Chemically Meaningful Atomic Charges That Reproduce the Electrostatic Potential in Periodic and Nonperiodic Materials

How Grain Boundaries and Interfacial Electrostatic Interactions Modulate Water Desalination via Nanoporous Hexagonal Boron Nitride

To fulfill the increasing demand for drinking water, researchers are currently exploring nanoporous two-dimensional materials, such as hexagonal boron nitride (hBN), as potential desalination membranes. A prominent, yet unsolved challenge is to understand how such membranes will perform in the presence of defects or surface charge in the membrane material. In this work, we study the effect of grain boundaries (GBs) and interfacial electrostatic interactions on the desalination performance of bicrystalline nanoporous hBN using classical molecular dynamics simulations supported by quantum-mechanical density functional theory (DFT) calculations. We investigate three different nanoporous bicrystalline hBN configurations, with symmetric tilt GBs having misorientation angles of 13.2, 21.8, and 32.2°. Using lattice dynamics calculations, we find that grain boundaries alter the areas and shapes of nanopores in bicrystalline hBN, as compared to the nanopores in monocrystalline hBN. We observe that, although bicrystalline nanoporous hBN with a misorientation angle of 13.2° shows an improved water flow rate by ∼30%, it demonstrates reduced Na⁺ ion rejection by ∼6%, as compared to monocrystalline hBN. We also uncover the role of the nanopore shape in water desalination, finding that more elongated pores with smaller sizes (in 21.8- and 32.2°-misoriented bicrystalline hBN) can match water permeation through less elongated pores of slightly larger sizes, with a concomitant ∼3-4% decrease in Na⁺ rejection. Simulations also predict that the water flow rate is significantly affected by interfacial electrostatic interactions. Indeed, the water flow rate is the highest when altered partial charges on B and N atoms were determined using DFT calculations, as compared to when no partial charges or bulk partial charges (i.e., charged hBN) were considered. Overall, our work on water/ion transport through nanopores in bicrystalline hBN indicates that the presence of GBs and surface charge can lead, respectively, to a decrease in the ion rejection and water permeation performance of hBN membranes.

Using atomic charges to model molecular polarization

We review different models for introducing electric polarization in force fields, with special focus on methods where polarization is modelled at the atomic charge level. While electric polarization has been included in several force fields, the common approach has been to focus on atomic dipole polarizability. Several approaches allow modelling electric polarization by using charge-flow between charge sites instead, but this has been less exploited, despite that atomic charges and charge-flow is expected to be more important than atomic dipoles and dipole polarizability. A number of challenges are required to be solved for charge-flow models to be incorporated into polarizable force fields, for example how to parameterize the models and how to make them computational efficient.

Benzene and triazine-based porous organic polymers with azo, azoxy and azodioxy linkages: a computational study

Computational study of azoxy and azodioxy-based 2D layered structures revealed their potential for the selective binding of CO2 over N2.

Apples to apples comparison of standardized to unstandardized principal component analysis of methods that assign partial atomic charges in molecules

Articles by Cho et al. (ChemPhysChem, 2020, 21, 688–696) and Manz (RSC Adv., 2020, 10, 44121–44148) performed unstandardized and standardized, respectively, principal component analysis (PCA) to study atomic charge assignment methods for molecular systems. Both articles used subsets of atomic charges computed by Cho et al.; however, the data subsets employed were not strictly identical. Herein, an element by element analysis of this dataset is first performed to compare the spread of charge values across individual chemical elements and charge assignment methods. This reveals an underlying problem with the reported Becke partial atomic charges in this dataset. Due to their unphysical values, these Becke charges were not included in the subsequent PCA. Standardized and unstandardized PCA are performed across two datasets: (i) 19 charge assignment methods having a complete basis set limit and (ii) all 25 charge assignment methods (excluding Becke) for which Cho et al. computed atomic charges. The dataset contained ∼2000 molecules having a total of 29 907 atoms in materials. The following five methods (listed here in alphabetical order) showed the greatest correlation to the first principal component in standardized and unstandardized PCA: DDEC6, Hirshfeld-I, ISA, MBIS, and MBSBickelhaupt (note: MBSBickelhaupt does not appear in the 19 methods dataset). For standardized PCA, the DDEC6 method ranked first followed closely by MBIS. For unstandardized PCA, Hirshfeld-I (19 methods) or MBSBickelhaupt (25 methods) ranked first followed by DDEC6 in second place (both 19 and 25 methods).

Standardized and unstandardized principal component analyses are directly compared for a dataset of ∼2000 molecules across various charge assignment methods.

