Determination of surface polarity by heterogeneous gas-solid

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Anal. Chem. 1987,59,353-358

could effect the ability of the presearch program to choose the correct library spectrum. The variance (3 standard deviations (SD)) data calculated for Table IV are presented to show the fluctuation of FTA values in the 10 test compounds. Dyphylline exhibited the most variance (3 SD = 0.0210) in FTA of the 10 compounds in one of its two ,A, values (207 nm). The second band for dyphilline (275 nm), however, had a very low variance (3 SD = 0.0006) in FTA. The presearch values in a given routine is designed to examine up to five ,A, and spectra. Test spectra are required to duplicate the ,A, FTA values of at least one band in a library spectra to meet the criteria for being chosen by the presearch routine. LOW variance in only one band of a multiband spectra is required to ensure proper selectivity for the presearch routine. Therefore, use of an FTA window of 0.001 would assure that dyphylline was selected in the presearch routine because one of its bands (275 nm) had an I T A variance below 0.001. These data can also serve as an indicator for selecting the optimal FTA window to use for the presearch routine. Of the compounds tested for this purpose, 2 of the 10 would require opening the FTA window beyond 0.001. Fell et al. (9) recently demonstrated the ability to perform library search routines on digitalized UV spectra. In this method, a presearch routine relied on the retrieval of spectra that had A, and Ah, values similar to the unknown spectral values. The fit of unknown spectra to reference spectra was calculated on the "smoothed" spectra as the mean square root of the difference between the two spectra. This routine was tested on a limited spectral library of eight compounds and demonstrated the ability to distinguish between similar spectral profiles. The search routine described in this paper was tested on a library of approximately 300 spectra. The presearch routine narrows the number of possible spectra to approximately 20 or less, and in each of the test cases this subfile contained the correct spectrum. Additionally, an absolute difference algorithm on "nonsmoothed" spectra was sufficient to give correct relative comparison of spectra including spectra that were relatively noisy.

353

Some structurally related compounds generate spectra that are very similar. The search routine has consistently distinguished between spectra of structurally related compounds, such as the alkylparabens when they differed by at least two methylene groups. This algorithm has been used in our laboratory for over a year and has consistently indicated the correct UV spectra for compounds tested that were contained in the library. We feel that this method will aid in the use of diode array UV detectors as qualitative instruments.

ACKNOWLEDGMENT We thank Albert Berrebi for conducting statistical analyses for the data presented in Table 111. Registry No. p-HoC6H4NHAc,103-90-2;n-H2NC6H4CO2H, 99-05-8;P - H ~ N C ~ H ~ C O150-13-0; ~H, O-HOC~H~CO~H, 69-72-7; chlorothiazide, 58-94-6; mefenamic acid, 61-68-7; probenecid, 57-66-9;sulfadiazine,6835-9; sulindac, 38194-50-2;methylparaben, 99-76-3; ethylparaben, 120-47-8;propylparaben, 94-13-3;butylparaben, 94-26-8; dyphylline, 479- 18-5.

LITERATURE CITED (1) Hertz, H. S.; Hites, R A.; Bieman, K. Anal. Chem. 1971, 4 3 , 681-691. (2) Lowry, S. R.; Huppler, D. A. Anal. Chem. 1983, 55, 1288-1291. (3) Delaney, M. F.; Uden, P. C. Anal. Chem. 1979, 51, 1242-1249. (4) Hanna, A.; Marshall, J. C.; Isenhour, T. L. J. Chromafogr. Sci. 1979, 17, 434-440. (5) Azarraaa, L. V.; Williams, R. R.;de Haseth, J. A. Appl. Specfrosc. 1981, 35, 468-469. (6) de Haseth, J. A.; Azarraga, L. V. Anal. Chem. 1981, 53, 2292-2298. (7) Hanaac, G.; Wleboldt, R. C.; Lam, R. B.; Isenhour, T. L. Appl. Specfrosc. 1982, 36, 40-47. (8) Erickson, M. D. Appl. Specfrosc. 1981, 35, 181-184. (9) Fell, A. F.; Clark, B. J.; Scott, H.P. J. Chromafogr. 1984, 316, 423-440. (IO) Armor, D. J.; Couch, A. S.Data Text Primer; Collier Macmiiian: London, 1972; pp 92-99. '

