Articles you may be interested inWe estimate the prediction sensitivity with respect to Hartree-Fock exchange in approximate density functionals for representative Fe(II) and Fe(III) octahedral complexes. Based on the observation that the range of parameters spanned by the most widely employed functionals is relatively narrow, we compute electronic structure property and spin-state orderings across a relatively broad range of Hartree-Fock exchange (0%-50%) ratios. For the entire range considered, we consistently observe linear relationships between spin-state ordering that differ only based on the element of the direct ligand and thus may be broadly employed as measures of functional sensitivity in predictions of organometallic compounds. The role Hartree-Fock exchange in hybrid functionals is often assumed to play is to correct self-interaction error-driven electron delocalization (e.g., from transition metal centers to neighboring ligands). Surprisingly, we instead observe that increasing Hartree-Fock exchange reduces charge on iron centers, corresponding to effective delocalization of charge to ligands, thus challenging notions of the role of Hartree-Fock exchange in shifting predictions of spin-state ordering. C 2015 AIP Publishing LLC. [http://dx

We present an automated, open source toolkit for the first-principles screening and discovery of new inorganic molecules and intermolecular complexes. Challenges remain in the automatic generation of candidate inorganic molecule structures due to the high variability in coordination and bonding, which we overcome through a divide-and-conquer tactic that flexibly combines force-field preoptimization of organic fragments with alignment to first-principles-trained metal-ligand distances. Exploration of chemical space is enabled through random generation of ligands and intermolecular complexes from large chemical databases. We validate the generated structures with the root mean squared (RMS) gradients evaluated from density functional theory (DFT), which are around 0.02 Ha/au across a large 150 molecule test set. Comparison of molSimplify results to full optimization with the universal force field reveals that RMS DFT gradients are improved by 40%. Seamless generation of input files, preparation and execution of electronic structure calculations, and post-processing for each generated structure aids interpretation of underlying chemical and energetic trends. © 2016 Wiley Periodicals, Inc.

Virtual high throughput screening, typically driven by first-principles, density functional theory calculations, has emerged as a powerful tool for the discovery of new materials. Although the computational materials science community has benefited from open source tools for the rapid structure generation, calculation, and analysis of crystalline inorganic materials, software and strategies to address the unique challenges of inorganic complex discovery have not been as widely available. We present a unified view of our recent developments in the open source molSimplify code for inorganic discovery. Building on our previous efforts in the automated generation of highly accurate inorganic molecular structures, first-principles simulation, and property analysis to accelerate high-throughput screening, we have recently incorporated a neural network that both improves structure generation and predicts electronic properties prior to first-principles calculation. We also provide an overview of how multi-million molecule organic libraries can be leveraged for inorganic discovery alongside cheminformatics concepts of molecular diversity in order to efficiently traverse chemical space. We demonstrate all of these tools on the discovery of design rules for octahedral Fe(II/III) redox couples with nitrogen ligands. Over a search of only approximately 40 new molecules, we obtain redox potentials relative to the Fc/Fc + couple ranging from-1 to 4.5 V in aqueous solution. Our new automated correlation analysis reveals heteroatom identity and the degree of structural branching to be key ligand descriptors in determining redox potential. This inorganic discovery toolkit provides a promising approach to advancing transition metal complex design.

Piecewise linearity of the energy with respect to fractional electron removal or addition is a requirement of an electronic structure method that necessitates the presence of a derivative discontinuity at integer electron occupation. Semi-local exchange-correlation (xc) approximations within density functional theory (DFT) fail to reproduce this behavior, giving rise to deviations from linearity with a convex global curvature that is evidence of many-electron, self-interaction error and electron delocalization. Popular functional tuning strategies focus on reproducing piecewise linearity, especially to improve predictions of optical properties. In a divergent approach, Hubbard U-augmented DFT (i.e., DFT+U) treats self-interaction errors by reducing the local curvature of the energy with respect to electron removal or addition from one localized subshell to the surrounding system. Although it has been suggested that DFT+U should simultaneously alleviate global and local curvature in the atomic limit, no detailed study on real systems has been carried out to probe the validity of this statement. In this work, we show when DFT+U should minimize deviations from linearity and demonstrate that a "+U" correction will never worsen the deviation from linearity of the underlying xc approximation. However, we explain varying degrees of efficiency of the approach over 27 octahedral transition metal complexes with respect to transition metal (Sc-Cu) and ligand strength (CO, NH3, and H2O) and investigate select pathological cases where the delocalization error is invisible to DFT+U within an atomic projection framework. Finally, we demonstrate that the global and local curvatures represent different quantities that show opposing behavior with increasing ligand field strength, and we identify where these two may still coincide.

