system. Also, the a -plots ( Fig. 2) show that the micros porosity of the various samples is different. As mentioned already, the a -plots of the Cr-PMs s show an upward deviation at low a values due to s the filling of ultramicropores [22]. This deviation becomes less pronounced when the pillar density decreases; it indicates a lowering of the contribution of those pores. In the case of the Ti-PMs, such a deviation is not observed, reflecting the lower importance of ultramicropores for these
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Fig. 8. Micropore width distribution of the Cr-PM and Ti-PM samples obtained via the method of Zhu et al.
Fig. 9. Contribution of the ultramicropore volume to the total micropore volume of PILCs studied.
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PILCs. However, their a -plots show an upward s swing in the a region of 0.6–1.0 that can be s attributed to the condensation of N in super2 micropores [22]. From these observations, one may conclude that the porous structure of the Cr-PM preparations contains a significant amount of ultramicropores, whereas their Ti-PM counterparts show an important contribution of supermicropores. According to Remy et al. [25], the adsorption isotherms of PILCs reflect the adsorption within the micropores as well as the adsorption on the external surface (S ). The latter parameter can be ext derived from the slope of the extrapolation of the a -plot plateau to the ordinate [19,22]. The data s collected in Table 1 indicate that the contribution of Sa tends to increase with decreasing pillar ext concentration. Additionally, the Ti-PM materials exhibit a larger external surface area than the Cr-PMs do. This agrees well with the data reported by Gil et al. [21], obtained also by the a method s and being obviously characteristic of titania-pillared clays. Furthermore, the micropore volume (Va ) and mt specific surface area (S ) (which is considered to a be a total surface area) can be calculated by means of this method [19,22]. The extrapolation of the a -plot plateau to the ordinate gives the Va params mt eter, whereas the slope of the extrapolation line passing through the origin leads to S . The results a thus obtained are collected in Tables 1 and 3 and are discussed below. Summarizing, it should be pointed out that the a method provides important s information about the porous structure of PILCs. Recently, Remy et al. [25] have shown that neither the BET nor the Langmuir methods yield a truly satisfying determination of the surface area for pillared clays with pore heights around 0.8 nm. The pillared samples under study exhibit a basal spacing between 2.03 and 2.25 nm that corresponds (after subtracting the thickness of the clay layer, 0.96 nm) to pore heights between 1.07 and 1.29 nm. Therefore, it can be assumed that the adsorption isotherms can be fitted by the BET and possibly also by the Langmuir equations. From the data collected in Table 1 and the plots presented in Fig. 3, it follows that for the Cr-PMs, the adsorption isotherms give a good fit on both the Langmuir and BET equations. Nevertheless, the
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latter method shows lower correlation coefficients ( Table 1). This can be attributed to the significant influence of ultramicropores, the presence of which was evidenced by the shape analysis of the adsorption isotherms and a -plots (see Figs. 1 and 2). s The size of those pores allows monolayer adsorption described by the Langmuir equation. The correlation coefficients of the BET equation improved with decreasing pillar density (see Table 1). This is due to the increasing influence of supermicropores, the size of which is large enough to allow multilayer adsorption of nitrogen molecules. For the titania-pillared clays, the Langmuir equation fails, and the BET approach (considering multilayer adsorption) becomes more accurate because of the larger supermicropore contents. This result agrees well with the findings derived from the adsorption isotherms and a -plots and s coincides also with the data reported by Yamanaka et al. [33]. Fig. 4 compares the values of S and BET S withS , the surface area obtained from Langmuir a the a -plots. As can be seen, S is systematically s a larger than S . Similar results were reported by BET Del Castillo and Grange [37] for titania-pillared clays. Apparently, this difference is caused by the influence of ultramicropores in which the multilayer adsorption of N molecules is not possible. 2 Indeed, for those samples having the largest fraction of such pores [Cr-PM(0.85) and Ti-PM(0.85)], the difference between S and S a BET is the most pronounced. With respect to S , Langmuir the relative overestimation of the surface area derived from the a -plots tends to increase with s decreasing pillar density. For Cr-PM(0.85), being the sample with the highest contribution of ultramicropores, the surface areas derived from both methods are very close to each other. Hence, for such materials, the surface area determined from the Langmuir equation is more realistic than that obtained by the BET approach. The values of the respective correlation coefficients are in line herewith (see Table 1). Moreover, based on the data presented, it is possible to conclude that the BET method underestimates, whereas the Langmuir approach overestimates, the total surface area of PILCs with a significant content of supermicropores. This is in line with the results reported by Remy et al. [25]. Furthermore, it is reasonable to
suggest that S gives realistic values of the total a surface area of PILCs. The Dubinin–Radushkevich formalism was used to describe the volume filling of micropores and the energetic heterogeneity of pillared clays under investigation. The shape of the DR plots is similar for all the preparations. However, it differs in the linearity (see Fig. 5). The pillar density reduction in both the Cr-PM and Ti-PM samples causes an increase in the DR plot curvature that makes the corresponding correlation coefficient less favorable (Table 2). This tendency becomes more pronounced for the Ti-PMs. Consequently, an accurate determination of the micropore and supermicropore volumes becomes difficult. The same applies to the specific adsorption energy. Additionally, the pillar density decrease results in an increase in the external surface of the samples ( Table 1). This finding can be considered as an indication for the increase of the surface heterogeneity [21]. Therefore, taking into account that the DR equation is applicable for homogeneous or nearly homogeneous microporous solids [2], the data obtained by means of this method for PILCs should be interpreted carefully. However, even under this condition, the DR formalism provides important information about textural differences. For instance, the observation of two linear parts of the DR plots reflects the presence of two types of micropores in our PILCs [21]. Due to the increase of the supermicropore contribution, the specific total micropore volume, VDR , tends to mt decrease when the pillar concentration is reduced ( Table 3). However, the absolute value of this parameter cannot be determined completely satisfactorily by the DR equation because the parts of the DR plots used for the determination of V mt suffer from an imperfect linearity. Therefore, it is possible only to provide a picture of how the V mt varies within a series of PILCs. Comparison of the E values ( Table 2) indicates that the Cr-PM i samples exhibit a larger contribution of narrow pores than the Ti-PMs do. This is based on the statement that the specific adsorption energy (E ) 0 is related to the micropore size [22,38]. Summarizing, it can be concluded that the DR method can be applied to determine the specific total micropore volume and specific adsorption energy for the pillared clays exhibiting homoge-
