Nearest neighbour diagnostic statistics on the accuracy of APT solute cluster characterisation

Diagnostic statistics and information theory techniques have been developed to investigate the accuracy to which solute clusters characterised in atom probe tomography (APT) data can reflect the true nature of the physical clusters in the original specimen. Simulated atom-probe datasets representing a range of atomic solute clustering within a pseudo-binary alloy upon an fcc aluminium lattice were generated for the study. The effectiveness of partitioning the APT-like simulated data based upon a binary classification defined by a distance threshold d _max upon the kth nearest neighbour distance distribution was investigated. Information theory was also used to optimise the selection of the threshold d _max. Analysis of variation was performed upon a factorial design of data simulations with low and high levels of: solute concentration; short-range order; and background to the mass-to-charge-state-ratio spectrum. This meta-analysis showed that the background levels have a significant compromising effect upon the binary classification in low solute systems with relatively low or random levels of clustering. Although the random clustering of higher solute concentrations is better analysed, significantly non-random clustering in both low and high solute concentrations is analysed well despite the presence of high levels of background. A meta-analysis of the binary classification upon a simulated dispersion of coherent precipitates within a similar matrix was also undertaken. Optimal k and d _max parameters are likely a dependent upon the physical dimensions of precipitate size as well as the precipitate/matrix solute concentrations.     

A Dual Threat: Redox-Activity and Electronic Structures of Well-Defined Donor–Acceptor Fulleretic Covalent-Organic Materials

The effect of donor (D)–acceptor (A) alignment on the materials electronic structure was probed for the first time using novel purely organic porous crystalline materials with covalently bound two- and three-dimensional acceptors. The first studies towards estimation of charge transfer rates as a function of acceptor stacking are in line with the experimentally observed drastic, eight-fold conductivity enhancement. The first evaluation of redox behavior of buckyball- or tetracyanoquinodimethane-integrated crystalline was conducted. In parallel with tailoring the D-A alignment responsible for “static” changes in materials properties, an external stimulus was applied for “dynamic” control of the electronic profiles. Overall, the presented D–A strategic design, with stimuli-controlled electronic behavior, redox activity, and modularity could be used as a blueprint for the development of electroactive and conductive multidimensional and multifunctional crystalline porous materials.     

Stack the Bowls: Tailoring the Electronic Structure of Corannulene‐Integrated Crystalline Materials

We report the first examples of purely organic donor–acceptor materials with integrated π‐bowls (πBs) that combine not only crystallinity and high surface areas but also exhibit tunable electronic properties, resulting in a four‐orders‐of‐magnitude conductivity enhancement in comparison with the parent framework. In addition to the first report of alkyne–azide cycloaddition utilized for corannulene immobilization in the solid state, we also probed the charge transfer rate within the Marcus theory as a function of mutual πB orientation for the first time, as well as shed light on the density of states near the Fermi edge. These studies could foreshadow new avenues for πB utilization for the development of optoelectronic devices or a route for highly efficient porous electrodes.     

(2E)‐N‐(2‐Iodo‐4,6‐dimethylphenyl)‐2‐methylbut‐2‐enamide

The title compound, C₁₄H₁₈INO, crystallizes as +sc/+sp/+sc 2‐iodoanilide molecules (and racemic opposites) and shows significant intermolecular I...O interactions in the solid state, forming dimeric pairs about centres of symmetry. Under asymmetric Heck conditions, the S enantiomer of the dihydroindol‐2‐one was obtained using (R)‐(+)‐2,2′‐bis(diphenylphosphino)‐1,1′‐binaphthyl [(R)‐BINAP], suggesting a mechanism that proceeds by oxidative addition to give the title (P) enantiomer of the compound and pro‐S coordination of the Re face of the alkene in a conformation similar to that defined crystallographically, except that rotation about the C—C bond of the butenyl group is required.     

