Extending the applicability of the Tkatchenko-Scheffler dispersion correction via iterative Hirshfeld partitioning

Surface Engineering of the Mechanical Properties of Molecular Crystals via an Atomistic Model for Computing the Facet Stress Response of Solids

Dynamic molecular crystals are an emerging class of crystalline materials that can respond to mechanical stress by dissipating internal strain in a number of ways. Given the serendipitous nature of the discovery of such crystals, progress in the field requires advances in computational methods for the accurate and high-throughput computation of the nanomechanical properties of crystals on specific facets which are exposed to mechanical stress. Here, we develop and apply a new atomistic model for computing the surface elastic moduli of crystals on any set of facets of interest using dispersion-corrected density functional theory (DFT-D) methods. The model was benchmarked against a total of 24 reported nanoindentation measurements from a diverse set of molecular crystals and was found to be generally reliable. Using only the experimental crystal structure of the dietary supplement, L-aspartic acid, the model was subsequently applied under blind test conditions, to correctly predict the growth morphology, facet and nanomechanical properties of L-aspartic acid to within the accuracy of the measured elastic stiffness of the crystal, 24.53±0.56 GPa. This work paves the way for the computational design and experimental realization of other functional molecular crystals with tailor-made mechanical properties.

To Pair or not to Pair? Machine-Learned Explicitly-Correlated Electronic Structure for NaCl in Water

The extent of ion pairing in solution is an important phenomenon to rationalize transport and thermodynamic properties of electrolytes. A fundamental measure of this pairing is the potential of mean force (PMF) between solvated ions. The relative stabilities of the paired and solvent shared states in the PMF and the barrier between them are highly sensitive to the underlying potential energy surface. However, direct application of accurate electronic structure methods is challenging, since long simulations are required. We develop wave function based machine learning potentials with the random phase approximation (RPA) and second order Møller-Plesset (MP2) perturbation theory for the prototypical system of Na and Cl ions in water. We show both methods in agreement, predicting the paired and solvent shared states to have similar energies (within 0.2 kcal/mol). We also provide the same benchmarks for different DFT functionals as well as insight into the PMF based on simple analyses of the interactions in the system.

Disentangling the effects of structure and lone-pair electrons in the lattice dynamics of halide perovskites

Halide perovskites show great optoelectronic performance, but their favorable properties are paired with unusually strong anharmonicity. It was proposed that this combination derives from the ns2 electron configuration of octahedral cations and associated pseudo-Jahn-Teller effect. We show that such cations are not a prerequisite for the strong anharmonicity and low-energy lattice dynamics encountered in these materials. We combine X-ray diffraction, infrared and Raman spectroscopies, and molecular dynamics to contrast the lattice dynamics of CsSrBr3 with those of CsPbBr3, two compounds that are structurally similar but with the former lacking ns2 cations with the propensity to form electron lone pairs. We exploit low-frequency diffusive Raman scattering, nominally symmetry-forbidden in the cubic phase, as a fingerprint of anharmonicity and reveal that low-frequency tilting occurs irrespective of octahedral cation electron configuration. This highlights the role of structure in perovskite lattice dynamics, providing design rules for the emerging class of soft perovskite semiconductors.

Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights

Chiral organic-inorganic perovskites exhibit unique physicochemical properties driven by the symmetry of monovalent organic cations. However, an atomistic understanding of how chiral cations transfer their chirality to the inorganic framework and the role played by van der Waals (vdW) interactions in this process is still incomplete. In this work, we report a theoretical investigation, based on density functional theory calculations within the Perdew-Burke-Ernzerhof (PBE) formulation for the exchange-correlation functional, into the role of the vdW interactions in the chirality transfer process. For that, we selected several vdW corrections, namely, Grimme (D2, D3, D3(BJ)), Tkatchenko-Scheffler (TS, TS+SCS, TS+HSI), density-dependent energy correction (dDsC), and many-body scattering (MBD) energy method correction. For the chiral perovskite systems, we selected a set of chiral organic-inorganic perovskites with several dimensions, namely, from zero-dimensional to three-dimensional, each having enantiomers with R and S configurations. Based on a statistical treatment of the relative errors of all lattice parameters with respect to experimental data, we found that D3, D3(BJ), TS, TS+SCS, TS+HSI, and MBD vdW are the most accurate corrections to describe the equilibrium structural properties of chiral perovskites using the PBE method. We identify chirality-induced sequential asymmetries of distorted octahedrons and propose angular descriptors to quantify them, where the orientations of these distortions depend on the R or S nature of the chiral cations. Furthermore, we demonstrate the importance of accurate vdW interactions in precisely describing these asymmetric distortions. By means of binding energies and charge-transfer analysis, we show that the impact of vdW corrections on the charge distribution leads to a subtle strengthening of hydrogen bonds between chiral cations and inorganic octahedra, resulting in an increase in the binding energy. Finally, we identified that the Rashba-Dresselhaus effect in two-dimensionality is refined by vdW interactions.

Atomic structure and water arrangement on K-feldspar microcline (001)

The properties of clouds, such as their reflectivity or their likelihood to precipitate, depend on whether the cloud droplets are liquid or frozen. Thus, understanding the ice nucleation mechanisms is essential for the development of reliable climate models. Most ice nucleation in the atmosphere is heterogeneous, i.e., caused by ice nucleating particles such as mineral dusts or organic aerosols. In this regard, K-feldspar minerals have attracted great interest recently as they have been identified as one of the most important ice nucleating particles under mixed-phase cloud conditions. The mechanism by which feldspar minerals facilitate ice nucleation remains, however, elusive. Here, we present atomic force microscopy (AFM) experiments on microcline (001) performed in an ultrahigh vacuum and at the solid-water interface together with density functional theory (DFT) and molecular dynamics (MD) calculations. Our ultrahigh vacuum data reveal features consistent with a hydroxyl-terminated surface. This finding suggests that water in the residual gas readily reacts with the surface. Indeed, the corresponding DFT calculations confirm a dissociative water adsorption. Three-dimensional AFM measurements performed at the mineral-water interface unravel a layered hydration structure with two features per surface unit cell. A comparison with MD calculations suggests that the structure observed in AFM corresponds to the second hydration layer rather than the first water layer. In agreement with previous computation results, no ice-like structure is seen, questioning an explanation of the ice nucleation ability by lattice match. Our results provide an atomic-scale benchmark for the clean and water-covered microcline (001) plane, which is mandatory for understanding the ice nucleation mechanism on feldspar minerals.

