Self-consistent charge equilibration method and its application to Au13Na(n) (n = 1,10) clusters

Unified polarizable electrode models for open and closed circuits: Revisiting the effects of electrode polarization and different circuit conditions on electrode-electrolyte interfaces

A precise understanding of the interfacial structure and dynamics is essential for the optimal design of various electrochemical devices. Herein, we propose a method for classical molecular dynamics simulations to deal with electrochemical interfaces with polarizable electrodes under the open circuit condition. Less attention has been paid to electrochemical circuit conditions in computation despite being often essential for a proper assessment, especially comparison between different models. The present method is based on the chemical potential equalization principle, as is a method developed previously to deal with systems under the closed circuit condition. These two methods can be interconverted through the Legendre transformation, so that the difference in the circuit conditions can be compared on the same footing. Furthermore, the electrode polarization effect can be correctly studied by comparing the present method with the conventional simulations with the electrodes represented by fixed charges, since both of the methods describe systems under the open circuit condition. The method is applied to a parallel-plate capacitor composed of platinum electrodes and an aqueous electrolyte solution. The electrode polarization effects have an impact on the interfacial structure of the electrolyte solution. We found that the difference in the circuit conditions significantly affects the dynamics of the electrolyte solution. The electric field at the charged electrode surface is poorly screened by the nonequilibrium solution structure in the open circuit condition, which accelerates the motion of the electrolyte solution.

Atomic Charge Calculator II: web-based tool for the calculation of partial atomic charges

Partial atomic charges serve as a simple model for the electrostatic distribution of a molecule that drives its interactions with its surroundings. Since partial atomic charges are frequently used in computational chemistry, chemoinformatics and bioinformatics, many computational approaches for calculating them have been introduced. The most applicable are fast and reasonably accurate empirical charge calculation approaches. Here, we introduce Atomic Charge Calculator II (ACC II), a web application that enables the calculation of partial atomic charges via all the main empirical approaches and for all types of molecules. ACC II implements 17 empirical charge calculation methods, including the highly cited (QEq, EEM), the recently published (EQeq, EQeq+C), and the old but still often used (PEOE). ACC II enables the fast calculation of charges even for large macromolecular structures. The web server also offers charge visualization, courtesy of the powerful LiteMol viewer. The calculation setup of ACC II is very straightforward and enables the quick calculation of high-quality partial charges. The application is available at https://acc2.ncbr.muni.cz.

Incorporating charge transfer effects into a metallic empirical potential for accurate structure determination in (ZnMg)N nanoalloys

We report the results of a combined empirical potential-density functional theory (EP-DFT) study to assess the global minimum structures of free-standing zinc-magnesium nanoalloys of equiatomic composition and with up to 50 atoms. Within this approach, the approximate potential energy surface generated by an empirical potential is first sampled with unbiased basin hopping simulations, and then a selection of the isomers so identified is re-optimized at a first-principles DFT level. Bader charges calculated in a previous work [A. Lebon, A. Aguado and A. Vega, Corros. Sci., 2017, 124, 35-45] revealed a significant transfer of electrons from Mg to Zn atoms in these nanoalloys; so the main novelty in the present work is the development of an improved EP, termed Coulomb-corrected-Gupta potential, which incorporates an explicit charge-transfer correction term onto a metallic Gupta potential description. The Coulomb correction has a many-body character and is fed with parameterized values of the ab initio Bader charges. The potentials are fitted to a large training set containing DFT values of cluster energies and atomic forces, and the DFT results are used as benchmark data to assess the performance of Gupta and Coulomb-corrected-Gupta EP models. Quite surprisingly, the charge-transfer correction is found to represent only 6% of the nanoalloy binding energies, yet this quantitatively small correction has a sizable beneficial effect on the predicted relative energies of homotops. Zn-Mg bulk alloys are used as the sacrificial material in corrosion-protective coatings, and the long-term goal of our research is to disclose whether those corrosion-protected capabilities are enhanced at the nanoscale.

