Resonance Raman intensity analysis of photoactive metal-organic frameworks.

Metal-organic frameworks (MOFs) are promising candidate materials for photo-driven processes. Their crystalline and tunable structure makes them well-suited for placing photoactive molecules at controlled distances and orientations that support processes such as light harvesting and photocatalysis. In order to optimize their performance, it is important to understand how these molecules evolve shortly after photoexcitation. Here, we use resonance Raman intensity analysis (RRIA) to quantify the excited state nuclear distortions of four modified UiO-68 MOFs. We find that stretching vibrations localized on the central ring within the terphenyl linker are most distorted upon interaction with light. We use a combined computational and experimental approach to create a picture of the early excited state structure of the MOFs upon photoactivation. Overall, we show that RRIA is an effective method to probe the excited state structure of photoactive MOFs and can guide the synthesis and optimization of photoactive designs.

Leveraging Ligand Steric Demand to Control Ligand Exchange and Domain Composition in Stratified Metal-Organic Frameworks.

Incorporating diverse components into metal-organic frameworks (MOFs) can expand their scope of properties and applications. Stratified MOFs (sMOFs) consist of compositionally unique concentric domains (strata), offering unprecedented complexity through partitioning of structural and functional components. However, the labile nature ofmetal-ligand coordination handicaps achieving compositionally-distinct domains due to ligand exchange reactions occurring concurrently with secondary strata growth. To achieve complex sMOF compositions, characterizing and controlling the competing processes of new strata growth and ligand exchange are vital. This work systematicallyexamines controlling ligand exchange in UiO-67 sMOFs by tuning ligand sterics. We present quantitative methods for assessing and visualizing the outcomes of strata growth and ligand exchange that rely on high-angle annular dark-field images and elemental mapping via scanning transmission electron microscopy-energy dispersive X-ray spectroscopy. In addition, we leverage ligand sterics to create 'blocking layers' that minimize ligand exchange between strata which are particularly susceptible to ligand exchange and inter-strata ligand mixing. Finally, we evaluate strata compositional integrity in various solvents and find that sMOFs can maintain their compositions for >12 months in some cases.Collectively, these studies and methods enhance understanding and control over ligand placement in multi-domain MOFs, factors that underscore careful tunning of properties and function.

How Do Self-Interaction Errors Associated with Stretched Bonds Affect Barrier Height Predictions?

Density functional theory (DFT) suffers from self-interaction errors (SIEs) that generally result in the underestimation of chemical reaction barrier heights. This is commonly attributed to the tendency of density functional approximations to overstabilize delocalized densities that typically occur in the stretched bonds of transition state structures. The Perdew-Zunger self-interaction correction (PZSIC) and locally scaled self-interaction correction (LSIC) improve the prediction of barrier heights of chemical reactions, with LSIC giving better accuracy than PZSIC on average. These methods employ an orbital-by-orbital correction scheme to remove the one-electron SIE. In the context of barrier heights, this allows an analysis of how the self-interaction correction (SIC) for each orbital contributes to the calculated barriers using Fermi-Löwdin orbitals (FLOs). We hypothesize that the SIC contribution to the reaction barrier comes mainly from a limited number of orbitals that are directly involved in bond-breaking and bond-making in the reaction transition state. We call these participant orbitals (POs), in contrast to spectator orbitals (SOs) which are not directly involved in changes to the bonding. Our hypothesis is that ΔETotalSIC ≈ ΔEPOSIC, where ΔETotalSIC is the difference in the SIC corrections for the reactants or products and the transition state. We test this hypothesis for the reaction barriers of the BH76 benchmark set of reactions. We find that the stretched-bond orbitals indeed make the largest individual SIC contributions to the barriers. These contributions increase the barrier heights relative to LSDA, which underpredicts the barrier. However, the full stretched-bond hypothesis does not hold in all cases for either PZSIC or LSIC. There are many cases where the total SIC contribution from the SOs is significant and cannot be ignored. The size of the SIC contribution to the barrier height is a key indicator. A large SIC correction is correlated to a large LSDA error in the barrier, showing that PZSIC properly gives larger corrections when corrections are needed most. A comparison of the performance of PZSIC and LSIC shows that the two methods have similar accuracy for reactions with large LSDA errors, but LSIC is clearly better for reactions with small errors. We trace this to an improved description of reaction energies in LSIC.

Use of FLOSIC for understanding anion-solvent interactions.

