Long-range Dispersion Interactions Research Articles

Structure of Graphene Grown on Cu(111): X-Ray Standing Wave Measurement and Density Functional Theory Prediction.

We report the quantitative adsorption structure of pristine graphene on Cu(111) determined using the normal incidence x-ray standing wave technique. The experiments constitute an important benchmark reference for the development of density functional theory approximations able to capture long-range dispersion interactions. Electronic structure calculations based on many-body dispersion-inclusive density functional theory are able to accurately predict the absolute measure and variation of adsorption height when the coexistence of multiple moiré superstructures is considered. This provides a structural model consistent with scanning probe microscopy results.

Combined study of phase transitions in the P2-type NaXNi1/3Mn2/3O2 cathode material: experimental, ab-initio and multiphase-field results

The research of new electrode materials such as sodium intercalation compounds is key to meet the challenges of future demands of sustainable energy storage. For these batteries, the intercalation behavior on the micro-scale is governed by a complex interplay of chemical, electrical and mechanical forces strongly influencing the overall cell performance. The multiphase-field method is a suitable tool to study these multi-physics and bridge the scale from ab-initio methods to the cell level. In this work, we follow a combined approach of experiments, density functional theory (DFT) calculations and multiphase-field simulations to predict thermodynamic and kinetic properties for the P2-type NaXNi1/3Mn2/3O2 sodium-ion cathode material. Experimentally, we obtain the thermodynamic potential and diffusion coefficients at various sodium contents using electrochemical techniques and discuss limitations of the experimentally applied methods. DFT is used to identify stable phases by calculating an energy hull curve. Then, the influence of long-range dispersion interactions and the exchange-correlation functional on the voltage curve is investigated by comparison with experimental results. Finally, multiphase-field simulations are performed based on inputs from experiments and DFT. The fitting of phase-specific chemical free energies from DFT calculations and experimental data is discussed. Our results highlight the thermodynamic consistency of all three approaches close to thermodynamic equilibrium. Furthermore, the phase-field method accurately describes the kinetics of the system including multiple phase transitions, by which we unravel the mechanism of the P2-O2 phase transition in a single crystal under the influence of intercalation reaction, bulk diffusion and elastic deformation. The model is able to predict the kinetic capacity loss depending on charging rate in agreement with C-rate experiments.

Toward Modeling the Structure of Electrolytes at Charged Mineral Interfaces Using Classical Density Functional Theory.

The organization of water molecules and ions between charged mineral surfaces determines the stability of colloidal suspensions and the strength of phase-separated particulate gels. In this article, we assemble a density functional that measures the free energy due to the interaction of water molecules and ions in electric double layers. The model accounts for the finite size of the particles using fundamental measure theory, hydrogen-bonding between water molecules using Wertheim's statistical association theory, long-range dispersion interactions using Barker and Henderson's high-temperature expansion, electrostatic correlations using a functionalized mean-spherical approximation, and Coulomb forces through the Poisson equation. These contributions are shown to produce highly correlated structures, aptly rendering the layering of counterions and co-ions at highly charged surfaces and permitting the solvation of ions and surfaces to be measured by a combination of short-range associations and long-ranged attractions. The model is tested in a planar geometry near soft, charged surfaces to reproduce the structure of water near graphene and mica. For mica surfaces, explicitly representing the density of the outer oxygen layer of the exposed silica tetrahedra allows water molecules to hydrogen-bond to the solid. When electrostatic interactions are included, water molecules assume a hybrid character, being accounted for implicitly in the dielectric constant but explicitly otherwise. The disjoining pressure between approaching like-charged surfaces is calculated, demonstrating the model's ability to probe pressure oscillations that arise during the expulsion of ions and water layers from the interfacial gap and predict strong interattractive stresses that form at narrow interfacial spacing when the surface charge is overscreened. This interattractive stress arises not due to in-plane correlations under strong electrostatic coupling but due to the out-of-plane structuring of associating ions and water molecules.