Incorporating Flexibility Effects into Metal-Organic Framework Adsorption Simulations Using Different Models

High-throughput calculations based on molecular simulations to predict the adsorption of molecules inside metal-organic frameworks (MOFs) have become a useful complement to experimental efforts to identify promising adsorbents for chemical separations and storage. For computational convenience, all existing efforts of this kind have relied on simulations in which the MOF is approximated as rigid. In this paper, we use extensive adsorption-relaxation simulations that fully include MOF flexibility effects to explore the validity of the rigid framework approximation. We also examine the accuracy of several approximate methods to incorporate framework flexibility that are more computationally efficient than adsorption-relaxation calculations. We first benchmark various models of MOF flexibility for four MOFs with well-established CO₂ experimental consensus isotherms. We then consider a range of adsorption properties, including Henry's constants, nondilute loadings, and adsorption selectivity, for seven adsorbates in 15 MOFs randomly selected from the CoRE MOF database. Our results indicate that in many MOFs adsorption-relaxation simulations are necessary to make quantitative predictions of adsorption, particularly for adsorption at dilute concentrations, although more standard calculations based on rigid structures can provide useful information. Finally, we investigate whether a correlation exists between the elastic properties of empty MOFs and the importance of including framework flexibility in making accurate predictions of molecular adsorption. Our results did not identify a simple correlation of this type.

Crystal structure of silver pentazolates AgN5 and AgN6

Silver pentazolate, a high energy density compound containing the cyclo-N₅^- anion, has recently been synthesized under ambient conditions. However, due to high sensitivity to irradiation, its crystal structure has not been determined. In this work, silver-nitrogen crystalline compounds under ambient conditions and at high pressures, up to 100 GPa, are predicted and characterized by performing first-principles evolutionary crystal structure searching with variable stoichiometry. It is found that newly discovered AgN₅ and AgN₆ are the only thermodynamically stable silver-nitrogen compounds at pressures between 42 and 80 GPa. In contrast to AgN₅, the pentazolate AgN₆ compound contains N₂ diatomic molecules in addition to cyclo-N₅^-. These AgN₅ and AgN₆ crystals are metastable under ambient conditions with positive formation enthalpies of 54.95 kJ mol^-1 and 46.24 kJ mol^-1, respectively. The underlying cause of the stability of cyclo-N₅^- silver pentazolates is the enhanced aromaticity enabled by the charge transfer from silver atoms to nitrogen rings. To aid in the experimental identification of these materials, calculated Raman spectra are reported at ambient pressure: the frequencies of N₅^- vibrational modes of AgN₅ are in good agreement with those measured in the experiment.

Identifying the Critical Surface Descriptors for the Negative Slopes in the Adsorption Energy Scaling Relationships via Density Functional Theory and Compressed Sensing

Adsorption energy scaling relationships have progressed beyond their original form, which was primarily focused on optimizing catalytic sites and lowering computational costs in simulations. The recent rise in interest in adsorption energy scaling relations is to investigate surfaces other than transition metals (TMs) as well as interactions involving complex compounds. In this work, we report our extensive study on the scaling relation (SR) between oxygen (O), with elements of neighboring groups such as boron (B), aluminum (Al), carbon (C), silicon (Si), nitrogen (N), phosphorus (P), and fluorine (F) on magnetic bimetallic surfaces. We observed that only O versus N and F seems to have a positive slope; the other slopes are negative. We present new theoretical model in terms of multiple surface descriptors using density functional theory and compressed sensing, whereas the original scaling theory was based on a single adsorbate descriptor: adsorbate valency.

Modulating Water Slip Using Atomic-Scale Defects: Friction on Realistic Hexagonal Boron Nitride Surfaces

Atomic-scale defects are ubiquitous in nanomaterials, yet their role in modulating fluid flow is inadequately understood. Hexagonal boron nitride (hBN) is an important two-dimensional material with applications in desalination and osmotic power. Although pristine hBN offers higher friction to the flow of water than graphene, we show here that certain defects can enhance water slippage on hBN. Using classical molecular dynamics simulations assisted by quantum-mechanical density functional theory, we compute the friction coefficient of water on hBN containing various vacancies (B, N, BN, B₂N, and B₃N) and the Stone-Wales defect. By investigating two defect concentrations, we obtain friction coefficients ranging from 0.4 to 2.6 times that of pristine hBN, leading to a maximum water slip length of 18.1 nm on hBN with a N vacancy or a Stone-Wales defect. Our work informs the use of defects to tune water flow and reveals defective hBN as an alternative high-slip surface to graphene.

Protein C-GeM: A Coarse-Grained Electron Model for Fast and Accurate Protein Electrostatics Prediction

The electrostatic potential (ESP) is a powerful property for understanding and predicting electrostatic charge distributions that drive interactions between molecules. In this study, we compare various charge partitioning schemes including fitted charges, density-based quantum mechanical (QM) partitioning schemes, charge equilibration methods, and our recently introduced coarse-grained electron model, C-GeM, to describe the ESP for protein systems. When benchmarked against high quality density functional theory calculations of the ESP for tripeptides and the crambin protein, we find that the C-GeM model is of comparable accuracy to ab initio charge partitioning methods, but with orders of magnitude improvement in computational efficiency since it does not require either the electron density or the electrostatic potential as input.

