Catalytic, Conductive Bipolar Membrane Interfaces through Layer-by-Layer Deposition for the Design of Membrane-Integrated Artificial Photosynthesis Systems

In the presence of an electric field, bipolar membranes (BPMs) are capable of initiating water disassociation (WD) within the interfacial region, which can make water splitting for renewable energy in the presence of a pH gradient possible. In addition to WD catalytic efficiency, there is also the need for electronic conductivity in this region for membrane-integrated artificial photosynthesis (AP) systems. Graphene oxide (GO) was shown to catalyze WD and to be controllably reduced, which resulted in electronic conductivity. Layer-by-layer (LbL) film deposition was employed to improve GO film uniformity in the interfacial region to enhance WD catalysis and, through the addition of a conducting polymer in the process, add electronic conductivity in a hybrid film. Three different deposition methods were tested to optimize conducting polymer synthesis with the oxidant in a metastable solution and to yield the best film properties. It was found that an approach that included substrate dipping in a solution containing the expected final monomer/oxidant ratio provided the most predictable film growth and smoothest films (by UV/Vis spectroscopy and atomic force microscopy/scanning electron microscopy, respectively), whereas dipping in excess oxidant or co-spraying the oxidant and monomer produced heterogeneous films. Optimized films were found to be electronically conductive and produced a membrane ohmic drop that was acceptable for AP applications. Films were integrated into the interfacial region of BPMs and revealed superior WD efficiency (≥1.4 V at 10 mA cm⁻²) for thinner films (<10 bilayers≈100 nm) than for either the pure GO catalyst or conducting polymer individually, which indicated that there was a synergistic effect between these materials in the structure configured by the LbL method.National Science Foundation (Grant CHE‐1305124

Relatively Smooth Convex Optimization by First-Order Methods, and Applications

The usual approach to developing and analyzing first-order methods for smooth convex optimization assumes that the gradient of the objective function is uniformly smooth with some Lipschitz constant L. However, in many settings the differentiable convex function f(?) is not uniformly smooth-for example, in D-optimal design where f(x) := -ln det(HXHT) and X := Diag(x), or even the univariate setting with f(x) := -ln(x)+x2. In this paper we develop a notion of "relative smoothness" and relative strong convexity that is determined relative to a user-specified "reference function" h(?) (that should be computationally tractable for algorithms), and we show that many differentiable convex functions are relatively smooth with respect to a correspondingly fairly simple reference function h(?). We extend two standard algorithms-the primal gradient scheme and the dual averaging scheme-to our new setting, with associated computational guarantees. We apply our new approach to develop a new first-order method for the D-optimal design problem, with associated computational complexity analysis. Some of our results have a certain overlap with the recent work [H. H. Bauschke, J. Bolte, and M. Teboulle, Math. Oper. Res., 42 (2017), pp. 330-348]

Accelerating greedy coordinate descent methods

We introduce and study two algorithms to accelerate greedy coordinate descent in theory and in practice: Accelerated Semi-Greedy Coordinate Descent (ASCD) and Accelerated Greedy Co-ordinate Descent (AGCD). On the theory side, our main results are for ASCD: We show that ASCD achieves 0(l/k[superscript 2]) convergence, and it also achieves accelerated linear convergence for strongly convex functions. On the empirical side, while both AGCD and ASCD outperform Accelerated Randomized Coordinate Descent on most instances in our numerical experiments, we note that AGCD significantly outperforms the other two methods in our experiments, in spite of a lack of theoretical guarantees for this method. To complement this empirical finding for AGCD, we present an explanation why standard proof techniques for acceleration cannot work for AGCD, and we introduce a technical condition under which AGCD is guaranteed to have accelerated convergence. Finally, we confirm that this technical condition holds in our numerical experiments

