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USING COMPUTATIONAL MOLECULAR MODELING TO STUDY TRANSPORT PROCESSES OF INTEREST IN SEPARATIONS
Title
USING COMPUTATIONAL MOLECULAR MODELING TO STUDY TRANSPORT PROCESSES OF INTEREST IN SEPARATIONS
Creator
Wang, Xiaoyu
Date
2020
Description
Separation processes are widely used in chemical productions. The further development of membrane-based separation processes, compared with...
Show moreSeparation 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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USING COMPUTATIONAL MOLECULAR MODELING TO STUDY TRANSPORT PROCESSES OF INTEREST IN SEPARATIONS
Title
USING COMPUTATIONAL MOLECULAR MODELING TO STUDY TRANSPORT PROCESSES OF INTEREST IN SEPARATIONS
Creator
Wang,Xiaoyu
Date
2020, 2020
Publisher
ProQuest
Description
Separation processes are widely used in chemical productions. The further development of membrane-based separation processes, compared with...
Show moreSeparation 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
Title
Modeling enantiomeric separations as an interfacial process using amylose tris(3,5-dimethylphenyl carbamate) (ADMPC) polymers coated on amorphous silica
Creator
Wang,Xiaoyu, Jameson, Cynthia, Murad, Sohail
Date
2020, 2020-01-20
Publisher
ACS Langmuir
Description
In the present study, we present a model to predict the chiral separation results for drug enantiomers by ADMPC chiral stationary phase in...
Show moreIn 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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