Toward accurate modeling of structure and energetics of bulk hexagonal boron nitride

Materials that exhibit both strong covalent and weak van der Waals interactions pose a considerable challenge to many computational methods, such as DFT. This makes assessing the accuracy of calculated properties, such as exfoliation energies in layered materials like hexagonal boron nitride (h-BN) problematic, when experimental data are not available. In this paper, we investigate the accuracy of equilibrium lattice constants and exfoliation energy calculation for various DFT-based computational approaches in bulk h-BN. We contrast these results with available experiments and reference fixed-node diffusion quantum Monte Carlo (QMC) results. From our reference QMC calculation, we obtained an exfoliation energy of - 33 ± 2 meV/atom (-0.38 ± 0.02 J/m2 ).

Investigating the role of dispersion corrections and anharmonic effects on the phase transition in SrZrS3: A systematic analysis from AIMD free energy calculations

A thermally driven needle-like (NL) to distorted perovskite (DP) phase transition in SrZrS3 was investigated by means of ab initio free energy calculations accelerated by machine learning. As a first step, a systematic screening of the methods to include long-range interactions in semilocal density functional theory Perdew-Burke-Ernzerhof calculations was performed. Out of the ten correction schemes tested, the Tkatchenko-Scheffler method with iterative Hirshfeld partitioning method was found to yield the best match between calculated and experimental lattice geometries, while predicting the correct order of stability of NL and DP phases at zero temperature. This method was then used in free energy calculations, performed using several approaches, so as to determine the effect of various anharmonicity contributions, such as the anisotropic thermal lattice expansion or the thermally induced internal structure changes, on the phase transition temperature (TNP→DP). Accounting for the full anharmonicity by combining the NPT molecular dynamics data with thermodynamic integration with harmonic reference provided our best estimate of TNL→DP = 867 K. Although this result is ∼150 K lower than the experimental value, it still provides an improvement by nearly 300 K compared to the previous theoretical report by Koocher et al. [Inorg. Chem. 62, 11134-11141 (2023)].

Cation Dynamics as Structure Explorer in Hybrid Perovskites-The Case of MAPbI3

Hybrid organic-inorganic perovskites exhibit remarkable potential as cost-effective and high-efficiency materials for photovoltaic applications. Their exceptional chemical tunability opens further routes for optimizing their optical and electronic properties through structural engineering. Nevertheless, the extraordinary softness of the lattice, stemming from its interconnected organic-inorganic composition, unveils formidable challenges in structural characterization. Here, by focusing on the quintessential methylammonium lead triiodide, MAPbI3, we combine first-principles modeling with high-resolution neutron scattering data to identify the key stationary points on its shallow potential energy landscape. This combined experimental and computational approach enables us to benchmark the performance of a collection of semilocal exchange-correlation functionals and to track the local distortions of the perovskite framework, hallmarked by the inelastic neutron scattering response of the organic cation. By conducting a thorough examination of structural distortions, we introduce the IKUR-PVP-1 structural data set. This data set contains nine mechanically stable structural models, each manifesting a distinct vibrational response. IKUR-PVP-1 constitutes a valuable resource for assessing thermal behavior in the low-temperature perovskite phase. In addition, it paves the way for the development of accurate force fields, enabling a comprehensive understanding of the interplay between the structure and dynamics in MAPbI3 and related hybrid perovskites.

On-off conduction photoswitching in modelled spiropyran-based metal-organic frameworks

Materials with photoswitchable electronic properties and conductance values that can be reversibly changed over many orders of magnitude are highly desirable. Metal-organic framework (MOF) films functionalized with photoresponsive spiropyran molecules demonstrated the general possibility to switch the conduction by light with potentially large on-off-ratios. However, the fabrication of MOF materials in a trial-and-error approach is cumbersome and would benefit significantly from in silico molecular design. Based on the previous proof-of-principle investigation, here, we design photoswitchable MOFs which incorporate spiropyran photoswitches at controlled positions with defined intermolecular distances and orientations. Using multiscale modelling and automated workflow protocols, four MOF candidates are characterized and their potential for photoswitching the conductivity is explored. Using ab initio calculations of the electronic coupling between the molecules in the MOF, we show that lattice distances and vibrational flexibility tremendously modulate the possible conduction photoswitching between spiropyran- and merocyanine-based MOFs upon light absorption, resulting in average on-off ratios higher than 530 and 4200 for p- and n-conduction switching, respectively. Further functionalization of the photoswitches with electron-donating/-withdrawing groups is demonstrated to shift the energy levels of the frontier orbitals, permitting a guided design of new spiropyran-based photoswitches towards controlled modification between electron and hole conduction in a MOF.

Identification of High-Reliability Regions of Machine Learning Predictions Based on Materials Chemistry

Progress in the application of machine learning (ML) methods to materials design is hindered by the lack of understanding of the reliability of ML predictions, in particular, for the application of ML to small data sets often found in materials science. Using ML prediction for transparent conductor oxide formation energy and band gap, dilute solute diffusion, and perovskite formation energy, band gap, and lattice parameter as examples, we demonstrate that (1) construction of a convex hull in feature space that encloses accurately predicted systems can be used to identify regions in feature space for which ML predictions are highly reliable; (2) analysis of the systems enclosed by the convex hull can be used to extract physical understanding; and (3) materials that satisfy all well-known chemical and physical principles that make a material physically reasonable are likely to be similar and show strong relationships between the properties of interest and the standard features used in ML. We also show that similar to the composition-structure-property relationships, inclusion in the ML training data set of materials from classes with different chemical properties will not be beneficial for the accuracy of ML prediction and that reliable results likely will be obtained by ML model for narrow classes of similar materials even in the case where the ML model will show large errors on the data set consisting of several classes of materials.

