Molecular Simulations of Adsorption and Diffusion in Metal-Organic Frameworks (MOFs)

Metal-organic frameworks (MOFs) are a new class of nanoporous materials that have received great interest since they were first synthesized in the late 1990s. Practical applications of MOFs are continuously being discovered as a better understanding of the properties of materials adsorbed within the nanopores of MOFs emerges. One such potential application is as a component of an explosive-sensing system. Another potential application is for hydrogen storage. This work is focused on tailoring MOFs to adsorb/desorb the explosive, RDX. Classical grand canonical Monte Carlo (GCMC) and molecular dynamic (MD) simulations have been performed to calculate adsorption isotherms and self-diffusivities of RDX in several IRMOFs. Because gathering experimental data on explosive compounds is dangerous, data is limited. Simulation can in part fill the gap of missing information. Through these simulations, many of the key issues associated with MOFs preconcentrating RDX have been resolved. The issues include both theoretical issues associated with the computational generation of properties and practical issues associated with the use of MOFs in explosive-sensing system. Theoretically, we evaluate the method for generating partial charges for MOFs and the impact of this choice on the adsorption isotherm and diffusivity. Practically, we show that the tailoring of an MOF with a polar group like an amine can lead to an adsorbent that (i) concentrates RDX from the bulk by as much as a factor of 3000, (ii) is highly selective for RDX, and (iii) retains sufficient RDX mobility allowing for rapid, real time sensing. Many of the impediments to the effective explosive detection can be framed as shortcomings in the understanding of molecule surface interactions. A fundamental, molecular-level understanding of the interaction between explosives and functionalized MOFs would provide the necessary guidance that allows the next generation of sensors to be developed. This is one of the main driving forces behind this dissertation. Another important achievement in this work is the demonstration of a new direction for tailoring MOFs. A new class of tailored MOFs containing porphyrins has been proposed. These tailored MOFs show greater capability for hydrogen storage, which also demonstrated the great functionalization of MOFs and great potential to serve as preconcentrators. The use of a novel multiscale modeling technique to develop equations of state for inhomogeneous fluids is included as a supplement to this dissertation

Self-Consistent Multiscale Modeling in the Presence of Inhomogeneous Fields

Molecular dynamics (MD) simulations of a Lennard–Jones fluid in an inhomogeneous external field generate steady-state profiles of density and pressure with nanoscopic heterogeneities. The continuum level of mass, momentum, and energy transport balances is capable of reproducing the MD profiles only when the equation of state for pressure as a function of density is extracted directly from the molecular level of description. We show that the density profile resulting from simulation is consistent with both a molecular-level theoretical prediction from statistical mechanics as well as the solution of the continuum-level set of differential equations describing the conservation of mass and momentum

Application and Mechanism of High-Sensitivity Indicator Film for Monitoring Fish Freshness

The sensitivity of freshness indicator labels/films has become an important research direction of intelligent food packaging. In this study, a high-sensitivity indicator film containing gelatin and Fe2＋ was prepared by electrospinning using blueberry anthocyanins as the indicator and zein as the matrix for monitoring fish freshness. The validity and sensitivity of the indicator film for detecting the freshness of silver carp were tested and the potential mechanism was elucidated. The results of pH sensitivity, ammonia sensitivity and anthocyanin release showed that the addition of gelatin and Fe2+ improved the sensitivity of the indicator film to pH and ammonia, and contributed to better binding of the anthocyanins in the film. There was a strong correlation between the color response (P = (L* + a* + b* + R + G + B)/a*) of the film and the content of total volatile basic nitrogen (TVB-N) content in fish meat as a freshness indicator (R2 > 0.98). In conclusion, the prepared indicator film can effectively monitor fish freshness, and the hydrogen bond interactions between anthocyanins and gelatin/Fe2+ may affect the color response characteristics and sensitivity of the indicator film

Molecular Screening of Alcohol and Polyol Adsorption onto MFI-Type Zeolites

Configurational-bias grand canonical Monte Carlo (CB-GCMC) simulations and expanded ensemble (EE)-CB-GCMC simulations were performed to obtain adsorption isotherms of alcohols and polyols onto MFI-type zeolites from the gas phase and aqueous solution. In adsorption from both phases, Henry’s constants and heats of adsorption at infinite dilution for straight-chain alcohols, diols, and triols in silicalite-1 are found to increase, and the saturation loadings decrease with increasing carbon number. Adsorption of straight-chain alcohols is more favorable than that of branched-chain alcohols. Henry’s constants increase with increasing number of hydroxyl groups for gas-phase adsorption but decrease for adsorption from aqueous solution due to the strong hydrophilic solvent effect of water. The location of the hydroxyls does not affect significantly the adsorption from aqueous solution but does so in gas-phase adsorption. The saturation pressures for gas-phase adsorption decrease by orders of magnitude from the alcohols to the triols. Nonframework cations increase the adsorption of the small alcohols by an order magnitude at low concentrations (<1 mg/mL), but result in only a factor of 2 increase for larger alcohols like butanol at low concentrations (<0.03 mg/mL), and then decrease the adsorption at higher concentrations. Overall, the simulated results are in reasonable agreement with available experimental data