The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems.

The effective fragment molecular orbital (EFMO) method has been developed to predict the total energy of a very large molecular system accurately (with respect to the underlying quantum mechanical method) and efficiently by taking advantage of the locality of strong chemical interactions and employing a two-level hierarchical parallelism. The accuracy of the EFMO method is partly attributed to the accurate and robust intermolecular interaction prediction between distant fragments, in particular, the many-body polarization and dispersion effects, which require the generation of static and dynamic polarizability tensors by solving the coupled perturbed Hartree-Fock (CPHF) and time-dependent HF (TDHF) equations, respectively. Solving the CPHF and TDHF equations is the main EFMO computational bottleneck due to the inefficient (serial) and I/O-intensive implementation of the CPHF and TDHF solvers. In this work, the efficiency and scalability of the EFMO method are significantly improved with a new CPU memory-based implementation for solving the CPHF and TDHF equations that are parallelized by either message passing interface (MPI) or hybrid MPI/OpenMP. The accuracy of the EFMO method is demonstrated for both covalently bonded systems and noncovalently bound molecular clusters by systematically examining the effects of basis sets and a key distance-related cutoff parameter, Rcut. Rcut determines whether a fragment pair (dimer) is treated by the chosen ab initio method or calculated using the effective fragment potential (EFP) method (separated dimers). Decreasing the value of Rcut increases the number of separated (EFP) dimers, thereby decreasing the computational effort. It is demonstrated that excellent accuracy (<1 kcal/mol error per fragment) can be achieved when using a sufficiently large basis set with diffuse functions coupled with a small Rcut value. With the new parallel implementation, the total EFMO wall time is substantially reduced, especially with a high number of MPI ranks. Given a sufficient workload, nearly ideal strong scaling is achieved for the CPHF and TDHF parts of the calculation. For the first time, EFMO calculations with the inclusion of long-range polarization and dispersion interactions on a hydrated mesoporous silica nanoparticle with explicit water solvent molecules (more than 15k atoms) are achieved on a massively parallel supercomputer using nearly 1000 physical nodes. In addition, EFMO calculations on the carbinolamine formation step of an amine-catalyzed aldol reaction at the nanoscale with explicit solvent effects are presented.

Analysing the stability of He-filled hydrates: how many He atoms fit in the sII crystal?

Clathrate hydrates have the ability to encapsulate atoms and molecules within their cavities, and thus they could be potentially large storage capacity materials. The present work studies the multiple cage occupancy effects in the recently discovered He@sII crystal. On the basis of previous theoretical and experimental findings, the stability of He(1/1)@sII, He(1/4)@sII and He(2/4)@sII crystals was analysed in terms of structural, mechanical and energetic properties. For this purpose, first-principles DFT/DFT-D computations were performed by using both semi-local and non-local functionals, not only to elucidate which configuration is the most energetically favoured, but also to scrutinize the relevance of the long-range dispersion interactions in these kinds of compounds. We have encountered that dispersion interactions play a fundamental role in describing the underlying interactions, and different tendencies were observed depending on the choice of the functional. We found that PW86PBE-XDM shows the best performance, while the non-local functionals tested here were not able to correctly account for them. The present results reveal that the most stable configuration is the one presenting singly occupied D cages and tetrahedrally occupied H cages (He(1/4)@sII) in line with the experimental observation.

Thermophysical property prediction of biodiesel mixtures at extreme conditions using molecular dynamics simulation