Unraveling H2 chemisorption and physisorption on metal decorated graphene using quantum Monte Carlo

Molecular hydrogen has the potential to significantly reduce the use of carbon dioxide emitting energy processes. However, hydrogen gas storage is a major bottleneck for its large-scale use as current storage methods are energy intensive. Among different storage methods, physisorbing molecular hydrogen at ambient pressure and temperatures is a promising alternative-particularly in light of the advancements in tunable lightweight nanomaterials and high throughput screening methods. Nonetheless, understanding hydrogen adsorption in well-defined nanomaterials remains experimentally challenging and reference information is scarce despite the proliferation of works predicting hydrogen adsorption. We focus on Li, Na, Ca, and K, decorated graphene sheets as substrates for molecular hydrogen adsorption, and compute the most accurate adsorption energies available to date using quantum diffusion Monte Carlo (DMC). Building on our previous insights at the density functional theory (DFT) level, we find that a weak covalent chemisorption of molecular hydrogen, known as Kubas interaction, is feasible on Ca decorated graphene according to DMC, in agreement with DFT. This finding is in contrast to previous DMC predictions of the 4H2/Ca+ gas cluster (without graphene) where chemisorption is not favored. However, we find that the adsorption energy of hydrogen on metal decorated graphene according to a widely used DFT method is not fully consistent with DMC. The reference adsorption energies reported herein can be used to find better work-horse methods for application in large-scale modeling of hydrogen adsorption. Furthermore, the implications of this work affect strategies for finding suitable hydrogen storage materials and high-throughput methods.

libMBD: A general-purpose package for scalable quantum many-body dispersion calculations

Many-body dispersion (MBD) is a powerful framework to treat van der Waals (vdW) dispersion interactions in density-functional theory and related atomistic modeling methods. Several independent implementations of MBD with varying degree of functionality exist across a number of electronic structure codes, which both limits the current users of those codes and complicates dissemination of new variants of MBD. Here, we develop and document libMBD, a library implementation of MBD that is functionally complete, efficient, easy to integrate with any electronic structure code, and already integrated in FHI-aims, DFTB+, VASP, Q-Chem, CASTEP, and Quantum ESPRESSO. libMBD is written in modern Fortran with bindings to C and Python, uses MPI/ScaLAPACK for parallelization, and implements MBD for both finite and periodic systems, with analytical gradients with respect to all input parameters. The computational cost has asymptotic cubic scaling with system size, and evaluation of gradients only changes the prefactor of the scaling law, with libMBD exhibiting strong scaling up to 256 processor cores. Other MBD properties beyond energy and gradients can be calculated with libMBD, such as the charge-density polarization, first-order Coulomb correction, the dielectric function, or the order-by-order expansion of the energy in the dipole interaction. Calculations on supramolecular complexes with MBD-corrected electronic structure methods and a meta-review of previous applications of MBD demonstrate the broad applicability of the libMBD package to treat vdW interactions.

Potential of nanostructured carbon materials for iodine detection in realistic environments revealed by first-principles calculations

In the context of effective detection of iodine species (I2, CH3I) formed in nuclear power plants and nuclear fuel reprocessing facilities, we perform a comparative study of the potential sensing performance of four expectedly promising 2D materials (8-Pmmn borophene, BC3, C3N, and BC6N) towards the iodine-containing gases and, with the view of checking selectivity, towards common inhibiting gases in the containment atmosphere (H2O and CO), applying methods of dispersion-corrected density functional theory with periodic boundary conditions. A covalent bond is formed between the CO molecule and boron in BC3 or in 8-Pmmn borophene, compromising the anticipated applicability of these materials for iodine detection. The presence of nitrogen atoms in BC6N-2 prevents the formation of a covalent bond with CO; however, the closeness of adsorption energies for all the four gases studied does not distinguish this material as specifically sensitive to iodine species. Finally, the energies of adsorption on C3N yield a significant and promising discrimination between the adsorption energies of (I2, CH3I) vs. (CO, H2O), revealing possibilities for this material's use as an iodine sensor. The conclusions are supported by simulations at finite temperature; underlying electronic structures are also discussed.

Phenol as a Tethering Group to Gold Surfaces: Stark Response and Comparison to Benzenethiol

Understanding the adsorption of organic molecules on metals is important in numerous areas of surface science, including electrocatalysis, electrosynthesis, and biosensing. While thiols are commonly used to tether organic molecules on metals, it is desirable to broaden the range of anchoring groups. In this study, we use a combined spectroelectrochemical and computational approach to demonstrate the adsorption of 4-cyanophenols (CPs) on polycrystalline gold. Using the nitrile stretching vibration as a marker, we confirm the adsorption of CP on the gold electrode and compare our results with those obtained for the thiol counterpart, 4-mercaptobenzonitirle (MBN). Our results reveal that CP adsorbs on the gold electrode via the OH linker, as evidenced by the similarity in the direction and magnitude of the nitrite Stark shifts for CP and MBN. This finding paves the way for exploring new approaches to modify electrode surfaces for controlled reactivity. Furthermore, it highlights adsorption on metals as an important step in the electroreactivity of phenols.

How the Temperature and Composition Govern the Structure and Band Gap of Zr-Based Chalcogenide Perovskites: Insights from ML Accelerated AIMD

The effects of temperature and composition on the structural and electronic properties of chalcogenide perovskite (CP) materials AZrX3 (A = Ba, Sr, Ca; X = S, Se) in the distorted perovskite (DP) phase are investigated using ab initio molecular dynamics (AIMD) accelerated by machine-learned force fields. Long-range van der Waals (vdW) interactions, incorporated into the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional using the DFT-D3 scheme, are found to be crucial for achieving correct predictions of structural parameters. Our calculations show that the distortion of the DP structure with respect to the parent cubic (C) phase, realized in the form of interoctahedral tilting, decreases with the increasing size of the A cations. The tendency for a gradual transformation of the DP-to-C phase with increasing temperature is shown to be strongly composition-dependent. The transformation temperature decreases with the size of cation A and increases with the size of anion X. Thus, within the range of the temperatures considered here (300-1200 K), a complete transformation is observed only for BaZrS3 (∼600 K) and BaZrSe3 (∼900 K). The computed band gap of CPs is shown to monotonically decrease with increasing temperature, and the magnitude of this decrease is found to be proportional to the extent of the thermally induced changes in the internal structure. Diverse factors affecting the magnitude of band gaps of CP materials are analyzed.

Interplay between alkali-metal cations and silanol sites in nanosized CHA zeolite and implications for CO2 adsorption

Silanols are key players in the application performance of zeolites, yet, their localization and hydrogen bonding strength need more studies. The effects of post-synthetic ion exchange on nanosized chabazite (CHA), focusing on the formation of silanols, were studied. The significant alteration of the silanols of the chabazite nanozeolite upon ion exchange and their effect on the CO2 adsorption capacity was revealed by solid-state nuclear magnetic resonance (NMR), Fourier-transform infrared (FTIR) spectroscopy, and periodic density functional theory (DFT) calculations. Both theoretical and experimental results revealed changing the ratio of extra-framework cations in CHA zeolites changes the population of silanols; decreasing the Cs+/K+ ratio creates more silanols. Upon adsorption of CO2, the distribution and strength of the silanols also changed with increased hydrogen bonding, thus revealing an interaction of silanols with CO2 molecules. To the best of our knowledge, this is the first evidence of the interplay between alkali-metal cations and silanols in nanosized CHA.