An Achille's heel of lower-rung density-functional approximations is that the highest-occupied-molecular-orbital energy levels of anions, known to be stable or metastable in nature, are often found to be positive in the worst case or above the lowest-unoccupied-molecular-orbital levels on neighboring complexes that are not expected to accept charge. A trianionic example, [Cr(C2O4)3]3-, is of interest for constraining models linking Cr isotope ratios in rock samples to oxygen levels in Earth's atmosphere over geological timescales. Here we describe how crowd sourcing can be used to carry out self-consistent Fermi-Löwdin-Orbital-Self-Interaction corrected calculations (FLOSIC) on this trianion in solution. The calculations give a physically correct description of the electronic structure of the trianion and water. In contrast, uncorrected local density approximation (LDA) calculations result in approximately half of the anion charge being transferred to the water bath due to the effects of self-interaction error. Use of group-theory and the intrinsic sparsity of the theory enables calculations roughly 125 times faster than our initial implementation in the large N limit reached here. By integrating charge density densities and Coulomb potentials over regions of space and analyzing core-level shifts of the Cr and O atoms as a function of position and functional, we unambiguously show that FLOSIC, relative to LDA, reverses incorrect solute-solvent charge transfer in the trianion-water complex. In comparison to other functionals investigated herein, including Hartree-Fock and the local density approximation, the FLOSIC Cr 1s eigenvalues provide the best agreement with experimental core ionization energies.

Study of self-interaction-errors in barrier heights using locally scaled and Perdew-Zunger self-interaction methods.

We study the effect of self-interaction errors on the barrier heights of chemical reactions. For this purpose, we use the well-known Perdew-Zunger self-interaction-correction (PZSIC) [J. P. Perdew and A. Zunger, Phys. Rev. B 23, 5048 (1981)] as well as two variations of the recently developed, locally scaled self-interaction correction (LSIC) [Zope et al., J. Chem. Phys. 151, 214108 (2019)] to study the barrier heights of the BH76 benchmark dataset. Our results show that both PZSIC and especially the LSIC methods improve the barrier heights relative to the local density approximation (LDA). The version of LSIC that uses the iso-orbital indicator z as a scaling factor gives a more consistent improvement than an alternative version that uses an orbital-dependent factor w based on the ratio of orbital densities to the total electron density. We show that LDA energies evaluated using the self-consistent and self-interaction-free PZSIC densities can be used to assess density-driven errors. The LDA reaction barrier errors for the BH76 set are found to contain significant density-driven errors for all types of reactions contained in the set, but the corrections due to adding SIC to the functional are much larger than those stemming from the density for the hydrogen transfer reactions and of roughly equal size for the non-hydrogen transfer reactions.

Fermi-Löwdin orbital self-interaction correction of adsorption energies on transition metal ions.

Density functional theory (DFT)-based descriptions of the adsorption of small molecules on transition metal ions are prone to self-interaction errors. Here, we show that such errors lead to a large over-estimation of adsorption energies of small molecules on Cu+, Zn+, Zn2+, and Mn+ in local spin density approximation (LSDA) and Perdew, Burke, Ernzerhof (PBE) generalized gradient approximation calculations compared to reference values computed using the coupled-cluster with single, doubles, and perturbative triple excitations method. These errors are significantly reduced by removing self-interaction using the Perdew-Zunger self-interaction correction (PZ-SIC) in the Fermi-Löwdin Orbital (FLO) SIC framework. In the case of FLO-PBE, typical errors are reduced to less than 0.1 eV. Analysis of the results using DFT energies evaluated on self-interaction-corrected densities [DFT(@FLO)] indicates that the density-driven contributions to the FLO-DFT adsorption energy corrections are roughly the same size in DFT = LSDA and PBE, but the total corrections due to removing self-interaction are larger in LSDA.

Application of Self-Interaction Corrected Density Functional Theory to Early, Middle, and Late Transition States.

Density functional theory (DFT)-based methods often significantly underpredict chemical reaction barriers compared with experiments because of the tendency of DFT to overstabilize transition states with stretched bonds due to the impact of unphysical electron self-interaction. However, many reactions have early or late transition states where the transition state geometry closely resembles the reactants or products, respectively. The role of self-interaction in those cases is not known. Here we compare the performance of DFT with and without self-interaction correction (SIC) for describing the hydrogenation of CO and CO2 catalyzed by a Lewis acid-base pair incorporated onto an aromatic cluster, using CCSD(T) results for reference. The three elementary steps in these reactions consist of an early, a middle, and a late transition. Our results show that the Perdew-Zunger SIC (PZ-SIC), implemented in the Fermi-Löwdin orbital SIC (FLO-SIC) approach, qualitatively improves the description of the forward and reverse reaction barriers relative to uncorrected DFT for the middle transition but not the early or late transitions. By contrast, the local scaling SIC (LSIC) method, also implemented in the FLO-SIC framework, significantly improves the calculated barriers over DFT and PZ-SIC in all but one case. The results also show how the FLO-SIC approach can provide insight into the bonding in aromatic systems.