RECEIVED for review January 14, 1986. Resubmitted August 25, 1986. Accepted September 3, 1986. This publication is recorded with the Storrs Agricultural Experiment Station as Scientific Contribution No. 1149.

Determination of Surface Polarity by Heterogeneous Gas-Solid Chromatography Scott P. Boudreau and William T. Cooper*

Department of Chemistry, Florida State University, Tallahassee, Florida 32306-3006

A polarity scale for heterogeneous surfaces is proposed that uses energy distrlbutionfunctlons calculated from chromatographic reigntion data. The energy requlred to form a com-

plete monolayer (€,,), obtained from the energy distribution functlon, has been chosen as the parameter best suited for descrlMng the heat of adsorption on a heterogeneoussurface. E,, values for chloroform (proton donor), pyrldine (proton acceptor), and dlchioromethane (dlpoie interactor) are used as parameters in the surface polarity scale that is analogous to the Rohrschnelder and McReynolds scales that describe the poiarlty of gas-llquld chromatography stationary phases. Monolayer energies have also been used to construct a surface selectivity trlangie. Results are presented for a variety of surfaces differing in the relative number of acldlc, basic, and dipolar sites.

Table I. Material and Column Characteristics column

material

dimensions, cm

kaolinite

60 X 0.4

silanized silica gel

26 X 0.4

alumina

23

silica pel

26 X 0.4

X

0.4

surface area, m2/g 3.9 180 70

200

particles size

weight, g

(mesh)

7.0606 1.4865 2.3719 1.4865

100-200 100-200 100-200 100-200

The importance of solid and particulate surfaces in chemical processes relevant in such diverse fields as analytical chemistry, environmental geochemistry, catalysis, and biomedical engineering has been recognized for some time. However, studies of these processes are often complicated by the inevitable chemical and physical heterogeneity of the surfaces.

0003-2700/S7/0359-0353$01.50/00 1987 American Chemical Society

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ANALYTICAL CHEMISTRY, VOL. 59, NO. 2, JANUARY 1987

Furthermore, since this heterogeneity is frequently a major factor in adsorption and desorption mechanisms, and these mechanisms are integral components of the chemical processes, one must include heterogeneity in accurate descriptions of nearly all surface chemical phenomena ( I ) . For example, it is now known that changes in the efficiency of platinumalumina re-forming catalysts resulting from different platinum impregnation techniques are actually due to variations in the size and distribution of platinum “islands” on the alumina support surface (2). It has also been demonstrated that water does not form a conventional monolayer on kaolinite surfaces but rather clusters around higher energy sites leaving lower energy, hydrophobic sites available for direct interaction with sparingly soluble organic solutes ( 3 ) . There is thus a need for characterization methods that yield direct and quantitative information about the heterogeneity and energetics of such surfaces. Although many spectroscopic techniques such as X-ray photoelectron, Auger electron, and secondary ion mass spectroscopy show promise, they are not at present applicable to the wide range of materials for which physiochemical surface descriptions would be useful. In addition, many of these techniques must be done in vacuo, limiting their use to idealized situations in which adsorbed species such as water are not important to the behavior of the surfaces in their working environments. This lack of directly applicable spectroscopic techniques has resulted in virtually all studies of surface heterogeneity relying on indirect integral methods that use gas-solid or liquid-solid adsorption data ( 4 ) . The energy distribution functions and heterogeneity factors that can be obtained from such data yield information about the macroscopic details of surface heterogeneity and, through the judicious choice of adsorbate “probes”, the chemical nature of adsorption sites. Most adsorption data have been obtained by conventional static methods in which a reduction in adsorbate pressure (gas-solid) or concentration (liquid-solid) is recorded upon exposure to the surface. However, there is a growing awareness that in favorable situations dynamic chromatographic methods are ideally suited for such studies (5). Chromatographic adsorption methods are fast, straightforward, and capable of producing a large body of accurate data in a relatively short period of time. Conventional chromatography is also done slightly above atmospheric pressures and thus more realistic surfaces with associated adlayers and other modifications can be studied. Finally, chromatographic methods have become increasingly important in studies of surface heterogeneity with the development of techniques that allow calculation of the complete distribution of adsorption energies directly from retention data (6, 7). Regardless of the manner in which adsorption data are acquired, a quantitative description of surface heterogeneity is typically given by this distribution of adsorption energies, or energy distribution function (f(E)).The overall, experimentally determined isotherm (0) is related to the energy distribution function by the integral equation ( 8 ) W , T ) = jmOdP,T,E) 0 f ( E )dE