Large Distortion of Fused Aromatics on Dielectric Interlayers Quantified by Photoemission Orbital Tomography

Polycyclic aromatic compounds with fused benzene rings offer an extraordinary versatility as next-generation organic semiconducting materials for nanoelectronics and optoelectronics due to their tunable characteristics, including charge-carrier mobility and optical absorption. Nonplanarity can be an additional parameter to customize their electronic and optical properties without changing the aromatic core. In this work, we report a combined experimental and theoretical study in which we directly observe large, geometry-induced modifications in the frontier orbitals of a prototypical dye molecule when adsorbed on an atomically thin dielectric interlayer on a metallic substrate. Experimentally, we employ angle-resolved photoemission experiments, interpreted in the framework of the photoemission orbital tomography technique. We demonstrate its sensitivity to detect geometrical bends in adsorbed molecules and highlight the role of the photon energy used in experiment for detecting such geometrical distortions. Theoretically, we conduct density functional calculations to determine the geometric and electronic structure of the adsorbed molecule and simulate the photoemission angular distribution patterns. While we found an overall good agreement between experimental and theoretical data, our results also unveil limitations in current van der Waals corrected density functional approaches for such organic/dielectric interfaces. Hence, photoemission orbital tomography provides a vital experimental benchmark for such systems. By comparison with the state of the same molecule on a metallic substrate, we also offer an explanation why the adsorption on the dielectric induces such large bends in the molecule.

Computational investigation of van der Waals corrections in the adsorption properties of molecules on the Cu(111) surface

Here, we report a computational investigation on the role of the most common van der Waals (vdW) corrections (D2, D3, D3(BJ), TS, TS+SCS, TS+HI, and dDsC) employed in density functional theory (DFT) calculations within local and semilocal exchange-correlation functionals to improve the description of the interaction between molecular species and solid surfaces. For this, we selected several molecular model systems, namely, the adsorption of small molecules (CH₃, CH₄, CO, CO₂, H₂O, and OH) on the close-packed Cu(111) surface, which bind via chemisorption or physisorption mechanisms. As expected, we found that the addition of the vdW corrections enhances the energetic stability of the Cu bulk in the face-centered cubic structure, which contributes to increasing the magnitude of the mechanical properties (elastic constants, bulk, Young, and shear modulus). Except for the TS+SCS correction, all vdW corrections substantially increase the surface energy, while the work function changes by about 0.05 eV (largest change). However, we found substantial differences among the vdW corrections when comparing its effects on interlayer spacing relaxations. Based on bulk and surface results, we selected only the D3 and dDsC vdW corrections for the study of the adsorption properties of the selected molecules on the Cu(111) surface. Overall, the addition of these vdW corrections has a greater effect on weakly interacting systems (CH₄, CO₂, H₂O), while the chemisorption systems (CH₃, CO, OH) are less affected.

Density Functional Response Calculations of Dispersion Coefficients C6 and C9 of Closed- and Open-Shell Systems

Dipole polarizabilities and C₆ and C₉ dispersion coefficients are computed for closed- and open-shell atoms and molecules, using dynamic (time-dependent) density functional (TD-DFT) linear response theory as implemented in the response module of the NWChem quantum chemistry package. The response module is capable of accurate calculations of these properties, based on spin-restricted and spin-unrestricted formalisms. The calculated static polarizabilities and dispersion coefficients are compared to available experimental and other theoretical data. The behavior of the dynamic polarizability at imaginary frequencies is analyzed for differently sized closed- and open-shell systems. An interpolation method enforcing the monotonic decrease of the polarizability with increasing imaginary frequency is beneficial for the integration used to obtain C₆ and C₉. Scaling of the TD-DFT data by ratios of the static polarizability, which can be calculated with a variety of methods, including highly accurate theories, may be used as a leading-order correction.

Grazing incidence fast atom and molecule diffraction: theoretical challenges

This perspective article reviews the state-of-the-art of grazing incidence fast atom and molecule diffraction (GIFAD and GIFMD) simulations and addresses the main challenges that theorists, aiming to provide useful inputs in this topic, are facing. We first discuss briefly the methods used to build accurate potential energy surfaces describing the interaction between the projectile and the surface. Subsequently, we focus on the dynamics simulation methods for GIFAD, a phenomenon that has received a lot of experimental attention since 2007, when the first measurements were published. Following this experimental effort, theorists have developed and adapted a bunch of methods able to simulate, analyze and extract information from the experimental outputs. We review these methods, from the very simple ones based on classical dynamics to the full quantum ones, paying special attention to more versatile semiclassical approaches, which include quantum ingredients in the dynamics at a computational cost only slightly higher than that required in classical dynamics. Within the semiclassical framework it is possible, for example, to include in the dynamics the surface phonons and the projectile coherence, two factors that may have a relevant influence on the experimental measurements, at a reasonable computational cost. Finally, we address GIFMD, a phenomenon that has received much less attention and for which there is still a lot of room for research. We review the few examples of GIFMD available in the literature, and we discuss new phenomena associated with the molecular internal degrees of freedom, which may have some impact in other closely related fields, such as molecular reactivity on metal surfaces. Finally, we point out opened questions, raised from the comparisons between theoretical and experimental results, which claim for further experimental efforts.

Accurate Deep Learning-Aided Density-Free Strategy for Many-Body Dispersion-Corrected Density Functional Theory

Using a deep neuronal network (DNN) model trained on the large ANI-1 data set of small organic molecules, we propose a transferable density-free many-body dispersion (DNN-MBD) model. The DNN strategy bypasses the explicit Hirshfeld partitioning of the Kohn-Sham electron density required by MBD models to obtain the atom-in-molecules volumes used by the Tkatchenko-Scheffler polarizability rescaling. The resulting DNN-MBD model is trained with minimal basis iterative Stockholder atomic volumes and, coupled to density functional theory (DFT), exhibits comparable (if not greater) accuracy to other approaches based on different partitioning schemes. Implemented in the Tinker-HP package, the DNN-MBD model decreases the overall computational cost compared to MBD models where the explicit density partitioning is performed. Its coupling with the recently introduced Stochastic formulation of the MBD equations (J. Chem. Theory Comput. 2022, 18 (3), 1633-1645) enables large routine dispersion-corrected DFT calculations at preserved accuracy. Furthermore, the DNN electron density-free features extend the MBD model's applicability beyond electronic structure theory within methodologies such as force fields and neural networks.