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neously distributed narrow micropores, for instance Al-PILC. As mentioned in Section 1, the distribution of the adsorption potential characterizes the total heterogeneity of an adsorbent and is the sum of the structural and surface heterogeneities [21,39]. Since the samples used for the X(A) analysis exhibit a low external surface ( Table 1), the observed heterogeneity can be related to their microporosity [21]. Comparing the values of A for the Cr-PM max and Ti-PM materials, one may conclude that the chromia-pillared clays contain adsorption centers of higher energy (see Fig. 6). This can be attributed to the fact that the micropores in the Cr-PM samples are narrower, and the relevant adsorption potential is more enhanced [38,39]. In addition, a reduction of the pillar density in the Cr-PMs results in a shift of the lower energy peak to lower A values (see Fig. 6). Furthermore, this peak max seems to grow at the expense of the higher energy peak. This observation reflects the increase of the supermicropore contribution to the total microporosity caused by the pillar density reduction. These findings agree with the micropore size distribution calculated according to the Dubinin–Stoeckli (DS) relation ( Fig. 7). As can be seen, the Ti-PM(0.85) sample contains micropores wider than its chromia counterpart Cr-PM(0.85) does. For the latter material, the pillar density decrease leads to a shift in supermicropore size towards larger values. On the contrary, the size of narrow micropores is much less affected. Additionally, the size of those micropores is slightly less than the pore height values derived from XRD (1.07–1.29 nm). The results obtained from the adsorption potential distribution and micropore size distribution derived from the DS relation have a rather qualitative character. Nevertheless, it is reasonable to conclude that these methods give a realistic picture of the structural features of pillared clays containing a significant fraction of ultramicropores. Fig. 8 presents the micropore size distributions calculated by the method of Zhu et al. [30]. The Cr-PM materials contain more ultramicropores that contribute to the micropore volume than Ti-PMs do. Moreover, for both kinds of pillared clays, the content of such micropores decreases
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when the pillar density decreases (see also Fig. 9). A more complex situation is observed for the pore width distribution in the supermicropore region (0.7–2.0 nm). In the case of the Cr-PMs, reduction of the pillar density results in the appearance of new pores in the range of 1.06–1.42 nm. In parallel, herewith, the contribution of the supermicropores of 1.42–1.77 nm decreases. Most likely, these changes caused the shift of the low energy peak in the adsorption potential distribution (see Fig. 6), and the shift in supermicropore size towards larger values, as was derived using the DS equation ( Fig. 7). This finding shows a good agreement between the trends obtained by all the above methods. For the Ti-PM samples, a similar tendency is observed. The pillar density decrease leads to the appearance of large supermicropores (1.77– 2.12 nm). Additionally, the total micropore volumes derived by the method of Zhu et al. [30] agree with, or are close to, those obtained by the a -method ( Table 3). Therefore, based on the data s presented, it is reasonable to conclude that the method of Zhu et al. [30] is useful for the characterization of pillared clays having a significant content of supermicropores.
5. Conclusions Adsorption data at low relative pressures are sources of valuable information about the micropore structure of pillared clays. The shape analysis of the N adsorption isotherms and the a -plots 2 s provide important information about the porous structure of those materials. This analysis approach confirms the existence of two sizes of micropores in the Cr-PM and Ti-PM samples. The surface area calculated by the a method can be s considered as S . The BET method underestitotal mates, whereas the Langmuir approach overestimates, the total surface area of these pillared clays. The Dubinin–Radushkevich method can be applied only for determination of the specific total micropore volume and the specific adsorption energy for PILCs with homogeneously distributed narrow micropores. In such a case, both the DR method and the adsorption potential distribution give a realistic picture of the structural features of
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the pillared clays. The Dubinin–Stoeckli (DS) relation can be used for determination of the micropore size distribution of PILCs having a significant content of ultramicropores. Both the DS approach and the method proposed by Zhu et al. [30] demonstrate that the PILCs studied contain micropores over a broad pore-size range. The latter method is useful for characterization of the porous structure of PILCs with significant contribution of supermicropores. The total micropore volumes derived from the method of Zhu et al. were found to be in good agreement with those obtained by the a method. s All the methods applied show that the chromiapillared montmorillonites contain a significant amount of ultramicropores, whereas the Ti-PMs contain an important amount of supermicropores. Variation of the pillar density causes changes in the surface area, micropore volume and pore-size distribution of these materials.
Acknowledgements The authors thank Mr R. Prihod’ko and Dr K. Erdmann for help. These investigations are supported in part by the Ukrainian Ministry of Education, the Polish Committee for Scientific Research ( KBN ), grant 3 TO9A 04714, and by a Spinoza grant (to R.A.v.S.) by NWO.
References [1] J.M. Thomas, C.R. Theocharis, in: J.M. Thomas, K.I. Zamaraev ( Eds.), Perspectives in Catalysis, Blackwell, London, 1992, p. 465. [2] M.S.A. Baksh, E.S. Kikkinides, R.T. Yang, Ind. Eng. Chem. Res. 39 (1992) 303. [3] V. Hoffmann, R. Klemen, Z. Anorg. Allg. Chem. 262 (1950) 95. [4] M. Horio, K. Suzuki, H. Masuda, T. Mori, Appl. Catal. 72 (1991) 109. [5] K. Suzuki, M. Horio, T. Mori, Bull. Chem. Soc. Jpn. 64 (1991) 732. [6 ] J.R. Jones, J.H. Purnell, Catal. Lett. 28 (1994) 283. [7] M. Sychev, V.H.J. de Beer, R.A. van Santen, Microporous Mater. 8 (1997) 255. [8] M.-S. Tzou, T.J. Pinnavaia, Catal. Today 2 (1988) 243.