Efficient evaluation of electrostatic potential with computerized optimized code

The evaluation of molecular electrostatic potential (ESP) is a performance bottleneck for many computational chemical tasks like restrained ESP charge fitting or quantum mechanics/molecular mechanics simulations. In this paper, an efficient algorithm for the evaluation of ESP is proposed. It regroups the expression in terms of primitive Gaussian type orbitals (GTOs) with identical angular momentum types and nuclei centers. Each term is calculated using a computerized optimized code. This algorithm was integrated into the wavefunction analysis program Multiwfn and was tested on several large systems. In the cases of dopamine and remdesivir, the performance of this algorithm was comparable to or better than some popular state-of-the-art codes. For meta1-organic framework-5, where the number of GTOs and ESP points is 4840 and 259 262, respectively, our code could finish the evaluation in 1874 seconds on ordinary hardware. It also exhibits good parallelization scaling. The source code of this algorithm is freely available and can become a useful tool for computational chemists.

Performance-Based Screening of Porous Materials for Carbon Capture

Computational screening methods have changed the way new materials and processes are discovered and designed. For adsorption-based gas separations and carbon capture, recent efforts have been directed toward the development of multiscale and performance-based screening workflows where we can go from the atomistic structure of an adsorbent to its equilibrium and transport properties at different scales, and eventually to its separation performance at the process level. The objective of this work is to review the current status of this new approach, discuss its potential and impact on the field of materials screening, and highlight the challenges that limit its application. We compile and introduce all the elements required for the development, implementation, and operation of multiscale workflows, hence providing a useful practical guide and a comprehensive source of reference to the scientific communities who work in this area. Our review includes information about available materials databases, state-of-the-art molecular simulation and process modeling tools, and a complete catalogue of data and parameters that are required at each stage of the multiscale screening. We thoroughly discuss the challenges associated with data availability, consistency of the models, and reproducibility of the data and, finally, propose new directions for the future of the field.

Systematic optimization of a fragment-based force field against experimental pure-liquid properties considering large compound families: application to oxygen and nitrogen compounds

The CombiFF approach is a workflow for the automated refinement of force-field parameters against experimental condensed-phase data, considering entire classes of organic molecules constructed using a fragment library via combinatorial isomer enumeration. One peculiarity of this approach is that it relies on an electronegativity-equalization scheme to account for induction effects within molecules, with values of the atomic hardness and electronegativity as electrostatic parameters, rather than the partial charges themselves. In a previous article [M. P. Oliveira, M. Andrey, S. R. Rieder, L. Kern, D. F. Hahn, S. Riniker, B. A. C. Horta and P. H. Hünenberger, J. Chem. Theory. Comput. 2020, 16, 7525], CombiFF was introduced and applied to calibrate a GROMOS-compatible united-atom force field for the saturated acyclic (halo-)alkane family. Here, this scheme is employed for the construction of a corresponding force field for saturated acyclic compounds encompassing eight common chemical functional groups involving oxygen and/or nitrogen atoms, namely: ether, aldehyde, ketone, ester, alcohol, carboxylic acid, amine, and amide. Monofunctional as well as homo-polyfunctional compounds are considered. A total of 1712 experimental liquid densities ρliq and vaporization enthalpies ΔHvap concerning 1175 molecules are used for the calibration (339 molecules) and validation (836 molecules) of the 102 non-bonded interaction parameters of the force field. Using initial parameter values based on the GROMOS 2016H66 parameter set, convergence is reached after five iterations. Given access to one processor per simulated system, this operation only requires a few days of wall-clock computing time. After optimization, the root-mean-square deviations from experiment are 29.9 (22.4) kg m-3 for ρliq and 4.1 (5.5) kJ mol-1 for ΔHvap for the calibration (validation) set. Thus, a very good level of agreement with experiment is achieved in terms of these two properties, although the errors are inhomogeneously distributed across the different chemical functional groups.

Recent advances in simulating gas permeation through MOF membranes

In the last two decades, metal organic frameworks (MOFs) have gained increasing attention in membrane-based gas separations due to their tunable structural properties. Computational methods play a critical role in providing molecular-level information about the membrane properties and identifying the most promising MOF membranes for various gas separations. In this review, we discuss the current state-of-the-art in molecular modeling methods to simulate gas permeation through MOF membranes and review the recent advancements. We finally address current opportunities and challenges of simulating gas permeation through MOF membranes to guide the development of high-performance MOF membranes in the future.

Zr-MOFs for CF4/CH4, CH4/H2, and CH4/N2 separation: towards the goal of discovering stable and effective adsorbents