Strain modulation in small molecule physisorption in two dimensions: LEED structure analysis and DFT modeling of the system

The structure of the system was investigated experimentally by means of quantitative LEED I(V) analysis and computationally using dispersion corrected density functional theory (DFT-D). Three different structure models with four, five, and six molecules were considered. The lowest reliability factors and thus best agreement of measured and calculated I(V) curves was found for the structure model containing five molecules per surface unit cell. Essential features of the experimental best-fit adlayer structure are supported by DFT. A slight inclination and lateral shift of twofold coordinated molecules away from the on-top position over Na⁺ adsorption sites is interpreted as compensation of strain between substrate and adlayer.

Comprehensive Basis-Set Testing of Extended Symmetry-Adapted Perturbation Theory and Assessment of Mixed-Basis Combinations to Reduce Cost

Hybrid or "extended" symmetry-adapted perturbation theory (XSAPT) replaces traditional SAPT's treatment of dispersion with better performing alternatives while at the same time extending two-body (dimer) SAPT to a many-body treatment of polarization using a self-consistent charge embedding procedure. The present work presents a systematic study of how XSAPT interaction energies and energy components converge with respect to the choice of Gaussian basis set. Errors can be reduced in a systematic way using correlation-consistent basis sets, with aug-cc-pVTZ results converged within <0.1 kcal/mol. Similar (if slightly less systematic) behavior is obtained using Karlsruhe basis sets at much lower cost, and we introduce new versions with limited augmentation that are even more efficient. Pople-style basis sets, which are more efficient still, often afford good results if a large number of polarization functions are included. The dispersion models used in XSAPT afford much faster basis-set convergence as compared to the perturbative description of dispersion in conventional SAPT, meaning that "compromise" basis sets (such as jun-cc-pVDZ) are no longer required and benchmark-quality results can be obtained using triple-ζ basis sets. The use of diffuse functions proves to be essential, especially for the description of hydrogen bonds. The "δ(Hartree-Fock)" correction for high-order induction can be performed in double-ζ basis sets without significant loss of accuracy, leading to a mixed-basis approach that offers 4× speedup over the existing (cubic scaling) XSAPT approach.

CO2 reduction to CH4 on Cu-doped phosphorene: a first-principles study

Optimizing the electrochemical carbon dioxide reduction reaction (CRR) to fuels is one of the most significant challenges in materials science and chemistry. Recently, single metal atom catalysts based on 2D materials have shown promise to improve the electroreduction performance of pristine 2D materials in the CRR. The physical origins of such performance enhancements are still poorly understood. Herein, we report the potential of a single Cu atom doped phosphorene catalyst for CO₂ electroreduction based on density functional theory (DFT) calculations. The doping sites (hollow, bridge, and on-top) of Cu on phosphorene are investigated first. Phosphorene with a Cu atom anchored on the hollow site is chosen for further study. The pathways for different CRR products, including HCOOH, CO, CH₃OH, and CH₄, are examined via constructing free energy diagrams and via comparing the limiting potentials. CH₄ is the most likely product after analysis of the adsorption energies and free energy pathways. Cu-Doped phosphorene in general shows improved CRR performance with lower limiting potential values. Cu doping leads to a decrease in the band gap value (about 0.2 eV), which is likely to be the physical origin of the CRR performance enhancement. Our study provides a novel promising CRR candidate catalyst based on phosphorene.

Establishing the accuracy of density functional approaches for the description of noncovalent interactions in ionic liquids

We test a number of dispersion corrected versatile Generalized Gradient Approximation (GGA) and meta-GGA functionals for their ability to predict the interactions of ionic liquids, and show that most can achieve energies within 1 kcal mol^-1 of benchmarks. This compares favorably with an accurate dispersion corrected hybrid, ωB97X-V. Our tests also reveal that PBE (Perdew-Burke-Ernzerhof GGA) calculations using the plane-wave projector augmented wave method and Gaussian Type Orbitals (GTOs) differ by less than 0.6 kJ mol^-1 for ionic liquids, despite ions being difficult to evaluate in periodic cells - thus revealing that GTO benchmarks may be used also for plane-wave codes. Finally, the relatively high success of explicit van der Waals density functionals, compared to elemental and ionic dispersion models, suggests that improvements are required for low-cost dispersion correction models of ions.

Anisotropic Interlayer Force Field for Transition Metal Dichalcogenides: The Case of Molybdenum Disulfide

An anisotropic interlayer force field that describes the interlayer interactions in molybdenum disulfide (MoS2) is presented. The force field is benchmarked against density functional theory calculations for both bilayer and bulk systems within the Heyd-Scuseria-Ernzerhof hybrid density functional approximation, augmented by a nonlocal many-body dispersion treatment of long-range correlation. The parametrization yields good agreement with the reference calculations of binding energy curves and sliding potential energy surfaces for both bilayer and bulk configurations. Benchmark calculations for the phonon spectra of bulk MoS2 provide good agreement with experimental data, and the calculated bulk modulus falls in the lower part of experimentally measured values. This indicates the accuracy of the interlayer force field near equilibrium. Under external pressures up to 20 GPa, the developed force field provides a good description of compression curves. At higher pressures, deviations from experimental data grow, signifying the validity range of the developed force field.

Adsorption of Toluene and Water over Cationic-Exchanged Y Zeolites: A DFT Exploration

In this study, density functional theory (DFT) calculations have been performed to investigate the adsorption mechanisms of toluene and water onto various cationic forms of Y zeolite (LiY, NaY, KY, CsY, CuY and AgY). Our computational investigation revealed that toluene is mainly adsorbed via π-interactions on alkalis exchanged Y zeolites, where the adsorbed toluene moiety interacts with a single cation for all cases with the exception of CsY, where two cations can simultaneously contribute to the adsorption of the toluene, hence leading to the highest interaction observed among the series. Furthermore, we find that the interaction energies of toluene increase while moving down in the alkaline series where interaction energies are 87.8, 105.5, 97.8, and 114.4 kJ/mol for LiY, NaY, KY and CsY, respectively. For zeolites based on transition metals (CuY and AgY), our calculations reveal a different adsorption mode where only one cation interacts with toluene through two carbon atoms of the aromatic ring with interaction energies of 147.0 and 131.5 kJ/mol for CuY and AgY, respectively. More importantly, we show that water presents no inhibitory effect on the adsorption of toluene, where interaction energies of this latter were 10 kJ/mol (LiY) to 47 kJ/mol (CsY) higher than those of water. Our results point out that LiY would be less efficient for the toluene/water separation while CuY, AgY and CsY would be the ideal candidates for this application.