Application of computer simulation free-energy methods to compute the free energy of micellization as a function of micelle composition. 1. Theory

The widespread use of surfactant mixtures and surfactant/solubilizate mixtures in practical applications motivates the development of predictive theoretical approaches to improve fundamental understanding of the behavior of these complex self-assembling systems and to facilitate the design and optimization of new surfactant and surfactant/solubilizate mixtures. This paper is the first of two articles introducing a new computer simulation-free-energy/molecular thermodynamic (CS-FE/MT) model. The two articles explore the application of computer simulation free-energy methods to quantify the thermodynamics associated with mixed surfactant/cosurfactant and surfactant/solubilizate micelle formation in aqueous solution. In this paper (article 1 of the series), a theoretical approach is introduced to use computer simulation free-energy methods to compute the free-energy change associated with changing micelle composition (referred to as DeltaDeltaGi). In this approach, experimental critical micelle concentration (CMC) data, or a molecular thermodynamic model of micelle formation, is first used to evaluate the free energy associated with single (pure) surfactant micelle formation, g(form,single), in which the single surfactant micelle contains only surfactant A molecules. An iterative approach is proposed to combine the estimated value of gform,single with free-energy estimates of DeltaDeltaGi based on computer simulation to determine the optimal free energy of mixed micelle formation, the optimal micelle aggregation number and composition, and the optimal bulk solution composition. After introducing the CS-FE/MT modeling framework, a variety of free-energy methods are briefly reviewed, and the selection of the thermodynamic integration free-energy method is justified and selected to implement the CS-FE/MT model. An alchemical free-energy pathway is proposed to allow evaluation of the free-energy change associated with exchanging a surfactant A molecule with a surfactant/solubilizate B molecule through thermodynamic integration. In article 2 of this series, the implementation of the CS-FE/MT model to make DeltaDeltaGi free-energy predictions for several surfactant/solubilizate systems is discussed, and the predictions of the CS-FE/MT model are compared with the DeltaDeltaGi predictions of a molecular thermodynamic model fitted to relevant experimental data.     

Application of computer simulation free-energy methods to compute the free energy of micellization as a function of micelle composition. 2. Implementation

In this paper, the implementation of the CS-FE/MT model introduced in article 1 is discussed, and computer simulations are performed to evaluate the feasibility of the new theoretical approach. As discussed in article 1, making predictions of surfactant/solubilizate aqueous solution behavior using the CS-FE/MT model requires evaluation of DeltaDeltaG for multiple surfactant-to-solubilizate or surfactant-to-cosurfactant transformations. The central goal of this article is to evaluate the quantitative accuracy of the alchemical computer simulation method used in the CS-FE/MT modeling approach to predict DeltaDeltaG for a single surfactant-to-solubilizate or for a single surfactant-to-cosurfactant transformation. A hybrid single/dual topology approach was used to morph the ionic surfactant sodium dodecyl sulfate (SDS) into the ionic solubilizate ibuprofen (IBU), and a dual topology approach was used to morph the nonionic surfactant octyl glucoside (OG) into the nonionic solubilizate p-aminobenzoate (PAB). In addition, a single topology approach was used to morph the nonionic surfactant n-decyl dimethylphosphine oxide (C10PO) into the nonionic cosurfactant n-decyl methyl sulfoxide (C10SO), the nonionic surfactant octylsulfinyl ethanol (C8SE) into the nonionic cosurfactant decylsulfinyl ethanol (C10SE), and the nonionic surfactant n-decyl methyl sulfoxide (C10SO) into the nonionic cosurfactant n-octyl methyl sulfoxide (C8SO). Each DeltaDeltaG value was computed by using thermodynamic integration to determine the difference in free energy associated with (i) transforming a surfactant molecule of type A into a cosurfactant/solubilizate molecule of type B in a micellar environment (referred to as DeltaG2) and (ii) transforming a surfactant molecule of type A into a cosurfactant/solubilizate molecule of type B in aqueous solution (referred to as DeltaG1). CS-FE/MT model predictions of DeltaDeltaG for each alchemical transformation were made at a number of simulation conditions, including (i) different equilibration times at each value of the coupling parameter lambda, (ii) different data-gathering times at each lambda value, and (iii) simulation at a different number of lambda values. For the three surfactant-to-cosurfactant transformations considered here, the DeltaDeltaG values predicted by the CS-FE/MT model were compared with DeltaDeltaG values predicted by an accurate molecular thermodynamic (MT) model developed by fitting to experimental CMC data. Even after performing lengthy equilibration and data gathering at each lambda value, physically unrealistic values of DeltaDeltaG were predicted by the CS-FE/MT model for the transformations of SDS into IBU and of OG into PAB. However, more physically realistic DeltaDeltaG values were predicted for the transformation of C10PO into C10SO, and reasonable free-energy predictions were obtained for the transformations of C8SE into C10SE and C10SO into C8SO. Each of the surfactant-to-cosurfactant transformations considered here involved less extensive structural changes than the surfactant-to-solubilizate transformations. As computer power increases and as improvements are made to alchemical free-energy methods, it may become possible to apply the CS-FE/MT model to make accurate predictions of the free-energy changes associated with forming multicomponent surfactant and solubilizate micelles in aqueous solution where the chemical structures of the surfactants, cosurfactants, and solubilizates differ significantly.     