(1)

where B,(P,T,E) is the local isotherm describing the relative coverage on each type of adsorption site. The solution of eq 1for the distribution function from observed adsorption data and various assumed local isotherm functions has been a major area of interest in adsorption science for the past 30 years and has been summarized in recent review articles (4,9, 10). In this paper we will show how one particular method that allows calculation of the complete energy distribution function directly from chromatographic retention data can be used to evaluate surface polarity. Since the energy distribution function represents the full

spectrum of adsorbateladsorbent interaction energies, it can be used to give large amounts of quantitative and qualitative information on a wide variety of surfaces. It has been pointed out, however, that there is a need for a single-valued parameter that describes the heat of adsorption on a heterogeneous surface, and a number of parameters from the distribution function have been suggested, including average site energy, most probable site energy and energy range (11). In this paper we have chosen an extensive parameter obtained from the distribution function that yields, in a relative manner, the contributions of acidic, basic, and dipolar sites to the adsorption energetics of a surface. This parameter, which is related to the total energy required to reach a monolayer (12),E,,,, will be discussed in more detail in later sections. It suffices here to say that E,, values for adsorbate probes that interact with surfaces in well-defined ways will be used to generate a surface polarity scale. Our scale is analogous to the Rohrschneider (13) and McReynolds ( 1 4 ) scales used in classifying stationary phases in gas-liquid chromatography, in that the “total” polarity of a surface is viewed as the sum of acid, base, and dipolar contributions. It differs from polarity scales useful in conventional gas chromatography, however, since the whole surface is taken into account, not just the most active sites which are usually responsible for analytical separations. Since the work reported in this paper is directed toward the development of a general surface analysis method applicable to a wide variety of problems, we believe it is more appropriate to include the entire surface and not just the most active (energetic) sites. Any attempt to describe a complex function such as an energy distribution with a single parameter will of necessity result in some averaging, and it is important to include relevant limits in this averaging. Polarity values that include only high energy sites and would be applicable to the characterization of chromatographic stationary phases could be determined from energy distribution functions by including only the appropriate energy range in the calculations.

THEORY We have calculated distribution functions by the Hobson method (6) which employs a local isotherm approximation consisting of a Henry’s law region at all pressures below some characteristic “patch” pressure and a relative coverage of unity for all greater pressures. This approximation, which was termed the “asymptotically correct approximation” and thoroughly discussed by Cerofolini (15-1 7), was originally proposed by Zel’dovich (18). In a rather ingenious application of the Hobson method, Rudzifiski et al. (7) showed how the distribution function can be calculated directly from the pressure dependency of chromatographic retention data. In a slight modification from the one used by Rudzidski and co-workers, we have used a form of the fundamental equation of elution chromatography (eq 2) that includes the “sorption effect” while, like Rudzifiski, assuming negligible “thermal effects”, “carrier gas adsorption effects”, and gas phase nonideality. The “sorption effect”, which becomes significant in finite elution chromatography a t gas phase mole fractions above is a change in mobile phase flow rate in a solute band due to the adsorption or desorption of solute molecules and manifests itself in the (1 - jy,) term of the retention equation derived by Conder and Purnell ( 5 , 19, 20) In this equation, V Gis~the specific retention volume at column temperature T (K) corrected for gas compressibility and column void volume and expressed in mL/kg, R , the universal gas constant in (mL atm)/(mol K), N , the monolayer capacity (mol/kg), j the James-Martin compressibility factor (21),yo the solute gas-phase mole fraction as measured