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.

Ab initiostudies for characterization and identification of nanocrystalline copper pyrophosphate confined in mesoporous silica

Here we employ a novel method for preparing the homogeneous copper pyrophosphate nanocrystals inside silica mesopores. In order to characterize and identify synthesized nanocrystals we performed theab initiostudies of theαphase of Cu₂P₂O₇. The electronic and crystal structure were optimized within the density functional theory with the strong electron interactions in the3dstates on copper atoms and van der Waals corrections included in calculations. The relaxed lattice parameters and atomic positions agree very well with the results of the diffraction measurements for nanocrystalline copper pyrophosphates embedded inside SBA-15 silica pores. The obtained Mott insulating state with the energy gap of 3.17 eV exhibits the antiferromagnetic order with magnetic moments on copper atoms (0.8μB) that is compatible with the experimental studies. The phonon dispersion relations were obtained to study the dynamical properties of the Cu₂P₂O₇lattice and the element-specific atomic vibrations were analyzed using the partial phonon density of states. The calculated Raman spectrum revealed the consistency of typical bands of Cu₂P₂O₇with the experimental data. The investigation that combines a new synthesis of nanomaterials with the first-principles calculations is important for better characterization and understanding of the physical properties relevant for nanotechnological applications.

Computational Insights into Molecular Adsorption Characteristics of Methylated DNA on Graphene Oxide for Multicancer Early Detection

DNA methylation is an epigenetic modification involving the transfer of a methyl group to cytosine residues of a DNA molecule. Altered DNA methylation of certain genes is associated with several diseases including cancer. Nanomaterials, such as graphene oxide (GO), offer great potential as sensing elements for methylated DNA (mDNA) detection due to their distinct properties. Understanding molecular interactions between mDNA and GO can make provision for developing a universal cancer screening test. Molecular dynamics (MD) simulation and density functional theory (DFT) calculation have been employed for investigating their detailed macro- and microscale interactions. Based upon the MD simulation, different adsorption levels of methylated and unmethylated DNAs on GO were represented by a contacting surface area (CSA), which depends on surrounding conditions (in water or a MgCl₂ solution). In water, the CSAs of the methylated and unmethylated single-stranded DNA (ssDNA) were ≈13 and ≈5 nm², respectively, representing more preferable adsorption on GO for the methylated ssDNA. In the presence of divalent ions (Mg²⁺), the CSAs of both methylated and unmethylated DNA molecules were ≈8 nm², suggesting that there was no significant difference in adsorption in a saline solution. To reveal the electrical property of GO covered by either methylated or unmethylated DNA, its electronic structure was investigated by the DFT calculation. The energy gaps of pristine graphene (pG) and GO adsorbed by 5-methylcytosine (5mC) were 1.6 and 12.9 meV, respectively, while cytosine adsorption resulted in lower energy gaps (1.2 meV for pG and 9.5 meV for GO). When comparing methylated DNA-covered GO with that covered with unmethylated DNA, remarkable differences in electrical conductivity, which were caused by the electronic structure of GO, were observed. These findings will provide a new route for an efficient detection method of DNA methylation, which can further be used to develop a universal cancer test.

Uncertainty of exchange-correlation functionals in density functional theory calculations for lithium-based solid electrolytes on the case study of lithium phosphorus oxynitride

Amorphous lithium phosphorus oxynitride (LIPON) has emerged as a promising solid electrolyte for all-solid-state thin-film lithium batteries. In this context, the use of theoretical modeling to characterize, understand, or screen material properties is becoming increasingly important to complement experimental analysis or elucidate features at atomistic level that are difficult to obtain through experimental studies. Density functional theory (DFT) is the method of choice for quantum mechanical material modeling at the atomistic scale. The current state of the art represents DFT values, such as the formation or migration energies relevant for bulk phase of materials, as absolute numbers. Estimating the accuracy or fluctuation range of the different density functionals is challenging. In order to investigate the thermodynamic and kinetic properties of LIPON by DFT, an approach to describe the fluctuation range caused by the choice of the exchange-correlation (XC) functional is developed. Three different model systems were chosen to characterize various structural features of amorphous LIPON, which are distinguished by the cross-linking of the PO_u N_4-u -structural units. The uncertainty Ũ is introduced as a parameter describing the fluctuation range of energy values. The uncertainty approach does not determine the accuracy of DFT results, but rather a fluctuation range in the DFT results without the need for a reference value from a higher level of theory or experiment. The uncertainty was determined for both the thermodynamic Li-vacancy formation energies and the kinetic Li-vacancy migration energies in LIPON. We assume that the uncertainty approach can be applied to different material systems with different density functionals.

First-principles calculations of hybrid inorganic-organic interfaces: from state-of-the-art to best practice

The computational characterization of inorganic-organic hybrid interfaces is arguably one of the technically most challenging applications of density functional theory. Due to the fundamentally different electronic properties of the inorganic and the organic components of a hybrid interface, the proper choice of the electronic structure method, of the algorithms to solve these methods, and of the parameters that enter these algorithms is highly non-trivial. In fact, computational choices that work well for one of the components often perform poorly for the other. As a consequence, default settings for one materials class are typically inadequate for the hybrid system, which makes calculations employing such settings inefficient and sometimes even prone to erroneous results. To address this issue, we discuss how to choose appropriate atomistic representations for the system under investigation, we highlight the role of the exchange-correlation functional and the van der Waals correction employed in the calculation and we provide tips and tricks how to efficiently converge the self-consistent field cycle and to obtain accurate geometries. We particularly focus on potentially unexpected pitfalls and the errors they incur. As a summary, we provide a list of best practice rules for interface simulations that should especially serve as a useful starting point for less experienced users and newcomers to the field.

