Aggregation patterns of curcumin and piperine mixtures in different polar media.

This work reports a thorough molecular dynamics investigation on the aggregation patterns of curcumin and piperine in water, ethanol and a mixture of both solvents. The low solubility of curcumin in water results in a rapid formation of very stable dimers for both keto and enol tautomers. In agreement with a higher solubility, piperine molecules move closer and farther apart several times during the simulation, which indicates the formation of a less stable dimer in water. In contrast, both curcumin and piperine are soluble in ethanol and, thus, dimers can hardly be formed in this media. In comparison with a pure-water solvent, a 30 : 70 mixture of ethanol and water significantly reduces the probability of formation of most dimers of curcumin and piperine molecules. The simulations show that larger clusters may be complex structures, but the formation of stacks (in the case of piperine and enol tautomer of curcumin) and cages (when the keto tautomer of curcumin is involved) are not rare. Furthermore, it is shown that each single molecule presents a certain degree of mobility in the cluster, especially on the surface, but without leading to dissociation.

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

We propose a new methodology to study, at the density functional theory (DFT) level, the clusters resulting from the microsolvation of alkali-metal ions with rare-gas atoms. The workflow begins with a global optimization search to generate a pool of low-energy minimum structures for different cluster sizes. This is achieved by employing an analytical potential energy surface (PES) and an evolutionary algorithm (EA). The next main stage of the methodology is devoted to establish an adequate DFT approach to treat the microsolvation system, through a systematic benchmark study involving several combinations of functionals and basis sets, in order to characterize the global minimum structures of the smaller clusters. In the next stage, we apply machine learning (ML) classification algorithms to predict how the low-energy minima of the analytical PES map to the DFT ones. An early and accurate detection of likely DFT local minima is extremely important to guide the choice of the most promising low-energy minima of large clusters to be re-optimized at the DFT level of theory. In this work, the methodology was applied to the Li+Krn (n = 2-14 and 16) microsolvation clusters for which the most competitive DFT approach was found to be the B3LYP-D3/aug-pcseg-1. Additionally, the ML classifier was able to accurately predict most of the solutions to be re-optimized at the DFT level of theory, thereby greatly enhancing the efficiency of the process and allowing its applicability to larger clusters.

Aggregation of coronene: the effect of carboxyl and amine functional groups.

The aggregation of coronene is relevant to understand the formation of carbon nanomaterials, including graphene quantum dots (GQDs) that show exceptional photophysical properties. This article evaluates the influence of carboxyl and amine substituting groups on the aggregation of coronene by performing a global optimization study based on a new potential energy surface. The structures of clusters with substituted coronene are similar to those formed by un-substituted monomers, that is, stacked (non-stacked) motifs are favoured for small-size (large-size) clusters. Nonetheless, the presence of carboxyl and amine groups leads to an increase of the number of local minima of comparable energy. The clusters with substituted monomers have also shown to enhance the attractive component interaction, which can be attributed to weak induction and charge transfer effects and to stronger electrostatic contributions. Moreover, the calculated height of magic-number structures of the clusters in this work is compatible with the morphology of the GQDs reported in the literature.

A thermodynamic view on the microsolvation of ions by rare gas: application to Li+ with argon.

We present a thermodynamic perspective of the microsolvation of ions by rare gas atoms, which is based on parallel tempering Monte Carlo (PTMC) simulations. This allows the establishment of a clear relationship between the structure of the solvation shells and the heat capacity (CV) as a function of the number of individual solvent species. The dependence of CV on the temperature allows the identification of the internal structure rearrangements and the onset of partial or total melting of the clusters. As an application, we have employed the PTMC technique to study the thermodynamic properties of clusters resulting from the microsolvation of Li+ by argon atoms. Specifically, calculations have been carried out for the clusters Li+Arn (n = 4-18, 33, 34, and 38) by applying two different potential energy surfaces (PESs): one includes only two-body interactions, while the other also incorporates three-body contributions. Whenever possible, we compare the present thermodynamic results with global optimization studies carried out previously (F. V. Prudente, J. M. C. Marques and F. B. Pereira, Phys. Chem. Chem. Phys., 2017, 19, 25707; W. S. Jesus et al., Int. J. Quantum Chem., 2019, 119, e25860). We conclude that the melting process arises for lower temperatures when the model PES accounts for three-body interactions. Additionally, we characterize the melting processes of the first and second solvation shells. For some specific clusters, structural rearrangements of the most external argon atoms are observed at very low temperatures.