[9] T.J. Pinnavaia, M.-S. Tzou, S.D. Landau, J. Am. Chem. Soc. 107 (1985) 4783. [10] H. Auer, H. Hofmann, Appl. Catal. 97 (1993) 23. [11] M. Sychev, V.H.J. de Beer, A. Kodentsov, E.M. van Oers, R.A. van Santen, J. Catal. 168 (1997) 254. [12] H. Yoneyama, S. Haga, S. Yamanaka, J. Phys. Chem. 93 (1989) 335. [13] J.F. Tanguay, S.L. Suib, R.W. Coughlin, J. Catal. 117 (1989) 335. [14] M. Sychev, N. Kostoglod, A. Kosorukov, V. Goncharuk, V. Kashkovski, in: M. Rozwadowski (Ed.), Proc. PolishGerman Zeol. Col., Nicholas Copernicus University Press, Torun, Poland, 1992, p. 63. [15] A. Lamesch, H. del Castillo, P. Vanderwegen, in: Preprints of 3rd Int. Symp. Heterogeneous Catalysis and Fine Chemicals, 5–8 April 1993, Poitiers, France (1993) 241. [16 ] R.T. Yang, W. Li, J. Catal. 115 (1995) 414. [17] K. Bahranowski, R. Dula, J. Komorek, E. Serwicka, in: Preparation of Catalysts VI, G. Poncelet, J. Martens, B. Delmon, P.A. Jacobs, P. Grange (Eds.), Stud. Surf. Sci. Catal. Vol. 91, Elsevier, Amsterdam, 1995, p. 747. [18] A. Gil, M. Montes, Langmuir 10 (1994) 291. [19] S.J. Gregg, K.S.W. Sing (Eds.), Adsorption, Surface Area and Porosity, Academic Press, London, 1991, Chapter 4. [20] Z. Ge, D. Li, T.J. Pinnavaia, Microporous Mater. 3 (1994) 165. [21] A. Gil, A. Massinon, P. Grange, Microporous Mater. 4 (1995) 369. [22] K. Kaneko, J. Membr. Sci. 96 (1994) 59. [23] M.M. Dubinin, Carbon 23 (1985) 373. [24] J.H. de Boer, B.G. Linsen, T.J. Osinga, J. Catal. 4 (1964) 643. [25] M.J. Remy, A.C. Vieira Coelho, G. Poncelet, Microporous Mater. 7 (1996) 287. [26 ] K.S.W. Sing, Chem. Ind. 20 (1967) 829. [27] G.F. Cerofilini, Surf. Sci. 24 (1971) 391. [28] M.M. Dubinin, H.F. Stoeckli, J. Colloid Interf. Sci. 75 (1980) 34. [29] G. Horvath, K. Kawazoe, J. Chem. Eng. Jpn. 16 (1983) 470. [30] H.Y. Zhu, N. Maes, E.F. Vansant, in: Characterization of Porous Solids III, J. Rouquerol, F. Rodriguez-Reinoso, K.S.W. Sing, K.K. Unger (Eds.), Stud. Surf. Sci. Catal. Vol. 87, Elsevier, Amsterdam, 1994, p. 457. [31] H.Y. Zhu, A. Molinard, E.F. Vansant, Microporous Mater. 3 (1994) 35. [32] M. Tokarz, J. Shabtai, Clays Clay Miner. 33 (1985) 89. [33] S. Yamanaka, T. Nishihara, M. Hattori, Mater. Chem. Phys. 17 (1987) 87. [34] K.S.W. Sing, D.H. Everett, R.A.W. Haul, L. Moscow, R.A. Pierotti, J. Rouquerol, T. Siemieniewska, Pure Appl. Chem. 57 (4) (1985) 603. [35] N. Kostoglod, M. Sychev, R. Prihodrsquoko, I.M. Astrelin, A. Stepanenko, M. Rozwadowski, Kinetics Catal. 39 (1998) 547. [36 ] P. Cool, E.F. Vansant, Microporous Mater. 6 (1996) 27. [37] H.L. Del Castillo, P. Grange, Appl. Catal. 103 (1993) 23. [38] R.H. Bradley, B. Rand, J. Colloid Interf. Sci. 169 (1995) 168. [39] K.E. Wisniewski, R. Wojsz, Zeolites 12 (1992) 37.
Characterization of the microporosity of chromia- and titaniapillared montmorillonites differing in pillar density. I. Adsorption of nitrogen Mikhail Sychev a, *, Tatjana Shubina a, Michal Rozwadowski b, A.P.B. Sommen c, V.H.J. De Beer c, Rutger A. van Santen c a National Technical University of Ukraine ‘Kiev Polytechnic Institute’, Faculty of Chemical Technology, TNV, 252056 Kiev, pr. Peremogy 37, Ukraine b Faculty of Chemistry, Nicholas Copernicus University, 87–100 Torun, Gagarina 7, Poland c Schuit Institute of Catalysis, Eindhoven University of Technology, PO Box 513, 5600 MB Eindhoven, The Netherlands Received 29 March 1999; received in revised form 6 October 1999; accepted for publication 8 October 1999
Abstract The microporosity of chromia- and titania-pillared clays differing in pillar density has been explored. Nitrogen adsorption data determined at very low relative pressures were used. These data were analyzed by means of the a s method and the BET, Langmuir, Dubinin–Radushkevich and Dubinin–Stoeckli approaches. The applicability of these methods for determination of the PILCs’ microporosity was studied. The surface area calculated by the a method s can be considered as a total surface area of the materials studied. The BET method underestimates, whereas the Langmuir approach overestimates, the total surface area of these solids. The Dubinin–Radushkevich method can be applied only to characterize textural features of PILCs exhibiting homogeneously distributed narrow micropores (<0.7–1.0 nm width). The same holds for the Dubinin–Stoeckli relation. The method developed by Zhu et al. is useful for the determination of the porous structure of PILCs having a significant contribution of supermicropores (0.7–2.0 nm width). A good agreement between the total micropore volume of the materials studied and that obtained from the a method was found. All the methods applied demonstrated that these solids possess micropores over a s broad pore-size range. Chromia-pillared montmorillonites contain a significant amount of ultramicropores (<0.7 nm width), whereas titania-pillared clays show an important contribution of supermicropores. An alteration of the pillar density can provide a family of pillared clays that differ in the surface area, micropore volume, and micropore size distribution. © 2000 Elsevier Science B.V. All rights reserved. Keywords: Chromia-pillared clays; Microporosity analysis; Nitrogen adsorption; Titania-pillared clays
* Corresponding author. Tel.: +380-44-441-1279; fax: +380-44-274-2004. E-mail address: [email protected] (M. Sychev) 1387-1811/00/$ - see front matter © 2000 Elsevier Science B.V. All rights reserved. PII: S1 3 8 7 -1 8 1 1 ( 9 9 ) 0 0 26 5 - 6
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1. Introduction Intercalation of smectite clays via exchange of cations located in their interlayer space with hydroxy-metal polycations, followed by a thermal treatment, is an effective approach to modulate them with the purpose to obtain adsorbents, catalyst supports or catalysts [1,2]. The materials thus prepared are referred to as pillared interlayered clays (PILCs). The amount of an incorporated phase can be changed by varying the cation exchange capacity (CEC ) of the host clay mineral. In turn, it is possible to adjust the CEC by means of the Hoffmann–Klemen effect [3], the essence of which consists of migration of some cations with small ionic radii (Li, Co, Ni) to vacant octahedral sites in the clay layers upon heating. Alumina-, zirconiaand chromia-pillared clays differing in pillar density were prepared using clays with a reduced CEC [4–7]. It can be concluded from the literature that the materials considered in the present study exhibit promising catalytic properties [8–17]. Montmorillonite pillared with chromia displays a high catalytic activity for cyclohexene dehydrogenation [8], hydrocracking of n-decane [9], and toluene disproportionation [10]. Its sulfide form is an active and stable catalyst for both thiophene hydrodesulfurization and butene hydrogenation [11]. Titania-pillared montmorillonite is known to have a high thermal stability and attractive catalytic properties [12–14]. This material exhibits a high reactivity in photodegradation of compounds such as 2-propanol, some carboxylic acids, dichloromethane, and chloroform [12–14]. Modification of Ti-PILC with Pd, Cu or V resulted in active and selective catalysts for the hydrogenation of butenonitriles [15], reduction of NO by hydrocarbons and by ammonia [16 ] as well as for the oxidative dehydrogenation of propane [17]. 1.1. Theoretical considerations on micropore analysis The purpose of this section is to review briefly the most commonly used approaches dealing with the characterization of pillared clay microporosity.