ANALYTICAL CHEMISTRY, VOL. 59, NO. 2, JANUARY 1987

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where E,,, is given in cal/kg. The range of submonolayer energies (Q)needed to accurately determine the distribution function has been the topic of many theoretical and applied papers (26-28). In fact, many of the numerical techniques require the a priori estimation of these parameters from 'idealized theoretical considerations in solving for the distribution function. The Hobson method offers the distinct advantage in that solving for the unnormalized distribution function does not require such a priori estimations and one must only be sure to have included a broad enough energy region such that the entire submonolayer distribution function is obtained. The large dynamic range and excellent sensitivity of the flame ionization detector (FID) make it the superior choice for meeting this criterion.

Kaolinite. One hundred grams of kaolinite (Ward's Natural Science Establishment, Inc.) was ground with a mortar and pestle to less than 150 Fm,washed twice with 200 mL of an equivolume mixture of benzene/methanol/dichloromethane,and then elutriated several times with deionized-distilledwater. After being dried in an oven at 110 "C for 15 h, the clay was reground and doubly sieved. The clay mineral was packed into a glass column and dried overnight at 150 "C under helium flow. Silica Gel. Chromatographic grade silica gel (EM Reagents) was used as received after double sieving and dried in the same manner as the kaolinite column. Silanized Silica Gel. Silanization of the silica gel in the column described above was carried out by injecting several 5-rL quantities of the silanizing agent on the column at 180 "C. Extent of silanization was monitored by periodically injecting 5 p L of methanol at the above temperature and monitoring its peak shape and retention time. When the retention time and peak tailing of methanol failed to decrease substantially, the "end capping" of the residual silanols on the silica gel was deemed to be as complete as possible. Alumina. Chromatographic grade alumina (Alcoa Chemicals) was used as received after being doubly sieved, and dried overnight in the same manner as the kaolinite column. Procedures. Solute injections ranging from 1to 150 pL were made on each of the five columns described above with Hamilton microsyringes. All studies were carried out at temperatures of 50 "C for dichloromethane, 51 "C for chloroform, and 150 "C for pyridine, except chloroform on alumina studies which were done at 71 "C and 81 "C in order to study the effects of temperature on Em?,* Helium filtered through a 13X molecular sieve trap was used as the carrier gas at optimum flow rates as determined by van Deemter plots (29)of reduced plate height w. linear velocity. The resulting flow rates, corrected for gas compressibility, and corresponding pressure drops were approximately 30 mL/min and 0.88 atm, respectively, for all columns except kaolinite, for which 20 mL/min and 2.25 atm were employed. Retention volumes were determined as a function of solute pressure by the refined peak profile technique, "elution by characteristic Point (ECP)", introduced by Cremer, Huber, and Keulemans (30,31). Upon verification of the proper conditions (see Results and Discussion),the retention volume functions and subsequent distribution functions were determined from one injection volume of sufficientsize to exceed the monolayer capacity for each surface/probe combination studied. An FID calibration factor was determined for each experimental run. The average calibration value was used in order to compensate for the uncertainties in absolute injection volumes. Solute pressures in the mobile phase were then calculated by standard methods assuming ideal gas behavior (32). Retention volume functions were differentiated for energy distribution function calculations using a five-point numerical differentiation technique (33),the advantages of which have been explained previously (3). A simple trapezoidal rule numerical integration that included at least 75 data points was used for all required integrations. Nitrogen surface areas were measured with a dynamic method in which the amout of nitrogen adsorbed from a stream of helium and nitrogen is measured by use of a thermal conductivity detector (34). A two-point BET method was used to calculate surface areas with the conventional liquid density value of 16.2 A2 taken as the cross sectional area of nitrogen.

