Mercedes
Vázquez
*ab,
David
Moore
b,
Xiaoyun
He
a,
Aymen
Ben Azouz
ab,
Ekaterina
Nesterenko
a,
Pavel
Nesterenko
c,
Brett
Paull
c and
Dermot
Brabazon
ab
aIrish Separation Science Cluster, National Centre for Sensor Research, Dublin City University, Glasnevin, Dublin 9, Ireland. E-mail: mercedes.vazquez@dcu.ie; Fax: +353 1 700 8021; Tel: +353 1 700 7602
bAdvanced Processing Technology Research Centre, School of Mechanical Engineering, Dublin City University, Glasnevin, Dublin 9, Ireland
cAustralian Centre for Research on Separation Science, University of Tasmania, Hobart, Tasmania, Australia
First published on 17th October 2013
A new characterisation method, based on the utilisation of focussed ion beam-scanning electron microscopy (FIB-SEM), has been employed for the evaluation of morphological parameters in porous monolithic materials. Sample FIB serial sectioning, SEM imaging and image processing techniques were used to extract the pore boundaries and reconstruct the 3D porous structure of carbon and silica-based monoliths. Since silica is a non-conducting material, a commercial silica monolith modified with activated carbon was employed instead to minimise the charge build-up during FIB sectioning. This work therefore presents a novel methodology that can be successfully employed for 3D reconstruction of porous monolithic materials which are or can be made conductive through surface or bulk modification. Furthermore, the 3D reconstructions were used for calculation of the monolith macroporosity, which was in good agreement with the porosity values obtained by mercury intrusion porosimetry (MIP).
Recently, porous carbon monoliths have attracted considerable attention due not only to their unique physicochemical properties, such as chemical inertness, thermal stability and electrical conductivity, but also due to the availability of template-based preparation methods5,6 that provide a means to precisely control pore size and pore structures in the resulting carbon monolith.
Indeed, the performance of monolithic materials is significantly affected by morphological parameters such as the pore size, surface area and the total porosity. Common analytical techniques used for morphological characterisation of monolithic materials include transmission electron microscopy (TEM), scanning electron microscopy (SEM), nitrogen adsorption and mercury intrusion porosimetry (MIP).
MIP provides information on the porosity, pore size distribution and specific surface area of porous materials containing pores with sizes in the range 3.5 nm to 500 μm (i.e. mesopores and macropores).7 Nitrogen adsorption measurements are commonly used for calculation of the specific surface area (SBET) via the Brunauer–Emmett–Teller equation, as well as for the determination of the micro- and mesoporosity.8 However, calculations of the total pore volume by both techniques exclude closed pores (pores isolated from the material surface) and assume an ideal pore shape, typically spherical.7,8 In addition, both MIP and nitrogen adsorption techniques are unsuitable for analysis of monoliths prepared in capillaries with internal diameters (ID) in the micrometer range due to insufficient sample amount (minimum amount of sample required for analysis is approximately 35 mg), or rather complex sample preparation. Therefore, considering that the morphology of porous monolithic materials prepared in bulk (macroscopic scale) can significantly differ from those prepared in a much smaller, confined space,9 alternative techniques such as SEM and TEM10 are typically used for characterisation of monoliths prepared at microscopic (capillary) scale. SEM and TEM provide real visualisation of a single cross-section of the sample prepared either in bulk or in capillaries. Thus, direct information on the pore size (including closed pores), true pore shape, and pore connectivity can be obtained. Nevertheless, a significant number of images need to be taken at different points along the sample in order for TEM and SEM analysis results to be representative of the whole sample, which leads to a significant increase in the time and cost of the analysis.
