Toward Accurate Adsorption Energetics on Clay Surfaces

First-principles study of the effects of doping B, N, and O on the photoelectric properties of Cr adsorbed GaS

CONTEXT

To lessen the impact of the dangerous metal Cr, this paper applies the first principles to investigate the adsorption behavior and photoelectric properties of GaS on Cr. The effects of doped GaS on Cr adsorption behavior are investigated with four GaS systems, which are pure, boron (B)-doped, nitrogen (N)-doped, and oxygen (O)-doped, in order to maximize the characteristics of GaS for use in novel sectors, to obtain understanding of the impact of doping on the electronic structure and optical properties of GaS adsorption of Cr, as well as to promote the development of the material. Four GaS adsorbed Cr systems, pure, B-doped, N-doped, and O-doped, are optimized, and the optimized results show that the stable adsorption position of Cr on both pure and doped GaS is the top position of Ga atoms, whereas doped elements B, N, and O can promote the adsorption of Cr on GaS, and the order of the strength of this promotion is B > N > O.

METHOD

In this paper, molecular simulation calculations and analyses using the CASTEP module in the software Materials Studio are performed to simulate the structure optimization of GaS-adsorbed Cr materials doped with B, N, and O atoms by using the generalized gradient approximation (GGA) plane-wave pseudopotential approach [1] and the Perdew-Burke-Ernzerhof (PBE) generalized function [2]. From the convergence test, it is reasonable to set the K-point network to 4 × 4 × 1 and the truncation energy to 500 eV [3]. In this paper, a 3 × 3 × 1 supercell structure with 18 S atoms and 18 Ga atoms is selected. The convergence value of the iterative accuracy is 1.0e - 5 eV/atom, and all the atomic forces are less than 0.02 eV/Å. A vacuum layer of 16 Å is also set in the C direction to avoid interlayer interactions of GaS. First, we optimize the geometry of the model and then analyze the nature of the adsorption energy and electronic structure corresponding to the model.

Many-Body Methods for Surface Chemistry Come of Age: Achieving Consensus with Experiments

The adsorption energy of a molecule onto the surface of a material underpins a wide array of applications, spanning heterogeneous catalysis, gas storage, and many more. It is the key quantity where experimental measurements and theoretical calculations meet, with agreement being necessary for reliable predictions of chemical reaction rates and mechanisms. The prototypical molecule-surface system is CO adsorbed on MgO, but despite intense scrutiny from theory and experiment, there is still no consensus on its adsorption energy. In particular, the large cost of accurate many-body methods makes reaching converged theoretical estimates difficult, generating a wide range of values. In this work, we address this challenge, leveraging the latest advances in diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] to obtain accurate predictions for CO on MgO. These reliable theoretical estimates allow us to evaluate the inconsistencies in published temperature-programed desorption experiments, revealing that they arise from variations in employed pre-exponential factors. Utilizing this insight, we derive new experimental estimates of the (electronic) adsorption energy with a (more) precise pre-exponential factor. As a culmination of all of this effort, we are able to reach a consensus between multiple theoretical calculations and multiple experiments for the first time. In addition, we show that our recently developed cluster-based CCSD(T) approach provides a low-cost route toward achieving accurate adsorption energies. This sets the stage for affordable and reliable theoretical predictions of chemical reactions on surfaces to guide the realization of new catalysts and gas storage materials.

A fully quantum-mechanical treatment for kaolinite

Neural network potentials for kaolinite minerals have been fitted to data extracted from density functional theory calculations that were performed using the revPBE + D3 and revPBE + vdW functionals. These potentials have then been used to calculate the static and dynamic properties of the mineral. We show that revPBE + vdW is better at reproducing the static properties. However, revPBE + D3 does a better job of reproducing the experimental IR spectrum. We also consider what happens to these properties when a fully quantum treatment of the nuclei is employed. We find that nuclear quantum effects (NQEs) do not make a substantial difference to the static properties. However, when NQEs are included, the dynamic properties of the material change substantially.

Long-Range Ionic and Short-Range Hydration Effects Govern Strongly Anisotropic Clay Nanoparticle Interactions

The aggregation of clay particles in aqueous solution is a ubiquitous everyday process of broad environmental and technological importance. However, it is poorly understood at the all-important atomistic level since it depends on a complex and dynamic interplay of solvent-mediated electrostatic, hydrogen bonding, and dispersion interactions. With this in mind, we have performed an extensive set of classical molecular dynamics simulations (included enhanced sampling simulations) on the interactions between model kaolinite nanoparticles in pure and salty water. Our simulations reveal highly anisotropic behavior, in which the interaction between the nanoparticles varies from attractive to repulsive depending on the relative orientation of the nanoparticles. Detailed analysis reveals that at large separation (>1.5 nm), this interaction is dominated by electrostatic effects, whereas at smaller separations, the nature of the water hydration structure becomes critical. This study highlights an incredible richness in how clay nanoparticles interact, which should be accounted for in, for example, coarse-grained models of clay nanoparticle aggregation.