Crystal Structure Prediction Methods for Organic Molecules: State of the Art

The prediction of the crystal structures that a given organic molecule is likely to form is an important theoretical problem of significant interest for the pharmaceutical and agrochemical industries, among others. As evidenced by a series of six blind tests organized over the past 2 decades, methodologies for crystal structure prediction (CSP) have witnessed substantial progress and have now reached a stage of development where they can begin to be applied to systems of practical significance. This article reviews the state of the art in general-purpose methodologies for CSP, placing them within a common framework that highlights both their similarities and their differences. The review discusses specific areas that constitute the main focus of current research efforts toward improving the reliability and widening applicability of these methodologies, and offers some perspectives for the evolution of this technology over the next decade.

New atoms-in-molecules dispersion models for use in ab initio derived force fields

Recently, substantial research efforts have gone into bridging the accuracy-efficiency gap between parameterized force field models and quantum chemical calculations by extracting molecule-specific force fields directly from ab initio data in a robust and automated manner. One of the challenging aspects is deriving localized atomic polarizabilities for pairwise distributed dispersion models. The Tkatchenko-Scheffler model is based upon correcting free-atom C₆ coefficients according to the square of the ratio of the atom-in-molecule volume to the free-atom volume. However, it has recently been shown that a more accurate relationship can be found if static atomic polarizabilities are also taken into account. Using this relationship, we develop two modified Tkatchenko-Scheffler dispersion models and benchmark their performance against SAPT2+3 reference data and other commonly used dispersion models.

Density Functional Theory Study of the Structure of the Pillared Hofmann compound Ni(3-Methy-4,4'-bipyridine)[Ni(CN)4] (Ni-BpyMe or PICNIC-21)

We use dispersion-corrected density functional theory (DFT) to investigate the structure of the pillared Hofmann compound Ni(3-Methy-4,4'-bipyridine)[Ni(CN)4] (Ni-BpyMe for short, or PICNIC-21). We model the disorder found in experimental X-ray structure refinement via an ensemble of supercells with ordered ligand orientation configurations. The ensemble-averaged structure agrees very well with experiment, except for the positions of the methyl group hydrogen atoms. While the dihedral angles between the bipyridal rings of each BpyMe ligand of the averaged structure is 90°, the local dihedral angles are about 80°. DFT screening of configurations where the crystallographic a/b ratio is constrained to equal 1 fail to find the configurations that are most stable when a/b is set to its distorted experimental value of a/b = 0.86, demonstrating the difficulty of solving pillared Hofmann structures purely theoretically without experimental input. The waviness of the Ni(CN)2 sheets is explained as a tendency to maximize dispersion interactions between these sheets and the methyl pyridine rings. This waviness leads to greater residual pore space and greater adsorbate uptake at low pressure compared with the analogous pillared compound Ni-Bpene (PICNIC-60).

Encapsulation of Highly Volatile Fragrances in Y Zeolites for Sustained Release: Experimental and Theoretical Studies

Volatility is an inherent fragrance attribute and typically implies a reduced perception over time. One possibility to elongate odor perception is utilizing controlled fragrance-delivery systems. Herein, the Y type of faujasite with different extra-framework cations (abbreviated as ZY, where Z represents Na+, Ca2+, or La3+) was examined as potential carriers for fragrance entrapment and delivery. d-Limonene (Lim) and linalool (Lol) as model fragrances were loaded in the pore space of Y zeolites, yielding composites FG@ZY (FG = Lim, Lol). It was found that the fragrance release profiles correlate highly with the cationic species located in the nonframework. The retention of fragrances in matrices increases in the order NaY < CaY < LaY for either limonene or linalool. Interestingly, the release rate of limonene was significantly slower than that of linalool when encapsulated in the same zeolite, although neat limonene has a much higher saturated vapor pressure than linalool. For instance, the total fraction of aroma released from Lim@LaY over 30 days was about 10%, while the value was ∼20% for Lol@LaY. Based on the density functional theory calculations, the above results could be well rationalized by the electrostatic attraction and shape selectivity of microporous matrices to the dopant molecules.

Deep Learning Based Prediction of Perovskite Lattice Parameters from Hirshfeld Surface Fingerprints

This Letter describes the use of deep learning methods on Hirshfeld surface representations of crystal structure, as an automated means of predicting lattice parameters in cubic inorganic perovskites. While Hirshfeld Surface Analysis is a well-established tool in organic crystallography, we also introduce modified computational protocols for Hirshfeld Surface Analysis tailored specifically to account for nuanced but important differences dealing with inorganic crystals. We demonstrate how two-dimensional Hirshfeld surface fingerprints can serve as a rich "database" of information encoding the complexity of relationships between chemical bonding and bond geometry characteristics of perovskites. Our results are compared with other studies on lattice parameter prediction involving both experimental and computationally derived data, and it is shown that our approach is an improvement over other reported methods. The paper concludes by discussing how this work opens new avenues for data-driven high throughput computational predictions of structure-property relationships involving complex crystal chemistries.

Alkali Doping Leads to Charge-Transfer Salt Formation in a Two-Dimensional Metal-Organic Framework

Efficient charge transfer across metal-organic interfaces is a key physical process in modern organic electronics devices, and characterization of the energy level alignment at the interface is crucial to enable a rational device design. We show that the insertion of alkali atoms can significantly change the structure and electronic properties of a metal-organic interface. Coadsorption of tetracyanoquinodimethane (TCNQ) and potassium on a Ag(111) surface leads to the formation of a two-dimensional charge transfer salt, with properties quite different from those of the two-dimensional Ag adatom TCNQ metal-organic framework formed in the absence of K doping. We establish a highly accurate structural model by combination of quantitative X-ray standing wave measurements, scanning tunnelling microscopy, and density-functional theory (DFT) calculations. Full agreement between the experimental data and the computational prediction of the structure is only achieved by inclusion of a charge-transfer-scaled dispersion correction in the DFT, which correctly accounts for the effects of strong charge transfer on the atomic polarizability of potassium. The commensurate surface layer formed by TCNQ and K is dominated by strong charge transfer and ionic bonding and is accompanied by a structural and electronic decoupling from the underlying metal substrate. The consequence is a significant change in energy level alignment and work function compared to TCNQ on Ag(111). Possible implications of charge-transfer salt formation at metal-organic interfaces for organic thin-film devices are discussed.