Prediction of spin-state ordering in transition metal complexes is essential for understanding catalytic activity and designing functional materials. Semi-local approximations in density functional theory, such as the generalized-gradient approximation (GGA), suffer from several errors notably including delocalization error that give rise to systematic bias for more covalently bound low-spin electronic states. Incorporation of exact exchange is known to counteract this bias, instead favoring high-spin states, in a manner that has recently been identified to be ligand-field dependent. In this work, we introduce a tuning strategy to identify the effect of incorporating the Laplacian of the density (i.e., a meta-GGA) in exchange on spinstate ordering. We employ a diverse test set of M(II) and M(III) first-row transition metal ions from Ti to Cu as well as octahedral complexes of these ions with ligands of increasing field strength (i.e., H 2 O, NH 3 , and CO). We show that the sensitivity of spin-state ordering to meta-GGA exchange is highly ligand-field dependent, stabilizing high-spin states in strong-field (i.e., CO) cases and stabilizing low-spin states in weak-field (i.e., H 2 O, NH 3 , and isolated ions) cases. This diverging behavior leads to generally improved treatment of isolated ions and strong field complexes over a standard GGA but worsened treatment for the hexa-aqua or hexa-ammine complexes. These observations highlight the sensitivity of functional performance to subtle changes in chemical bonding.2

Catechol O-methyltransferase (COMT) is a SAM- and Mg2+-dependent methyltransferase that regulates neurotransmitters through methylation. Simulations and experiments have identified divergent catecholamine substrate orientations in the COMT active site: molecular dynamics simulations have favored a monodentate coordination of catecholate substrates to the active site Mg2+, and crystal structures instead preserve bidentate coordination along with short (2.65 Å) methyl donor-acceptor distances. We carry out longer dynamics (up to 350 ns) to quantify interconversion between bidentate and monodentate binding poses. We provide a systematic determination of the relative free energy of the monodentate and bidentate structures in order to identify whether structural differences alter the nature of the methyl transfer mechanism and source of enzymatic rate enhancement. We demonstrate that the bidentate and monodentate binding modes are close in energy but separated by a 7 kcal/mol free energy barrier. Analysis of interactions in the two binding modes reveals that the driving force for monodentate catecholate orientations in classical molecular dynamics simulations is derived from stronger electrostatic stabilization afforded by alternate Mg2+ coordination with strongly charged active site carboxylates. Mixed semi-empirical-classical (SQM/MM) substrate C-O distances (2.7 Å) for the bidentate case are in excellent agreement with COMT X-ray crystal structures, as long as charge transfer between the substrates, Mg2+, and surrounding ligands is permitted. SQM/MM free energy barriers for methyl transfer from bidentate and monodentate catecholate configurations are comparable at around 21–22 kcal/mol, in good agreement with experiment (18–19 kcal/mol). Overall, the work suggests that both binding poses are viable for methyl transfer, and accurate descriptions of charge transfer and electrostatics are needed to provide balanced relative barriers when multiple binding poses are accessible, for example in other transferases.

First-principles simulation has played an ever-increasing role in the discovery and interpretation of the chemical properties of surface-adsorbate interactions.Nevertheless, key challenges remain for the computational chemist wishing to study surface chemistry: modelling the full extent of experimental conditions, managing computational cost, minimizing human effort in simulation setup, and maximizing accuracy. This article introduces new tools for streamlining surface chemistry simulation setup and reviews some of the challenges in first-principles, density functional theory (DFT) simulation of surface phenomena. Furthermore, we provide a worked example of Co tetraphenylporphyrin (CoTPP) on Au (111) in which we both analyze electronic and energetic properties with both semi-local DFT and compare to predictions made from hybrid functional and the so-called DFT+U correction. Through both review and the worked example, we aim to provide a pedagogical introduction to both the challenges and the insight that first-principles simulation can provide in surface chemistry.

Selective ion separation is a major challenge with far-ranging impact from water desalination to product separation in catalysis. Recently introduced ferrocenium(Fc + )/ferrocene(Fc) polymer electrode materials have been demonstrated experimentally and theoretically to selectively bind carboxylates over perchlorate through weak C-H … O hydrogen bond (HB) interactions that favor carboxylates, despite the comparable size and charge of the two species. However, practical application of this technology in aqueous environments requires further selectivity enhancement. Using a first-principles discovery approach, we investigate the effect of Fc/Fc + functional groups (FGs) on the selectivity and reversibility of formate-Fc + adsorption with respect to perchlorate in aqueous solution. Our wide design space of 44 FGs enables identification of FGs with higher selectivity and rationalization of trends through electronic energy decomposition analysis or geometric hydrogen bonding analysis. Overall, we observe weaker, longer HBs for perchlorate as compared to formate with Fc + . We further identify Fc + functionalizations that simultaneously increase selectivity for formate in aqueous environments but permit rapid release from neutral Fc. We introduce the materiaphore, a 3D abstraction of these design rules, to help guide nextgeneration material optimization for selective ion sorption. This approach is expected to have broad relevance in computational discovery for molecular recognition, sensing, separations, and catalysis.2