High-Density “Windowpane” Coordination Patterns of Water Clusters and Their NBO/NRT Characterization

Cluster mixture models for liquid water at higher pressures suggest the need for water clusters of higher coordination and density than those commonly based on tetrahedral H-bonding motifs. We show here how proton-ordered water clusters of increased coordination and density can assemble from a starting cyclic tetramer or twisted bicyclic (Möbius-like) heptamer to form extended Aufbau sequences of stable two-, three-, and four-coordinate “windowpane” motifs. Such windowpane clusters exhibit sharply reduced (~90°) bond angles that differ appreciably from the tetrahedral angles of idealized crystalline ice I_h. Computed free energy and natural resonance theory (NRT) bond orders provide quantitative descriptors for the relative stabilities of clusters and strengths of individual coordinative linkages. The unity and consistency of NRT description is demonstrated to extend from familiar supra-integer bonds of the molecular regime to the near-zero bond orders of the weakest linkages in the present H-bond clusters. Our results serve to confirm that H-bonding exemplifies resonance–covalent (fractional) bonding in the sub-integer range and to further discount the dichotomous conceptions of “electrostatics” for intermolecular bonding vs. “covalency” for intramolecular bonding that still pervade much of freshman-level pedagogy and force-field methodology.

Pauling's Conceptions of Hybridization and Resonance in Modern Quantum Chemistry

We employ the tools of natural bond orbital (NBO) and natural resonance theory (NRT) analysis to demonstrate the robustness, consistency, and accuracy with which Linus Pauling's qualitative conceptions of directional hybridization and resonance delocalization are manifested in all known variants of modern computational quantum chemistry methodology.

Efficient optimization of natural resonance theory weightings and bond orders by gram-based convex programming

We describe the formal algorithm and numerical applications of a novel convex quadratic programming (QP) strategy for performing the variational minimization that underlies natural resonance theory (NRT). The QP algorithm vastly improves the numerical efficiency, thoroughness, and accuracy of variational NRT description, which now allows uniform treatment of all reference structures at the high level of detail previously reserved only for leading "reference" structures, with little or no user guidance. We illustrate overall QPNRT search strategy, program I/O, and numerical results for a specific application to adenine, and we summarize more extended results for a data set of 338 species from throughout the organic, bioorganic, and inorganic domain. The improved QP-based implementation of NRT is a principal feature of the newly released NBO 7.0 program version. © 2019 Wiley Periodicals, Inc.

Resonance Theory Reboot

What is now called "resonance theory" has a long and conflicted history. We first sketch the early roots of resonance theory, its heritage of diverse physics and chemistry conceptions, and its subsequent rise to reigning chemical bonding paradigm of the mid-20th century. We then outline the alternative "natural" pathway to localized Lewis- and resonance-structural conceptions that was initiated in the 1950s, given semi-empirical formulation in the 1970s, recast in ab initio form in the 1980s, and successfully generalized to multi-structural "natural resonance theory" (NRT) form in the 1990s. Although earlier numerical applications were often frustrated by the ineptness of then-available numerical solvers, the NRT variational problem was recently shown to be amenable to highly efficient convex programming methods that yield provably optimal resonance weightings at a small fraction of previous computational costs. Such convexity-based algorithms now allow a full "reboot" of NRT methodology for tackling a broad range of chemical applications, including the many familiar resonance phenomena of organic and biochemistry as well as the still broader range of resonance attraction effects in the inorganic domain. We illustrate these advances for prototype chemical applications, including (i) stable near-equilibrium species, where resonance mixing typically provides only small corrections to a dominant Lewis-structural picture, (ii) reactive transition-state species, where strong resonance mixing of reactant and product bonding patterns is inherent, (iii) coordinative and related supramolecular interactions of the inorganic domain, where sub-integer resonance bond orders are the essential origin of intermolecular attraction, and (iv) exotic long-bonding and metallic delocalization phenomena, where no single "parent" Lewis-structural pattern gains pre-eminent weighting in the overall resonance hybrid.

Quantitative structure-activity relationship analysis of perfluoroiso-propyldinitrobenzene derivatives known as photosystem II electron transfer inhibitors

Quantitative structure-activity relationship (QSAR) analysis of the twenty-six perfluoroisopropyl-dinitrobenzene (PFIPDNB) derivatives was performed to explain their ability to suppress photochemical activity of the plants photosystem II using chloroplasts and subchloroplast thylakoid membranes enriched in photosystem II, called DT-20. Compounds were optimized by semi-empirical PM3 and DFT/B3LYP/6-31G methods. The Heuristic and the Best Multi-Linear Regression (BMLR) method in CODESSA were used to select the most appropriate molecular descriptors and to develop a linear QSAR model between experimental pI(50) values and the most significant set of the descriptors. The obtained models were validated by cross-validation (R(2)(cv)) and internal validation to confirm the stability and good predictive ability. The obtained eight models with five-parameter show that: (a) coefficient (R(2)) value of the chloroplast samples are slightly higher than that of the DT-20 samples both of Heuristic and BMLR models; (b) the coefficients of the BMLR models are slightly higher than that of Heuristic models both of chloroplasts and DT-20 samples; (c) The YZ shadow parameter and the indicator parameter, for presence of NO(2) substituent in the ring, are the most important descriptor at PM3-based and DFT-based QSAR models, respectively. This article is part of a Special Issue entitled: Photosynthesis Research for Sustainability: from Natural to Artificial.

The role of chemistry in graphene doping for carbon-based electronics

Graphene forms an important two-dimensional (2D) material class that displays both a high electronic conductivity and optical transparency when doped. Yet, the microscopic origin of the doping mechanism in single sheet or bulk intercalated systems remains unclear. Using large-scale ab initio simulations, we show the graphene surface acts as a catalytic reducing/oxidizing agent, driving the chemical disproportionation of adsorbed dopant layers into charge-transfer complexes which inject majority carriers into the 2D carbon lattice. As pertinent examples, we focus on the molecular SbCl(5) and HNO(3) intercalates, and the solid compound AlCl(3). Identifying the microscopic mechanism for the catalytic action of graphene is important, given the availability of large area graphene sheets, to spur research into new redox reactions for use in science and technology.