An Improvement to COSMO-SAC for Predicting Thermodynamic Properties

A modified COSMO-SAC model is presented to calculate thermodynamic properties of pure fluids and mixtures using statistical thermodynamics and the surface charge density of each compound obtained from a quantum mechanics (QM) calculation. The main differences from the previous models are that the new model includes a dispersion contribution in the mixture interaction, and is reparametrized using measured pure and mixture thermodynamic data simultaneously. With a single set of universal parameters, the new model provides higher accuracy than our previous models for predicting mixture thermodynamic properties while maintaining the same accuracy for pure compound thermodynamic properties. The overall root-mean-square deviation (RMSD) in the logarithms of partition coefficients for 992 octanol–water partitioning systems and 829 other solvent–water partitioning systems with this new model is reduced by about 10% compared to the results from previous models. Also, the agreement between the predicted and measured partition coefficients over a wide range of values is improved as a result of better activity coefficient predictions at high dilution by inclusion of the dispersive mixture interaction in the model. The accuracy in the vapor–liquid equilibrium (VLE) predictions is comparable to, or better than, the previous model that was developed for phase equilibria calculations only. The new model also provides parameters for use with the Amsterdam Density Functional (ADF) in addition to DMol³

Novel Fabrication of Zein-Soluble Soybean Polysaccharide Nanocomposites Induced by Multifrequency Ultrasound, and Their Roles on Microstructure, Rheological Properties and Stability of Pickering Emulsions

In this work, soluble soybean polysaccharides (SSPS) were employed together with multifrequency ultrasound to fabricate zein nanocomposites which were conducive to enhancing the stability of high internal phase emulsions (HIPEs). Compared with non-ultrasonic treated zein colloidal particle samples (132.23 ± 0.85 nm), the zein nanoparticles samples induced by dual-frequency ultrasound exhibited a smaller particle size (114.54 ± 0.23 nm). Furthermore, the particle size of the zein composite nanoparticles (256.5 ± 4.81) remarkably increased with SPSS coating, consequently leading to larger fluorescence intensity together with lower zeta-potential (−21.90 ± 0.46 mv) and surface hydrophobicity (4992.15 ± 37.28). Meanwhile, zein-SSPS composite nanoparticles induced by DFU showed remarkably enhanced thermal stability. Fourier transform infrared (FTIR) spectroscopy and Circular dichroism (CD) spectroscopy were also used to characterize zein-SSPS composite nanoparticles. The results confirmed that DFU combined with SSPS treatment significantly increased β-sheets (from 12.60% ± 0.25 b to 21.53% ± 0.37 c) and reduced α-helix content (34.83% ± 0.71 b to 23.86% ± 0.66 a) remarkably. Notably, HIPEs prepared from zein-SSPS nanocomposites induced by dual-frequency simultaneous ultrasound (DFU) at 40/60 kHz showed better storage stability. HIPEs stabilized by DFU induced zein-SSPS nanoparticles exhibited higher storage modulus (G′) and loss modulus (G″), leading to lower fluidity, together with better stability contributing to the water-binding capacity and three-dimensional (3D) network structure of the HIPEs emulsion. The findings of this study indicate that this method can be utilized and integrated to further extend the application of zein and SSPS and explore HIPEs

Untargeted Metabolomics on Skin Mucus Extract of Channa argus against Staphylococcus aureus: Antimicrobial Activity and Mechanism