Liquid biofuels such as biodiesel are playing an increasing role in renewable energy utilisation, but accurate predictions of fuel properties at extreme conditions remain challenging. In this study, molecular dynamics (MD) simulation with classical force field is performed to obtain the thermophysical properties of biodiesel over extended ranges of temperatures and pressures. The predicted properties include the critical temperature, critical density, critical pressure, surface tension, viscosity, thermal conductivity and diffusion coefficient. The specific MD setup for fuel thermophysical property prediction is examined. It is observed that the long-range dispersion interaction is essential to accurately predicting the surface tension, and averaging over a sufficient number of independent replication simulations is required to eliminate the statistical error when using the Green-Kubo method for viscosity calculation. The reliability of MD approach is validated against experimental data at normal temperature and pressure. The equilibrium MD simulation has an advantage over nonequilibrium MD simulation when building databases of fuel properties. Moreover, the properties of biodiesel are compared with conventional diesel to elucidate the effects of fuel composition and molecular structure of the fuel surrogates on fuel thermophysical properties. For biodiesel utilisation, higher values of critical temperature, surface tension and viscosity, lower diffusivity together with the increased aggregation tendency in bath gas indicate the needs of further optimisation of injection system to achieve the desired mixing in combustion applications.

Charge-modulated calcite surface for anionic surfactant adsorption from molecular dynamics simulations

Since surfactant adsorption on reservoir rock means the loss of a valuable component, it makes surfactant flooding economically less feasible. In this work, adsorption behaviors of anionic surfactant on calcite surface were investigated with different charge states for the first time using molecular dynamic (MD) simulations. To reveal the underlying adsorption mechanism, adsorption processes were systematically analyzed with the adsorption energy, mean square displacement (MSD), relative concentration distribution (RCD), and radial distribution function (RDF). The results showed that sodium dodecyl sulfate had the strongest adsorption on the surface of calcite. When calcite surface was modelled with a charge state up to 80 e (8.24 × 1014 e/cm2), sodium dodecyl benzene sulfonate (SDBS) was found to be most stable on 10 e (1.03 × 1014 e/cm2) positively charge surface, with the maximum adsorption energy and the minimum diffusion coefficient. Increasing the carbon chain length of surfactant tail, the adsorption energy of SDBS became weaker, which can be attributed to the van der Waals interactions (long-range dispersion interactions) among surfactants. A monolayer or bilayer of surfactants can be derived based on the RCD. RDF curves revealed that hydrogen bonds played an important role in interactions among calcite surface, water molecules, and head groups of surfactants. The obtained results offer important insights into charge-modulated anionic surfactant adsorption on calcite surface at molecular scale and a guide to optimal flooding conditions with reduced surfactant loss.

The effect of alkylation on the micro-solvation of ethers revealed by highly localized water librational motion.

The specific far-infrared spectral signatures associated with highly localized large-amplitude out-of-plane librational motion of water molecules have recently been demonstrated to provide sensitive spectroscopic probes for the micro-solvation of organic molecules [Mihrin et al., Phys. Chem. Chem. Phys. 21(4), 1717 (2019)]. The present work employs this direct far-infrared spectroscopic approach to investigate the non-covalent intermolecular forces involved in the micro-solvation of a selection of seven ether molecules with systematically varied alkyl substituents: dimethyl ether, diethyl ether, diisopropyl ether, ethyl methyl ether, t-butyl methyl ether, and t-butyl ethyl ether. The ranking of the observed out-of-plane water librational band signatures for this selected series of ether-water complexes embedded in inert neon matrices at 4K reveals information about the interplay of directional intermolecular hydrogen bond motifs and non-directional and long-range dispersion interactions for the micro-solvated structures. These far-infrared observables differentiate minor subtle effects introduced by specific alkyl substituents and serve as rigorous experimental benchmarks for modern quantum chemical methodologies of various levels of scalability, which often fail to accurately predict the structural variations and corresponding vibrational signatures of the closely related systems. The accurate interaction energies of the series of ether-water complexes have been predicted by the domain based local pair natural orbital coupled cluster theory with single-, double-, and perturbative triple excitations, followed by a local energy decomposition analysis of the energy components. In some cases, the secondary dispersion forces are in direct competition with the primary intermolecular hydrogen bonds as witnessed by the specific out-of-plane librational signatures.

Catalytic formation of oxalic acid on the partially oxidised greigite Fe3S4(001) surface.