Designing Open Metal Sites in Metal-Organic Frameworks for Paraffin/Olefin Separations.

Incorporating open metal sites (OMS) into metal-organic frameworks allows design of well-defined binding sites for selective molecular adsorption, which has a profound impact on catalysis and separations. We demonstrate that Cu(I) sites incorporated into MFU-4l preferentially adsorb olefins over paraffins. Density functional theory (DFT) calculations show that the OMS are independent, with no dependence of binding energy on olefin loading up to one olefin per Cu(I). Experimentally, increasing Cu(I) loading increased olefin uptake without affecting the binding energy, as predicted by DFT and confirmed by temperature-programmed desorption. The potential of this material for olefin/paraffin separation under ambient conditions was investigated by gas adsorption and column breakthrough experiments for an equimolar ratio of olefin/paraffin. High-grade propylene and ethylene (>99.999%) can be generated using temperature-concentration swing recycling from a Cu(I)-MFU-4l packed column with no measurable paraffin breakthrough.

Shrinking Self-Interaction Errors with the Fermi-Löwdin Orbital Self-Interaction-Corrected Density Functional Approximation.

The self-interaction error (SIE) is one of the major drawbacks of practical exchange-correlation functionals for Kohn-Sham density functional theory. Despite this, the use of methods that explicitly remove SIE from approximate density functionals is scarce in the literature due to their relatively high computational cost and lack of consistent improvement over standard modern functionals. In this article we assess the performance of a novel approach recently proposed by Pederson, Ruzsinszky, and Perdew [ J. Chem. Phys. 2014, 140, 121103] for performing self-interaction free calculations in density functional theory based on Fermi orbitals. To this end, we employ test sets consisting of reaction energies that are considered particularly sensitive to SIE. We found that the parameter-free Fermi-Löwdin orbital self-interaction correction method combined with the standard local spin density approximation (LSDA) and Perdew-Burke-Ernzerhof (PBE) functionals gives a much better estimate of reaction energies compared to their parent LSDA and PBE functionals for most of the reactions in these two sets. They also perform on par with the global PBE0 and range-separated LC-ωPBE hybrids, which partially eliminate the SIE by including Hartree-Fock exchange. This shows the potential of the Fermi-Löwdin orbital self-interaction correction (FLOSIC) method for practical density functional calculations without SIE.

Facile Anhydrous Proton Transport on Hydroxyl Functionalized Graphane.

Graphane functionalized with hydroxyl groups is shown to rapidly conduct protons under anhydrous conditions through a contiguous network of hydrogen bonds. Density functional theory calculations predict remarkably low barriers to diffusion of protons along a 1D chain of surface hydroxyls. Diffusion is controlled by the local rotation of hydroxyl groups, a mechanism that is very different from that found in 1D water wires in confined nanopores or in bulk water. The proton mean square displacement in the 1D chain was observed to follow Fickian diffusion rather than the expected single-file mobility. A charge analysis reveals that the charge on the proton is essentially equally shared by all hydrogens bound to oxygens, effectively delocalizing the proton.

Publisher's Note: Facile Anhydrous Proton Transport on Hydroxyl Functionalized Graphane [Phys. Rev. Lett. 118, 186101 (2017)].

This corrects the article DOI: 10.1103/PhysRevLett.118.186101.

Adsorption and Diffusion of Fluids in Defective Carbon Nanotubes: Insights from Molecular Simulations.

Single-walled carbon nanotubes (SWNTs) have been shown from both simulations and experiments to have remarkably low resistance to gas and liquid transport. This has been attributed to the remarkably smooth interior surface of pristine SWNTs. However, real SWNTs are known to have various defects that depend on the synthesis method and procedure used to activate the SWNTs. In this paper, we study adsorption and transport properties of atomic and molecular fluids in SWNTs having vacancy point defects. We construct models of defective nanotubes that have either unrelaxed defects, where the overall structure of the SWNT is not changed, or reconstructed defects, where the bonding topology and therefore the shape of the SWNT is allowed to change. Furthermore, we include partial atomic charges on the SWNT carbon atoms due to the reconstructed defects. We consider adsorption and diffusion of Ar atoms and CO2 and H2O molecules as examples of a noble gas, a linear quadrupolar fluid, and a polar fluid. Adsorption isotherms were found to be fairly insensitive to the defects, even for the case of water in the charged, reconstructed SWNT. We have computed both the self-diffusivities and corrected diffusivities (which are directly related to the transport diffusivities) for each of these fluids. In general, we found that at zero loading that defects can dramatically reduce the self- and corrected diffusivities. However, at high, liquidlike loadings, the self-diffusion coefficients for pristine and defective nanotubes are very similar, indicating that fluid-fluid collisions dominate the dynamics over the fluid-SWNT collisions. In contrast, the corrected diffusion coefficients can be more than an order of magnitude lower for water in defective SWNTs. This dramatic decrease in the transport diffusion is due to the formation of an ordered structure of water, which forms around a local defect site. It is therefore important to properly characterize the level and types of defects when accurate transport diffusivities are needed.

