Understanding Material Characteristics through Signature Traits from Helium Pycnometry

Abstract

Although helium pycnometry is generally the method of choice for skeletal density measurements of porous materials, few studies have provided a wide range of case studies that demonstrate how to best interpret raw data and perform measurements using it. The examination of several different classes of materials yielded signature traits from helium pycnometry data that are highlighted. Experimental parameters important in obtaining the most precise and accurate value of skeletal density from the helium pycnometer are as high as possible percent fill volume and good thermostability. The degree of sample activation is demonstrated to affect the measured skeletal density of porous zeolitic, carbon, and hybrid inorganic-organic materials. In the presence of a significant amount of physisorbed contaminants (water vapor, atmospheric gases, residual solvents, etc.), which was the case for ZSM-5, MIL-53, and F400, but not ZIF-8, the skeletal density tended to be overestimated in the low percent volume region. In addition, the kinetic data (i.e., skeletal density vs measurement cycle) reveals distinctive traits for a properly activated vs a nonactivated sample for all examined samples: activated samples with a significant amount of mass loss show a curved down plot that eventually reaches the equilibrium value, whereas nonactivated, nonporous, or extremely hydrophobic samples exhibit a flat line. This work illustrates how helium pycnometry can provide information about the structure of a material, and that, conversely, when the structure of the material and its percent mass loss after activation (amount of physisorbed contaminants) are known, the behavior of activated and nonactivated samples in terms of skeletal density, percent fill volume, and measurement cycle can be predicted.

Figure 1.

Cross-sectional diagram of different types of volume. (left) Bulk volume includes all pores and interparticle spaces. (center) True volume excludes all pores and interparticle spaces. (right) Skeletal volume excludes accessible pores and interparticle spaces but includes closed pores. Black denotes region included in the volume. White denotes region excluded from the volume.

Figure 2.

Schematic of a typical helium pycnometer with sample chamber before reference chamber. A pressure sensor is located at the sample chamber and gives pressure reading of P. V_SH is the volume of the sample chamber. V_R is the volume of the reference chamber. V_S is the skeletal volume of the sample.

Figure 3.

(A) The skeletal density of Si determined from the slope of the linear fit for the plot of mass vs volume. (B–D) The skeletal density of Si measured using a He pycnometer under varied experimental parameters. (B) Sample percent fill volume and sample holder used were varied. (C) Analysis temperature was varied. (D) Analysis under poor thermal stability (± 1 K). In panels A and B, each data point is the average value of (A) the skeletal volume or (B) skeletal density and percent fill volume (along with uncertainty) from measurement cycles made on a different aliquot of Si. In panels C and D, each data point is the skeletal density from an individual measurement cycle made on the same aliquot of Si.

Figure 4.

Representative graphs of helium pycnometry kinetic data for the Si, ZSM-5, F400 carbon, MIL-53, and ZIF-8, in activated and nonactivated forms and at low and high percent fill volume. The data for Si, which was not activated but can be assumed to be free of physisorbed contaminants, is included in panels A and C, for the purpose of comparison only.

Figure 5.

(A–D) Skeletal densities of ZSM-5, F400, MIL-53, and ZIF-8 measured using a He pycnometer with percent fill volume varied. (E–H) Skeletal densities of ZSM-5, F400, MIL-53, and ZIF-8 determined from a fitted linear regression.