Greigite (Fe3S4), with its ferredoxin-like 4Fe-4S redox centres, is a naturally occurring mineral capable of acting as a catalyst in the conversion of carbon dioxide (CO2) into low molecular-weight organic acids (LMWOAs), which are of paramount significance in several soil and plant processes as well as in the chemical industry. In this paper, we report the reaction between CO2 and water (H2O) to form oxalic acid (H2C2O4) on the partially oxidised greigite Fe3S4(001) surface by means of spin-polarised density functional theory calculations with on-site Coulomb corrections and long-range dispersion interactions (DFT+U-D2). We have calculated the bulk phase of Fe3S4 and the two reconstructed Tasker type 3 terminations of its (001) surface, whose properties are in good agreement with available experimental data. We have obtained the relevant phase diagram, showing that the Fe3S4(001) surface becomes 62.5% partially oxidised, by replacing S by O atoms, in the presence of water at the typical conditions of calcination [Mitchell et al. Faraday Discuss. 2021, 230, 30-51]. The adsorption and co-adsorption of the reactants on the partially oxidised Fe3S4(001) surface are exothermic processes. We have considered three mechanistic pathways to explain the formation of H2C2O4, showing that the coupling of the C-C bond and second protonation are the elementary steps with the largest energy penalty. Our calculations suggest that the partially oxidised Fe3S4(001) surface is a mineral phase that can catalyse the formation of H2C2O4 under favourable conditions, which has important implications for natural ecosystems and is a process that can be harnessed for the industrial manufacture of this organic acid.

Considerations of Recent All-Atom Lipid Force Field Development.

Molecular simulations of biological molecules require an accurate description of molecular interactions through a force field (FF). The focus of this Perspective is on all-atom lipid FFs. Recent additions to the CHARMM36 lipid FF continue to expand a researcher's ability to probe membrane structure and function with a wide variety of biologically important lipids. Currently, there is an effort to reduce the assumptions in all-atom lipid FFs. The inclusion of long-range dispersion interaction through particle-mesh Ewald is allowing for more accurate descriptions of lipid bilayer and monolayer properties without additional computational cost. Soon, simulations with lipid FFs will no longer depend on short-range cutoffs and will accurately represent long-range dispersion. This requires efficient FF parametrization with an automated approach due to FF complexity. In addition, polarizable FFs for lipids will be important for the next generation of simulations that accurately represent how molecule interactions respond to a varied environment.

Van der Waals corrected density functionals for cylindrical surfaces: Ammonia and nitrogen dioxide adsorbed on a single-walled carbon nanotube

We extend the damped Zaremba-Kohn model (dZK) for long-range dispersion interaction between a molecule and a planar surface [J. Tao, H. Tang, A. Patra, P. Bhattarai, and J. P. Perdew, Phys. Rev. B 97, 165403 (2018)] to molecules adsorbed on a curved cylindrical surface, and employ this extended model as an additive correction to the semilocal density functionals PBE (Perdew-Burke-Ernzerhof) and SCAN (strongly constrained and appropriately normed). The resulting PBE+vdW (van der Waals)-dZK and SCAN+vdW-dZK are applied to two systems, $\mathrm{N}{\mathrm{H}}_{3}$ and $\mathrm{N}{\mathrm{O}}_{2}$ molecules adsorbed on a single-wall carbon nanotube (CNT), for calculations of binding energies and equilibrium distances. For comparison, the results from vdW nonlocal functionals, such as SCAN+rVV10 and PBE+rVV10, are also presented. The binding energies from PBE+rVV10 (Vydrov and Van Voorhis), SCAN+rVV10, PBE+vdW-dZK, and SCAN+vdW-dZK are about 70--115 meV for the system of $\mathrm{CNT}+\mathrm{N}{\mathrm{H}}_{3}$ and 300--500 meV for the system of $\mathrm{CNT}+\mathrm{N}{\mathrm{O}}_{2}$. The results from PBE+vdW-dZK and SCAN+vdW-dZK are closer to each other than those from PBE+rVV10 and SCAN+rVV10 are. The relatively closer results from PBE+vdW-dZK and SCAN+vdW-dZK indicate the consistency of our developed vdW\ensuremath{-}dZK model for cylindrical surfaces. All methods, including PBE, SCAN, PBE+rVV10, SCAN+rVV10, PBE+vdW-dZK, and SCAN+vdW-dZK, give approximately the same binding energy differences between two adsorption configurations (types I and II) for the two systems. This implies that the two adsorption sites have approximately the same adsorption stability. The exponent of the vdW interaction power law from our vdW-dZK model for the two systems is about 0 at short distance, largely due to the damping factor, and tends slowly to \ensuremath{-}4 to \ensuremath{-}4.5 at distances $D$ about 20--50 \AA{}. At even larger distances, the vdW power-law exponent approaches \ensuremath{-}5. This feature is very similar to the one calculated with random-phase approximation and renormalization group approaches, supporting the applicability of our methods. Our developed vdW-dZK method provides a highly efficient and reliable method for large systems with cylindrical surfaces, such as vdW interactions with nanotubes.