Zirconium metal-organic frameworks (MOFs) can be promising adsorbents for various applications as they are highly stable in different chemical environments. In this work, a collection of Zr-MOFs comprised of more than 100 materials is screened for CF₄/CH₄, CH₄/H₂, and CH₄/N₂ separations using atomistic-level simulations. The top three MOFs for the CF₄/CH₄ separation are identified as PCN-700-BPDC-TPDC, LIFM-90, and BUT-67 exhibiting CF₄/CH₄ adsorption selectivities of 4.8, 4.6, and 4.7, CF₄ working capacities of 2.0, 2.0, and 2.1 mol kg^-1, and regenerabilities of 85.1, 84.2, and 75.7%, respectively. For the CH₄/H₂ separation, MOF-812, BUT-67, and BUT-66 are determined to be the top performing MOFs demonstrating CH₄/H₂ selectivities of 61.6, 36.7, and 46.2, CH₄ working capacities of 3.0, 4.1, and 3.4 mol kg^-1, and CH₄ regenerabilities of 70.7, 82.7, and 74.7%, respectively. Regarding the CH₄/N₂ separation, BUT-67, Zr-AbBA, and PCN-702 achieving CH₄/N₂ selectivities of 4.5, 3.4, and 3.8, CH₄ working capacities of 3.6, 3.9, and 3.5 mol kg^-1, and CH₄ regenerabilities of 81.1, 84.0, and 84.5%, in successive order, show the best overall separation performances. To further elucidate the adsorption in top performing adsorbents, the adsorption sites in these materials are analyzed using radial distribution functions and adsorbate density profiles. Finally, the water affinities of Zr-MOFs are explored to comment on their practical use in real gas separation applications. Our findings may inspire future studies probing the adsorption/separation mechanisms and performances of Zr-MOFs for different gases.

In Silico Tuning of the Pore Surface Functionality in Al-MOFs for Trace CH3I Capture

Aluminum (Al)-based metal-organic frameworks (MOFs) have been shown to have good stability toward γ irradiation, making them promising candidates for durable adsorbents for capturing volatile radioactive nuclides. In this work, we studied a series of existing Al-MOFs to capture trace radioactive organic iodide (ROI) from a gas composition (100 ppm CH₃I, 400 ppm CO₂, 21% O₂, and 78% N₂) resembling the off-gas composition from reprocessing the used nuclear fuel using Grand canonical Monte Carlo (GCMC) simulations and density functional theory (DFT) calculations. Based on the results and understanding established from studying the existing Al-MOFs, we proceed by functionalizing the top-performing CAU-11 with different functional groups to propose better MOFs for ROI capture. Our study suggests that extraordinary ROI adsorption and separation capability could be realized by -SO₃H functionalization in CAU-11. It was mainly owing to the joint effect of the enhanced pore surface polarity arising from -SO₃H functionalization and the μ-OH group of CAU-11.

Efficient Parametrization of Force Field for the Quantitative Prediction of the Physical Properties of Ionic Liquid Electrolytes

The prediction of transport properties of room-temperature ionic liquids from nonpolarizable force field-based simulations has long been a challenge. The uniform charge scaling method has been widely used to improve the agreement with the experiment by incorporating the polarizability and charge transfer effects in an effective manner. While this method improves the performance of the force fields, this prescription is ad hoc in character; further, a quantitative prediction is still not guaranteed. In such cases, the nonbonded interaction parameters too need to be refined, which requires significant effort. In this work, we propose a three-step semiautomated refinement procedure based on (1) atomic site charges obtained from quantum calculations of the bulk condensed phase; (2) quenched Monte Carlo optimizer to shortlist suitable force field candidates, which are then tested using pilot simulations; and (3) manual refinement to further improve the accuracy of the force field. The strategy is designed in a sequential manner with each step improving the accuracy over the previous step, allowing the users to invest the effort commensurate with the desired accuracy of the refined force field. The refinement procedure is applied on N,N-diethyl-N-methyl-N-(2-methoxyethyl)ammonium bis(trifluoromethanesulfonyl)imide (DEME-TFSI), a front-runner as an electrolyte for electric double-layer capacitors and single-molecule-based devices. The transferability of the refined force field is tested on N,N-dimethyl-N-ethyl-N-methoxyethoxyethylammonium bis(trifluoromethanesulfonyl)imide (N_112,2O2O1-TFSI). The refined force field is found to be better at predicting both structural and transport properties compared to the uniform charge scaling procedure, which showed a discrepancy in the X-ray structure factor. The refined force field showed quantitative agreement with structural (density and X-ray structure factor) and transport properties-diffusion coefficients, ionic conductivity, and shear viscosity over a wide temperature range, building a case for the wide adoption of the procedure.

Implementation of the QUBE Force Field in SOMD for High-Throughput Alchemical Free-Energy Calculations

The quantum mechanical bespoke (QUBE) force-field approach has been developed to facilitate the automated derivation of potential energy function parameters for modeling protein-ligand binding. To date, the approach has been validated in the context of Monte Carlo simulations of protein-ligand complexes. We describe here the implementation of the QUBE force field in the alchemical free-energy calculation molecular dynamics simulation package SOMD. The implementation is validated by demonstrating the reproducibility of absolute hydration free energies computed with the QUBE force field across the SOMD and GROMACS software packages. We further demonstrate, by way of a case study involving two series of non-nucleoside inhibitors of HIV-1 reverse transcriptase, that the availability of QUBE in a modern simulation package that makes efficient use of graphics processing unit acceleration will facilitate high-throughput alchemical free-energy calculations.

