Machine Learning Predictions of Simulated Self-Diffusion Coefficients for Bulk and Confined Pure Liquids.

Diffusion properties of bulk fluids have been predicted using empirical expressions and machine learning (ML) models, suggesting that predictions of diffusion also should be possible for fluids in confined environments. The ability to quickly and accurately predict diffusion in porous materials would enable new discoveries and spur development in relevant technologies such as separations, catalysis, batteries, and subsurface applications. In this work, we apply artificial neural network (ANN) models to predict the simulated self-diffusion coefficients of real liquids in both bulk and pore environments.

Symbolic regression development of empirical equations for diffusion in Lennard-Jones fluids.

Symbolic regression (SR) with a multi-gene genetic program has been used to elucidate new empirical equations describing diffusion in Lennard-Jones (LJ) fluids. Examples include equations to predict self-diffusion in pure LJ fluids and equations describing the finite-size correction for self-diffusion in binary LJ fluids. The performance of the SR-obtained equations was compared to that of both the existing empirical equations in the literature and to the results from artificial neural net (ANN) models recently reported.

Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks.

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for individual components in binary fluid mixtures. The ANNs were tested on an experimental database of 4328 self-diffusion constants from 131 mixtures containing 75 unique compounds. The presence of strong hydrogen bonding molecules may lead to clustering or dimerization resulting in non-linear diffusive behavior.

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids.

The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids.

NMR spectroscopy of coin cell batteries with metal casings.

Battery cells with metal casings are commonly considered incompatible with nuclear magnetic resonance (NMR) spectroscopy because the oscillating radio-frequency magnetic fields (“rf fields”) responsible for excitation and detection of NMR active nuclei do not penetrate metals. Here, we show that rf fields can still efficiently penetrate nonmetallic layers of coin cells with metal casings provided “ damming” configurations are avoided. With this understanding, we demonstrate noninvasive high-field in situ Li and F NMR of coin cells with metal casings using a traditional external NMR coil.

Modes of Disorder in Poly(carbon monofluoride).

Poly(carbon monofluoride), or (CF), is a layered fluorinated graphite material consisting of nanosized platelets. Here, we present experimental multidimensional solid-state NMR spectra of (CF), supported by density functional theory (DFT) calculations of NMR parameters, which overhauls our understanding of structure and bonding in the material by elucidating many ways in which disorder manifests. We observe strong F NMR signals conventionally assigned to elongated or "semi-ionic" C-F bonds and find that these signals are in fact due to domains where the framework locally adopts boat-like cyclohexane conformations.

Artificial neural network prediction of self-diffusion in pure compounds over multiple phase regimes.

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for pure components in liquid, gas and super critical phases. The ANNs were tested on an experimental database of 6625 self-diffusion constants for 118 different chemical compounds. The presence of multiple phases results in a heavy skew in the distribution of diffusion constants and multiple approaches were used to address this challenge.

Machine Learning-Based Upscaling of Finite-Size Molecular Dynamics Diffusion Simulations for Binary Fluids.

Molecular diffusion coefficients calculated using molecular dynamics (MD) simulations suffer from finite-size (i.e., finite box size and finite particle number) effects.

Formation of monomeric Sn(ii) and Sn(iv) perfluoropinacolate complexes and their characterization by Sn Mössbauer and Sn NMR spectroscopies.

The synthesis and characterization of a series of Sn(ii) and Sn(iv) complexes supported by the highly electron-withdrawing dianionic perfluoropinacolate (pin) ligand are reported herein. Three analogs of [Sn(pin)] with NEtH (1), K (2), and {K(18C6)} (3) counter cations and two analogs of [Sn(pin)] with K (4) and {K(15C5)} (5) counter cations were prepared and characterized by standard analytical methods, single-crystal X-ray diffraction, and Sn Mössbauer and NMR spectroscopies. The six-coordinate Sn(pin) complexes display Sn NMR resonances and Sn Mössbauer spectra similar to SnO (cassiterite).

Arene Substitution Design for Controlled Conformational Changes of Dibenzocycloocta-1,5-dienes.

We report that an agile eight-membered cycloalkane can be stabilized by fusing a benzene ring on each side, substituted with proper functional groups. The conformational change of dibenzocycloocta-1,5-diene (DBCOD), a rigid-flexible-rigid organic moiety, from its Boat to Chair conformation requires an activation energy of 42 kJ/mol, which is substantially lower than those of existing submolecular shape-changing units. Experimental data corroborated by theoretical calculations demonstrate that intramolecular hydrogen bonding can stabilize Boat, whereas electron repulsive interaction from opposing ester substituents favors Chair.

Machine learning prediction of self-diffusion in Lennard-Jones fluids.