Room temperature gas sensing mechanism of SnO2 towards chloroform: Comparing first principles calculations with sensing experiments

Herein, room temperature sensing of chloroform (CHCl3) gas using SnO2 nanostructured thin films synthesized via a single-step aerosol chemical vapor deposition (ACVD) process is demonstrated. The sensing mechanism is investigated by means of dispersion-corrected density functional theory (DFT) calculations and ab initio molecular dynamics (AIMD) simulations of chloroform’s adsorption on the (110) facet of rutile SnO2. Theoretical calculations demonstrate that direct adsorption of chloroform on the stoichiometric and the oxygen defective SnO2 surface is thermodynamically favorable. Upon adsorption, chloroform molecules donate charge to the surface inducing a drop in the surface resistance, thus promoting a sensing response. Calculated adsorption energies are in the range of (0.7–1.0 eV) per chloroform molecule, which is noticeably larger than the previously calculated adsorption energies on graphene and graphene oxide (0.2–0.4 eV), suggesting a stronger binding on metal-oxides compared to carbon-based materials. Long-range dispersive interactions are found to account for>50% of the calculated adsorption energies. AIMD simulations in the canonical ensemble at room temperature show that chloroform molecules minimally interact with the ionosorbed oxygen species (O2-) suggesting that the room temperature sensing mechanism is mainly attributed to the direct binding of chloroform molecules on the sensor surface.

Exploring the Limits of the XYG3-Type Doubly Hybrid Approximations for the Main-Group Chemistry: The xDH@B3LYP Model.

Despite being the most accurate class of density functional approximations for the main-group chemistry, doubly hybrid approximations (DHAs) are generally considered to be incomplete in describing the medium- to long-range dispersive interactions. The existing DHAs are often supplemented with empirical long-range dispersion corrections. By using the extensive and chemically diverse GMTKN55 database, we explore the limits of the XYG3-type DHAs using the B3LYP reference orbitals, namely, xDH@B3LYP, with a gradually relaxed constraint on the mixing parameters of DHAs. Our results demonstrate that the xDH@B3LYP model can provide a balanced description of both covalent and noncovalent interactions with the accuracy and robustness comparable to or even better than the very expensive composite methods in wave function theory. Such an accuracy can be achieved without resorting to the use of any long-range correction scheme, shedding new light on the development of DHAs.

An accurate and transferable machine learning potential for carbon.

