Modeling microsolvation clusters with electronic-structure calculations guided by analytical potentials and predictive machine learning techniques

Structures and stability of K+ cation solvated in Arn clusters

The solvation of K+ cation plays an important role in various phenomena such as biological procedures, geological time, and archaeological properties. Monte Carlo (MC) simulation and DFT method are employed to study the structural and energetic characteristics of the K + Arn (n = 1-14) clusters. The potential model (PM) and the Basin-Hopping (BH) method are the foundation of the MC simulation. The pairwise PM (PW-PM) is improved by introducing the N-body interactions via the polarizable potential model (PPM). On the other side, the DFT functional M05-2X, combined with the 6-311++G(3d2f,2p) basis set, and the Grimme dispersion correction GD3 was used to deeply investigate the geometrical properties and the relative stability of the K + Arn clusters. Starting from n = 12, a structural transition from square antiprism (SA) to icosahedron (ICOS) form is detected. Additionally, the PPM allows us to examine the largest sizes (n = 15-54). Herein, the first ICOS layers are found for n = 12 and 54 cluster sizes, respectively. The binding energy and the second energy difference as a function of cluster size are used to evaluate the relative stability of K + Arn clusters. The obtained data are in concordance with the available results in the literature.

Microsolvation of lithium cation in xenon clusters: An octahedral growth pattern

The structural and energetic proprieties for the Li ⁺ Xe_n (n = 1-18) clusters are investigated using both Basin-Hopping combined with Potential Model description (BH-PM) and DFT methods. A structural transition from tetrahedral (4 coordination) form to octahedral (6 coordination) one is observed for n = 6. Above this size, all structures have an octahedral core. The cubic-face-centered arrangement for xenon atoms is detected for Li ⁺ Xe₁₄. To the best of our knowledge, the Li ⁺ Xe_n (n = 1-18) clusters are studied in the present work for the first time using the DFT theoretical approach. The M062X functional combined with aug-cc-pVDZ (for Li) and def2-TZVP (for Xe) basis sets reproduces accurately the CCSD(T) potential energy curve of Li + Xe system. Atom-Centered Density Matrix Propagation (ADMP) molecular dynamic calculations have been carried. Moreover, we investigate the larger sizes n = 31-35, 44, and 55 for the first time using the BH-PM theoretical approach. The closing of the first and second octahedron shells are proved for the n = 6 and 34 sizes, respectively. The relative stabilities of the Li ⁺ Xe_n molecules are also studied by computing the total energy, the binding energy per atoms for each size n. Then, the second energy difference between the size n and its two near neighbors allows identifying the magic number series. Our present data are analyzed, discussed and compared with the available theoretical and experimental data.

Solvation of Isoelectronic Halide and Alkali Metal Ions by Argon Atoms

This work systematically examines the interactions of alkali metal cations and their isoelectronic halide counterparts with up to six solvating Ar atoms (M⁺Ar_n and X^-Ar_n, where M = Li, Na, K, and Rb; X = H, F, Cl, and Br; and n = 1-6) via full geometry optimizations with the MP2 method and robust, correlation-consistent quadruple-ζ (QZ) basis sets. 116 unique M⁺Ar_n and X^-Ar_n stationary points have been characterized on the MP2/QZ potential energy surface. To the best of our knowledge, approximately two dozen of these stationary points have been reported here for the first time. Some of these new structures are either the lowest-energy stationary point for a particular cluster or energetically competitive with it. The CCSD(T) method was employed to perform additional single-point energy computations upon all MP2/QZ-optimized structures using the same basis set. CCSD(T)/QZ results indicate that internally solvated structures with the ion at/near the geometric center of the cluster have appreciably higher energies than those placing the ion on the periphery. While this study extends the prior investigations of M⁺Ar_n clusters found within the literature, it notably provides one of the first thorough characterizations of and comparisons to the corresponding negatively charged X^-Ar_n clusters.