Microbial contamination is one of the most common food safety issues that lead to food spoilage and foodborne illness, which readily affects the health of the masses as well as gives rise to huge economic losses. In this study, Channa argus was used as a source of antimicrobial agent that was then analyzed by untargeted metabolomics for its antibacterial mechanism against Staphylococcus aureus. The results indicated that the skin mucus extract of C. argus had great inhibitory action on the growth of S. aureus, and the morphology of S. aureus cells treated with the skin mucus extract exhibited severe morphological damage under scanning electron microscopy. In addition, metabolomics analysis revealed that skin mucus extract stress inhibited the primary metabolic pathways of S. aureus by inducing the tricarboxylic acid cycle and amino acid biosynthesis, which further affected the normal physiological functions of biofilms. In conclusion, the antimicrobial effect of the skin mucus extract is achieved by disrupting cell membrane functions to induce an intracellular metabolic imbalance. Hence, these results conduce to amass novel insights into the antimicrobial mechanism of the skin mucus extract of C. argus against S. aureus

Molecular Simulations of Adsorption and Diffusion of RDX in IRMOF-1

In order to test the feasibility of using metal-organic frameworks (MOFs) to pre-concentrate explosive molecules for detection, molecular simulations of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) within IRMOF-1 were performed. Grand canonical Monte Carlo (GCMC) simulations were used to generate adsorption isotherms for pure RDX, RDX in dry air, and RDX in wet air. In addition to the isotherms, the GCMC simulations provide adsorption energies and density distributions of the adsorbates within the MOF. Molecular dynamics simulations calculate diffusivities and provide a detailed understanding of the change in conformation of the RDX molecule upon adsorption. The presence of dry air has little influence on the amount of RDX that adsorbs. The presence of wet air increases the amount of RDX that adsorbs due to favourable interactions between RDX and water. We found a Henry\u27s law constant of 21.2 mol/kg/bar for both pure RDX and RDX in dry air. The RDX adsorption sites are located (i) in big cages, (ii) near a vertex, and (iii) between benzene rings. The energy of adsorption of RDX at infinite dilution was found to be - 9.2 kcal/mol. The distributions of bond lengths, bond angles and torsion angles in RDX are uniformly slightly broader in the gas phase than in the adsorbed phase, but not markedly so. The self-diffusivity of RDX in IRMOF-1 is a strong function of temperature, with an activation energy of 6.0 kcal/mol

Quantum Chemically Estimated Abraham Solute Parameters Using Multiple Solvent–Water Partition Coefficients and Molecular Polarizability

Polyparameter Linear Free Energy Relationships (pp-LFERs), also called Linear Solvation Energy Relationships (LSERs), are used to predict many environmentally significant properties of chemicals. A method is presented for computing the necessary chemical parameters, the Abraham parameters (AP), used by many pp-LFERs. It employs quantum chemical calculations and uses only the chemical’s molecular structure. The method computes the Abraham <i>E</i> parameter using density functional theory computed molecular polarizability and the Clausius–Mossotti equation relating the index refraction to the molecular polarizability, estimates the Abraham <i>V</i> as the COSMO calculated molecular volume, and computes the remaining AP <i>S</i>, <i>A</i>, and <i>B</i> jointly with a multiple linear regression using sixty-five solvent–water partition coefficients computed using the quantum mechanical COSMO-SAC solvation model. These solute parameters, referred to as Quantum Chemically estimated Abraham Parameters (QCAP), are further adjusted by fitting to experimentally based APs using QCAP parameters as the independent variables so that they are compatible with existing Abraham pp-LFERs. QCAP and adjusted QCAP for 1827 neutral chemicals are included. For 24 solvent–water systems including octanol–water, predicted log solvent–water partition coefficients using adjusted QCAP have the smallest root-mean-square errors (RMSEs, 0.314–0.602) compared to predictions made using APs estimated using the molecular fragment based method ABSOLV (0.45–0.716). For munition and munition-like compounds, adjusted QCAP has much lower RMSE (0.860) than does ABSOLV (4.45) which essentially fails for these compounds

Nanoporous Metal Porphyrin Frameworks (MPFs)

The investigation of nanoporous Metal Porphyrin Frameworks (MPFs) for on-board vehicular hydrogen storage is a research project spanning two colleges and four departments at the University of Tennessee. In the Chemistry Department, Dr. Peter Zhang and a post-doctoral researcher, Dr. Ying Chen, are synthesizing MPFs. In the Chemical Engineering Department, Dr. David Keffer, Dr. Brian Edwards, and Ruichang Xiong, a Ph.D. student, are modeling the hydrogen adsorptive capacity of MPFs using molecular simulation. In the Materials Science and Engineering Department, Dr. Claudia Rawn, who holds a joint appointment at ORNL, is using state-of-the-art diffraction facilities at ORNL to characterize the MPF\u27s created by Drs. Zhang and Chen. In the Civil and Environmental Engineering Department, Dr. Sandeep Agnihotri, plans to measure the hydrogen adsorptive capacity of the synthesized MPFs