Mechanistic study of iron(III) [tetrakis(pentafluorophenyl)porphyrin triflate (F(20)TPP)Fe(OTf) catalyzed cyclooctene epoxidation by hydrogen peroxide

We have recently proposed a mechanism for the epoxidation of cyclooctene by H2O2 catalyzed by iron(III) [tetrakis(pentafluorophenyl)]porphyrin chloride, (F20TPP)FeCl, in solvent containing methanol [Stephenson, N. A.; Bell, A.T. Inorg. Chem. 2006, 45, 2758-2766]. In that study, we found that catalysis did not occur unless (F20TPP)FeCl first dissociated, a process facilitated by the solvation of the Cl- anion by methanol and the coordination of methanol to the (F20TPP)Fe+ cation. Methanol as well as other alcohols was also found to facilitate the heterolytic cleavage of the O-O bond of H2O2 coordinated to the (F20TPP)Fe+ cation via a generalized acid mechanism. In the present study, we have shown that catalytic activity of the (F20TPP)Fe+ cation can be achieved in aprotic solvent by displacing the tightly bound chloride anion with a weakly bound triflate anion. By working in an aprotic solvent, acetonitrile, it was possible to determine the rate of heterolytic O-O bond cleavage in coordinated H2O2 unaffected by the interaction of the peroxide with methanol. A mechanism is proposed for this system and is shown to be valid over a range of reaction conditions. The mechanisms for cyclooctene epoxidation and H2O2 decomposition for the aprotic and protic solvent systems are similar with the only difference being the mechanism of proton-transfer prior to heterolytic cleavage of the oxygen-oxygen bond of coordinated hydrogen peroxide. Comparison of the rate parameters indicates that the utilization of hydrogen peroxide for cyclooctene epoxidation is higher in a protic solvent than in an aprotic solvent and results in a smaller extent of porphyrin degradation due to free radical attack. It was also shown that water can coordinate to the iron porphyrin cation in aprotic systems resulting in catalyst deactivation; this effect was not observed when methanol was present, since methanol was found to displace all of the coordinated water.     

Quantifying the hydrophobic effect. 1. A computer simulation-molecular-thermodynamic model for the self-assembly of hydrophobic and amphiphilic solutes in aqueous solution