Accurate amorphous silica surface models from first-principles thermodynamics of surface dehydroxylation.

Accurate atomically detailed models of amorphous materials have been elusive to-date due to limitations in both experimental data and computational methods. We present an approach for constructing atomistic models of amorphous silica surfaces encountered in many industrial applications (such as catalytic support materials). We have used a combination of classical molecular modeling and density functional theory calculations to develop models having predictive capabilities. Our approach provides accurate surface models for a range of temperatures as measured by the thermodynamics of surface dehydroxylation. We find that a surprisingly small model of an amorphous silica surface can accurately represent the physics and chemistry of real surfaces as demonstrated by direct experimental validation using macroscopic measurements of the silanol number and type as a function of temperature. Beyond accurately predicting the experimentally observed trends in silanol numbers and types, the model also allows new insights into the dehydroxylation of amorphous silica surfaces. Our formalism is transferrable and provides an approach to generating accurate models of other amorphous materials.

A first-principles study of lithium-decorated hybrid boron nitride and graphene domains for hydrogen storage.

First-principles calculations are performed to investigate the adsorption of hydrogen onto Li-decorated hybrid boron nitride and graphene domains of (BN)(x)C(1-x) complexes with x = 1, 0.25, 0.5, 0.75, 0, and B0.125C0.875. The most stable adsorption sites for the nth hydrogen molecule in the lithium-decorated (BN)(x)C(1-x) complexes are systematically discussed. The most stable adsorption sites were affected by the charge localization, and the hydrogen molecules were favorably located above the C-C bonds beside the Li atom. The results show that the nitrogen atoms in the substrate planes could increase the hybridization between the 2p orbitals of Li and the orbitals of H2. The results revealed that the (BN)(x)C(1-x) complexes not only have good thermal stability but they also exhibit a high hydrogen storage of 8.7% because of their dehydrogenation ability.

Correction to "Ligand Chromophore Modification Approach for Predictive Incremental Tuning of Metal-Organic Framework Color".

[This corrects the article DOI: 10.1021/acs.chemmater.3c01603.].

Experimental and theoretical comparison of gas desorption energies on metallic and semiconducting single-walled carbon nanotubes.

Single-walled carbon nanotubes (SWNTs) exhibit high surface areas and precisely defined pores, making them potentially useful materials for gas adsorption and purification. A thorough understanding of the interactions between adsorbates and SWNTs is therefore critical to predicting adsorption isotherms and selectivities. Metallic (M-) and semiconducting (S-) SWNTs have extremely different polarizabilities that might be expected to significantly affect the adsorption energies of molecules. We experimentally and theoretically show that this expectation is contradicted, for both a long chain molecule (n-heptane) and atoms (Ar, Kr, and Xe). Temperature-programmed desorption experiments are combined with van der Waals corrected density functional theory, examining adsorption on interior and exterior sites of the SWNTs. Our calculations show a clear dependence of the adsorption energy on nanotube diameter but not on whether the tubes are conducting or insulating. We find no significant experimental or theoretical difference in adsorption energies for molecules adsorbed on M- and S-SWNTs having the same diameter. Hence, we conclude that the differences in polarizabilities between M- and S-SWNTs have a negligible influence on gas adsorption for spherical molecules as well as for highly anisotropic molecules such as n-heptane. We expect this conclusion to apply to all types of adsorbed molecules where van der Waals interactions govern the molecular interaction with the SWNT.

Is there a difference in van der Waals interactions between rare gas atoms adsorbed on metallic and semiconducting single-walled carbon nanotubes?

The differences in the polarizabilities of metallic (M) and semiconducting (S) single-walled carbon nanotubes (SWNTs) might give rise to differences in adsorption potentials. We show from experiments and van der Waals--corrected density functional theory that the binding energies of Xe adsorbed on M- and S-SWNTs are nearly identical. Temperature programed desorption experiments of Xe on purified M- and S-SWNTs give similar peak temperatures, indicating that desorption kinetics and binding energies are independent of the type of SWNT. Binding energies computed from vdW-corrected density functional theory are in good agreement with experiments.