Hydrogen-bonding and nuclear quantum effects in clays

Hydrogen bonds are of paramount importance in the chemistry of clays, mediating the interaction between the clay surface and water, and for some materials between separate layers. It is well-established that the accuracy of a computational model for clays depends on the level of theory at which the electronic structure is treated. However, for hydrogen-bonded systems, the motion of light H nuclei on the electronic potential energy surface is often affected by quantum delocalization. Using path integral molecular dynamics, we show that nuclear quantum effects lead to a relatively small change in the structure of clays, but one that is comparable to the variation incurred by treating the clay at different levels of electronic structure theory. Accounting for quantum effects weakens the hydrogen bonds in clays, with H-bonds between different layers of the clay affected more than those within the same layer; this is ascribed to the fact that the confinement of an H atom inside a layer is independent of its participation in hydrogen-bonding. More importantly, the weakening of hydrogen bonds by nuclear quantum effects causes changes in the vibrational spectra of these systems, significantly shifting the O–H stretching peaks and meaning that in order to fully understand these spectra by computational modeling, both electronic and nuclear quantum effects must be included. We show that after reparameterization of the popular clay forcefield CLAYFF, the O–H stretching region of their vibrational spectra better matches the experimental one, with no detriment to the model’s agreement with other experimental properties.

Interactions between large molecules pose a puzzle for reference quantum mechanical methods

Quantum-mechanical methods are used for understanding molecular interactions throughout the natural sciences. Quantum diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] are state-of-the-art trusted wavefunction methods that have been shown to yield accurate interaction energies for small organic molecules. These methods provide valuable reference information for widely-used semi-empirical and machine learning potentials, especially where experimental information is scarce. However, agreement for systems beyond small molecules is a crucial remaining milestone for cementing the benchmark accuracy of these methods. We show that CCSD(T) and DMC interaction energies are not consistent for a set of polarizable supramolecules. Whilst there is agreement for some of the complexes, in a few key systems disagreements of up to 8 kcal mol^-1 remain. These findings thus indicate that more caution is required when aiming at reproducible non-covalent interactions between extended molecules.

Water Bridges in Clay Nanopores: Mechanisms of Formation and Impact on Hydrocarbon Transport

Clays are prevalent in the earth's crust and usually deposited in the presence of water. An unusual finding in clays is that under certain conditions, water molecules can collectively form a bridge across a clay-hosted pore. However, there are relatively few studies focused on the formation mechanism of the water bridge in clay nanopores. In this work, we use molecular dynamics simulations to investigate the formation of the water bridge and its influence on fluid transport in slit-shaped illite nanopores. Two different basal illite surface chemistries are constructed: potassium-hydroxyl (P-H) and hydroxyl-hydroxyl (H-H) structures. Because pore size and water concentration are expected to control the formation of the water bridge, our simulations span a wide range of pore sizes and water concentrations. Generally, positive potassium layers and negative hydroxyl groups in P-H nanopore can induce partial charges which in return produce instant and local electric fields, favoring the formation of the water bridge. In P-H nanopores, the water bridge happens at a relatively low water concentration. However, in H-H nanopores, the water bridge only forms at high water concentrations. Additionally, smaller pore sizes favor the formation of water bridges. However, the presence of an electric field promotes the formation of a water bridge even in larger pore sizes in P-H pores. The results also indicate that in both P-H and H-H nanopores, water adsorption films initially create a smooth surface to promote the hydrocarbon flow. In P-H nanopores, further increases in the water concentration causes a sharp decline in the self-diffusion coefficients of the hydrocarbon and water due to the formation of the water bridge. The presence of electric fields in P-H pores can however weaken the confinement effect of illite and promote the hydrocarbon flow. In contrast, in H-H nanopores, the self-diffusion coefficients decline slowly with the increase of water concentration. This is because no water bridge is formed at low water concentrations in H-H nanopores.

Efficient and accurate description of adsorption in zeolites

Accurate theoretical methods are needed to correctly describe adsorption on solid surfaces or in porous materials. The random phase approximation (RPA) with singles corrections scheme and the second order Møller-Plesset perturbation theory (MP2) are two schemes, which offer high accuracy at affordable computational cost. However, there is little knowledge about their applicability and reliability for different adsorbates and surfaces. Here, we calculate adsorption energies of seven different molecules in zeolite chabazite to show that RPA with singles corrections is superior to MP2, not only in terms of accuracy but also in terms of computer time. Therefore, RPA with singles is a suitable scheme for obtaining highly accurate adsorption energies in porous materials and similar systems.

