Monte Carlo Simulations of Water Pollutant Adsorption at Parts-per-Billion Concentration: A Study on 1,4-Dioxane.

1,4-dioxane, an emerging water pollutant with high production volumes, is a probable human carcinogen. The inadequacy of conventional treatment processes demonstrates the need for an effective remediation strategy. Crystalline nanoporous materials are cost-effective adsorbents due to their high capacity and selective separation in mixtures. This study explores the potential of all-silica zeolites for the separation of 1,4-dioxane from water. These zeolites are highly hydrophobic and can preferentially adsorb nonpolar molecules from mixtures. We investigated six zeolite frameworks (BEA, EUO, FER, IFR, MFI, and MOR) using Monte Carlo simulations in the Gibbs ensemble. The simulations indicate high selectivity by FER and EUO, especially at low pressures, which we attribute to pore sizes and shapes with a greater affinity to 1,4-dioxane. We also demonstrate a Monte Carlo simulation workflow using gauge cells to model the adsorption of an aqueous solution of 1,4-dioxane at a 0.35 ppb concentration. We quantify 1,4-dioxane and water coadsorption and observe selectivities ranging from 1.1 × 105 in MOR to 8.7 × 106 in FER. We also demonstrate that 1,4-dioxane is in the infinite dilution regime in the aqueous phase at this concentration. This simulation technique can be extended to model other emerging water contaminants such as perfluoroalkyl and polyfluoroalkyl substances (PFAS), chlorofluorocarbons, and others, which are also found in extremely low concentrations.

Combining data and theory for derivable scientific discovery with AI-Descartes.

Scientists aim to discover meaningful formulae that accurately describe experimental data. Mathematical models of natural phenomena can be manually created from domain knowledge and fitted to data, or, in contrast, created automatically from large datasets with machine-learning algorithms. The problem of incorporating prior knowledge expressed as constraints on the functional form of a learned model has been studied before, while finding models that are consistent with prior knowledge expressed via general logical axioms is an open problem. We develop a method to enable principled derivations of models of natural phenomena from axiomatic knowledge and experimental data by combining logical reasoning with symbolic regression. We demonstrate these concepts for Kepler's third law of planetary motion, Einstein's relativistic time-dilation law, and Langmuir's theory of adsorption. We show we can discover governing laws from few data points when logical reasoning is used to distinguish between candidate formulae having similar error on the data.

Nonane and Hexanol Adsorption in the Lamellar Phase of a Nonionic Surfactant: Molecular Simulations and Comparison to Ideal Adsorbed Solution Theory.

Adsorption of n-nonane/1-hexanol (C9/C6OH) mixtures into the lamellar phase formed by a 50/50 w/w triethylene glycol mono-n-decyl ether (C10E3)/water system was studied using configurational-bias Monte Carlo simulations in the osmotic Gibbs ensemble. The interactions were described by the Shinoda-Devane-Klein coarse-grained force field. Prior simulations probing single-component adsorption indicated that C9 molecules preferentially load near the center of the bilayer, increasing the bilayer thickness, whereas C6OH molecules are more likely to be found near the interface of the polar and nonpolar moieties, swelling the bilayer in the lateral dimension. Here, we extend this work to binary C9/C6OH adsorption to probe whether the difference in the spatial preferences may lead to a synergistic effect and enhanced loadings for the mixture. Comparing loading trends and the thermodynamics of binary adsorption to unary adsorption reveals that C9-C9 interactions lead to the largest enhancement, whereas C9-C6OH and C6OH-C6OH interactions are less favorable for this bilayer system. Ideal adsorbed solution theory yields satisfactory predictions of the binary loading.

Ethanol and Water Adsorption in Conventional and Hierarchical All-Silica MFI Zeolites.