Aggregation enhancement of coronene molecules by seeding with alkali-metal ions.

Microsolvation constitutes the first step in the formation of cluster structures of molecules that surround a solute in the bulk and it allows for a deep insight into the relationship between the structure of the solvation shells and other physical properties. We propose semiempirical potential energy functions that are able to describe the interaction between K+ or Cs+ with coronene. Such functions were calibrated through the comparison with accurate estimations of the interaction between the cation and the planar hydrocarbon, obtained by means of ab initio electronic-structure calculations. By employing the potential energy functions and an evolutionary algorithm (EA), we have investigated the structure and energetics of the clusters resulting from the microsolvation of either K+ or Cs+ with coronene molecules. The reliability of the results for smaller clusters was checked by performing geometry re-optimization exploiting a suitable DFT level of theory. This has allowed for the characterization of the first solvation shells of planar molecules of coronene around an alkali-metal ion. It has also been found that the presence of metal ion impurities considerably enhances the formation of small coronene clusters leading to much stronger binding energies for heterogeneous with respect to homogeneous aggregates. These clusters could represent relevant species involved in the early stages of soot nucleation.

Molecular Dynamics Insights for Screening the Ability of Polymers to Remove Pesticides from Water.

The use of pesticides in agriculture is known to have environmental impacts, namely it leads to underground and spring water contamination. Thus, it turns out that nowadays general-endeavor towards the sustainability of farmer production requires novel strategies to capture pesticides from water and soils. We propose a methodology based on molecular dynamics simulations to identify polymers that are potentially featured to be applied for pesticide remediation in water and soils. We have employed cymoxanil (CYM), glufosinate ammonium (GLF), imidacloprid (IMI) and mancozeb (MAN) as pesticides, and have tested polymers with different characteristics as removing agents. Specifically, we have investigated oligomers of polypropylene (PP), poly(acrylic acid) protonated (PAAH) and deprotonated (PAA), and chitosan protonated (CTH) and deprotonated (CT). It has been found that all oligomers show a certain degree of selectivity concerning the interaction with the tested pesticides.

A global optimization perspective on molecular clusters.

Although there is a long history behind the idea of chemical structure, this is a key concept that continues to challenge chemists. Chemical structure is fundamental to understanding most of the properties of matter and its knowledge for complex systems requires the use of state-of-the-art techniques, either experimental or theoretical. From the theoretical view point, one needs to establish the interaction potential among the atoms or molecules of the system, which contains all the information regarding the energy landscape, and employ optimization algorithms to discover the relevant stationary points. In particular, global optimization methods are of major importance to search for the low-energy structures of molecular aggregates. We review the application of global optimization techniques to several molecular clusters; some new results are also reported. Emphasis is given to evolutionary algorithms and their application in the study of the microsolvation of alkali-metal and Ca2+ ions with various types of solvents.This article is part of the themed issue 'Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces'.

Improved evolutionary algorithm for the global optimization of clusters with competing attractive and repulsive interactions.

We propose improvements to our evolutionary algorithm (EA) [J. M. C. Marques and F. B. Pereira, J. Mol. Liq. 210, 51 (2015)] in order to avoid dissociative solutions in the global optimization of clusters with competing attractive and repulsive interactions. The improved EA outperforms the original version of the method for charged colloidal clusters in the size range 3 ≤ N ≤ 25, which is a very stringent test for global optimization algorithms. While the Bernal spiral is the global minimum for clusters in the interval 13 ≤ N ≤ 18, the lowest-energy structure is a peculiar, so-called beaded-necklace, motif for 19 ≤ N ≤ 25. We have also applied the method for larger sizes and unusual quasi-linear and branched clusters arise as low-energy structures.