One of the main problems in the characterization of porous materials, including PILCs, is the determination of their surface area, micropore volume and pore size distribution, which plays an essential role in their application as catalysts or adsorbents. Several methods have been developed to deduce the pore structure of microporous solids from adsorption isotherms. Owing to their simplicity and the importance of the information generated, the t, a and Dubinin–Radushkevich methods are s often used [18–23]. The first two methods are based on the comparison of adsorption data obtained for the material to be tested with adsorption on a non-porous sample (reference isotherm). They assumed that at relative pressures above a certain value, the micropores are completely filled, and only the adsorption on the external surface influences the isotherm [22]. When the adsorbed volume at each experimental point is plotted against the statistical thickness, t, a linear relation between the adsorbed volume and the t values can be obtained [24]. The estimation of t should be based on the reference isotherm, which yields the same BET constant (C ) as that of the material BET tested. However, C of the external surface of a BET microporous solid is rather difficult to determine [25]. As was demonstrated previously [25], the choice of the standard t function and the part of the V–t curve used for linear fitting may drastically affect the values of the external surface and micropore volume. The strong influence of the chemical composition of the surface on the evolution of t as a function of P/P was evidenced [25]. To avoid 0 the above complications, Sing [26 ] introduced and developed the a method in which the normalized s adsorption, a (=n/n ), is derived from the isos 0.4 therm of a reference material by using the amount adsorbed at a relative pressure of 0.4 (n ) as the 0.4 normalization factor. The adsorption in micropores can be interpreted using the thermodynamic Dubinin–Radushkevich (DR) equation [23] that holds for a variety of adsorption systems. This equation is based on the assumption that adsorbed molecules exhibit an adsorption potential, A, that governs the fractional pore filling. The DR equation is expressed by V /V =exp[−(A/bE )2], a 0 0
(1)
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189
with V , V , E and b being the amount of adsorpa 0 0 tion at equilibrium pressure, P, the micropore volume, the characteristic adsorption energy, and the affinity coefficient characterizing the adsorbate, respectively. The term ‘adsorption potential’ (A) was introduced by Polanyi, and it corresponds to the change of a molar free energy caused by the change of a vapor pressure [22]:
tion of the pore width from experimental isotherms [22]). This relation is used for transformation of the characteristic adsorption energy to the half-width of the slit-shaped micropores. A Gaussian distribution of these pore widths is given by
A=RT ln(P /P)=−DG, (2) 0 with DG and R being the differential free energy of adsorption and the universal gas constant, respectively. The total heterogeneity, i.e. the sum of the structural and surface heterogeneities of an adsorbent, is usually characterized by a distribution function (X ) of the adsorption potential and may be evaluated by means of the condensation approximation method [27] as
with d and x being the dispersion of the Gaussian distribution and the value of the pore half-width [22], respectively. The micropore size distribution can be derived from the relationship dV /dx vs. x. a The calculation using this method has been widely applied to a great number of carbonaceous adsorbents giving reasonable results [22]. Horvath and Kawazoe described a method for calculating the effective micropore volume distribution of slit-shaped pores [29]. They took into account the interaction between adsorbent and adsorptive using the interaction parameter that depends on their nature. It was established that in the case of materials containing pores with a width less than 1.0 nm, the results determined by this method are in good agreement with the data obtained by other approaches [2,30]. For zeolites having small pores, as well as for alumina-pillared clays with a free space (interlayer free spacing) of 0.7–0.8 nm, the H–K approach gives reasonable pore size distributions [2,30]. However, for materials having a significant fraction of supermicropores, the data obtained by this method were found to be unrealistic [30,31]. Recently, Zhu et al. [30,31] proposed a method using the low-pressure part of the adsorption isotherm for determination of the micropore size distribution of PILCs. The authors assume that the relative pressure at which micropores of each type are completely filled depends on the number of nitrogen layers that can be accommodated. Consequently, the micropore range can be subdivided into five pore groups as a function of the nitrogen monolayers that they can be adsorb. The N adsorption isotherm is replotted as log(P/P ) 2 0 vs. the ratio of the nitrogen volume adsorbed at each relative pressure to the total volume adsorbed. The curve thus obtained contains steps that are
X(A)=−dH(A)/dA,
(3)
with H being the relative adsorption. The intercept of the linear part with the lower slope of the plot lnV vs. ln2(P /P) yields the 0 micropore volume. The micropore filling of a system with a distribution of pore sizes can be described by the sum of the contributions from individual pore groups that are characterized by their own pore volume, V , and adsorption energy i E . Adsorption on microporous solids having two i kinds of micropores can be described by a twoterm DR equation [18,22], expressed as: V=V exp[−(R2T2 ln2(P /P)/E2 ]+V 1 0 1 2 ×exp[−(R2T2 ln2(P /P)/E2 ] (4) 0 2 The Dubinin–Stoeckli (DS) relation [28] describes an empirical relationship between the characteristic adsorption energy (E ) and the 0 average half-width of the slit-shaped micropores (x ) 0 E =k/x , (5) 0 0 where k=13.03–1.53×10−5E3.5 0 A constant value of 10 or 12 is used for x (the 0 constant 10 is more appropriate for the determina-
dV /dx =[V /d(2p)1/2)] exp[−(x −x)2/2d2], a 0 0 0 (6)
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thermodynamically related to the filling of pores of a certain size. The derivative of this curve, dV/d log(P/P ), clearly exhibits the position of 0 these steps. By locating the main maxima, the pore-size range can be correlated with a certain P/P range. 0 For pillared clays, however, the methods reviewed above yield different micropore volumes. The present paper deals with the characterization of the microporosity of pillared montmorillonites differing in pillar density via the nitrogen adsorption. An attempt is also made to analyze the applicability of different methods for distinguishing the microporosity of these PILCs.
