Characterizing Porous Materials and Powders N 2 Adsorption

  • Slides: 30
Download presentation
Characterizing Porous Materials and Powders N 2 Adsorption Isotherms Laleh Emdadi Advisor: Dr. Dongxia

Characterizing Porous Materials and Powders N 2 Adsorption Isotherms Laleh Emdadi Advisor: Dr. Dongxia Liu Department of Chemical & Biomolecular Engineering University of Maryland College Park, MD, 20742 04/04/2013

Characterizing Porous Materials and Powders Objective: To give you a basic understanding of adsorption

Characterizing Porous Materials and Powders Objective: To give you a basic understanding of adsorption chemistry and how it is used to characterize powders and porous materials. We focus on physisorption. Good References to Study: 1] 2] K. Y. Foo, B. H. Hameed. Insights into the modeling of adsorption isotherms systems. Chemical Engineering Journal 156 (2010) 2 -10. 3] K. S. W. Sing, R. T. Williams. Physisorption hysteresis loops and the characterization of nonporous materials. Adsorption Science and Technology 22(10) (2004) 773 -782. 2

Characterizing Porous Materials and Powders - Surface Area - Multipoint BET Method - Single

Characterizing Porous Materials and Powders - Surface Area - Multipoint BET Method - Single Point BET Method - Multipoint/ Single Point Comparison - Porosity by Gas Adsorption - Isotherms - Total Pore Volume and Average Pore Radius - Pore Size Distributions (Mesopore): - BJH Method - DH Method - Surface Area of Microporous Samples by Langmuir Method - Micropore Analysis - V-t Method - Alpha-s Method - MP Method - DR Method - DA Method - HK Method - SF Method - Density Functional Theory (DFT) and Monte Carlo Simulation Methods 3

Characterizing Porous Materials and Powders Surface Area The Brunauer-Emmett-Teller (BET) method is the most

Characterizing Porous Materials and Powders Surface Area The Brunauer-Emmett-Teller (BET) method is the most widely used procedure for the determination of the surface area of solid materials and involves the use of BET equation: Usually N 2 is used as the adsorbate and C for nitrogen is (50 -250) Intercept (i) Slope (s) 4

Characterizing Porous Materials and Powders Multiple BET Method The BET equation requires a linear

Characterizing Porous Materials and Powders Multiple BET Method The BET equation requires a linear plot of versus which for most solids using nitrogen as adsorbate is restricted to a limited region in the P/P 0 range of 0. 05 to 0. 35. This linear region is shifted to lower relative pressures for microporous materials. A Typical BET Plot The standard multipoint BET procedure requires a minimum of 3 points in this range. Wm can be obtained from slope and intercept of the BET plot. 5

Characterizing Porous Materials and Powders Multiple BET Method The second step in the application

Characterizing Porous Materials and Powders Multiple BET Method The second step in the application of the BET method is the calculation of the surface area. The total surface area of the sample can be expressed as: N : Avogadro's number (6. 0221415 × 1023 molecules/mol), Wm: weight of adsorbate constituting a monolayer of surface coverage Acs: molecular cross section of the adsorbate molecule, (16. 2 A° 2 for N 2 at 77 K) M: molar mass (molecular weight) of the adsorbate gas The second parameter can be calculated is specific surface area of the solid can be calculated as: St: total surface area, W: sample weight 6

Characterizing Porous Materials and Powders Single Point BET Method For routine measurements of surface

Characterizing Porous Materials and Powders Single Point BET Method For routine measurements of surface areas, a simplified procedure may be applied. In this method, only a single point on the adsorption isotherm in the linear region of the BET plot is used ( = 0. 3). For microporous materials P/P 0 as high as possible, yet still in the linear region of the BET plot should be chosen!!! The assumption is that the intercept in the BET equation is zero: Ideal gas equation 7

Characterizing Porous Materials and Powders Multipoint/Single Point Comparison The relative error in single point

Characterizing Porous Materials and Powders Multipoint/Single Point Comparison The relative error in single point versus multipoint for determining of surface area of the sample is a function of BET C constant and the relative pressure used. For multipoint BET we have: For single point BET we have: As a result the relative error of single point method is: Usually if you chose the P/P 0 properly, this error is very low and so it is acceptable. 8