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal-Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal-organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO₂. Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal-Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. A strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

Construction of an Anion-Pillared MOF Database and the Screening of MOFs Suitable for Xe/Kr Separation

The separation of xenon/krypton (Xe/Kr) mixtures is a challenging process. Many porous materials allow the adsorption of both Xe and Kr but only with low selectivity. Anion-pillared metal-organic frameworks (MOFs), featuring the anion groups as structural pillars, show potential in gas separations, but only a limited number of them have been synthesized. Here, we describe a collection of 936 anion-pillared MOFs based on 22 experimentally available structures. We performed density functional theory (DFT) optimization and then assigned density-derived electrostatic and chemical (DDEC) charges for each MOF to make them well suited to molecular simulations. The structural properties of the MOFs vary more strongly with the choice of the organic ligand than with other aspects like fluorine groups and metal centers. We then screened the entire collection of MOFs in the context of Xe/Kr separation at room temperature. Compared with previously reported MOFs, the interpenetrated MOF SIFSIX-6-Cd-i is predicted to perform better for Xe/Kr separations, with a good balance between working capacity (1.62 mmol/g) and separation selectivity (16.4) at 298 K and 100 kPa. We also found that the heterogeneity of fluorine groups within a MOF can help to enhance Xe working capacity without reducing the Xe/Kr selectivity, suggesting that synthesis of anion-pillared MOFs with mixed fluorine groups may lead to improved Xe/Kr separation performance.

Dipolar relaxation in thin films of supramolecular stacks of benzenecarboxamides and insights to enhance their ferroelectric characteristics

The relationship between molecular structure and ferroelectric behaviour of thin films is explored in an all-organic supramolecular polymer material based on benzenecarboxamides, using atomistic molecular dynamics simulations. While increasing the number of amide groups around the phenyl core increases the dipole density of a molecule, increasing the length of the corresponding alkyl groups decreases the same. The interplay between these two contributions displays a rich behaviour on key material characteristics, in particular, the polarisation retention time. The latter is shown to be inversely proportional to the alkyl chain length, a consequence of weaker interactions between macrodipoles of stacks. Polarisation retention time was observed to be the highest in a molecule with five amide groups around the aromatic phenyl core which is explained as due to the large barrier for amide group rotation, which is one of the crucial channels for dipolar relaxation. Simulations also demonstrate that the barrier, however, does not affect the switchability of polarization, upon field reversal.

Seven confluence principles: a case study of standardized statistical analysis for 26 methods that assign net atomic charges in molecules

This article studies two kinds of information extracted from statistical correlations between methods for assigning net atomic charges (NACs) in molecules. First, relative charge transfer magnitudes are quantified by performing instant least squares fitting (ILSF) on the NACs reported by Cho et al. (ChemPhysChem, 2020, 21, 688-696) across 26 methods applied to ∼2000 molecules. The Hirshfeld and Voronoi deformation density (VDD) methods had the smallest charge transfer magnitudes, while the quantum theory of atoms in molecules (QTAIM) method had the largest charge transfer magnitude. Methods optimized to reproduce the molecular dipole moment (e.g., ACP, ADCH, CM5) have smaller charge transfer magnitudes than methods optimized to reproduce the molecular electrostatic potential (e.g., CHELPG, HLY, MK, RESP). Several methods had charge transfer magnitudes even larger than the electrostatic potential fitting group. Second, confluence between different charge assignment methods is quantified to identify which charge assignment method produces the best NAC values for predicting via linear correlations the results of 20 charge assignment methods having a complete basis set limit across the dataset of ∼2000 molecules. The DDEC6 NACs were the best such predictor of the entire dataset. Seven confluence principles are introduced explaining why confluent quantitative descriptors offer predictive advantages for modeling a broad range of physical properties and target applications. These confluence principles can be applied in various fields of scientific inquiry. A theory is derived showing confluence is better revealed by standardized statistical analysis (e.g., principal components analysis of the correlation matrix and standardized reversible linear regression) than by unstandardized statistical analysis. These confluence principles were used together with other key principles and the scientific method to make assigning atom-in-material properties non-arbitrary. The N@C60 system provides an unambiguous and non-arbitrary falsifiable test of atomic population analysis methods. The HLY, ISA, MK, and RESP methods failed for this material.

Analysis and visualization of energy densities. II. Insights from linear-response time-dependent density functional theory calculations

Inspired by the analysis of Kohn-Sham energy densities by Nakai and coworkers, we extended the energy density analysis to linear-response time-dependent density functional theory (LR-TDDFT) calculations. Using ethylene-tetrafluoroethylene and oxyluciferin-water complexes as examples, distinctive distribution patterns were demonstrated for the excitation energy densities of local excitations (within a molecular fragment) and charge-transfer excitations (between molecular fragments). It also provided a simple way to compute the effective energy of both hot carriers (particle and hole) from charge-transfer excitations via an integration of the excitation energy density over the donor and acceptor grid points.