2. Experimental 2.1. Materials Preparation conditions were chosen as to obtain samples with different microporosities. The starting material was a purified Oglanlinsky bentonite (CIS) [7]. Its monoionic Li form, which contains 0.85 mequiv. g−1, of exchangeable Li+, was prepared following the technique described elsewhere [32]. Portions of this cationic form were calcined at 408 and 423 K for 24 h. A small amount of each was then exchanged with NH+ to allow 4 determination of the CEC by the micro-Kjeldahl method. A fraction of the air-dried and calcined Li-form containing particles smaller than 2 mm (collected by sedimentation) was used for pillaring. Since the calcined clay does not swell fully in water, an acetone–aqueous suspension was applied for the pillaring. The preparation method of Cr-PILCs was similar to that proposed by Tzou and Pinnavaia [8]. The pillaring reagent containing Cr oligomers was formed by heating a 1.0 mol dm−3 solution of Cr(NO ) and Na CO at 368 K for 36 h. Prior to 33 2 3 this operation, the base was gradually added to the vigorously stirred Cr(NO ) solution at room 33 temperature so that the molar concentration ratio of hydroxide to the Cr ion was equal to 2.0. The aqueous or acetone–aqueous suspension of the host clay (1.0 wt%) was added slowly to the vigorously stirred pillaring reagent (50 mmol Cr3+ per
mequiv. clay) at 313 K, and the mixture was stirred for 1.5 h. Titania-pillared clays were prepared following the procedure of Yamanaka et al. [33]. Ti isopropoxide was added dropwise in an inert atmosphere to a vigorously stirred 1 mol dm−3 HCl solution. The molar ratio of acid to alkoxide was equal to four. The resulting slurry was peptized by further stirring at 298 K for 3 h. Next, the obtained sol was mixed with an acetone–aqueous suspension of the cationic form of montmorillonite. The amount of titania sol used for pillaring was such that the molar TiO /clay CEC ratio was 40. Then, the 2 mixture was kept at 298 K for 3 h under continuous stirring. After completion of the pillaring reaction, both chromia- and titania-pillared clays were separated by centrifugation, washed 10-fold with de-ionized water (i.e. the Ti-PMs were Cl−-free as checked by AgNO ) air-dried in a thin layer at 295 K, and 3 heat-treated in a He flow at 473 K for 5 h. The samples synthesized are referred to as Cr- or Ti-PM(0.85), -PM(0.40) and -PM(0.28), where the numbers in parentheses indicate the CEC of the parent material. The amount of Cr and Ti incorporated in the montmorillonite was determined by atomic-absorption spectroscopy (AAS ) with a Perkin Elmer 3030 spectrometer using the Li metaborate method [7]. 2.2. Nitrogen adsorption N adsorption experiments were performed at 2 liquid-nitrogen temperature (77 K ), using a Micromeritics ASAP 2010 apparatus (a static volumetric technique). Prior to the determination of an adsorption isotherm, a sample (approximately 0.25 g) was outgassed at 473 K for 5 h under a residual pressure lower than 10−4 mbar. The pressure was measured with an accuracy of ±0.25%. For the a -plots, the adsorption isotherm of s Na-montmorillonite calcined at 973 K was used as a reference.
3. Results At low relative pressures, the N adsorption– 2 desorption isotherms of the Cr-PM preparations
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Fig. 1. Nitrogen adsorption isotherms at low relative pressures: (A) (1) Cr-PM(0.85), (2) Cr-PM(0.40), (3) Cr-PM(0.28) and (B) (1) Ti-PM(0.85), (2) Ti-PM(0.40), (3) Ti-PM(0.28).
are close to Type I of the IUPAC classification [34]. The results are similar to those reported by us earlier [7,11,35]. For the Ti-PM materials, the adsorption isotherms are rather a combination of Type I and Type IV. All isotherms show that the pillared clays are essentially microporous with some mesoporosity [33,35]. The N adsorption isotherms obtained at very 2 low pressures are shown in Fig. 1. According to Gil et al. [21], their shape indicates the presence of two groups of micropores differing in size. One group is filled with N at lower relative pressures, 2 approximately up to p/p =1.5 10−4, and can be 0 classified as ultramicropores (<0.7 nm width). The other group is filled at higher relative pressures, and can be considered as supermicropores (0.7– 2.0 nm width) [22]. The abundance of both pore groups depends on the nature of the intercalated
species (see Fig. 1). In the case of the Ti-PM materials, the fraction of ultramicropores is somewhat smaller compared to that of Cr-PMs. In parallel, herewith, the contribution of such pores tends to decrease with a reduced pillar concentration. Also, the results presented in Table 1 demonstrate that the specific total pore volume (V ) derived from the adsorption isotherms, except t for the Cr-PM(0.28) sample containing a small fraction of incompletely pillared clay [7], increases with decreasing pillar population. Fig. 2 shows the a -plots derived from the N s 2 adsorption isotherms. Each a -plot exhibits a plas teau with an insignificant slope, and can be extrapolated to the origin. For the Cr-PM samples, the lowest a values part of these plots do not accus rately fit the extrapolation due to an upward swing. This kind of deviation in the a -plot has been s
Table 1 Specific surface areas and specific total pore volume (V ) for chromia and titania pillared claysa t Sample
Cr ( Ti) content (mol kg−1)
S Langmuir (m2 g−1)
Correlation coefficient
S BET (m2 g−1)
Correlation coefficient
S a (m2 g−1)
Sa ext (m2 g−1)
V t (ml g−1)
Cr-PM(0.85) Cr-PM(0.40) Cr-PM(0.28) Ti-PM(0.85) Ti-PM(0.40) Ti-PM(0.28)
5.10 3.11 1.72 5.69 2.68 1.87
363 324 285 440 402 356
0.9999 0.9999 0.9999 0.9990 0.9985 0.9976
308 285 210 290 287 254
0.9989 0.9992 0.9995 0.9997 0.9999 0.9999
366 301 225 332 298 267
21 35 42 46 54 75
0.191 0.233 0.227 0.210 0.274 0.302
a V : determined from N adsorption isotherm at P/P =0.995. S : total and Sa external surface areas were derived from a -plot. t 2 0 a ext s
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Fig. 2. a -plots of chromia and titania PILCs. s
designated as the filling swing, suggesting the presence of ultramicropores [22]. In the case of the Ti-PM materials, the a -plots exhibit the condensas tion swing corresponding to the filling of supermicropores [22]. The N adsorption isotherms were analyzed by 2 means of the BET and Langmuir approaches and the a method. The two former methods were s applied for P/P values between 0.05 and 0.25, i.e. 0 within the range used by Remy et al. [25]. The results are compiled in Table 1. In the case of the Cr-PM materials, the adsorption isotherms give a good fit on both the Langmuir and BET equations, although the latter method shows a lower correlation coefficient. For the BET equation, an improvement in the correlation coefficient with a decrease of the pillar density is observed. The application of the Langmuir equation to the adsorption isotherms of the Ti-PM samples leads to less favorable correlation coefficients. A much better fit is obtained when the BET equation is used ( Table 1). For all materials studied, the S is larger Langmuir than the S . Table 1 also contains the surface BET areas calculated from a -plots via the slope of the s
extrapolation line passing through the origin [22]. Except for Cr-PM(0.85), the a method gives s surface area values in between S and S . Langmuir BET In addition, the external surface areas obtained from the a -plots increased with the pillar density s reduction (see Table 1). Fig. 3 shows the relative errors between the experimental points obtained from the BET (Cr-PM ) and Langmuir ( Ti-PM ) plots, and the slope determined by a linear regression. As can be seen, in the case of the chromia pillared clays [Fig. 3(A)], a relative error of about 5% is found for an experimental point at a low relative pressure. This is almost more than fivefold higher than the maximum relative error derived from the isotherm of the non-porous reference material (Na-montmorillonite calcined at 973 K ) measured under the same experimental conditions. The noticeable curvature of the Langmuir plots observed for the Ti-PM samples [Fig. 3(B)], together with the low correlation coefficients ( Table 1), indicates that this approach is not suitable for the determination of the surface area of these materials. Fig. 4 compares the surface area calculated by
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Fig. 3. Difference between the experimental points (X ) and those determined from the straight line obtained by linear regression i (C ) expressed in% of C for: (A) BET Eq. (1) Cr-PM(0.85), (2) Cr-PM(0.40), (3) Cr-PM(0.28) and (B) Langmuir Eq. (1) i i Ti-PM(0.85), (2) Ti-PM(0.40), (3) Ti-PM(0.28).