Incorporating Electronic Information into Machine Learning Potential Energy Surfaces via Approaching the Ground-State Electronic Energy as a Function of Atom-Based Electronic Populations

Machine learning (ML) approximations to density functional theory (DFT) potential energy surfaces (PESs) are showing great promise for reducing the computational cost of accurate molecular simulations, but at present, they are not applicable to varying electronic states, and in particular, they are not well suited for molecular systems in which the local electronic structure is sensitive to the medium to long-range electronic environment. With this issue as the focal point, we present a new machine learning approach called "BpopNN" for obtaining efficient approximations to DFT PESs. Conceptually, the methodology is based on approaching the true DFT energy as a function of electron populations on atoms; in practice, this is realized with available density functionals and constrained DFT (CDFT). The new approach creates approximations to this function with neural networks. These approximations thereby incorporate electronic information naturally into a ML approach, and optimizing the model energy with respect to populations allows the electronic terms to self-consistently adapt to the environment, as in DFT. We confirm the effectiveness of this approach with a variety of calculations on Li_nH_n clusters.

Evaluating Charge Equilibration Methods To Generate Electrostatic Fields in Nanoporous Materials

Charge equilibration (Qeq) methods can estimate the electrostatic potential of molecules and periodic frameworks by assigning point charges to each atom, using only a small fraction of the resources needed to compute density functional (DFT)-derived charges. This makes possible, for example, the computational screening of thousands of microporous structures to assess their performance for the adsorption of polar molecules. Recently, different variants of the original Qeq scheme were proposed to improve the quality of the computed point charges. One focus of this research was to improve the gas adsorption predictions in metal–organic frameworks (MOFs), for which many different structures are available. In this work, we review the evolution of the method from the original Qeq scheme, understanding the role of the different modifications on the final output. We evaluated the result of combining different protocols and set of parameters, by comparing the Qeq charges with high quality DFT-derived DDEC charges for 2338 MOF structures. We focused on the systematic errors that are attributable to specific atom types to quantify the final precision that one can expect from Qeq methods in the context of gas adsorption where the electrostatic potential plays a significant role, namely, CO₂ and H₂S adsorption. In conclusion, both the type of algorithm and the input parameters have a large impact on the resulting charges, and we draw some guidelines to help the user to choose the proper combination of the two for obtaining a meaningful set of charges. We show that, considering this set of MOFs, the accuracy of the original Qeq scheme is often still comparable with the most recent variants, even if it clearly fails in the presence of certain atom types, such as alkali metals.

A first-principles based force-field for Li+ and OH- in ethanolic solution

We report on the development of force-field parameters for accurately modeling lithium and hydroxide ions in ethanol in solution. Based on quantum calculations of small molecular clusters mimicking the solvent structure of individual ions as well as the solvated LiOH dimer, significant improvements of off-the-shelf force-fields are obtained. The quality of our model is demonstrated by comparison to ab initio molecular dynamics of the bulk solution and to experimental data available for ethanol/water mixtures.

Optimization of chemical ordering in AgAu nanoalloys

The determination of optimal chemical ordering in nanoalloys, i.e. of the most stable pattern in which atoms are arranged in bi- or multicomponent metallic clusters, is quite complex due to the enormous number of different possible configurations. This problem is very difficult to tackle by first-principle methods except for very small systems. On the other hand, the treatment at the atomistic potential level is complicated in many cases (such as AgAu) by charge transfer effects between atoms of different species in different coordination environments. Here an empirical atomistic model is developed to take into account such effects. The model is used to determine the optimal chemical ordering in AgAu nanoalloys. Charge transfer between atoms is taken into account by a modification of the charge equilibration method of Goddard and Rappé [J. Phys. Chem., 1991, 95, 3358], in which a coordination-dependent electronegativity and hardness are introduced. The model is applied to the determination of chemical ordering in AgAu nanoalloys. It is shown that the inclusion of charge transfer effects is important for improving the agreement of the atomistic model with density-functional calculations, leading to the determination of lower-energy chemical ordering patterns.

Competition between mixing and segregation in bimetallic AgnRbn clusters (n = 2–10),

We found the minimum-energy structures of AgnRbn (n = 2–10) clusters by a combination of density functional theory (DFT) and taboo search global optimization. The global minimum geometry is mixed for n ≤ 4 and segregated, with a core-shell arrangement, for n > 4. There is a change in the nature of the bonding, from ionic to metallic, between n = 4 and n = 5. Although metallic bonding dominates at n > 4, large atomic charges (in the order of ±0.5) persist. These atomic charges (negative on the interior Ag atoms, positive on the surface Rb atoms) make AgnRbn clusters analogous to Zintl compounds and could prevent them from coalescing. This makes them intriguing potential building blocks for cluster-assembled materials. Ag4Rb4 is relatively stable compared with other AgnRbn clusters; it has a nearly cubic shape, a large HOMO–LUMO gap (2 eV), and a highly ionic character with atomic charges equal to roughly ±1 au.