We present an accurate machine learning (ML) model for atomistic simulations of carbon, constructed using the Gaussian approximation potential (GAP) methodology. The potential, named GAP-20, describes the properties of the bulk crystalline and amorphous phases, crystal surfaces, and defect structures with an accuracy approaching that of direct ab initio simulation, but at a significantly reduced cost. We combine structural databases for amorphous carbon and graphene, which we extend substantially by adding suitable configurations, for example, for defects in graphene and other nanostructures. The final potential is fitted to reference data computed using the optB88-vdW density functional theory (DFT) functional. Dispersion interactions, which are crucial to describe multilayer carbonaceous materials, are therefore implicitly included. We additionally account for long-range dispersion interactions using a semianalytical two-body term and show that an improved model can be obtained through an optimization of the many-body smooth overlap of atomic positions descriptor. We rigorously test the potential on lattice parameters, bond lengths, formation energies, and phonon dispersions of numerous carbon allotropes. We compare the formation energies of an extensive set of defect structures, surfaces, and surface reconstructions to DFT reference calculations. The present work demonstrates the ability to combine, in the same ML model, the previously attained flexibility required for amorphous carbon [V. L. Deringer and G. Csányi, Phys. Rev. B 95, 094203 (2017)] with the high numerical accuracy necessary for crystalline graphene [Rowe et al., Phys. Rev. B 97, 054303 (2018)], thereby providing an interatomic potential that will be applicable to a wide range of applications concerning diverse forms of bulk and nanostructured carbon.

Theoretical analysis of doped graphene as cathode catalyst in Li-O2 and Na-O2 batteries – the impact of the computational scheme

Understanding the reactions in M-O2 cells (M = Li or Na) is of great importance for further advancement of this promising technology. Computational modelling can be helpful along this way, but an adequate approach is needed to model such complex systems. We propose a new scheme for modelling processes in M-O2 cells, where reference energies are obtained from high-level theory, CCSD(T), while the interactions of reaction intermediates with catalyst surfaces are extracted from computationally less expensive DFT. The approach is demonstrated for the case of graphene-based surfaces as model catalysts in Li-O2 and Na-O2 cells using the minimum viable mechanism. B-doped graphene was identified as the best catalyst amongst considered surfaces, while pristine graphene performs poorly. Moreover, we show that the inclusion of dispersion corrections for DFT has a significant impact on calculated discharge and charge potentials and suggests that long-range dispersion interactions should always be considered when graphene-based materials are modelled as electrocatalysts. Finally, we offer general guidelines for designing new ORR catalysts for M-O2 cells in terms of the optimization of the interactions of catalyst surface with reaction intermediates.

Experimental and Theoretical Investigation of the Elastic Properties of HfV2O7

We investigated the elastic properties of the HfV2O7 high-temperature phase, exhibiting negative thermal expansion, in a synergetic strategy of first-principle calculations and nanoindentation experiments performed on sputtered films. Self-consistent results were obtained for the measured elastic modulus (73 ± 14 GPa) and dispersion-corrected density functional theory calculations. The elastic properties of HfV2O7 are affected by long-range dispersion interaction, which may be induced by severe modification in the second-nearest neighbor O-O bond distance as obtained upon compression. HfV2O7 is composed of HfO6, VO4, and V2O7 building blocks, whereby the latter is characterized by an increasing V-O(-V) bond length upon compression.

Compressed intramolecular dispersion interactions.

The feasibility of the compression of localized virtual orbitals is explored in the context of intramolecular long-range dispersion interactions. Singular value decomposition (SVD) of coupled cluster doubles amplitudes associated with the dispersion interactions is analyzed for a number of long-chain systems, including saturated and unsaturated hydrocarbons and a silane chain. Further decomposition of the most important amplitudes obtained from these SVDs allows for the analysis of the dispersion-specific virtual orbitals that are naturally localized. Consistent with previous work on intermolecular dispersion interactions in dimers, it is found that three important geminals arise and account for the majority of dispersion interactions at the long range, even in the many body intramolecular case. Furthermore, it is shown that as few as three localized virtual orbitals per occupied orbital can be enough to capture all pairwise long-range dispersion interactions within a molecule.

Reducing the Many-Electron Self-Interaction Error in the Second-Order Screened Exchange Method.