EXPERIMENTAL SECTION Apparatus. All chromatographic measurements used in polarity scale determinations were made with a Becker gas chromatograph equipped with an FID maintained at 200 " C . Reagents. Spectrophotometric grade (99+ % ) dichloromethane, chloroform, and pyridine were obtained from Aldrich Chemical Co. and were used as received. The silanizing agent used for both glass columns and silica gel was 1,1,1,3,3,3-hexamethyldisilizane (Aldrich, 98%). Surfaces. General characteristics for each material studied are given in Table I. Each material was packed under reduced preasure with agitation into glaas columns that had been previously silanized with a 10% (v/v) mixture of the silanizing agent in pyridine under anhydrous conditions.

R E S U L T S AND DISCUSSION Use of the E C P Method. The ECP technique has been thoroughly discussed by Conder and Young (5). The use of this technique requires the absence of any inflection point in the investigated region of the isotherm and that the influence of nonideality in the chromatographic process be much less than the influence of isotherm nonlinearity. The failure to meet either of these criteria manifests itself in a noncoincidence of peak tails when chromatograms of various injection sizes are superimposed. In the case of adsorption in gas-solid chromatography (GSC), these criteria are frequently met, as isotherm curvature is often very substantial. As indicated by the representative chromatograms of Figure 1,the criteria for

at the column outlet, and P the partial pressure of solute in the mobile phase (atm). Calculation of the distribution function proceeds in the same general manner as given by Rudzidski et al. (7)and used by several others (22-24). This calculation uses a form of Hobson's original expression for the distribution function

(3) Taking the derivative of eq 2 with respect to pressure, rearranging, and substituting into eq 3 yield

(4) where R2is the universal gas constant expressed in kcal/(K mol). The d(1- jyo)/8Pterm has not been included in eq 4 since it contributes less than 1 % to the overall calculation, which is greatly simplified if it is ignored. F(E) is the unnormalized distribution function and is the quantity actually calculated and used since the a priori determination of N , involves further assumptions in adsorption models and distribution function shapes (7). One should note that by integrating eq 2 the *sorptionn corrected isotherm, 0, can be obtained. The relationship between solute mobile phase pressure and adsorption energy, E, is obtained by using Hobson's local isotherm and an expression originally given by Langmuir

E = -R2TIn ( P / A o ) The constant Ao is related to the partition function of the adsorbate and has been evaluated for organic vapors from the low-pressure limit of the BET equation (25). The monolayer energy for each solute probe/surface combination is then calculated from the unnormalized energy distribution function via

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ANALYTICAL CHEMISTRY. VOL. 59. NO. 2, JANUARY 1987

6.0z

>

-2 -Y LL

9.0.

2.0-

0

20

40

60

80

0.0-

TIME lminl

Flgure 1. Superimposed chromatograms of pyridine on silica gel at

indicated in-wtion volumes.

Flgure 2. F ( E ) E plot for pyridine on silanized silica gel showing integration range (shaded area) for E, calculation.

use of the ECP method has been well met since the coincidence of chromatographic peak tails is quite good. The use of a peak profile technique greatly reduces analysis time and thus increases the general utility of the technique for studying energetically heterogeneous surfaces. Integration Range. As mentioned previously, it is necessary that a broad enough solute pressure region he investigated to ensure that all surface sites in the submonolayer region are included in the energy distribution function. At the high energy end of the distribution function, we have investigated relative coverages of