Characterizing Porous Materials and Powders Single Point BET Error This table shows the relative

Characterizing Porous Materials and Powders Single Point BET Error This table shows the relative error for various C calculated using P/P 0 of 0. 3. 9

Isotherms (IUPAC classifications) Microporous (chemisorption) Non-porous or macroporous materials consisting of welldefined cylindrical-like pore

Isotherms (IUPAC classifications) Microporous (chemisorption) Non-porous or macroporous materials consisting of welldefined cylindrical-like pore channels or agglomerates of compacts of approximately uniform spheres disordered materials and the distribution of pore size and shape is not well defined Not common; N 2 adsorption on polyethylene Mesoporous non-rigid aggregates of plate-like particles giving rise to slit-shaped pores Mesoporous Uniform non-porous surface narrow slit pores, but now including pores in the micropore region 10

Characterizing Porous Materials and Powders Porosity by Gas Adsorption Pores are characterized according to

Characterizing Porous Materials and Powders Porosity by Gas Adsorption Pores are characterized according to their sizes: a) Pores > 50 nm in diameter are called macropores. b) Pores 2 -50 nm in diameter are called mesopores. c) Pores < 2 nm in diameter are called micropores. Porosity of powders and other porous solids can be characterized by gas adsorption studies. There are 2 common techniques for describing porosity: 1) Determination of total pore volume 2) Pore size distribution For most solid materials, nitrogen at 77 K is the most suitable adsorptive. 11

Characterizing Porous Materials and Powders Total Pore Volume and Average Pore Radius The total

Characterizing Porous Materials and Powders Total Pore Volume and Average Pore Radius The total pore volume is derived from the amount of vapor adsorbed at a relative pressure close to unity (P/P 0 ≈1), by assuming that the pores are then filled with liquid adsorbate. The volume of nitrogen adsorbed (Vads) can be converted to the volume of liquid nitrogen (Vliq) contained in the pores using this equation: Pa: ambient pressure, T: ambient temperature Vm: molar volume of the liquid adsorbate (34. 7 cm 3/mol for nitrogen) R: universal gas constant Since pores which would not be filled below P/P 0 ≈1 have a negligible contribution to the total pore volume, the average pore size can be estimated from the pore volume. For example for cylindrical pore: S: BET surface area 12

Characterizing Porous Materials and Powders Pore Size Distributions (Mesopore) It means the distribution of

Characterizing Porous Materials and Powders Pore Size Distributions (Mesopore) It means the distribution of pore volume versus pore size. The desorption isotherm generally is more appropriate than the adsorption isotherm for this purpose. For some special cases like when a sample exhibits Type H 2 hysteresis, the adsorption isotherm is recommended! Mesopore size calculations based on cylindrical pore geometry assumption are done using Kelvin equation: For nitrogen as adsorbate: rp: actual pore radius t: thickness of the adsorbed layer; t=3. 54 (Vads/Vm) or from de Boer equation: Vads: volume of nitrogen adsorbed at a given relative pressure Vm: volume of nitrogen adsorbed at the completion of a monolayer for a nonporous solid of the same composition as the porous sample 13

Characterizing Porous Materials and Powders BJH Method (for pore size distribution) This method proposed

Characterizing Porous Materials and Powders BJH Method (for pore size distribution) This method proposed by Barrett, Joyner, and Halenda (BJH). This method is based on the assumption that the initial relative pressure is close to unity, all pores are filled with liquid. rp: pore radius Vp: pore volume r. K: inner capillary radius ∆t: thickness of adsorbed layer of nitrogen Ac: area exposed by the pore from which the physically adsorbed gas is desorbed. Ac can be calculated from Ap which is the area of each pore (see the Asi. Qwin software manual for more details). 14

Characterizing Porous Materials and Powders DH Method (for pore size distribution) This method proposed

Characterizing Porous Materials and Powders DH Method (for pore size distribution) This method proposed by Dollimore and Heal (DH). ∑Ap: areas of all the pores emptied of condensate in previous desorption steps. ∑Lp: lengths of all the pores emptied of condensate in previous desorption steps. Assuming cylindrical pore geometry, the cumulative pore areas and length can be estimated for each desorption step by: 15

Characterizing Porous Materials and Powders Surface Area of Microporous Samples by Langmuir Method In