Preserving the beneficial properties of the second-order screened exchange (SOSEX) method, such as its freedom from one-body self-correlation error, and its seamless treatment of long-range dispersion interaction, we construct new nonlocal functionals by down-scaling the higher-order terms in the SOSEX series to reduce the many-body self-correlation error in molecular systems. Our down-scaled SOSEX (dsSOSEX) and scaled equation SOSEX (seSOSEX) approaches deliver considerably more accurate noncovalent interaction energies, reaction energies, and barrier heights than the original SOSEX method. The dsSOSEX approach improves on the description of medium- and long-range correlation, for example, in isogyric processes, while the seSOSEX approach improves on the description of processes with short- and medium-range rearrangement in the electronic structure, such as atomization. The He2+ potential energy curve shows that the many-body self-correlation error is slightly smaller in the dsSOSEX method than in the seSOSEX approach. Furthermore, the H2 potential energy curve reveals that the static correlation error can also be reduced at medium range by the dsSOSEX and seSOSEX schemes. As our dsSOSEX method provides a better description of medium- and long-range correlation, it generally leads to more accurate energetics than the seSOSEX method; hence it should be preferred over the latter. We compare our results to other empirical and nonempirical direct random phase approximation (dRPA) and beyond-dRPA methods and also discuss the possibilities for further development.

CO2 Adsorption and Activation on the (110) Chalcopyrite Surfaces: ADispersion-Corrected DFT + U Study.

We have used the density functional theory within the plane-wave framework to understand the reconstruction of most stable (110) chalcopyrite surfaces. Reconstructions of the polar surfaces are proposed, and three different possible nonpolar terminations for the (110) surface, namely, I, II, and III, are investigated. A detailed discussion on stabilities of all three surface terminations is carried out. It is generally observed that the (110) chalcopyrite surfaces encounter significant reconstruction in which the metal Fe and Cu cations in the first atomic layer considerably move downward to the surface, while the surface S anions migrate slightly outward toward the surface. We also investigated the adsorption of the CO2 molecule on the three terminations for the (110) surface by exploring various adsorption sites and configurations using density functional theory calculations, in which long-range dispersion interactions are taken into consideration. We show that the CO2 molecule is adsorbed and activated, while spontaneous dissociation of the CO2 molecule is also observed on the (110) surfaces. Structural change from a neutral linear molecule to a negatively charged (CO2–δ) slightly or considerably bent species with stretched C–O bond distances are highlighted for description of the activation of the CO2 molecule. The results address the potential catalytic activity of the (110) chalcopyrite toward the reduction and conversion of CO2 to the organic molecule, which is appropriate to the production of liquid fuels.

Off-the-shelf DFT-DISPersion methods: Are they now "on-trend" for organic molecular crystals?

Organic molecular crystals contain long-range dispersion interactions that can be challenging for solid-state methods such as density functional theory (DFT) to capture, and in some industrial sectors are overlooked in favor of classical methods to calculate atomistic properties. Hence, this publication addresses the critical question of whether dispersion corrected DFT calculations for organic crystals can reproduce the structural and energetic trends seen from experiment, i.e., whether the calculations can now be said to be truly "on-trend." In this work, we assess the performance of three of the latest dispersion-corrected DFT methods, in calculating the long-range, dispersion energy: the pairwise methods of D3(0) and D3(BJ) and the many-body dispersion method, MBD@rsSCS. We calculate the energetics and optimized structures of two homologous series of organic molecular crystals, namely, carboxylic acids and amino acids. We also use a classical force field method (using COMPASS II) and compare all results to experimental data where possible. The mean absolute error in lattice energies is 9.59 and 343.85 kJ/mol (COMPASS II), 10.17 and 16.23 kJ/mol (MBD@rsSCS), 10.57 and 18.76 kJ/mol [D3(0)], and 8.52 and 14.66 kJ/mol [D3(BJ)] for the carboxylic acids and amino acids, respectively. MBD@rsSCS produces structural and energetic trends that most closely match experimental trends, performing the most consistently across the two series and competing favorably with COMPASS II.