Disentangling the complex network of non-covalent interactions in fenchone hydrates via rotational spectroscopy and quantum chemistry

The hydrates of the monoterpenoid fenchone (C₁₀H₁₆O)·(H₂O)_n (n = 1, 2, 3) were investigated by both computational chemistry and microwave spectroscopy. Two monohydrates, three dihydrates and for the first time three trihydrates were identified through the observation of the parent and ¹⁸O isotopologues in the rotational spectrum from 2 to 20 GHz. For each hydrate, the sets of rotational constants enabled the determination of the substitution coordinates of the oxygen water atoms as well as an effective structure accounting for the arrangement of the water molecules around fenchone. The hydrates consist of water chains anchored to fenchone by a -CO⋯H-O hydrogen bond and further stabilized by numerous -H-O⋯H-C- secondary hydrogen bonds with the alkyl hydrogen atoms of fenchone.

Infrared Spectroscopy of Chemically Diverse Carbon Clusters: A Data-Driven Approach

Carbon clusters exhibit a broad diversity of topologies and shapes, encompassing fullerene-like cages, graphene-like flakes, and more disordered pretzel-like and branched structures. Here, we examine computationally their infrared spectra in relation with these structures from a statistical perspective. Individual spectra for broad samples of isomers were determined by means of the self-consistent charge density functional-based tight-binding method, and an interpolation scheme is designed to reproduce the spectral features by regression on a much smaller subset of the sample. This interpolation proceeds by encoding the structures using appropriate descriptors and selecting them through principal component analysis, Gaussian regression or inverse distance weighting providing the nonlinear weighting functions. Metric learning is employed to reduce the global error on a preselected testing set. The interpolated spectra satisfactorily reproduce the specific spectral features and their dependence on the size and shape, enabling quantitative prediction away from the testing set. Finally, the classification of structures within the four proposed families is critically discussed through a statistical analysis of the sample based on iterative label spreading.

Free Energies of Hydrated Halide Anions: High Through-Put Computations on Clusters to Treat Rough Energy-Landscapes

With a longer-term goal of addressing the comparative behavior of the aqueous halides F−, Cl−, Br−, and I− on the basis of quasi-chemical theory (QCT), here we study structures and free energies of hydration clusters for those anions. We confirm that energetically optimal (H2O)nX clusters, with X = Cl−, Br−, and I−, exhibit surface hydration structures. Computed free energies, based on optimized surface hydration structures utilizing a harmonic approximation, typically (but not always) disagree with experimental free energies. To remedy the harmonic approximation, we utilize single-point electronic structure calculations on cluster geometries sampled from an AIMD (ab initio molecular dynamics) simulation stream. This rough-landscape procedure is broadly satisfactory and suggests unfavorable ligand crowding as the physical effect addressed. Nevertheless, this procedure can break down when n≳4, with the characteristic discrepancy resulting from a relaxed definition of clustering in the identification of (H2O)nX clusters, including ramified structures natural in physical cluster theories. With ramified structures, the central equation for the present rough-landscape approach can acquire some inconsistency. Extension of these physical cluster theories in the direction of QCT should remedy that issue, and should be the next step in this research direction.

Quantum Chemical Microsolvation by Automated Water Placement

We developed a quantitative approach to quantum chemical microsolvation. Key in our methodology is the automatic placement of individual solvent molecules based on the free energy solvation thermodynamics derived from molecular dynamics (MD) simulations and grid inhomogeneous solvation theory (GIST). This protocol enabled us to rigorously define the number, position, and orientation of individual solvent molecules and to determine their interaction with the solute based on physical quantities. The generated solute-solvent clusters served as an input for subsequent quantum chemical investigations. We showcased the applicability, scope, and limitations of this computational approach for a number of small molecules, including urea, 2-aminobenzothiazole, (+)-syn-benzotriborneol, benzoic acid, and helicene. Our results show excellent agreement with the available ab initio molecular dynamics data and experimental results.