Hierarchical zeolites containing both micro- (<2 nm) and mesopores (2-50 nm) have gained increasing attention in recent years because they combine the intrinsic properties of conventional zeolites with enhanced mass transport rates due to the presence of mesopores. The structure of the hierarchical self-pillared pentasil (SPP) zeolite is of interest because all-silica SPP consists of orthogonally intergrown single-unit-cell MFI nanosheets and contains hydrophilic surface silanol groups on the mesopore surface while its micropores are nominally hydrophobic. Therefore, the distribution of adsorbed polar molecules, like water and ethanol, in the meso- and micropores is of fundamental interest. Here, molecular simulation and experiment are used to investigate the adsorption of water and ethanol on SPP. Vapor-phase single-component adsorption shows that water occupies preferentially the mesopore corner and surface regions of the SPP material at lower pressures (P/P 0 < 0.5) while loading in the mesopore interior dominates adsorption at higher pressures. In contrast, ethanol does not exhibit a marked preference for micro- or mesopores at low pressures. Liquid-phase adsorption from binary water-ethanol mixtures demonstrates a 2 orders of magnitude lower ethanol/water selectivity for the SPP material compared to bulk MFI. For very dilute aqueous solutions of ethanol, the ethanol molecules are mostly adsorbed inside the SPP micropore region due to stronger dispersion interactions and the competition from water for the surface silanols. At high ethanol concentrations (C EtOH > 700 g L-1), the SPP material becomes selective for water over ethanol.

Renewable lubricants with tailored molecular architecture.

We present a strategy to synthesize three types of renewable lubricant base oils with up to 90% yield using 2-alkylfurans, derived from nonfood biomass, and aldehydes, produced from natural oils or biomass through three chemistries: hydroxyalkylation/alkylation (HAA), HAA followed by hydrogenation, and HAA followed by hydrodeoxygenation. These molecules consist of (i) furan rings, (ii) saturated furan rings, and (iii) deoxygenated branched alkanes. The structures of these molecules can be tailored in terms of carbon number, branching length, distance between branches, and functional groups. The site-specific, energy-efficient C-C coupling chemistry in oxygenated biomass compounds, unmatched in current refineries, provides tailored structure and tunable properties. Molecular simulation demonstrates the ability to predict properties in agreement with experiments, proving the potential for molecular design.

Solvent-induced frequency shifts of 5-hydroxymethylfurfural deduced via infrared spectroscopy and ab initio calculations.

Solvent-induced frequency shifts (SIFS) of the carbonyl stretching vibration ν(C═O) of 5-hydroxymethylfurfural were measured in protic, polar aprotic, and nonpolar solvents. The Gutmann acceptor number (AN) was found to correlate with the measured frequency shifts. The SIFS in six solvents were investigated using ab initio electronic structure calculations, treating the solvent implicitly and with an explicit solvent ligand interacting with the carbonyl. The conductor-polarizable continuum model (CPCM) of solvation predicted that ν(C═O) shifted according with the dielectric constant as (ε - 1)/(2ε + 1), in agreement with the analytical predictions of the Kirkwood-Bauer-Magat (KBM) theory for a dipole in a dielectric continuum, but in disagreement with the experimental trend. The experimental SIFS were best predicted using gas-phase complexes of HMF and explicit solvent-ligand. Natural bond orbital (NBO) analysis and Bader's atoms in molecules theory were used to investigate the electronic structure of these complexes. Strong SIFS were found to arise from stronger H-bonding interactions, as observed in delocalization of carbonyl lone-pair electrons by H-bonding solvent σ*(X-H) orbitals, and an increase in charge density and a decrease in local potential energy at the H-bond (3, -1) critical point. Consequently, by predicting the experimental SIFS and examining the electronic structure, we find the first theoretical evidence for treating Gutmann's solvent AN as a measure of solvent Lewis acidity.

Origin of 5-hydroxymethylfurfural stability in water/dimethyl sulfoxide mixtures.

In the present work, we combined vibrational spectroscopy with electronic structure calculations to understand the solvation of HMF in DMSO, water, and DMSO/water mixtures and to provide insights into the observed hindrance of HMF rehydration and aldol condensation reactions if it is dissolved in DMSO/water mixtures. To achieve this goal, the attenuated total reflection FTIR spectra of a wide composition range of binary and ternary mixtures were measured, analyzed, and compared to the findings of ab initio DFT calculations. The effect of solvent on the HMF C-O and O-H vibrational modes reveals significant differences that are ascribed to different intermolecular interactions between HMF and DMSO or water. We also found that DMSO binds to HMF more strongly than water, and interactions with the HMF hydroxyl group are stronger than those with the HMF carbonyl group. We also showed the preferential solvation of HMF C-O groups by DMSO if HMF is dissolved in DMSO/water mixed solvent. Frontier molecular orbital theory was used to examine the influence of the solvent on side reactions. The results show that HMF solvation by DMSO increases its LUMO energy, which reduces its susceptibility to nucleophilic attack and minimizes undesirable hydration and humin-formation reactions. This result, together with the preferential solvation of HMF by DMSO, provide an explanation for the enhanced HMF stability in DMSO/water mixtures observed experimentally.