A Detailed Study on the Low-Energy Structures of Charged Colloidal Clusters.

The target of this investigation is the systematic characterization of the low-energy structures of charged colloidal clusters that may be important to understand the self-assembling process of biomolecules. The aggregation of charged colloidal particles is governed by the attractive short-ranged Morse potential and the Yukawa repulsive tail to describe the long-range charge effect. A global optimization strategy, based on our own evolutionary algorithm, was adopted to discover the low-energy structures of colloidal clusters composed of up to 20 particles. A detailed analysis of the low-energy structures involving charged particles shows that the appearance of the Bernal spiral as the most stable motif occurs, first, at N = 6, but it is favored for larger clusters (N ≥ 13); for 6 ≤ N ≤ 12, there is a competition between the spiral (which is favored for higher charges) and more spherical-like structures. Finally, we study binary clusters composed by two sets of differently charged colloidal particles. Although a great diversity of low-energy structures is observed (especially for aggregates with one of the components in excess), the global minimum is disputed by three structural motifs depending on the composition of the cluster and, in some cases, on the range of the Morse potential.

Low-energy structures of benzene clusters with a novel accurate potential surface.

The benzene-benzene (Bz-Bz) interaction is present in several chemical systems and it is known to be crucial in understanding the specificity of important biological phenomena. In this work, we propose a novel Bz-Bz analytical potential energy surface which is fine-tuned on accurate ab initio calculations in order to improve its reliability. Once the Bz-Bz interaction is modeled, an analytical function for the energy of the Bzn clusters may be obtained by summing up over all pair potentials. We apply an evolutionary algorithm (EA) to discover the lowest-energy structures of Bzn clusters (for n=2-25), and the results are compared with previous global optimization studies where different potential functions were employed. Besides the global minimum, the EA also gives the structures of other low-lying isomers ranked by the corresponding energy. Additional ab initio calculations are carried out for the low-lying isomers of Bz3 and Bz4 clusters, and the global minimum is confirmed as the most stable structure for both sizes. Finally, a detailed analysis of the low-energy isomers of the n = 13 and 19 magic-number clusters is performed. The two lowest-energy Bz13 isomers show S6 and C3 symmetry, respectively, which is compatible with the experimental results available in the literature. The Bz19 structures reported here are all non-symmetric, showing two central Bz molecules surrounded by 12 nearest-neighbor monomers in the case of the five lowest-energy structures.

Microsolvation of the potassium ion with aromatic rings: comparison between hexafluorobenzene and benzene.

We employ a recently developed methodology to study structural and energetic properties of the first solvation shells of the potassium ion in nonpolar environments due to aromatic rings, which is important to understand the selectivity of several biochemical phenomena. Our evolutionary algorithm is used in the global optimization study of clusters formed of K(+) solvated with hexafluorobenzene (HFBz) molecules. The global intermolecular interaction for these clusters has been decomposed in HFBz-HFBz and in K(+)-HFBz contributions, using a potential model based on different decompositions of the molecular polarizability of hexafluorobenzene. Putative global minimum structures of microsolvation clusters up to 21 hexafluorobenzene molecules were obtained and compared with the analogous K(+)-benzene clusters reported in our previous work (J. Phys. Chem. A 2012, 116, 4947-4956). We have found that both K(+)-(Bz)n and K(+)-(HFBz)n clusters show a strong magic number around the closure of the first solvation shell. Nonetheless, all K(+)-benzene clusters have essentially the same first solvation shell geometry with four solvent molecules around the ion, whereas the corresponding one for K(+)-(HFBz)n is completed with nine HFBz species, and its structural motif varies as n increases. This is attributed to the ion-solvent interaction that has a larger magnitude for K(+)-Bz than in the case of K(+)-HFBz. In addition, the ability of having more HFBz than Bz molecules around K(+) in the first solvation shell is intimately related to the inversion in the sign of the quadrupole moment of the two solvent species, which leads to a distinct ion-solvent geometry of approach.

