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      A non-invasive method to directly quantify surface heterogeneity of porous materials

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          Abstract

          It is extremely challenging to measure the variation of pore surface properties in complex porous systems even though many porous materials have widely differing pore surface properties at microscopic levels. The surface heterogeneity results in different adsorption/desorption behaviors and storage capacity of guest molecules in pores. Built upon the conventional Porod’s law scattering theory applicable mainly to porous materials with relatively homogeneous matrices, here we develop a generalized Porod’s scattering law method (GPSLM) to study heterogeneous porous materials and directly obtain the variation of scattering length density (SLD) of pore surfaces. As SLD is a function of the chemical formula and density of the matrix, the non-invasive GPSLM provides a way to probe surface compositional heterogeneity, and can be applied to a wide range of heterogeneous materials especially, but not limited to, porous media and colloids, using either neutron or X-ray scattering techniques.

          Abstract

          Surface heterogeneity significantly influences the properties of porous materials, but remains extremely difficult to characterize. Here, the authors extend Porod’s scattering law from homogeneous to heterogeneous porous materials, allowing for surface variation to be non-invasively probed.

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          Morphology, Genesis, and Distribution of Nanometer-Scale Pores in Siliceous Mudstones of the Mississippian Barnett Shale

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            Reduction and analysis of SANS and USANS data using IGOR Pro

            A software package is presented for performing reduction and analysis of small-angle neutron scattering (SANS) and ultra-small-angle neutron scattering (USANS) data. A graphical interface has been developed to visualize and quickly reduce raw SANS and USANS data into one- or two-dimensional formats for interpretation. The resulting reduced data can then be analyzed using model-independent methods or non-linear fitting to one of a large and growing catalog of included structural models. The different instrumental smearing effects for slit-smeared USANS and pinhole-smeared SANS data are handled automatically during analysis. In addition, any number of SANS and USANS data sets can be analyzed simultaneously. The reduction operations and analysis models are written in a modular format for extensibility, allowing users to contribute code and models for distribution to all users. The software package is based on Igor Pro, providing freely distributable and modifiable code that runs on Macintosh and Windows operating systems.
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              Die Röntgenkleinwinkelstreuung von dichtgepackten kolloiden Systemen

              G POROD (1951)
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                Author and article information

                Contributors
                jinhong.chen@aramcoservices.com
                yunliu@nist.gov
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                22 February 2018
                22 February 2018
                2018
                : 9
                : 784
                Affiliations
                [1 ]Aramco Services Company, Aramco Research Center-Houston, Houston, TX 77084 USA
                [2 ]ISNI 000000012158463X, GRID grid.94225.38, Center for Neutron Research, , National Institute of Standards and Technology, ; Gaithersburg, MD 20899 USA
                [3 ]ISNI 0000 0001 0454 4791, GRID grid.33489.35, Department of Chemical and Biomolecular Engineering, , University of Delaware, ; Newark, DE 19716 USA
                Article
                3151
                10.1038/s41467-018-03151-w
                5823877
                29472604
                0dffd446-6cb0-4e0d-bb70-2526e24a8b4e
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 July 2017
                : 24 January 2018
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