Fig. 4. Evolution of S and S as a function of the Langmuir BET surface area determined by the a method. s
the a method with that derived from the Langmuir s and BET equations. Except for Cr-PM(0.85), the S overestimates, whereas the S underestiLangmuir BET mates, the surface area of pillared clays derived from the a -plots. For the S , the relative s Langmuir overestimation decreases with increasing S . a
As shown recently, using the Dubinin– Radushkevich formalism [23], it is possible to describe the micropore filling and the energetic heterogeneity of various pillared clays [18,21]. Therefore, this method was also applied to characterize the textural properties of our PILC materials. The general features of the DR plots are similar for all preparations. From these plots, two different linear parts can be observed (Fig. 5) and each corresponds to the filling of micropores with different sizes [18,21]. The linearity of those parts tends to decrease with decreasing pillar density, resulting in fewer experimental points that can be fitted ( Fig. 5). As mentioned already, the adsorption on microporous solids with two kinds of micropores has been described by a two-term DR equation. The values of V and E listed in Table 2 are obtained mi i by extrapolation to the ordinate and from the slope of each linear part, respectively (see Fig. 5). V and E were derived from data obtained in m1 1 the low-pressure region, namely log2(P /P)<50, 0 whereas for V and E , data obtained at higher m2 2 relative pressures [log2(P /P)≤4] were taken into 0 account. Since this low-pressure region includes not only the ultramicropores filling, the terms ‘micropores’ and ‘supermicropores’ will be used
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Fig. 5. Dubinin–Radushkevich (DR) plots obtained at high (A and B) and low (C and D) relative pressures: (1) Cr-PM(0.85), (2) Cr-PM(0.40), (3) Cr-PM(0.28) and (4) Ti-PM(0.85), (5) Ti-PM(0.40), (6) Ti-PM(0.28). Table 2 Micropore volumes (V ), specific adsorption energies (E ) derived from DR equation and corresponding correlation coefficients for m i chromia and titania PILCs Sample
V a (ml g−1) m1
E a (kJ mol−1) 1
Correlation coefficient
V b (ml g−1) m2
E b (kJ mol−1) 2
Correlation coefficient
Cr-PM(0.85) Cr-PM(0.40) Cr-PM(0.28) Ti-PM(0.85) Ti-PM(0.40) Ti-PM(0.28)
0.077 0.054 0.042 0.076 0.055 0.042
30.61 30.99 32.89 26.06 26.23 25.25
0.9986 0.9970 0.9956 0.9989 0.9966 0.9953
0.052 0.059 0.057 0.070 0.055 0.048
20.59 16.34 17.15 13.48 15.43 17.29
0.9991 0.9994 0.9990 0.9995 0.9950 0. 9972
a V and E were obtained from low relative pressures [ log2(P /P)]<50. m1 1 0 b V and E were obtained from low relative pressures [ log2(P /P)]<4. m2 2 0
hereunder as a definition of narrow (<0.7–1.0 nm width) and wide (1.0–2.0 nm width) micropores, respectively. The results collected in Table 2 indicate that the specific adsorption energy values E and E depend 1 2 on the nature of the pillared clays. For both Cr-PMs and Ti-PMs, the volumes of micropores
(V ) and supermicropores (V ) are related to the m1 m2 pillar concentration. However, the results reported in Table 2 also show a decrease in correlation coefficients with the reduced pillar concentration, which indicates a lowering of the E and V i mi accuracy. The VDR shown in Table 3 represents the specific mt
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Table 3 Ratios of the volume of the micropores (V ) and the supermicropores over the specific total micropore volume (VDR) derived from m1 mt the DR equation, the specific total micropore volumes (Va ) and (V1 ) obtained from the a method and the method used by Zhu mt mt s et al. [30] Sample
V /VDR m1 mt
V /VDR m2 mt
VDR ml g−1 mt
Va (ml g−1) mt
V1 (ml g−1) mt
Cr-PM(0.85) Cr-PM(0.40) Cr-PM(0.28) Ti-PM(0.85) Ti-PM(0.40) Ti-PM(0.28)
0.60 0.48 0.42 0.52 0.50 0.47
0.40 0.52 0.58 0.48 0.50 0.53
0.129 0.113 0.099 0.146 0.110 0.090
0.120 0.104 0.087 0.142 0.120 0.101
0.121 0.100 0.088 0.134 0.125 0.096
total volume [21] and is the sum of the two micropore-type volumes V and V . For all m1 m2 preparations, the specific total micropore volume (VDR) tends to decrease with decreasing pillar mt density. From the trends of the V /VDR and V m1 mt m2 /VDR ratios, one can see that this is caused by the mt decreasing contribution of micropores, since the value of the V /VDR ratio continuously decreases, m1 mt while V /VDR increases with decreasing pillar denm2 mt sity ( Table 3). Also compared in this table are the specific total micropore volumes obtained with the DR and a methods and with the approach by s Zhu et al. [30,31]. The functions of the adsorption potential distribution, X(A), derived from Eq. (3) for Cr-PM(0.85), Cr-PM(0.40), and Ti-PM(0.85) are presented in Fig. 6. These PILCs were chosen
because the fit of their adsorption data by the DR equation had the highest correlation coefficients (see Table 2). Distributions with two maxima in the A region from zero up to ca 30 kJ mol−1 were obtained. The positions of these maxima (see numbers added) are different for these materials. The larger A values are related to the micropores of a narrow size, which can be considered as ultramicropores and narrow supermicropores, while the smaller values correspond to the wider micropores, mainly supermicropores [21]. Fig. 7 presents the micropore width distributions for these samples, calculated according to Eq. (6) at a x value of 10. These results show 0 that both the nature of the intercalated species and the pillar density influence these distributions. The same conclusion can be derived from the
Fig. 6. Adsorption potential distributions of chromia and titania PILCs.