Circumventing Scaling Relations in Oxygen Electrochemistry Using Metal-Organic Frameworks

It has been well-established that unfavorable scaling relationships between *OOH, *OH, and *O are responsible for the high overpotentials associated with oxygen electrochemistry. A number of strategies have been proposed for breaking these linear constraints for traditional electrocatalysts (e.g., metals, alloys, metal-doped carbons); such approaches have not yet been validated experimentally for heterogeneous catalysts. Development of a new class of catalysts capable of circumventing such scaling relations remains an ongoing challenge in the field. In this work, we use density functional theory (DFT) calculations to demonstrate that bimetallic porphyrin-based MOFs (PMOFs) are an ideal materials platform for rationally designing the 3-D active site environments for oxygen reduction reaction (ORR). Specifically, we show that the *OOH binding energy and the theoretical limiting potential can be optimized by appropriately tuning the transition metal active site, the oxophilic spectator, and the MOF topology. Our calculations predict theoretical limiting potentials as high as 1.07 V for Fe/Cr-PMOF-Al, which exceeds the Pt/C benchmark for 4e ORR. More broadly, by highlighting their unique characteristics, this work aims to establish bimetallic porphyrin-based MOFs as a viable materials platform for future experimental and theoretical ORR studies.

High Throughput Methods in the Synthesis, Characterization, and Optimization of Porous Materials

Porous materials are widely employed in a large range of applications, in particular, for storage, separation, and catalysis of fine chemicals. Synthesis, characterization, and pre- and post-synthetic computer simulations are mostly carried out in a piecemeal and ad hoc manner. Whilst high throughput approaches have been used for more than 30 years in the porous material fields, routine integration of experimental and computational processes is only now becoming more established. Herein, important developments are highlighted and emerging challenges for the community identified, including the need to work toward more integrated workflows.

Incorporating charge transfer effects into a metallic empirical potential for accurate structure determination in (ZnMg)N nanoalloys

We report the results of a combined empirical potential-density functional theory (EP-DFT) study to assess the global minimum structures of free-standing zinc-magnesium nanoalloys of equiatomic composition and with up to 50 atoms. Within this approach, the approximate potential energy surface generated by an empirical potential is first sampled with unbiased basin hopping simulations, and then a selection of the isomers so identified is re-optimized at a first-principles DFT level. Bader charges calculated in a previous work [A. Lebon, A. Aguado and A. Vega, Corros. Sci., 2017, 124, 35-45] revealed a significant transfer of electrons from Mg to Zn atoms in these nanoalloys; so the main novelty in the present work is the development of an improved EP, termed Coulomb-corrected-Gupta potential, which incorporates an explicit charge-transfer correction term onto a metallic Gupta potential description. The Coulomb correction has a many-body character and is fed with parameterized values of the ab initio Bader charges. The potentials are fitted to a large training set containing DFT values of cluster energies and atomic forces, and the DFT results are used as benchmark data to assess the performance of Gupta and Coulomb-corrected-Gupta EP models. Quite surprisingly, the charge-transfer correction is found to represent only 6% of the nanoalloy binding energies, yet this quantitatively small correction has a sizable beneficial effect on the predicted relative energies of homotops. Zn-Mg bulk alloys are used as the sacrificial material in corrosion-protective coatings, and the long-term goal of our research is to disclose whether those corrosion-protected capabilities are enhanced at the nanoscale.

Rational design of a robust aluminum metal-organic framework for multi-purpose water-sorption-driven heat allocations

Adsorption-driven heat transfer technology using water as working fluid is a promising eco-friendly strategy to address the exponential increase of global energy demands for cooling and heating purposes. Here we present the water sorption properties of a porous aluminum carboxylate metal-organic framework, [Al(OH)(C₆H₃NO₄)]·nH₂O, KMF-1, discovered by a joint computational predictive and experimental approaches, which exhibits step-like sorption isotherms, record volumetric working capacity (0.36 mL mL⁻¹) and specific energy capacity (263 kWh m⁻³) under cooling working conditions, very high coefficient of performances of 0.75 (cooling) and 1.74 (heating) together with low driving temperature below 70 °C which allows the exploitation of solar heat, high cycling stability and remarkable heat storage capacity (348 kWh m⁻³). This level of performances makes this porous material as a unique and ideal multi-purpose water adsorbent to tackle the challenges of thermal energy storage and its further efficient exploitation for both cooling and heating applications.

Adsorption-based heat transfer devices are attractive for clean energy resources, but those using water as the working fluid require suitable water adsorbents. Here the authors use computation and experiment to develop an aluminum-based metal-organic framework adsorbent for adsorption-driven heat transfer devices.

Novel covalent organic framework/PVDF ultrafiltration membranes with antifouling and lead removal performance

Membrane separation technology is recognized as a competitive approach to remove Pb²⁺ from water system due to its high efficiency and low operating cost. In present study, a simple and facile approach was developed to fabricate covalent organic framework (COF) modified PVDF ultrafiltration membranes with comprehensive antifouling property and superior Pb²⁺ removal ability. Herein, COF was synthesised in a homogenous PVDF/DMAc solution to fabricate hydrophilic COF modified PVDF ultrafiltration membranes with the Pb²⁺ removal property. The filtration test demonstrated that the COF modified PVDF ultrafiltration membranes exhibited excellent antifouling property and high water flux. Moreover, the membranes showed remarkable potential for treating Pb²⁺-containing water. The removal efficiency was determined at 92.4%, and its removal efficiency was 87.5% at the fourth treatment cycle with Pb²⁺-containing water. The present work provides a valuable platform for further development of efficient composite membranes for the treatment of Pb²⁺-containing water.