Alkali-ion microsolvation with benzene molecules.

The target of this investigation is to characterize by a recently developed methodology, the main features of the first solvation shells of alkaline ions in nonpolar environments due to aromatic rings, which is of crucial relevance to understand the selectivity of several biochemical phenomena. We employ an evolutionary algorithm to obtain putative global minima of clusters formed with alkali-ions (M(+)) solvated with n benzene (Bz) molecules, i.e., M(+)-(Bz)(n). The global intermolecular interaction has been decomposed in Bz-Bz and in M(+)-Bz contributions, using a potential model based on different decompositions of the molecular polarizability of benzene. Specifically, we have studied the microsolvation of Na(+), K(+), and Cs(+) with benzene molecules. Microsolvation clusters up to n = 21 benzene molecules are involved in this work and the achieved global minimum structures are reported and discussed in detail. We observe that the number of benzene molecules allocated in the first solvation shell increases with the size of the cation, showing three molecules for Na(+) and four for both K(+) and Cs(+). The structure of this solvation shell keeps approximately unchanged as more benzene molecules are added to the cluster, which is independent of the ion. Particularly stable structures, so-called "magic numbers", arise for various nuclearities of the three alkali-ions. Strong "magic numbers" appear at n = 2, 3, and 4 for Na(+), K(+), and Cs(+), respectively. In addition, another set of weaker "magic numbers" (three per alkali-ion) are reported for larger nuclearities.

On the use of big-bang method to generate low-energy structures of atomic clusters modeled with pair potentials of different ranges.

The efficiency of the so-called big-bang method for the optimization of atomic clusters is analysed in detail for Morse pair potentials with different ranges; here, we have used Morse potentials with four different ranges, from long- ρ = 3) to short-ranged ρ = 14) interactions. Specifically, we study the efficacy of the method in discovering low-energy structures, including the putative global minimum, as a function of the potential range and the cluster size. A new global minimum structure for long-ranged ρ = 3) Morse potential at the cluster size of n= 240 is reported. The present results are useful to assess the maximum cluster size for each type of interaction where the global minimum can be discovered with a limited number of big-bang trials.

An evolutionary algorithm for the global optimization of molecular clusters: application to water, benzene, and benzene cation.

We have developed an evolutionary algorithm (EA) for the global minimum search of molecular clusters. The EA is able to discover all the putative global minima of water clusters up to (H(2)O)(20) and benzene clusters up to (C(6)H(6))(30). Then, the EA was applied to search for the global minima structures of (C(6)H(6))(n)(+) with n = 2-20, some of which were theoretically studied for the first time. Our results for n = 2-6 are consistent with previous theoretical work that uses a similar interaction potential. Excluding the very symmetric global minimum structure for n = 9, the growth pattern of (C(6)H(6))(n)(+) with n ≥ 7 involves the (C(6)H(6))(2)(+) dimer motif, which is placed off-center in the cluster. Such observation indicates that potentials commonly used in the literature for (C(6)H(6))(n)(+) cannot reproduce the icosahedral-type packing suggested by the available experimental data.

How different are two chemical structures?

We extend the scope of a recent method for superimposing two molecules ( J. Chem. Phys. 2009, 131, 124126-1-124126-10 ) to include the identification of chiral structures. This methodology is tested by applying it to several organic molecules and water clusters that were subjected to geometry optimization. The accuracy of four simpler, non-superimposing approaches is then analyzed by comparing pairs of structures for argon and water clusters. The structures considered in this work were obtained by a Markovian walk in the coordinate space. First, a random geometry is generated, and then, the iterative application of a mutation operator ensures the creation of increasingly dissimilar structures. The discriminating power of the non-superimposing approaches is tested by comparing the corresponding dissimilarity measures with the root-mean-square distance obtained from the superimposing method. Finally, we showcase the application of those methods to characterize the diversity of solutions in global geometry optimization by evolutionary algorithms.