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Fig. 7. Micropore width distribution of chromia and titania PILCs determined from the DS equation.
micropore size distributions calculated by the method of Zhu et al. [30,31], shown in Fig. 8. The ultramicropores of the Cr-PMs contribute more significantly to the micropore volume than those of the Ti-PMs (see Fig. 9). For the latter samples, the pore width distributions are shifted to wider supermicropores (see Fig. 8). Pores in the range of 0.71–1.06 nm are observed for all the pillared clays and are created probably by gaps in the faceto-face stacking of collapsed or non-intercalated clay layers [36 ].
4. Discussion The variations of the adsorption isotherm shape at low relative pressures ( Fig. 1) indicate that the microporosity of the samples studied differs. In the case of the chromia-pillared clays, the isotherms are more Type I-like, suggesting a significant contribution of ultramicropores, especially for the sample with maximal pillar density [Cr-PM(0.85)]. However, the Ti-PM materials contain a noticeable amount of supermicropores, as follows from the isotherm shape being a combination of Type I and Type IV ( Fig. 1). The latter
isotherm type is characteristic of a mesoporous solid [34], and was observed earlier by Yamanaka et al. [33] for several titania-pillared clays. Hence, our Ti-PMs also contain some mesopores. For both the Cr-PM and Ti-PM materials, a reduction of the pillar density causes an adsorption decrease at low relative pressures (P/P <1.5×10−4), thus 0 implying that the contribution of ultramicropores to the total microporosity tends to decrease with the reduced pillar density. With the exception of the Cr-PM(0.28) sample, the total pore volume increases systematically with decreasing pillar density ( Table 1). This effect can be ascribed to the increase in lateral pillar distance, leading to the development of a total sorption capacity of the pore system. Also, the a -plots ( Fig. 2) show that the micros porosity of the various samples is different. As mentioned already, the a -plots of the Cr-PMs s show an upward deviation at low a values due to s the filling of ultramicropores [22]. This deviation becomes less pronounced when the pillar density decreases; it indicates a lowering of the contribution of those pores. In the case of the Ti-PMs, such a deviation is not observed, reflecting the lower importance of ultramicropores for these
M. Sychev et al. / Microporous and Mesoporous Materials 37 (2000) 187–200
Fig. 8. Micropore width distribution of the Cr-PM and Ti-PM samples obtained via the method of Zhu et al.
Fig. 9. Contribution of the ultramicropore volume to the total micropore volume of PILCs studied.
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PILCs. However, their a -plots show an upward s swing in the a region of 0.6–1.0 that can be s attributed to the condensation of N in super2 micropores [22]. From these observations, one may conclude that the porous structure of the Cr-PM preparations contains a significant amount of ultramicropores, whereas their Ti-PM counterparts show an important contribution of supermicropores. According to Remy et al. [25], the adsorption isotherms of PILCs reflect the adsorption within the micropores as well as the adsorption on the external surface (S ). The latter parameter can be ext derived from the slope of the extrapolation of the a -plot plateau to the ordinate [19,22]. The data s collected in Table 1 indicate that the contribution of Sa tends to increase with decreasing pillar ext concentration. Additionally, the Ti-PM materials exhibit a larger external surface area than the Cr-PMs do. This agrees well with the data reported by Gil et al. [21], obtained also by the a method s and being obviously characteristic of titania-pillared clays. Furthermore, the micropore volume (Va ) and mt specific surface area (S ) (which is considered to a be a total surface area) can be calculated by means of this method [19,22]. The extrapolation of the a -plot plateau to the ordinate gives the Va params mt eter, whereas the slope of the extrapolation line passing through the origin leads to S . The results a thus obtained are collected in Tables 1 and 3 and are discussed below. Summarizing, it should be pointed out that the a method provides important s information about the porous structure of PILCs. Recently, Remy et al. [25] have shown that neither the BET nor the Langmuir methods yield a truly satisfying determination of the surface area for pillared clays with pore heights around 0.8 nm. The pillared samples under study exhibit a basal spacing between 2.03 and 2.25 nm that corresponds (after subtracting the thickness of the clay layer, 0.96 nm) to pore heights between 1.07 and 1.29 nm. Therefore, it can be assumed that the adsorption isotherms can be fitted by the BET and possibly also by the Langmuir equations. From the data collected in Table 1 and the plots presented in Fig. 3, it follows that for the Cr-PMs, the adsorption isotherms give a good fit on both the Langmuir and BET equations. Nevertheless, the
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latter method shows lower correlation coefficients ( Table 1). This can be attributed to the significant influence of ultramicropores, the presence of which was evidenced by the shape analysis of the adsorption isotherms and a -plots (see Figs. 1 and 2). s The size of those pores allows monolayer adsorption described by the Langmuir equation. The correlation coefficients of the BET equation improved with decreasing pillar density (see Table 1). This is due to the increasing influence of supermicropores, the size of which is large enough to allow multilayer adsorption of nitrogen molecules. For the titania-pillared clays, the Langmuir equation fails, and the BET approach (considering multilayer adsorption) becomes more accurate because of the larger supermicropore contents. This result agrees well with the findings derived from the adsorption isotherms and a -plots and s coincides also with the data reported by Yamanaka et al. [33]. Fig. 4 compares the values of S and BET S withS , the surface area obtained from Langmuir a the a -plots. As can be seen, S is systematically s a larger than S . Similar results were reported by BET Del Castillo and Grange [37] for titania-pillared clays. Apparently, this difference is caused by the influence of ultramicropores in which the multilayer adsorption of N molecules is not possible. 2 Indeed, for those samples having the largest fraction of such pores [Cr-PM(0.85) and Ti-PM(0.85)], the difference between S and S a BET is the most pronounced. With respect to S , Langmuir the relative overestimation of the surface area derived from the a -plots tends to increase with s decreasing pillar density. For Cr-PM(0.85), being the sample with the highest contribution of ultramicropores, the surface areas derived from both methods are very close to each other. Hence, for such materials, the surface area determined from the Langmuir equation is more realistic than that obtained by the BET approach. The values of the respective correlation coefficients are in line herewith (see Table 1). Moreover, based on the data presented, it is possible to conclude that the BET method underestimates, whereas the Langmuir approach overestimates, the total surface area of PILCs with a significant content of supermicropores. This is in line with the results reported by Remy et al. [25]. Furthermore, it is reasonable to