DeepAtomicCharge: a new graph convolutional network-based architecture for accurate prediction of atomic charges

Atomic charges play a very important role in drug-target recognition. However, computation of atomic charges with high-level quantum mechanics (QM) calculations is very time-consuming. A number of machine learning (ML)-based atomic charge prediction methods have been proposed to speed up the calculation of high-accuracy atomic charges in recent years. However, most of them used a set of predefined molecular properties, such as molecular fingerprints, for model construction, which is knowledge-dependent and may lead to biased predictions due to the representation preference of different molecular properties used for training. To solve the problem, we present a new architecture based on graph convolutional network (GCN) and develop a high-accuracy atomic charge prediction model named DeepAtomicCharge. The new GCN architecture is designed with only the atomic properties and the connection information between the atoms in molecules and can dynamically learn and convert molecules into appropriate atomic features without any prior knowledge of the molecules. Using the designed GCN architecture, substantial improvement is achieved for the prediction accuracy of atomic charges. The average root-mean-square error (RMSE) of DeepAtomicCharge is 0.0121 e, which is obviously more accurate than that (0.0180 e) reported by the previous benchmark study on the same two external test sets. Moreover, the new GCN architecture needs much lower storage space compared with other methods, and the predicted DDEC atomic charges can be efficiently used in large-scale structure-based drug design, thus opening a new avenue for high-performance atomic charge prediction and application.

In Silico Discovery of Covalent Organic Frameworks for Carbon Capture

We screen a database of more than 69 000 hypothetical covalent organic frameworks (COFs) for carbon capture using parasitic energy as a metric. To compute CO₂-framework interactions in molecular simulations, we develop a genetic algorithm to tune the charge equilibration method and derive accurate framework partial charges. Nearly 400 COFs are identified with parasitic energy lower than that of an amine scrubbing process using monoethanolamine; more than 70 are better performers than the best experimental COFs and several perform similarly to Mg-MOF-74. We analyze the effect of pore topology on carbon capture performance to guide the development of improved carbon capture materials.

The ONETEP linear-scaling density functional theory program

We present an overview of the onetep program for linear-scaling density functional theory (DFT) calculations with large basis set (plane-wave) accuracy on parallel computers. The DFT energy is computed from the density matrix, which is constructed from spatially localized orbitals we call Non-orthogonal Generalized Wannier Functions (NGWFs), expressed in terms of periodic sinc (psinc) functions. During the calculation, both the density matrix and the NGWFs are optimized with localization constraints. By taking advantage of localization, onetep is able to perform calculations including thousands of atoms with computational effort, which scales linearly with the number or atoms. The code has a large and diverse range of capabilities, explored in this paper, including different boundary conditions, various exchange-correlation functionals (with and without exact exchange), finite electronic temperature methods for metallic systems, methods for strongly correlated systems, molecular dynamics, vibrational calculations, time-dependent DFT, electronic transport, core loss spectroscopy, implicit solvation, quantum mechanical (QM)/molecular mechanical and QM-in-QM embedding, density of states calculations, distributed multipole analysis, and methods for partitioning charges and interactions between fragments. Calculations with onetep provide unique insights into large and complex systems that require an accurate atomic-level description, ranging from biomolecular to chemical, to materials, and to physical problems, as we show with a small selection of illustrative examples. onetep has always aimed to be at the cutting edge of method and software developments, and it serves as a platform for developing new methods of electronic structure simulation. We therefore conclude by describing some of the challenges and directions for its future developments and applications.

Non-bonded force field model with advanced restrained electrostatic potential charges (RESP2)

The restrained electrostatic potential (RESP) approach is a highly regarded and widely used method of assigning partial charges to molecules for simulations. RESP uses a quantum-mechanical method that yields fortuitous overpolarization and thereby accounts only approximately for self-polarization of molecules in the condensed phase. Here we present RESP2, a next generation of this approach, where the polarity of the charges is tuned by a parameter, δ, which scales the contributions from gas- and aqueous-phase calculations. When the complete non-bonded force field model, including Lennard-Jones parameters, is optimized to liquid properties, improved accuracy is achieved, even with this reduced set of five Lennard-Jones types. We argue that RESP2 with δ≈0.6 (60% aqueous, 40% gas-phase charges) is an accurate and robust method of generating partial charges, and that a small set of Lennard-Jones types is good starting point for a systematic re-optimization of this important non-bonded term.

On the Possibility of Helium Adsorption in Nitrogen Doped Graphitic Materials

The potassium salt of polyheptazine imide (K-PHI) is a promising photocatalyst for various chemical reactions. From powder X-ray diffraction data an idealized structural model of K-PHI has been derived. Using atomic coordinates of this model we defined an energetically optimized K-PHI structure, in which the K ions are present in the pore and between the PHI-planes. The distance between the anion framework and K+ resembles a frustrated Lewis pair-like structure, which we denote as frustrated Coulomb pair that results in an interesting adsorption environment for otherwise non-adsorbing, non-polar gas molecules. We demonstrate that even helium (He) gas molecules, which are known to have the lowest boiling point and the lowest intermolecular interactions, can be adsorbed in this polarized environment with an adsorption energy of  - 4.6 kJ mol-1 per He atom. The interaction between He atoms and K-PHI is partially originating from charge transfer, as disclosed by our energy decomposition analysis based on absolutely localized molecular orbitals. Due to very small charge transfer interactions, He gas adsorption saturates at 8 at%, which however can be subject to further improvement by cation variation.

