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.].

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.

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.

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.

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.

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.

Combined Deep Learning and Classical Potential Approach for Modeling Diffusion in UiO-66.

Modeling of diffusion of adsorbates through porous materials with atomistic molecular dynamics (MD) can be a challenging task if the flexibility of the adsorbent needs to be included. This is because potentials need to be developed that accurately account for the motion of the adsorbent in response to the presence of adsorbate molecules. In this work, we show that it is possible to use accurate machine learning atomistic potentials for metal-organic frameworks in concert with classical potentials for adsorbates to accurately compute diffusivities though a hybrid potential approach. As a proof-of-concept, we have developed an accurate deep learning potential (DP) for UiO-66, a metal-organic framework, and used this DP to perform hybrid potential simulations, modeling diffusion of neon and xenon through the crystal. The adsorbate-adsorbate interactions were modeled with Lennard-Jones (LJ) potentials, the adsorbent-adsorbent interactions were described by the DP, and the adsorbent-adsorbate interactions used LJ cross-interactions. Thus, our hybrid potential allows for adsorbent-adsorbate interactions with classical potentials but models the response of the adsorbent to the presence of the adsorbate through near-DFT accuracy DPs. This hybrid approach does not require refitting the DP for new adsorbates. We calculated self-diffusion coefficients for Ne in UiO-66 from DFT-MD, our hybrid DP/LJ approach, and from two different classical potentials for UiO-66. Our DP/LJ results are in excellent agreement with DFT-MD. We modeled diffusion of Xe in UiO-66 with DP/LJ and a classical potential. Diffusion of Xe in UiO-66 is about a factor of 30 slower than that of Ne, so it is not computationally feasible to compute Xe diffusion with DFT-MD. Our hybrid DP-classical potential approach can be applied to other MOFs and other adsorbates, making it possible to use an accurate DP generated from DFT simulations of an empty adsorbent in concert with existing classical potentials for adsorbates to model adsorption and diffusion within the porous material, including adsorbate-induced changes to the framework.

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.

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.

In Situ Nuclear Magnetic Resonance Investigation of Molecular Adsorption and Kinetics in Metal-Organic Framework UiO-66.

Thermodynamic and kinetic properties of molecular adsorption and transport in metal-organic frameworks (MOFs) are crucially important for many applications, including gas adsorption, filtration, and remediation of harmful chemicals. Using the in situ 1H nuclear magnetic resonance (NMR) isotherm technique, we measured macroscopic thermodynamic and kinetic properties such as isotherms and rates of mass transfer while simultaneously obtaining microscopic information revealed by adsorbed molecules via NMR. Upon investigating isopropyl alcohol adsorption in MOF UiO-66 by in situ NMR, we obtained separate isotherms for molecules adsorbed at distinct environments exhibiting distinct NMR characteristics. A mechanistic view of the adsorption process is obtained by correlating such resolved isotherms with the cage structure effect on the nucleus-independent chemical shift, molecular dynamics such as the crowding effect at high loading levels, and the loading level dependence of the mass transfer rate as measured by NMR and elucidated by classical Monte Carlo simulations.

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.

H2/CO2 separations in multicomponent metal-adeninate MOFs with multiple chemically distinct pore environments.

Metal-organic frameworks constructed from multiple (≥3) components often exhibit dramatically increased structural complexity compared to their 2 component (1 metal, 1 linker) counterparts, such as multiple chemically unique pore environments and a plurality of diverse molecular diffusion pathways. This inherent complexity can be advantageous for gas separation applications. Here, we report two isoreticular multicomponent MOFs, bMOF-200 (4 components; Cu, Zn, adeninate, pyrazolate) and bMOF-201 (3 components; Zn, adeninate, pyrazolate). We describe their structures, which contain 3 unique interconnected pore environments, and we use Kohn-Sham density functional theory (DFT) along with the climbing image nudged elastic band (CI-NEB) method to predict potential H2/CO2 separation ability of bMOF-200. We examine the H2/CO2 separation performance using both column breakthrough and membrane permeation studies. bMOF-200 membranes exhibit a H2/CO2 separation factor of 7.9. The pore space of bMOF-201 is significantly different than bMOF-200, and one molecular diffusion pathway is occluded by coordinating charge-balancing formate and acetate anions. A consequence of this structural difference is reduced permeability to both H2 and CO2 and a significantly improved H2/CO2 separation factor of 22.2 compared to bMOF-200, which makes bMOF-201 membranes competitive with some of the best performing MOF membranes in terms of H2/CO2 separations.