Physisorption of Water on Graphene: Subchemical Accuracy from Many-Body Electronic Structure Methods

Wet carbon interfaces are ubiquitous in the natural world and exhibit anomalous properties, which could be exploited by emerging technologies. However, progress is limited by lack of understanding at the molecular level. Remarkably, even for the most fundamental system (a single water molecule interacting with graphene), there is no consensus on the nature of the interaction. We tackle this by performing an extensive set of complementary state-of-the-art computer simulations on some of the world's largest supercomputers. From this effort a consensus on the water-graphene interaction strength has been obtained. Our results have significant impact for the physical understanding, as they indicate that the interaction is weaker than predicted previously. They also pave the way for more accurate and reliable studies of liquid water at carbon interfaces.

Understanding non-covalent interactions in larger molecular complexes from first principles

Non-covalent interactions pervade all matter and play a fundamental role in layered materials, biological systems, and large molecular complexes. Despite this, our accumulated understanding of non-covalent interactions to date has been mainly developed in the tens-of-atoms molecular regime. This falls considerably short of the scales at which we would like to understand energy trends, structural properties, and temperature dependencies in materials where non-covalent interactions have an appreciable role. However, as more reference information is obtained beyond moderately sized molecular systems, our understanding is improving and we stand to gain pertinent insights by tackling more complex systems, such as supramolecular complexes, molecular crystals, and other soft materials. In addition, accurate reference information is needed to provide the drive for extending the predictive power of more efficient workhorse methods, such as density functional approximations that also approximate van der Waals dispersion interactions. In this perspective, we discuss the first-principles approaches that have been used to obtain reference interaction energies for beyond modestly sized molecular complexes. The methods include quantum Monte Carlo, symmetry-adapted perturbation theory, non-canonical coupled cluster theory, and approaches based on the random-phase approximation. By considering the approximations that underpin each method, the most accurate theoretical references for supramolecular complexes and molecular crystals to date are ascertained. With these, we also assess a handful of widely used exchange-correlation functionals in density functional theory. The discussion culminates in a framework for putting into perspective the accuracy of high-level wavefunction-based methods and identifying future challenges.

Ice formation on kaolinite: Insights from molecular dynamics simulations

The formation of ice affects many aspects of our everyday life as well as important technologies such as cryotherapy and cryopreservation. Foreign substances almost always aid water freezing through heterogeneous ice nucleation, but the molecular details of this process remain largely unknown. In fact, insight into the microscopic mechanism of ice formation on different substrates is difficult to obtain even if state-of-the-art experimental techniques are used. At the same time, atomistic simulations of heterogeneous ice nucleation frequently face extraordinary challenges due to the complexity of the water-substrate interaction and the long time scales that characterize nucleation events. Here, we have investigated several aspects of molecular dynamics simulations of heterogeneous ice nucleation considering as a prototypical ice nucleating material the clay mineral kaolinite, which is of relevance in atmospheric science. We show via seeded molecular dynamics simulations that ice nucleation on the hydroxylated (001) face of kaolinite proceeds exclusively via the formation of the hexagonal ice polytype. The critical nucleus size is two times smaller than that obtained for homogeneous nucleation at the same supercooling. Previous findings suggested that the flexibility of the kaolinite surface can alter the time scale for ice nucleation within molecular dynamics simulations. However, we here demonstrate that equally flexible (or non flexible) kaolinite surfaces can lead to very different outcomes in terms of ice formation, according to whether or not the surface relaxation of the clay is taken into account. We show that very small structural changes upon relaxation dramatically alter the ability of kaolinite to provide a template for the formation of a hexagonal overlayer of water molecules at the water-kaolinite interface, and that this relaxation therefore determines the nucleation ability of this mineral.

Dispersion-Corrected Spin-Component-Scaled Double-Hybrid Density Functional Theory: Implementation and Performance for Non-covalent Interactions

The implementation of 300 combinations of generalized gradient approximation/local density approximation exchange-correlation dispersion-corrected spin-component-scaled double-hybrid (DSD) density functional theory (DFT) methods has been carried out and the performance assessed against several DFT and post-Hartree-Fock methods, enabling further advancements toward the long-standing challenge of accurate prediction of interaction energies and associated properties. The resulting framework is flexible and has been further extended to include the resolution of identity (RI) approximation for solving the critical four-center two-electron repulsion integrals in the basis of the Kohn-Sham orbitals for cost effectiveness. To evaluate the performance of this set of new cost-effective methods, denoted as RI-DSD-DFTs, seven validation data sets were designed to cover a broad range of non-covalent interactions with characteristic stabilizing contributions. Inclusion of the perturbative treatment of correlation effects is shown to significantly improve the description of weak interactions. The set of DSD-DFTs provide interaction energies with root-mean-square deviations and mean absolute errors within 0.5 kcal/mol. The cost-effective RI-DSD-DFT counterparts deviate by less than 0.18 kcal/mol on average with only 2% of the computational cost.