Density functional theory based studies on the adsorption of rare-earth ions from hydrated nitrate salt solutions on g-C3N4 monolayer surface

This article represents density functional theory (DFT) based comparative analysis on six trivalent rare-earth ions (RE³⁺; RE: Y, La, Ce, Sm, Eu and Gd) absorption, from the respective nitrate-hexahydrate salts, on graphitic carbon nitride (g-C₃N₄) 2D monolayer, and the photocatalytic properties of the RE³⁺ adsorbed g-C₃N₄ systems (g-C₃N₄/RE³⁺) based on the ground-state electronic structure calculations. Structure, stability and coordination chemistry of two configurations of each hydrated RE-salt system are discussed in detail. Both DFT (B3LYP/SDD) and semi-empirical (Sparkle/PM7) calculations identify the central N₆ vacancy of pristine g-C₃N₄ as the most suitable site for RE³⁺ adsorption. Bader's QTAIM, Mayer bond order and charge population analyses (ADCH, CHELPG and DDEC) are performed to describe the bond characteristics within the systems under study. Thermochemical calculations suggest that the adsorption process is thermodynamically more feasible for higher atomic number (Z) RE³⁺ [Sm³⁺, Eu³⁺ and Gd³⁺], compared to lower-Z RE³⁺ [Y³⁺, La³⁺ and Ce³⁺] ions. Besides, the better photocatalytic properties of higher-Z RE³⁺ adsorbed g-C₃N₄ systems are revealed from better HOMO-LUMO delocalization, decreased HOMO-LUMO gap, increased softness, higher electrophilicity and electron transfer parameter, compared to pristine or lower-Z RE³⁺ adsorbed g-C₃N₄ systems, as obtained from Hirshfeld orbital compositions, density of states and condensed Fukui function analyses.

Insights into the Gas Adsorption Mechanisms in Metal-Organic Frameworks from Classical Molecular Simulations

Classical molecular simulations can provide significant insights into the gas adsorption mechanisms and binding sites in various metal-organic frameworks (MOFs). These simulations involve assessing the interactions between the MOF and an adsorbate molecule by calculating the potential energy of the MOF-adsorbate system using a functional form that generally includes nonbonded interaction terms, such as the repulsion/dispersion and permanent electrostatic energies. Grand canonical Monte Carlo (GCMC) is the most widely used classical method that is carried out to simulate gas adsorption and separation in MOFs and identify the favorable adsorbate binding sites. In this review, we provide an overview of the GCMC methods that are normally utilized to perform these simulations. We also describe how a typical force field is developed for the MOF, which is required to compute the classical potential energy of the system. Furthermore, we highlight some of the common analysis techniques that have been used to determine the locations of the preferential binding sites in these materials. We also review some of the early classical molecular simulation studies that have contributed to our working understanding of the gas adsorption mechanisms in MOFs. Finally, we show that the implementation of classical polarization for simulations in MOFs can be necessary for the accurate modeling of an adsorbate in these materials, particularly those that contain open-metal sites. In general, molecular simulations can provide a great complement to experimental studies by helping to rationalize the favorable MOF-adsorbate interactions and the mechanism of gas adsorption.

Impact of intrinsic framework flexibility for selective adsorption of sarin in non-aqueous solvents using metal–organic frameworks

We assess the nontrivial deviation in predicting the adsorption selectivity from bulk mixtures of complex molecules using nanoporous adsorbents approximated as rigid and intrinsically flexible.

Analysis of the structures, stabilities and electronic properties of MB16− (M = V, Cr, Mn, Fe, Co, Ni) clusters and assemblies

Stacking of lowest-energy structures of Fe₂B₂₄⁻ and Co₂B₂₄⁻ dimers.

Adsorption energy scaling relation on bimetallic magnetic surfaces: role of surface magnetic moments

The scaling relationships between the adsorption energies of different reaction intermediates have a tremendous effect in the field of surface science, particularly in predicting new catalytic materials. In the last few decades, these scaling laws have been extensively studied and interpreted by a number of research groups which makes them almost universally accepted. In this work, we report the breakdown of the standard scaling law in magnetic bimetallic transition metal (TM) surfaces for hydrogenated species of oxygen (O), carbon (C), and nitrogen (N), where the adsorption energies are estimated using density functional theory (DFT). We propose that the scaling relationships do not necessarily rely solely on the adsorbates, they can also be strongly dependent on the surface properties. For magnetic bimetallic TM surfaces, the magnetic moment plays a vital role in the estimation of adsorption energy, and therefore towards the linear scaling relation.

Enabling efficient exploration of metal–organic frameworks in the Cambridge Structural Database

A tutorial review for mining the ever growing number of metal–organic frameworks data in the Cambridge Structural Database, for MOF scientists of all backgrounds.