Generation and characterization of low-energy structures in atomic clusters.

Factors relevant for controlling the structures determined in the local optimization of argon clusters are investigated. In particular, the role of volume and shape for the box where initial structures are generated is assessed. A thorough characterization of the optimization is also presented, based on a nearest-neighbor analysis, in clusters ranging from 30 to 55 atoms. This includes the assessment of the degree of preservation of aspects of the initial randomly generated structure in the final optimized counterpart, and the correlation between optimized energy and the number of nearest neighbors and average departure from the diatomic reference distance. The usefulness of this analysis to explore the energy landscape of atomic clusters is also highlighted.

On the use of different potential energy functions in rare-gas cluster optimization by genetic algorithms: application to argon clusters.

We study the effect of the potential energy function on the global minimum structures of argon clusters arising in the optimization performed by genetic algorithms (GAs). We propose a robust and efficient GA which allows for the calculation of all of the putative global minima of Ar(N) (N = 3-78) clusters modeled with four different potentials. Both energetic and structural properties of such minima are compared among each other and with those previously obtained for the Lennard-Jones function. In addition, the possibility of obtaining global minima of one potential through local optimization over the corresponding cluster geometry given by other potentials was associated with some structural parameters. The influence of the contribution from the three-body (Axilrod-Teller-Muto) triple-dipole potential (including or not a damping function to describe its correct behavior at smaller interatomic distances) has also been analyzed.

Trajectory dynamics study of collision-induced dissociation of the Ar + CH4 reaction at hyperthermal conditions: vibrational excitation and isotope substitution.

We investigate the role of vibrational energy excitation of methane and two deuterated species (CD(4) and CH(2)D(2)) in the collision-induced dissociation (CID) process with argon at hyperthermal energies. The quasi-classical trajectory method has been applied, and the reactive Ar + CH(4) system has been modeled by using a modified version of the CH(4) potential energy surface of Duchovic et al. (J. Phys. Chem. 1984, 88, 1339) and the Ar-CH(4) intermolecular potential function obtained by Troya (J. Phys. Chem. A 2005, 109, 5814). This study clearly shows that CID is markedly enhanced with vibrational excitation and, to a lesser degree, with collision energy. In general, CID increases by exciting stretch vibrational modes of the reactant molecule. For the direct dissociation of CH(4), however, the CID cross sections appear to be essentially independent of which vibrational mode is initially excited. In all situations studied, the CID cross sections are always greater for the Ar + CD(4) reaction than for the Ar + CH(4) one, the Ar + CH(2)D(2) being an intermediate situation. A detailed analysis of the energy transfer processes, including their relation with CID, is also presented.

Trajectory dynamics study of the Ar + CH4 dissociation reaction at high temperatures: the importance of zero-point-energy effects.

Large-scale classical trajectory calculations have been performed to study the reaction Ar + CH4--> CH3 +H + Ar in the temperature range 2500 < or = T/K < or = 4500. The potential energy surface used for ArCH4 is the sum of the nonbonding pairwise potentials of Hase and collaborators (J. Chem. Phys. 2001, 114, 535) that models the intermolecular interaction and the CH4 intramolecular potential of Duchovic et al. (J. Phys. Chem. 1984, 88, 1339), which has been modified to account for the H-H repulsion at small bending angles. The thermal rate coefficient has been calculated, and the zero-point energy (ZPE) of the CH3 product molecule has been taken into account in the analysis of the results; also, two approaches have been applied for discarding predissociative trajectories. In both cases, good agreement is observed between the experimental and trajectory results after imposing the ZPE of CH3. The energy-transfer parameters have also been obtained from trajectory calculations and compared with available values estimated from experiment using the master equation formalism; in general, the agreement is good.