Machine Learning Electron Density Prediction Using Weighted Smooth Overlap of Atomic Positions.

Having access to accurate electron densities in chemical systems, especially for dynamical systems involving chemical reactions, ion transport, and other charge transfer processes, is crucial for numerous applications in materials chemistry. Traditional methods for computationally predicting electron density data for such systems include quantum mechanical (QM) techniques, such as density functional theory. However, poor scaling of these QM methods restricts their use to relatively small system sizes and short dynamic time scales. To overcome this limitation, we have developed a deep neural network machine learning formalism, which we call deep charge density prediction (DeepCDP), for predicting charge densities by only using atomic positions for molecules and condensed phase (periodic) systems. Our method uses the weighted smooth overlap of atomic positions to fingerprint environments on a grid-point basis and map it to electron density data generated from QM simulations. We trained models for bulk systems of copper, LiF, and silicon; for a molecular system, water; and for two-dimensional charged and uncharged systems, hydroxyl-functionalized graphane, with and without an added proton. We showed that DeepCDP achieves prediction R2 values greater than 0.99 and mean squared error values on the order of 10-5e2 Å-6 for most systems. DeepCDP scales linearly with system size, is highly parallelizable, and is capable of accurately predicting the excess charge in protonated hydroxyl-functionalized graphane. We demonstrate how DeepCDP can be used to accurately track the location of charges (protons) by computing electron densities at a few selected grid points in the materials, thus significantly reducing the computational cost. We also show that our models can be transferable, allowing prediction of electron densities for systems on which it has not been trained but that contain a subset of atomic species on which it has been trained. Our approach can be used to develop models that span different chemical systems and train them for the study of large-scale charge transport and chemical reactions.

Calculation of Self, Corrected, and Transport Diffusivities of Isopropyl Alcohol in UiO-66.

The UiO-6x family of metal-organic frameworks has been extensively studied for applications in chemical warfare agent (CWA) capture and destruction. An understanding of intrinsic transport phenomena, such as diffusion, is key to understanding experimental results and designing effective materials for CWA capture. However, the relatively large size of CWAs and their simulants makes diffusion in the small-pored pristine UiO-66 very slow and hence impractical to study directly with direct molecular simulations because of the time scales required. We used isopropanol (IPA) as a surrogate for CWAs to investigate the fundamental diffusion mechanisms of a polar molecule within pristine UiO-66. IPA can form hydrogen bonds with the µ3-OH groups bound to the metal oxide clusters in UiO-66, similar to some CWAs, and can be studied by direct molecular dynamics simulations. We report self, corrected, and transport diffusivities of IPA in pristine UiO-66 as a function of loading. Our calculations highlight the importance of the accurate modeling of the hydrogen bonding interactions on diffusivities, with about an order of magnitude decrease in diffusion coefficients when the hydrogen bonding between IPA and the µ3-OH groups is included. We found that a fraction of the IPA molecules have very low mobility during the course of a simulation, while a small fraction are highly mobile, exhibiting mean square displacements far greater than the ensemble average.

In Silico Demonstration of Fast Anhydrous Proton Conduction on Graphanol.

Development of new materials capable of conducting protons in the absence of water is crucial for improving the performance, reducing the cost, and extending the operating conditions for proton exchange membrane fuel cells. We present detailed atomistic simulations showing that graphanol (hydroxylated graphane) will conduct protons anhydrously with very low diffusion barriers. We developed a deep learning potential (DP) for graphanol that has near-density functional theory accuracy but requires a very small fraction of the computational cost. We used our DP to calculate proton self-diffusion coefficients as a function of temperature, to estimate the overall barrier to proton diffusion, and to characterize the impact of thermal fluctuations as a function of system size. We propose and test a detailed mechanism for proton conduction on the surface of graphanol. We show that protons can rapidly hop along Grotthuss chains containing several hydroxyl groups aligned such that hydrogen bonds allow for conduction of protons forward and backward along the chain without hydroxyl group rotation. Long-range proton transport only takes place as new Grotthuss chains are formed by rotation of one or more hydroxyl groups in the chain. Thus, the overall diffusion barrier consists of a convolution of the intrinsic proton hopping barrier and the intrinsic hydroxyl rotation barrier. Our results provide a set of design rules for developing new anhydrous proton conducting membranes with even lower diffusion barriers.