In contrast, automated imaging techniques such as focussed ion beam-scanning electron microscopy (FIB-SEM) can provide a much faster approach for collection of typically about a hundred images by means of serial slicing and imaging. Briefly, this technique consists in the removal of thin slices (several nanometers/micrometers thick) from the target material by FIB sectioning, followed by image acquisition using SEM. By repeating this automated procedure until the desired volume has been removed from the sample, a series of parallel cross-sectional images of the material under study can be obtained. Finally, processing of the 2D-image stack via image-analysis routines allows the reconstruction of the corresponding 3D porous structure, which in turn can be used for calculation of the morphological parameters of interest. These 3D reconstructions can be further used for modelling of the material transport properties and/or designing numerical simulation tools allowing the prediction of the material performance, as well as for optimisation of the material morphology. Actually, the use of FIB-SEM for reconstruction and visualisation of 3D porous structures has been recently used for the morphological characterisation of a wide variety of samples including metamorphic rocks,11 biological tissues,12 neuronal cells,13 bones,14 ceramic mixed ionic-electronic conductors,15 and carbon materials for fuel cells, batteries and supercapacitors.16,17 SEM imaging and serial sectioning by means of an ultramicrotome has been also employed for 3D reconstruction of the macropore structure present in a polymer monolith in capillary format.18 This technique, known as serial block-face scanning electron microscopy (SBF-SEM), allowed identification of two distinct size domains within the macropore structure of the polymer monolith as well as the characterisation of the radial macroporosity profile of the capillary column. Alternatively, confocal laser scanning microscopy (CLSM) has been used for analysis of silica monoliths in capillary format. This optical “slicing” of specimens by CLSM allowed to reconstruct19 and compare20 the macropore structure of silica-based monoliths, and in turn to conduct benchmark simulations of flow21 and mass transport22 using these 3D reconstructions for derivation of quantitative morphology–transport relationships.
Although the above approaches represent a huge step towards the full characterisation of the “real” porous structure in monolithic materials, there are still several challenges associated with the use of these techniques for reconstruction of some of these materials. For example, although FIB-SEM is highly suitable for imaging electrically conducting materials (e.g. carbon monoliths), analysis of non-conducting materials (e.g. silica and polymer monoliths) is not straightforward owing to sample charging, which causes significant image drift. Due to the high magnification and precision required for sample positioning, sputtering the sample with gold or other metals after removal of each slice to avoid sample charging is not a practical approach. Thus, a common method for imaging non-conducting materials by FIB-SEM (e.g. biological samples) consists in staining the sample with an electrically conducting compound which increases the sample conductivity.23 Alternatively, a system integrating an environmental or “low vacuum” SEM (ESEM), i.e. FIB-ESEM, can be employed for serial sectioning and imaging, preventing the need for sample preparation steps directed to render the sample conductive. Despite these possible alternatives, as yet there are no reports on the use of FIB-SEM for imaging and reconstruction of silica and polymer monoliths. Similarly, only one report on the analysis of a polymer monolith using SBF-SEM was presented recently.18 It should be noted that although commercial SBF-SEM systems employ an ESEM, which allows direct analysis of insulating materials, conductive stains are still used for enhancement of the image contrast.18 In fact, SBF-SEM has the capability of slicing larger sample areas much faster than FIB-SEM, but the minimum slice thickness is generally larger than for FIB-SEM (ca. 30 nm vs. 10–15 nm). On the other hand, SBF-SEM was still found unsuitable for analysis of silica monoliths since the diamond knife of the ultramicrotome would not withstand the cutting process.24 Refractive index matching between sample and objective can also pose a significant challenge in CLSM,19 as pointed out by Tallarek's group, who found CLMS unsuitable for imaging polymer monoliths as a result of their high refractive index.18 In addition, one of the main drawbacks of CLSM compared to FIB-SEM and SBF-SEM is its lower resolution.
In the work presented herein, an in-house prepared carbon monolith and a commercial silica-based monolith were selected as samples to evaluate the potential of FIB-SEM for general application in the 3D reconstruction and morphological characterisation of porous monolithic materials. The in-house prepared carbon monolith employed in this study presented a hierarchical pore structure (macroporous/mesoporous) and excellent electrical conductivity. The commercial silica-based monolith consisted of a silica-skeleton modified with C18 groups and activated carbon (MonoTrap RCC18, GL Sciences). This commercial silica-based monolith was selected based on the assumption that the activated carbon would help to minimise the charge built-up following each slicing step. The methodology developed for imaging and 3D reconstruction of both monolithic materials is described in detail. The reconstructed volumes were further used for calculation of the average macroporosity and comparison with porosity measurements obtained by MIP. The final aim of the present work was to present an alternative method for characterisation and visualisation of porous monolithic materials that complements more conventional characterisation techniques such as MIP, BET, SEM and TEM.
