INTERPRETATION OF MERCURY POROSIMETRY DATA (CATALYSIS, MORPHOLOGY, PORES)
Mercury porosimetry is commonly used to measure pore size distributions in porous materials such as heterogeneous catalysts. The conventional interpretation of the data is inadequate to provide a realistic picture of the actual void space. Porosimetry experiments on a series of well-characterized po...
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1984
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ndltd-UMASS-oai-scholarworks.umass.edu-dissertations-25672020-12-02T14:37:51Z INTERPRETATION OF MERCURY POROSIMETRY DATA (CATALYSIS, MORPHOLOGY, PORES) LANE, ALAN MICHAEL Mercury porosimetry is commonly used to measure pore size distributions in porous materials such as heterogeneous catalysts. The conventional interpretation of the data is inadequate to provide a realistic picture of the actual void space. Porosimetry experiments on a series of well-characterized porous materials led to the development of a better model for data interpretation. This model was studied using Monte Carlo computer simulation, mathematical analysis, and application of percolation theory to the porosimetry process. This research resulted in providing a few easily applied heuristic rules for interpreting the data. These rules yield more and better information with no additional experimental data. 1984-01-01T08:00:00Z text https://scholarworks.umass.edu/dissertations/AAI8500090 Doctoral Dissertations Available from Proquest ENG ScholarWorks@UMass Amherst Chemical engineering |
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language |
ENG |
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topic |
Chemical engineering |
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Chemical engineering LANE, ALAN MICHAEL INTERPRETATION OF MERCURY POROSIMETRY DATA (CATALYSIS, MORPHOLOGY, PORES) |
description |
Mercury porosimetry is commonly used to measure pore size distributions in porous materials such as heterogeneous catalysts. The conventional interpretation of the data is inadequate to provide a realistic picture of the actual void space. Porosimetry experiments on a series of well-characterized porous materials led to the development of a better model for data interpretation. This model was studied using Monte Carlo computer simulation, mathematical analysis, and application of percolation theory to the porosimetry process. This research resulted in providing a few easily applied heuristic rules for interpreting the data. These rules yield more and better information with no additional experimental data. |
author |
LANE, ALAN MICHAEL |
author_facet |
LANE, ALAN MICHAEL |
author_sort |
LANE, ALAN MICHAEL |
title |
INTERPRETATION OF MERCURY POROSIMETRY DATA (CATALYSIS, MORPHOLOGY, PORES) |
title_short |
INTERPRETATION OF MERCURY POROSIMETRY DATA (CATALYSIS, MORPHOLOGY, PORES) |
title_full |
INTERPRETATION OF MERCURY POROSIMETRY DATA (CATALYSIS, MORPHOLOGY, PORES) |
title_fullStr |
INTERPRETATION OF MERCURY POROSIMETRY DATA (CATALYSIS, MORPHOLOGY, PORES) |
title_full_unstemmed |
INTERPRETATION OF MERCURY POROSIMETRY DATA (CATALYSIS, MORPHOLOGY, PORES) |
title_sort |
interpretation of mercury porosimetry data (catalysis, morphology, pores) |
publisher |
ScholarWorks@UMass Amherst |
publishDate |
1984 |
url |
https://scholarworks.umass.edu/dissertations/AAI8500090 |
work_keys_str_mv |
AT lanealanmichael interpretationofmercuryporosimetrydatacatalysismorphologypores |
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1719365191989198848 |