Different machine learning (ML) methods were explored for the prediction of self-diffusion in Lennard-Jones (LJ) fluids. Using a database of diffusion constants obtained from the molecular dynamics simulation literature, multiple Random Forest (RF) and Artificial Neural Net (ANN) regression models were developed and characterized. The role and improved performance of feature engineering coupled to the RF model development was also addressed.

Heterogeneous Polymer Dynamics Explored Using Static H NMR Spectra.

NMR spectroscopy continues to provide important molecular level details of dynamics in different polymer materials, ranging from rubbers to highly crosslinked composites. It has been argued that thermoset polymers containing dynamic and chemical heterogeneities can be fully cured at temperatures well below the final glass transition temperature (T). In this paper, we described the use of static solid-state H NMR spectroscopy to measure the activation of different chain dynamics as a function of temperature.

Quantification of Uncoupled Spin Domains in Spin-Abundant Disordered Solids.

Materials often contain minor heterogeneous phases that are difficult to characterize yet nonetheless significantly influence important properties. Here we describe a solid-state NMR strategy for quantifying minor heterogenous sample regions containing dilute, essentially uncoupled nuclei in materials where the remaining nuclei experience heteronuclear dipolar couplings. NMR signals from the coupled nuclei are dephased while NMR signals from the uncoupled nuclei can be amplified by one or two orders of magnitude using Carr-Meiboom-Purcell-Gill (CPMG) acquisition.

Computational and Experimental H-NMR Study of Hydrated Mg-Based Minerals.

Magnesium oxide (MgO) can convert to different magnesium-containing compounds depending on exposure and environmental conditions. Many MgO-based phases contain hydrated species allowing H-nuclear magnetic resonance (NMR) spectroscopy to be used in the characterization and quantification of proton-containing phases; however, surprisingly limited examples have been reported. Here, H-magic angle spinning (MAS) NMR spectra of select Mg-based minerals are presented and assigned.

Trapped Intermediate of a Meerwein-Pondorf-Verley Reduction of Hydroxy Benzaldehyde to a Dialkoxide by Titanium Alkoxides.

A series of titanium alkoxides ([Ti(OR)] (OR = OCH(CH) (OPr), OC(CH) (OBu), and OCHC(CH) (ONep)) were modified with a set of substituted hydroxyl-benzaldehydes [HO-BzA-L: = 1, 2-hydroxybenzaldehyde (L = H), 2-hydroxy-3-methoxybenzaldehyde (OMe-3), 5-bromo-2-hydroxybenzaldehyde (Br-5), 2-hydroxy-5-nitrobenzaldehyde (NO-5); = 2, 3,5-di--butyl-2-hydroxybenzaldehyde (Bu-3,5), 2-hydroxy-3,5-diiodobenzaldehyde (I-3,5)] in pyridine (py). Instead of the expected simple substitution, each of the HO-BzA-L modifiers were reduced to their respective diol [(py)(OR)Ti(κ(O,μ-O')(OCH(CHO)-2)(L)] (OR = OPr, = 1, L = H (), OMe-3 (), Br-5 (·py), NO-5 (·4py); = 2, Bu-3,5 (), I-3,5 (), ONep; = 1, L = H (), OMe-3 (), Br-5 (·py), NO-5 (); = 2, Bu-3,5 (), I-3,5 (·py)), as identified by single crystal X-ray studies. The H NMR spectral data were complex at room temperature but simplified at high temperatures (70 °C).

Hydration and Hydroxylation of MgO in Solution: NMR Identification of Proton-Containing Intermediate Phases.

Magnesium oxide (MgO)-engineered barriers used in subsurface applications will be exposed to high concentration brine environments and may form stable intermediate phases that can alter the effectiveness of the barrier. To explore the formation of these secondary intermediate phases, MgO was aged in water and three different brine solutions and characterized with X-ray diffraction (XRD) and H magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy. After aging, there is ∼4% molar equivalent of a hydrogen-containing species formed.

Resolving Confined Li Dynamics of Uranyl Peroxide Capsule U.

We obtained a kerosene-soluble form of the lithium salt [UO(O)(OH)] phase (Li-U), by adding cetyltrimethylammonium bromide surfactant to aqueous Li-U. Interestingly, its variable-temperature solution Li NMR spectroscopy resolves two narrowly spaced resonances down to -10 °C, which shift upfield with increasing temperature, and finally coalesce at temperatures > 85 °C. Comparison with solid-state NMR demonstrates that the Li dynamics in the Li-U-CTA phase involves only exchange between different local encapsulated environments.

Computational Study of Microhydration in Sulfonated Diels-Alder Poly(phenylene) Polymers.