x = {(cosθ, −sinθ), (sinθ, cosθ)}·u + Δu | (1) |
The resulting images were then cropped to reduce the area of analysis to approximately 58.2 μm × 26.5 μm (width × height) for the carbon monolith and 44.7 μm × 33.7 μm for the silica-based monolith, with a resolution of 74 nm/pixel. From the images captured for the carbon monolith, only the first 93 were used for analysis. Thus, the depth of the final image stack was 9.3 μm, with a resolution of 100 nm per pixel in the depth direction. The depth of the final image stack employed for the reconstruction of the silica-based monolith was 10 μm, with a resolution of 66.7 nm per pixel in the depth direction. No attempt was made to increase the resolution of the captured images by increasing the SEM magnification, thus decreasing the size of the detectable pores. The scope of this work was to demonstrate the suitability of FIB-SEM analysis for reconstruction of the bulk porous structure in porous monolithic materials. Therefore, a rather large reconstructed volume was considered to be more representative of the overall monolith morphology, as compared to a reconstructed volume just a few cubic micrometers in size that would have been needed for visualisation of the mesoporous structure.
Finally, the two image stacks were binarised after manual outlining and filling of the porous structures, as shown in Fig. 4.
Fig. 4 From L to R: Outline of the pores, filling of pores and binarisation applied to the image stack obtained for the carbon monolith. |
(2) |
To asses the accuracy of the resulting macroporosity values, MIP measurements were also carried out with the carbon and silica-based monoliths. The total porosity and pore size distribution were determined with an Autopore IV 9500 Series (Micromeritics Instrument Corporation). Dried samples with weights ranging from 36 mg to 47 mg were used for these measurements.
The 3D reconstruction of both monoliths from their respective image stacks was then performed using the volume rendering technique available within the Materialise Mimics 13.0 software (Materialise NV, Belgium).
The total macroporosity of the volume analysed following binarisation of the corresponding image stack was found to be 72.9%. This value agrees well with the results obtained by MIP, where the total porosity was found to be 76.8% and 80.2% for two consecutive analyses. MIP measurements also allowed determination of the pore size distribution, as shown in Fig. S-1 (see the ESI†). A median pore diameter (in volume terms) of 2.6 μm and 2.9 μm was obtained for the two consecutive MIP analyses, respectively.
The total macroporosity of the volume analysed for the carbon-modified silica-based monolith was found to be 52.9%, which agrees well with the 56.0% value for total porosity obtained by MIP. The pore size distribution of the silica-based monolith can be seen in Fig. S-2 (see the ESI†), with a median pore diameter (in volume terms) of 2.7 μm.
Based on all the above, it is envisaged that FIB-SEM analysis followed by 3D reconstruction can be a very useful technique for direct determination of porosity and other morphological parameters in porous monoliths prepared at microscopic (capillary) scale, such as those used in capillary-LC or nano-LC, preventing errors associated with extrapolation of results obtained for bulk monoliths from MIP and nitrogen adsorption measurements. In addition, this direct visualisation method does not exclude closed pores or assume an ideal pore morphology as for MIP and nitrogen adsorption. Furthermore, the 3D reconstructions could be used for determination of additional morphological parameters such as pore sphericity, aspect ratio, hydraulic ratio, and interconnectivity, among others. It is anticipated that a more comprehensive morphological characterisation of such monolithic materials may result in a better understanding of how monolith preparation and resulting pore morphologies affect the analytical performance of stationary phases. Last but not least, 3D reconstructions have been proven to be an excellent tool for successful modelling of the “real” fluid flow and mass transport properties in porous monolithic materials.21,22 Therefore, the methodology presented here is expected to help advance research and knowledge in this area.
Footnote |
† Electronic supplementary information (ESI) available: Video showing the series of captured 2D-images obtained for the carbon monolith once aligned and cropped; Mercury intrusion - extrusion curves and pore size distributions for the carbon and the silica-based monoliths. See DOI: 10.1039/c3an01827j |
This journal is © The Royal Society of Chemistry 2014 |