Characterizing Porous Materials and Powders Surface Area of Microporous Samples by Langmuir Method In the absence of meso and/or macropores, a sample containing micropores will exhibit a Type I (see slide 10) or Langmuir isotherm. The Langmuir equation is a limiting case of BET equation for the adsorption of a single molecular layer of adsorbate: W: weight of adsorbate at P/P 0, Wm: weight of adsorbate in a monolayer It can be rewritten in the form of a straight line: (Vm can be found from slope) This method is not applicable to composite materials containing micropores and meso-and/or macropores. 16

Characterizing Porous Materials and Powders Micropore Analysis (V-t Method) The procedure is same as

Characterizing Porous Materials and Powders Micropore Analysis (V-t Method) The procedure is same as BET surface area measurement, but it extends the pressure range to higher pressures to permit calculation of the external surface area, that is, non-microporous part of the material. A t-plot which is a plot of volume of gas adsorbed versus t (the statistical thickness of an adsorbed film) is used. The t values are calculated as a function of the relative pressure using the de Boer equation: the Carbon Black equation: Or the Halsey equation: For nitrogen adsorption at 77 K 17

Characterizing Porous Materials and Powders Micropore Analysis (V-t Method) Surface area of all the

Characterizing Porous Materials and Powders Micropore Analysis (V-t Method) Surface area of all the pores can be calculated as: Vads STP: volume of gas adsorbed, corrected to standard conditions of temperature and pressure 15. 47: the conversion of the gas volume to liquid volume SMP: micropore surface area St: external surface area 18

Characterizing Porous Materials and Powders Micropore Analysis (Alpha-s Method) An empirical analogue to the

Characterizing Porous Materials and Powders Micropore Analysis (Alpha-s Method) An empirical analogue to the t-method was proposed by Sing. It does not need statistical thickness, t which depends on BET surface area of nonporous reference material. Instead the BET area can be replaced by the amount adsorbed at some arbitrarily chosen P/P 0 (usually = 0. 4). It is used for the determination of micropore volumes by extrapolation of Alpha-s curves to αs=0, and for the determination of nonporous surface contributions (from the slopes of linear portions of Alpha-s curves). In practice, complications arise using this method because it is found to depend on the exact nature of the material chosen as nonporous reference! 19

Characterizing Porous Materials and Powders Micropore Analysis (MP Method) An extension of de Boer’s

Characterizing Porous Materials and Powders Micropore Analysis (MP Method) An extension of de Boer’s t-method for micropore analysis was proposed by Mikhail, Brunauer, and Bodor. This method calculate the t independently of the solid by: t(A ) = 104 Vliq/SBET A V versus t plot is constructed from t versus P/P 0 a shown in figure below, using linear slopes constructed for t-value intervals from the origin to 4 A , 4 to 4. 5 A , 4. 5 to 5 A , etc. The calculations are continued until no further decrease in the slope. The area of pores in the thickness range from 4 to 4. 5 A, for example is the difference between the values calculated from first and second slopes, and so on. 20

Characterizing Porous Materials and Powders Micropore Analysis (MP Method) Pore volumes can similarly be

Characterizing Porous Materials and Powders Micropore Analysis (MP Method) Pore volumes can similarly be calculated, using the relation: 21

Characterizing Porous Materials and Powders Micropore Analysis (Dubinin-Radushkevich (DR) Method) Dubinin and Radushkevich considered

Characterizing Porous Materials and Powders Micropore Analysis (Dubinin-Radushkevich (DR) Method) Dubinin and Radushkevich considered that the fraction of the adsorption volume V occupied by liquid adsorbate at various adsorption potentials ε can be expressed as a Gaussian function: A: free energy of adsorption, A= ε = RT ln (P/P 0) V 0: microspore volume E 0: characteristic energy of adsorption β: affinity coefficient v: liquid molar volume of a given adsorbate v. C 6 H 6: molar volume of benzene as the reference liquid Micropore volume (V 0) and E 0 parameter can be calculated from the linear fit of the isotherm data plotted as log (V) versus [log(P/P 0)]2. The linear range for these plots is usually found at relative pressures of less than 10 -2. 22

Characterizing Porous Materials and Powders Micropore Analysis (Dubinin-Astakhov (DA) Method) For the microporous materials