Surfactant micellization and micellar solubilization in aqueous solution can be modeled using a molecular-thermodynamic (MT) theoretical approach; however, the implementation of MT theory requires an accurate identification of the portions of solutes (surfactants and solubilizates) that are hydrated and unhydrated in the micellar state. For simple solutes, such identification is comparatively straightforward using simple rules of thumb or group-contribution methods, but for more complex solutes, the hydration states in the micellar environment are unclear. Recently, a hybrid method was reported by these authors in which hydrated and unhydrated states are identified by atomistic simulation, with the resulting information being used to make MT predictions of micellization and micellar solubilization behavior. Although this hybrid method improves the accuracy of the MT approach for complex solutes with a minimum of computational expense, the limitation remains that individual atoms are modeled as being in only one of two states-head or tail-whereas in reality, there is a continuous spectrum of hydration states between these two limits. In the case of hydrophobic or amphiphilic solutes possessing more complex chemical structures, a new modeling approach is needed to (i) obtain quantitative information about changes in hydration that occur upon aggregate formation, (ii) quantify the hydrophobic driving force for self-assembly, and (iii) make predictions of micellization and micellar solubilization behavior. This article is the first in a series of articles introducing a new computer simulation-molecular thermodynamic (CS-MT) model that accomplishes objectives (i)-(iii) and enables prediction of micellization and micellar solubilization behaviors, which are infeasible to model directly using atomistic simulation. In this article (article 1 of the series), the CS-MT model is introduced and implemented to model simple oil aggregates of various shapes and sizes, and its predictions are compared to those of the traditional MT model. The CS-MT model is formulated to allow the prediction of the free-energy change associated with aggregate formation (gform) of solute aggregates of any shape and size by performing only two computer simulations-one of the solute in bulk water and the other of the solute in an aggregate of arbitrary shape and size. For the 15 oil systems modeled in this article, the average discrepancy between the predictions of the CS-MT model and those of the traditional MT model for gform is only 1.04%. In article 2, the CS-MT modeling approach is implemented to predict the micellization behavior of nonionic surfactants; in article 3, it is used to predict the micellization behavior of ionic and zwitterionic surfactants.     

Quantifying the hydrophobic effect. 3. A computer simulation-molecular-thermodynamic model for the micellization of ionic and zwitterionic surfactants in aqueous solution

In this article, the validity and accuracy of the CS-MT model introduced in article 1 for oil aggregates and in article 2 for nonionic surfactants is further evaluated by using it to model the micellization behavior of ionic and zwitterionic surfactants in aqueous solution. In the CS-MT model, two separate free-energy contributions to the hydrophobic driving force for micelle formation are computed using hydration data obtained from computer simulation: gdehydr, the free-energy change associated with dehydration, and ghydr, the change in the hydration free energy. To enable straightforward estimation of gdehydr and ghydr for ionic and zwitterionic surfactants, a number of simplifying approximations were made. Reasonable agreement between the CMCs predicted using the CS-MT model and the experimental CMCs was obtained for sodium dodecyl sulfate (SDS), dodecylphophocholine (DPC), cetyltrimethylammonium bromide (CTAB), two 3-hydroxy sulfonate surfactants (AOS-12 and AOS-16), and a homologous series of four DCNA bromide surfactants with a dimethylammonium head attached to a dodecyl alkyl tail and to an alkyl side chain of length CN, having the chemical formula C12H25CNH2N+1N(CH3)2Br, with N = 1 (DC1AB), 2 (DC2AB), 4 (DC4AB), and 6 (DC6AB). For six of these nine surfactants, the CMCs predicted using the CS-MT model are closer to the experimental CMCs than the CMCs predicted using the traditional molecular-thermodynamic (MT) model. For DC2AB, DC4AB, and DC6AB, which are the most structurally complex of the ionic surfactants modeled, the CMCs predicted using the CS-MT model are in remarkably good agreement with the experimental CMCs, and the CMCs predicted using the traditional MT model are quite inaccurate. Our results suggest that the CS-MT model accurately quantifies the hydrophobic driving force for micelle formation for ionic and zwitterionic surfactants in aqueous solution. For complex ionic and zwitterionic surfactants where it is difficult to accurately quantify the hydrophobic driving force for micelle formation using the traditional MT modeling approach, the CS-MT model represents a very promising alternative.     

Vector generalized linear and additive extreme value models

Over recent years parametric and nonparametric regression has slowly been adopted into extreme value data analysis. Its introduction has been characterized by piecemeal additions and embellishments, which has had a negative effect on software development and usage. The purpose of this article is to convey the classes of vector generalized linear and additive models (VGLMs and VGAMs) as offering significant advantages for extreme value data analysis, providing flexible smoothing within a unifying framework. In particular, VGLMs and VGAMs allow all parameters of extreme value distributions to be modelled as linear or smooth functions of covariates. We implement new auxiliary methodology by incorporating a quasi-Newton update for the working weight matrices within an iteratively reweighted least squares (IRLS) algorithm. A software implementation by the first author, called the vgam package for , is used to illustrate the potential of VGLMs and VGAMs.