Institutional Repository
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- Bailey Hall, Illinois Institute of Technology
- Photograph of Bailey Hall (renamed George J. Kacek Hall in 2020), located at 3100 South Michigan Avenue, Chicago, Illinois
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- IIT Tower, Illinois Institute of Technology
- 10 West 35th Street, Chicago, Illinois
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- North Hall, Illinois Institute of Technology
- 71 East 32nd Street, Chicago, Illinois
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- Stephen Fienberg's influence on algebraic statistics
- Stephen (Steve) E. Fienberg (1942-2016) was an eminent statistician, whose impact on research, education and the practice of statistics, and many other fields is astonishing in its breadth. He was a visionary when it came to linking many different areas to address real scientific issues. He professed the importance of statistics in many disciplines, but recognized that true interdisciplinary work requires joining of the expertise across different areas, and it is in this spirit that he helped steer algebraic statistics toward becoming a thriving subject. Many of his favorite topics in the area are covered in this special issue. We are grateful to all authors for contributing to this volume to honor him and his influence on the field. During the preparation of this issue, we learned about the tragic killing of his widow, Joyce Fienberg, during the Tree of Life Synagogue massacre in Pittsburgh, PA on October 27, 2018. This issue is dedicated to their memory.
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- USING COMPUTATIONAL MOLECULAR MODELING TO STUDY TRANSPORT PROCESSES OF INTEREST IN SEPARATIONS
- Separation processes are widely used in chemical productions. The further development of membrane-based separation processes, compared with thermal separations, can lead to significant energy savings in chemical process industries. However, the main obstacle of experiments is that many separation processes are not well understood at the fundamental molecular level. In this dissertation, we use computational molecular modeling tools, mainly classical molecular dynamics (MD), to clarify molecular forces and provide detail at a molecular level, which can aid in the understanding of transport process and designing materials for a proposed application. In the first study, we investigated separation of water/alcohol vapor using zeolite membranes. Experimentally, the separation of water/isopropanol (IPA) mixtures shows a dramatic decrease in selectivity due to increase of IPA flux as the feed water concentration decrease when using the sodium A zeolite membrane. We used molecular dynamics simulations to help our experimental collaborators understand these puzzling results. The MD results reveal that the water molecules gather around the defect pores on the zeolite membrane, which stops the IPA from going through the membrane and has a positive effect on separation. Then, we studied the HPLC used to separate chiral drug mixtures. One popular chiral stationary phase, amylose tris(3,5-dimethylphenyl carbamate) (ADMPC), has been investigated using both experimental and computational methods; however, the dynamic nature of the interaction between enantiomers and ADMPC, as well as the solvent effects on the ADMPC-enantiomer interaction, are currently absent from the chiral recognition mechanism. We used MD simulations to model the ADMPC in different solvents to elucidate the chiral recognition mechanism from a new dynamic perspective. The ADMPC is found to hold the left-handed helical structure in both methanol and heptane/IPA (90/10); however, the ADMPC has a more extended average structure in heptane/IPA. We developed a model where the ADMPC atoms were restricted in the MD simulation. To better understand the molecular dynamic chiral recognition that provides the retention factor and the elution order in HPLC, we examined hydrogen bonding lifetimes, and mapped out ring-ring interactions between the drugs and the ADMPC. We discover several MD metrics related to hydrogen-bonding lifetimes and correlate them with HPLC results. One metric provides a prediction of the correct elution order 90%, and the ratios of these quantities for the enantiomers provide linear correlation (0.85 coefficient) with experimental retention factors. In the following study, we presented an improved model wherein multiple ADMPC polymer strands are coated on an amorphous silica slab. Using various MD techniques, we successfully coated ADMPCs onto the surface without losing the structural character of the backbone in the solvent. This model provides more opportunities for chiral molecules interacting with ADMPC, resulting in a better agreement compared with experiment when using the overall average metric. The new model also provides the possibility for drug molecules to interact with two polymer strands simultaneously, which is not possible in the previous single-strand model. For a better understanding of why some metrics are better predictors than others, we used charts of the distribution of hydrogen bonding lifetimes to display the information for various donor-acceptor pairs. The results are more consistent than the previous models and resolves the problematic cases of thalidomide and valsartan. Besides the membrane-based separations, immiscible liquid-liquid equilibrium states were also studied. We successfully predicted results based on MD simulations and showed comparable accuracy with experimental data. This method has applications in liquid-liquid extraction which is widely used in industrial separation process.
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- Modeling enantiomeric separations as an interfacial process using amylose tris(3,5-dimethylphenyl carbamate) (ADMPC) polymers coated on amorphous silica
- In the present study, we present a model to predict the chiral separation results for drug enantiomers by ADMPC chiral stationary phase in high performance liquid chromatography (HPLC) wherein multiple ADMPC polymer strands are coated on an amorphous silica slab. Both reactive and classical MD are used to prepare the surface. Using various MD techniques, we successfully coat ADMPCs onto the surface without losing the structural character of the backbone in the presence of the solvent system. Not only is this model more representative of the polymer surface on a solid support that is encountered by the enantiomers, it also provides more opportunities for chiral molecules interacting with ADMPC, resulting in a better agreement compared with experiment when we use overall average quantities as the metric. In our previous studies, we had used a single polymer strand of amylose tris(3,5-dimethylphenyl carbamate) (ADMPC) in the solvent system. The new model provides the possibility for large drug molecules to interact with two polymer strands at the same instant, which was not possible to model with only a single polymer strand in the solvent. For a better understanding of why some metrics are better predictors than others, we use charts of the distribution of hydrogen bonding lifetimes in this work to display the hydrogen-bonding information for various donor-acceptor pairs that contribute to the interaction events determining the relative retention times for the enantiomers. We also examine the contribution of the ring-ring interactions to the molecular recognition process and ultimately to differential retention of S and R enantiomers. The results using the new model are more consistent than the previous models and resolves the problematic case of two drugs, thalidomide and valsartan., Sponsorship: The National Science Foundation (CBET 1545560)
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- Robert F. Carr Memorial Chapel of St. Savior
- 65 East 32nd Street. Chicago, Illinois
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- Harold Leonard Stuart Building, Illinois Institute of Technology
- 10 West 31st Street, Chicago, Illinois
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- Arthur Keating Hall, Illinois Institute of Technology
- 3040 South Wabash Avenue, Chicago, Illinois
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- Arthur Keating Hall, Illinois Institute of Technology
- 3040 South Wabash Avenue, Chicago, Illinois
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- Graduate Hall, Illinois Institute of Technology
- 70 East 33rd Street, Chicago, Illinois
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- Cunningham Hall, Illinois Institute of Technology
- 3100 South Michigan Avenue, Chicago, Illinois
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- John T. Rettaliata Engineering Center, Illinois Institute of Technology
- 10 West 32nd Street, Chicago, Illinois
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- Heating Plant, Illinois Institute of Technology
- 3430 South Federal Street, Chicago, Illinois
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- Life Sciences Building, Illinois Institute of Technology
- 3105 South Dearborn Street, Chicago, Illinois
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- Perlstein Hall
- 10 West 33rd Street, Chicago, Illinois
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- Heating Plant, Illinois Institute of Technology
- 3430 South Federal Street, Chicago, Illinois