Characterizing Porous Materials and Powders Micropore Analysis (Dubinin-Astakhov (DA) Method) For the microporous materials with heterogeneous distributions or strongly activated carbons, the Dubinin-Radushkevich equation fails to linearize the adsorption data, the Dubinin-Astakhov equation is used: W: weight adsorbed at P/P 0 and T W 0: total weight adsorbed E: characteristic energy n: non-integer value (typically between 1 and 3 n and E are calculated re-iteratively by non -linear curve fitting to the adsorption isotherm in the low relative pressure, micropore region. The they are used in this equation where r is pore radius and K is a constant. 23

Characterizing Porous Materials and Powders Micropore Analysis (Horvath-Kawazoe (HK) Method) Many pore size distribution

Characterizing Porous Materials and Powders Micropore Analysis (Horvath-Kawazoe (HK) Method) Many pore size distribution methods are based on capillary condensation phenomenon which is questionable for small confines of micropores. Horvath and Kawazoe proposed a method which is independent of this assumption! The HK method expresses the adsorption potential function within slit-like micropores as a function of the effective pore width: 24

Characterizing Porous Materials and Powders Micropore Analysis (Horvath-Kawazoe (HK) Method) By selecting effective pore

Characterizing Porous Materials and Powders Micropore Analysis (Horvath-Kawazoe (HK) Method) By selecting effective pore widths in the micropore range, the HK equation can be used to calculate the corresponding relative pressures. From the adsorption isotherms, the amount of adsorption at each of these relative pressures is determined. Differentiation of weight (or volume) of gas adsorbed relative to the total uptake, W/W 0, with respect to the effective pore width yields a pore size distribution in the micropore range. 25

Characterizing Porous Materials and Powders Micropore Analysis (Saito-Foley (SF) Method) HK method is good

Characterizing Porous Materials and Powders Micropore Analysis (Saito-Foley (SF) Method) HK method is good for materials with a predominance of slit-like pores (like activated carbons), but for some solids like zeolites that usually have cylindrical pore geometry it is better to use the method that Saito and Floey presented: Everything (even numerical solution of this equation above) and the other parameter definitions except the pore shape are analogous to that of HK method and yields size distributions in the micropore range. 26

Characterizing Porous Materials and Powders Density Functional Theory (DFT) and Monte Carlo Simulation Methods

Characterizing Porous Materials and Powders Density Functional Theory (DFT) and Monte Carlo Simulation Methods Classical macroscopic theories that we have introduced until now such as DR method and BJH method and also semi-empirical treatments such as HK method and SF method do not give a realistic description of the filling of micropores and even narrow mesopores which leads to an underestimation of pore sizes. Treatments such as the Density Functional Theory (DFT) or methods of molecular simulation (Monte Carlosimulation (MC) and Molecular Dynamics (MD)) provide a much more accurate approach for pore size analysis and bridge the gap between the molecular level and macroscopic approaches. DFT is the best suggested method for micro-mesoporous zeolite samples! 27

Characterizing Porous Materials and Powders Density Functional Theory and Monte Carlo Simulation Methods The

Characterizing Porous Materials and Powders Density Functional Theory and Monte Carlo Simulation Methods The Non-Local Density Functional Theory (NLDFT) and the Grand Canonical Monte Carlo simulation (GCMC) methods correctly describe the local fluid structure near curved solid walls; adsorption isotherms in model pores are determined based on the intermolecular potentials of the fluid-fluid and solid-fluid interactions. The relation between isotherms determined by these microscopic approaches and the experimental isotherm on a porous solid can be interpreted in terms of a Generalized Adsorption Isotherm (GAI) equation : N(P/P 0): experimental adsorption isotherm data W: microspore volume N(P/P 0, w): isotherm on a single pore of width W f(W): pore size distribution function This equation can be solved numerically via a fast non-negative least square algorithm. 28

Characterizing Porous Materials and Powders Library of DFT and GCMC methods in Quantachrome’s Data

Characterizing Porous Materials and Powders Library of DFT and GCMC methods in Quantachrome’s Data Reduction Software This table is just part of the large library we have, for a complete table please read the manual page 382 29

Thank you for your attention 30

Thank you for your attention 30