Quest for Multifunctionality: Current Progress in the Characterization of Heterometallic Metal-Organic Frameworks.

Metal-organic frameworks (MOFs) are a class of porous, crystalline materials that have been systematically developed for a broad range of applications. Incorporation of two or more metals into a single crystalline phase to generate heterometallic MOFs has been shown to lead to synergistic effects, in which the whole is oftentimes greater than the sum of its parts. Because geometric proximity is typically required for metals to function cooperatively, deciphering and controlling metal distributions in heterometallic MOFs is crucial to establish structure-function relationships.

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.

Trends in Siting of Metals in Heterometallic Nd-Yb Metal-Organic Frameworks and Molecular Crystals.

Several studies suggest that metal ordering within metal-organic frameworks (MOFs) is important for understanding how MOFs behave in relevant applications; however, these siting trends can be difficult to determine experimentally. To garner insight into the energetic driving forces that may lead to nonrandom ordering within heterometallic MOFs, we employ density functional theory (DFT) calculations on several bimetallic metal-organic crystals composed of Nd and Yb metal atoms. We also investigate the metal siting trends for a newly synthesized MOF.

Dramatic Enhancement of Rare-Earth Metal-Organic Framework Stability Via Metal Cluster Fluorination.

Rare-earth polynuclear metal-organic frameworks (RE-MOFs) have demonstrated high durability for caustic acid gas adsorption and separation based on gas adsorption to the metal clusters. The metal clusters in the RE-MOFs traditionally contain RE metals bound by μ-OH groups connected via organic linkers. Recent studies have suggested that these hydroxyl groups could be replaced by fluorine atoms during synthesis that includes a fluorine-containing modulator.

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.

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.

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.

Insights into the solvent-assisted degradation of organophosphorus compounds by a Zr-based metal-organic framework.

The degradation of a chemical warfare agent simulant using a catalytically active Zr-based metal-organic framework (MOF) as a function of different solvent systems was investigated. Complementary molecular modelling studies indicate that the differences in the degradation rates are related to the increasing size in the nucleophile, which hinders the rotation of the product molecule during degradation. Methanol was identified as an appropriate solvent for non-aqueous degradation applications and demonstrated to support the MOF-based destruction of both sarin and soman.

Spectroscopically Resolved Binding Sites for the Adsorption of Sarin Gas in a Metal-Organic Framework: Insights beyond Lewis Acidity.

Here we report molecular level details regarding the adsorption of sarin (GB) gas in a prototypical zirconium-based metal-organic framework (MOF, UiO-66). By combining predictive modeling and experimental spectroscopic techniques, we unambiguously identify several unique bindings sites within the MOF, using the P═O stretch frequency of GB as a probe. Remarkable agreement between predicted and experimental IR spectrum is demonstrated.

Distinguishing between bulk and edge hydroxyl vibrational properties of 2 : 1 phyllosilicates via deuteration.

Observation of vibrational properties of phyllosilicate edges via a combined molecular modeling and experimental approach was performed. Deuterium exchange was utilized to isolate edge vibrational modes from their internal counterparts. The appearance of a specific peak within the broader D2O band indicates the presence of deuteration on the edge surface, and this peak is confirmed with the simulated spectra.

Molecular Simulations of Hydrogen Bond Cluster Size and Reorientation Dynamics in Liquid and Glassy Azole Systems.

We simulated the dynamics of azole groups (pyrazole, imidazole, 1,2,3-triazole, 1,2,4-triazole, and tetrazole) as neat liquids and tethered via linkers to aliphatic backbones to determine how tethering and varying functional groups affect hydrogen bond networks and reorientation dynamics, both factors which are thought to influence proton conduction. We used the DL_Poly_2 molecular dynamics code with the GAFF force field to simulate tethered systems over the temperature range 200-900 K and the corresponding neat liquids under liquid state temperatures at standard pressure. We computed hydrogen bond cluster sizes; orientational order parameters; orientational correlation functions associated with functional groups, linkers, and backbones; time scales; and activation energies associated with orientational randomization.

Solute location in a nanoconfined liquid depends on charge distribution.

Nanostructured materials that can confine liquids have attracted increasing attention for their diverse properties and potential applications. Yet, significant gaps remain in our fundamental understanding of such nanoconfined liquids. Using replica exchange molecular dynamics simulations of a nanoscale, hydroxyl-terminated silica pore system, we determine how the locations explored by a coumarin 153 (C153) solute in ethanol depend on its charge distribution, which can be changed through a charge transfer electronic excitation.

Thermodynamic Driving Forces for Dye Molecule Position and Orientation in Nanoconfined Solvents.

The results of replica exchange molecular dynamics simulations of a coumarin 153 (C153) dye molecule dissolved in ethanol confined within a 2.4 nm hydrophilic amorphous silica pore are presented. The C153 dye position and orientation distributions provide insight into time-dependent fluorescence measurements in nanoconfined solvents as well as general features of chemistry in mesoporous materials.

Simulating Hydrogen-Bond Structure and Dynamics in Glassy Solids Composed of Imidazole Oligomers.

We simulated structural and dynamical properties of imidazoles tethered to aliphatic backbones to determine how chain length influences the competition between extended hydrogen-bond networks and imidazole reorientation dynamics. We performed molecular dynamics simulations on hypothetical solids using the GAFF Amber force field over the temperature range 300-800 K, for chain lengths varying from monomers to pentamers. We investigated the effect of heterogeneity by simulating monodisperse and polydisperse solids with the same average chain length.