Exploitable Magnetic Anisotropy of the Two-Dimensional Magnet CrI3

Magnetic anisotropy often plays a central role in various static and dynamic properties of magnetic materials. In particular, for two-dimensional (2D) van der Waals materials, as inferred from the Mermin-Wagner theorem, it is an essential prerequisite for stabilizing ferromagnetic order. In this work, we carry out first-principles calculations for a CrI₃ monolayer and investigate how its magnetic anisotropy is interrelated to adjustable parameters governing the underlying electronic structure. We explore various routes for controlled manipulation of magnetic anisotropy: chemical adsorption, substitutional doping, optical excitation, and charge transfer through a heterostructure. In particular, the vertical stacking of CrI₃ and graphene is noteworthy in regard to controlling magnetic anisotropy: the spin anisotropy axis is switchable between the out-of-plane and in-plane directions, which is accompanied by a variation in the anisotropy energy of up to 500%. Our results show the possibility that dynamic control of the anisotropy of the 2D magnet CrI₃ may enable the development of an advanced spintronic device with enhanced energy efficiency and high operation speed.

Contributions of IQA electron correlation in understanding the chemical bond and non-covalent interactions

The quantum topological energy partitioning method Interacting Quantum Atoms (IQA) has been applied for over a decade resulting in an enlightening analysis of a variety of systems. In the last three years we have enriched this analysis by incorporating into IQA the two-particle density matrix obtained from Møller–Plesset (MP) perturbation theory. This work led to a new computational and interpretational tool to generate atomistic electron correlation and thus topologically based dispersion energies. Such an analysis determines the effects of electron correlation within atoms and between atoms, which covers both bonded and non-bonded “through -space” atom–atom interactions within a molecule or molecular complex. A series of papers published by us and other groups shows that the behavior of electron correlation is deeply ingrained in structural chemistry. Some concepts that were shown to be connected to bond correlation are bond order, multiplicity, aromaticity, and hydrogen bonding. Moreover, the concepts of covalency and ionicity were shown not to be mutually excluding but to both contribute to the stability of polar bonds. The correlation energy is considerably easier to predict by machine learning (kriging) than other IQA terms. Regarding the nature of the hydrogen bond, correlation energy presents itself in an almost contradicting way: there is much localized correlation energy in a hydrogen bond system, but its overall effect is null due to internal cancelation. Furthermore, the QTAIM delocalization index has a connection with correlation energy. We also explore the role of electron correlation in protobranching, which provides an explanation for the extra stabilization present in branched alkanes compared to their linear counterparts. We hope to show the importance of understanding the true nature of the correlation energy as the foundation of a modern representation of dispersion forces for ab initio, DFT, and force field calculations.

Temperature, strain and charge mediated multiple and dynamical phase changes of selenium and tellurium

Semiconducting selenium and tellurium in their 3D bulk trigonal structures consist of parallel and weakly interacting helical chains of atoms and display a number of peculiarities. We predict that thermal excitations, 2D compressive strain and excess charge of positive and negative polarity mediate metal-insulator transitions by transforming these semiconductors into different metallic crystal structures. When heated to high temperature, or compressed, or charged positively, they change into a simple cubic structure with metallic bands, which is very rare among elemental crystals. When charged negatively, they transform first into body-centered tetragonal and subsequently into the body-centered orthorhombic structures with increasing negative charging. These two new structures stabilized by excess electrons also have overlapping metallic bands and quasi 2D and 1D substructures of lower dimensionality. Since the external charging of crystals can be achieved through their surfaces, the effects of charging on 2D structures of selenium and tellurium are also investigated. Similar structural transformations have been mediated also in 2D nanosheets and free-standing monolayers of these elements. These phase changes assisted by phonons are dynamical, reversible and tunable; the resulting metal-insulator transitions can occur within very short time intervals and may offer important device applications.

Including dispersion in density functional theory for adsorption on flat oxide surfaces, in metal-organic frameworks and in acidic zeolites

We examine the performance of nine commonly used methods for including dispersion interactions in density functional theory (DFT): three different parametrizations of damped 1/Rn terms (n = 6, 8, …) added to the DFT energy (Grimme's D2 and D3 parameterizations as well as that of Tkatchenko and Scheffler), three different implementations of the many-body dispersion approach (MBD, MBD/HI and MBD/FI), the density-dependent energy correction, called dDsC, and two "first generation" van der Waals density functionals, revPBE-vdW and optB86b-vdW. As test set we use eight molecule-surface systems for which agreement has been reached between experiment and hybrid QM:QM calculations within chemical accuracy limits (±4.2 kJ mol-1). It includes adsorption of carbon monoxide and dioxide in the Mg2(2,5-dioxido-1,4-benzenedicarboxylate) metal-organic framework (Mg-MOF-74, CPO-27-Mg), adsorption of carbon monoxide as well as of monolayers of methane and ethane on the MgO(001) surface, as well as adsorption of methane, ethane and propane in H-chabazite (H-CHA). D2 with Ne parameters for Mg2+, D2(Ne), MBD/HI and MBD/FI perform best. With the PBE functional, the mean unsigned errors are 6.1, 5.6 and 5.4 kJ mol-1, respectively.

Extension and evaluation of the D4 London-dispersion model for periodic systems

We present an extension of the DFT-D4 model [J. Chem. Phys., 2019, 150, 154122] for periodic systems. The main new ingredients are additional reference polarizabilities for highly-coordinated group 1-5 elements derived from pseudo-periodic electrostatically-embedded cluster calculations. To illustrate the performance of the updated method, several test cases are considered, for which we compare D4 to its predecessor D3(BJ), as well as to a comprehensive set of other dispersion-corrected methods. The largest improvements are observed for solid-state polarizabilities of 16 inorganic salts, where the D4 model achieves an unprecedented accuracy, surpassing its predecessor as well as other, computationally much more demanding approaches. For cell volumes and lattice energies of two sets of chemically diverse molecular crystals, the accuracy gain is less pronounced compared to the already excellently performing D3(BJ) method. For the challenging adsorption energies of small organic molecules on metallic as well as on ionic surfaces, DFT-D4 provides values in good agreement with experimental and/or high-level references. These results suggest the application of the proposed D4 model as a physically improved yet computationally efficient dispersion correction for standard DFT calculations as well as low-cost approaches like semi-empirical or even force-field models.

Structural diversity in conducting bilayer salts (CNB-EDT-TTF)4A

The family of recently described salts based on the electron donor CNB-EDT-TTF and different anions A, with general formula (CNB-EDT-TTF)₄A, constitutes an unprecedented type of molecular conductor based on a bilayer structure of the donors.