suggest that S gives realistic values of the total a surface area of PILCs. The Dubinin–Radushkevich formalism was used to describe the volume filling of micropores and the energetic heterogeneity of pillared clays under investigation. The shape of the DR plots is similar for all the preparations. However, it differs in the linearity (see Fig. 5). The pillar density reduction in both the Cr-PM and Ti-PM samples causes an increase in the DR plot curvature that makes the corresponding correlation coefficient less favorable (Table 2). This tendency becomes more pronounced for the Ti-PMs. Consequently, an accurate determination of the micropore and supermicropore volumes becomes difficult. The same applies to the specific adsorption energy. Additionally, the pillar density decrease results in an increase in the external surface of the samples ( Table 1). This finding can be considered as an indication for the increase of the surface heterogeneity [21]. Therefore, taking into account that the DR equation is applicable for homogeneous or nearly homogeneous microporous solids [2], the data obtained by means of this method for PILCs should be interpreted carefully. However, even under this condition, the DR formalism provides important information about textural differences. For instance, the observation of two linear parts of the DR plots reflects the presence of two types of micropores in our PILCs [21]. Due to the increase of the supermicropore contribution, the specific total micropore volume, VDR , tends to mt decrease when the pillar concentration is reduced ( Table 3). However, the absolute value of this parameter cannot be determined completely satisfactorily by the DR equation because the parts of the DR plots used for the determination of V mt suffer from an imperfect linearity. Therefore, it is possible only to provide a picture of how the V mt varies within a series of PILCs. Comparison of the E values ( Table 2) indicates that the Cr-PM i samples exhibit a larger contribution of narrow pores than the Ti-PMs do. This is based on the statement that the specific adsorption energy (E ) 0 is related to the micropore size [22,38]. Summarizing, it can be concluded that the DR method can be applied to determine the specific total micropore volume and specific adsorption energy for the pillared clays exhibiting homoge-
M. Sychev et al. / Microporous and Mesoporous Materials 37 (2000) 187–200
neously distributed narrow micropores, for instance Al-PILC. As mentioned in Section 1, the distribution of the adsorption potential characterizes the total heterogeneity of an adsorbent and is the sum of the structural and surface heterogeneities [21,39]. Since the samples used for the X(A) analysis exhibit a low external surface ( Table 1), the observed heterogeneity can be related to their microporosity [21]. Comparing the values of A for the Cr-PM max and Ti-PM materials, one may conclude that the chromia-pillared clays contain adsorption centers of higher energy (see Fig. 6). This can be attributed to the fact that the micropores in the Cr-PM samples are narrower, and the relevant adsorption potential is more enhanced [38,39]. In addition, a reduction of the pillar density in the Cr-PMs results in a shift of the lower energy peak to lower A values (see Fig. 6). Furthermore, this peak max seems to grow at the expense of the higher energy peak. This observation reflects the increase of the supermicropore contribution to the total microporosity caused by the pillar density reduction. These findings agree with the micropore size distribution calculated according to the Dubinin–Stoeckli (DS) relation ( Fig. 7). As can be seen, the Ti-PM(0.85) sample contains micropores wider than its chromia counterpart Cr-PM(0.85) does. For the latter material, the pillar density decrease leads to a shift in supermicropore size towards larger values. On the contrary, the size of narrow micropores is much less affected. Additionally, the size of those micropores is slightly less than the pore height values derived from XRD (1.07–1.29 nm). The results obtained from the adsorption potential distribution and micropore size distribution derived from the DS relation have a rather qualitative character. Nevertheless, it is reasonable to conclude that these methods give a realistic picture of the structural features of pillared clays containing a significant fraction of ultramicropores. Fig. 8 presents the micropore size distributions calculated by the method of Zhu et al. [30]. The Cr-PM materials contain more ultramicropores that contribute to the micropore volume than Ti-PMs do. Moreover, for both kinds of pillared clays, the content of such micropores decreases
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when the pillar density decreases (see also Fig. 9). A more complex situation is observed for the pore width distribution in the supermicropore region (0.7–2.0 nm). In the case of the Cr-PMs, reduction of the pillar density results in the appearance of new pores in the range of 1.06–1.42 nm. In parallel, herewith, the contribution of the supermicropores of 1.42–1.77 nm decreases. Most likely, these changes caused the shift of the low energy peak in the adsorption potential distribution (see Fig. 6), and the shift in supermicropore size towards larger values, as was derived using the DS equation ( Fig. 7). This finding shows a good agreement between the trends obtained by all the above methods. For the Ti-PM samples, a similar tendency is observed. The pillar density decrease leads to the appearance of large supermicropores (1.77– 2.12 nm). Additionally, the total micropore volumes derived by the method of Zhu et al. [30] agree with, or are close to, those obtained by the a -method ( Table 3). Therefore, based on the data s presented, it is reasonable to conclude that the method of Zhu et al. [30] is useful for the characterization of pillared clays having a significant content of supermicropores.
5. Conclusions Adsorption data at low relative pressures are sources of valuable information about the micropore structure of pillared clays. The shape analysis of the N adsorption isotherms and the a -plots 2 s provide important information about the porous structure of those materials. This analysis approach confirms the existence of two sizes of micropores in the Cr-PM and Ti-PM samples. The surface area calculated by the a method can be s considered as S . The BET method underestitotal mates, whereas the Langmuir approach overestimates, the total surface area of these pillared clays. The Dubinin–Radushkevich method can be applied only for determination of the specific total micropore volume and the specific adsorption energy for PILCs with homogeneously distributed narrow micropores. In such a case, both the DR method and the adsorption potential distribution give a realistic picture of the structural features of
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the pillared clays. The Dubinin–Stoeckli (DS) relation can be used for determination of the micropore size distribution of PILCs having a significant content of ultramicropores. Both the DS approach and the method proposed by Zhu et al. [30] demonstrate that the PILCs studied contain micropores over a broad pore-size range. The latter method is useful for characterization of the porous structure of PILCs with significant contribution of supermicropores. The total micropore volumes derived from the method of Zhu et al. were found to be in good agreement with those obtained by the a method. s All the methods applied show that the chromiapillared montmorillonites contain a significant amount of ultramicropores, whereas the Ti-PMs contain an important amount of supermicropores. Variation of the pillar density causes changes in the surface area, micropore volume and pore-size distribution of these materials.
Acknowledgements The authors thank Mr R. Prihod’ko and Dr K. Erdmann for help. These investigations are supported in part by the Ukrainian Ministry of Education, the Polish Committee for Scientific Research ( KBN ), grant 3 TO9A 04714, and by a Spinoza grant (to R.A.v.S.) by NWO.
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