The nature of microhydration in sulfonated Diels-Alder poly(phenylene) (SDAPP) polymer membranes is explored using ab initio and density functional theory (DFT) electronic structure calculations. The impact of the aromatic poly(phenylene) structure, including cooperative effects between multiple spatially adjacent sulfonic groups, on the hydration environment is addressed using a series of DFT B3LYP/6-311**-optimized structures for different SDAPP· nHO clusters. In addition, larger SDAPP polymer fragments, along with selected hydrophilic domain structures extracted from molecular dynamic (MD) simulations, are also evaluated using ONIOM HF/PM6 semiempirical calculations.

Synthesis and characterization of thallium-salen derivatives for use as underground fluid flow tracers.

A pair of thallium salen derivatives was synthesized and characterized for potential use as monitors (or taggants) or as models for Group 13 complexes for subterranean fluid flows. These precursors were isolated from the reaction of thallium ethoxide with N,N'-bis(3,5-di-tert-butylsalicylidene)-ethylenediamine (H-salo-Bu), or N,N'-bis(3,5-di-tert-butylsalicylidene)-1,2-phenylenediamine (H-saloPh-Bu). The products were identified by single crystal X-ray diffraction as: [((μ-O),κ-(N)(N')salo-Bu)Tl] (1) and {[((μ-O)saloPh-Bu)Tl][((μ-O),κ-(N)(N')saloPh-Bu)Tl]} (2).

Single-Crystal Time-of-Flight Neutron Diffraction and Magic-Angle-Spinning NMR Spectroscopy Resolve the Structure and H and Li Dynamics of the Uranyl Peroxide Nanocluster U.

Single-crystal time-of-flight neutron diffraction has provided atomic resolution of H atoms of HO molecules and hydroxyl groups, as well as Li cations in the uranyl peroxide nanocluster U. Solid-state magic-angle-spinning nuclear magnetic resonance (MAS NMR) spectroscopy was used to confirm the dynamics of these constituents, revealing the transportation of Li atoms and HO through cluster walls. H atoms of hydroxyl units that are located on the cluster surface are involved in the transfer of HO and Li cations from inside to outside and vice versa.

H- F REDOR-filtered NMR spin diffusion measurements of domain size in heterogeneous polymers.

Solid state NMR spectroscopy is inherently sensitive to chemical structure and composition and thus makes an ideal method to probe the heterogeneity of multicomponent polymers. Specifically, NMR spin diffusion experiments can be used to extract reliable information about spatial domain sizes on multiple length scales, provided that magnetization selection of one domain can be achieved. In this paper, we demonstrate the preferential filtering of protons in fluorinated domains during NMR spin diffusion experiments using H- F heteronuclear dipolar dephasing based on rotational echo double resonance (REDOR) MAS NMR techniques.

Pt-Mg, Pt-Ca, and Pt-Zn Lantern Complexes and Metal-Only Donor-Acceptor Interactions.

Pt-based heterobimetallic lantern complexes of the form [PtM(SOCR)(L)] have been shown previously to form intermolecular metallophilic interactions and engage in antiferromagnetic coupling between lanterns having M atoms with open shell configurations. In order to understand better the influence of the carboxylate bridge and terminal ligand on the electronic structure, as well as the metal-metal interactions within each lantern unit, a series of diamagnetic lantern complexes, [PtMg(SAc)(OH)] (1), [PtMg(tba)(OH)] (2), [PtCa(tba)(OH)] (3), [PtZn(tba)(OH)] (4), and a mononuclear control (PhP)[Pt(SAc)] (5) have been synthesized. Crystallographic data show close Pt-M contacts enforced by the lantern structure in each dinuclear case.

Structural Properties of the Acidification Products of Scandium Hydroxy Chloride Hydrate.

The structural properties of a series of scandium inorganic acid derivatives were determined. The reaction of Sc(0) with concentrated aqueous hydrochloric acid led to the isolation of [(H2O)5Sc(μ-OH)]24Cl·2H2O (1). Compound 1 was modified with a series of inorganic acids (i.

Infrared signature of micro-hydration in the organophosphate Sarin: an ab initio study.

The infrared (IR) spectra of micro-hydrated Sarin•(H2O)n clusters containing between one and four explicit waters have been studied using ab initio density functional theory (DFT) methods. The phosphate group P=O bond vibration region (∼1270 to 1290 cm(-1)) revealed the largest frequency variation with hydration, with a frequency red shift reflecting the direct hydrogen bond formation between the P=O of Sarin and water. Small variations to the P-F stretch (∼810 to 815 cm(-1)) and the C-O-P vibrational modes (∼995 to 1004 cm(-1)) showed that the water interactions with these functional groups were minor, and that the structures of Sarin were not extensively perturbed in the hydrated complexes.