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.

Toward Understanding the Kinetics of CO2 Capture on Sodium Carbonate.

Sodium carbonate (Na2CO3) has been widely studied as a promising candidate for CO2 capture from humid flue gas because of its low cost, high abundance, reusability, and moderate operating temperatures. However, the slow kinetics of CO2 capture on unmodified Na2CO3 make it an unacceptable choice for practical applications. If the reaction kinetics could be dramatically improved, then Na2CO3 could be a viable material for large-scale carbon capture applications. The first step to systematic improvement of kinetics is to understand the rate-limiting steps in the uncatalyzed system. We have therefore investigated the structural, mechanistic, and energetic properties of CO2 capture on the (001) and (-402) surfaces of Na2CO3 using density functional theory to identify the origin of the slow kinetics observed in experiments. We have identified reaction pathways for co-adsorbed CO2 and H2O that lead to bicarbonate formation on the (001) and (-402) surfaces having activation energies of 0.40 and 0.34 eV, respectively. We modeled surface carbonation reactions under conditions of high surface loading of water by performing ab initio molecular dynamics simulations at typical operating temperatures. Multiple reactions were observed on picosecond time scales. Our results indicate that the Na2CO3 carbonation reaction is not controlled by the kinetics of the reaction at the surface but is likely by diffusion limitations. We propose two possible scenarios that could result in diffusion control of the reaction rate.

Unraveling Anhydrous Proton Conduction in Hydroxygraphane.

We predict that graphane functionalized with hydroxyl groups, hydroxygraphane, can conduct protons in the complete absence of water, as shown from density functional theory calculations. Hydroxygraphane's anhydrous intrinsic proton conductivity results from the self-assembling two-dimensional network of hydrogen bonds on its surface. We show that the proton conduction occurs through a Grotthuss-like mechanism, as protons hop between neighboring hydroxyl groups, aided by their rotation. Our calculations predict that hydroxygraphane has a direct bandgap of 3.43 eV, a phonon dispersion spectrum with no instabilities, and a 2-D Young's modulus and Poisson's ratio stiffer than those for graphane-the parent material for hydroxygraphane. Hence, hydroxygraphane has the desired electronic and mechanical properties to make it a viable candidate for a proton exchange membrane material capable of operating under anhydrous or low-humidity conditions.

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.

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.

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.

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.

Development of a ReaxFF reactive force field for tetrabutylphosphonium glycinate/CO2 mixtures.

Carbon dioxide interacts with the ionic liquid tetrabutylphosphonium glycinate, [P(C4)4][Gly], through both physical and chemical absorption. We present a parametrization of the ReaxFF force field for this system that accounts for both chemical and physical interactions. The parametrization was developed from an extensive training set including periodic density functional theory (DFT) calculations of reaction pathways between CO2 and the anion [Gly](-) in the condensed phase, condensed-phase molecular dynamics (MD) configurations, gas-phase CO2-anion and CO2-cation interactions, and gas-phase cluster calculations for intra-ion interactions. The optimized ReaxFF parameters capture the essential features of both physical and chemical interactions between CO2 and [P(C4)4][Gly] as compared with experiments, van der Waals-corrected DFT calculations, or, in the case of physical interactions, classical force field calculations. The probability distributions of the distance between C (from CO2) and N (from the anion) and the CO2 bend angles calculated from MD simulations with the optimized ReaxFF force field are in good general agreement with those from DFT-based MD simulations. We predict that the density of CO2/[P(C4)4][Gly] mixtures increases with increasing CO2 concentration up to at least 50 mol % CO2. We attribute the significant increase in density to the small effective volume occupied by chemically bound CO2 in the mixture. The predicted increase in density may be tested experimentally.