Designing Phononic Crystals With Convex Optimization

Designing phononic crystals by creating frequency bandgaps is of particular interest in the engineering of elastic and acoustic microstructured materials. Mathematically, the problem of optimizing the frequency bandgaps is often nonconvex, as it requires the maximization of the higher indexed eigenfrequency and the minimization of the lower indexed eigenfrequency. A novel algorithm [1] has been previously developed to reformulate the original nonlinear, nonconvex optimization problem to an iteration-specific semidefinite program (SDP). This algorithm separates two consecutive eigenvalues — effectively maximizing bandgap (or bandwidth) — by separating the gap between two orthogonal subspaces, which are comprised columnwise of “important” eigenvectors associated with the eigenvalues being bounded. By doing so, we avoid the need of computation of eigenvalue gradient by computing the gradient of affine matrices with respect to the decision variables. In this work, we propose an even more efficient algorithm based on linear programming (LP). The new formulation is obtained via approximation of the semidefinite cones by judiciously chosen linear bases, coupled with “delayed constraint generation”. We apply the two convex conic formulations, namely, the semidefinite program and the linear program, to solve the bandgap optimization problems. By comparing the two methods, we demonstrate the efficacy and efficiency of the LP-based algorithm in solving the category of eigenvalue bandgap optimization problems.United States. Air Force Office of Scientific Research (FA9550-11- 1-0141

Bandgap Optimization of Two-Dimensional Photonic Crystals Using Semidefinite Programming and Subspace Methods

In this paper, we consider the optimal design of photonic crystal structures for two-dimensional square lattices. The mathematical formulation of the bandgap optimization problem leads to an infinite-dimensional Hermitian eigenvalue optimization problem parametrized by the dielectric material and the wave vector. To make the problem tractable, the original eigenvalue problem is discretized using the finite element method into a series of finite-dimensional eigenvalue problems for multiple values of the wave vector parameter. The resulting optimization problem is large-scale and non-convex, with low regularity and non-differentiable objective. By restricting to appropriate eigenspaces, we reduce the large-scale non-convex optimization problem via reparametrization to a sequence of small-scale convex semidefinite programs (SDPs) for which modern SDP solvers can be efficiently applied. Numerical results are presented for both transverse magnetic (TM) and transverse electric (TE) polarizations at several frequency bands. The optimized structures exhibit patterns which go far beyond typical physical intuition on periodic media design

Numerical Assessment and Optimization of Discrete-Variable Time-Frequency Quantum Key Distribution

The discrete variables (DV) time-frequency (TF) quantum key distribution (QKD) protocol is a BB84 like protocol, which utilizes time and frequency as complementary bases. As orthogonal modulations, pulse position modulation (PPM) and frequency shift keying (FSK) are capable of transmitting several bits per symbol, i.e. per photon. However, unlike traditional binary polarization shift keying, PPM and FSK do not allow perfectly complementary bases. So information is not completely deleted when the wrong-basis filters are applied. Since a general security proof does not yet exist, we numerically assess DV-TF-QKD. We show that the secret key rate increases with a higher number of symbols per basis. Further we identify the optimal pulse relations in the two bases in terms of key rate and resistance against eavesdropping attacks.Comment: 9 Pages, 4 Figure

Sexual Attraction to Others: A Comparison of Two Models of Alloerotic Responding in Men

The penile response profiles of homosexual and heterosexual pedophiles, hebephiles, and teleiophiles to laboratory stimuli depicting male and female children and adults may be conceptualized as a series of overlapping stimulus generalization gradients. This study used such profile data to compare two models of alloerotic responding (sexual responding to other people) in men. The first model was based on the notion that men respond to a potential sexual object as a compound stimulus made up of an age component and a gender component. The second model was based on the notion that men respond to a potential sexual object as a gestalt, which they evaluate in terms of global similarity to other potential sexual objects. The analytic strategy was to compare the accuracy of these models in predicting a man’s penile response to each of his less arousing (nonpreferred) stimulus categories from his response to his most arousing (preferred) stimulus category. Both models based their predictions on the degree of dissimilarity between the preferred stimulus category and a given nonpreferred stimulus category, but each model used its own measure of dissimilarity. According to the first model (“summation model”), penile response should vary inversely as the sum of stimulus differences on separate dimensions of age and gender. According to the second model (“bipolar model”), penile response should vary inversely as the distance between stimulus categories on a single, bipolar dimension of morphological similarity—a dimension on which children are located near the middle, and adult men and women are located at opposite ends. The subjects were 2,278 male patients referred to a specialty clinic for phallometric assessment of their erotic preferences. Comparisons of goodness of fit to the observed data favored the unidimensional bipolar model

Benzoxaborole treatment perturbs S-adenosyl-L-methionine metabolism in Trypanosoma brucei

The parasitic protozoan Trypanosoma brucei causes Human African Trypanosomiasis and Nagana in other mammals. These diseases present a major socio-economic burden to large areas of sub-Saharan Africa. Current therapies involve complex and toxic regimens, which can lead to fatal side-effects. In addition, there is emerging evidence for drug resistance. AN5568 (SCYX-7158) is a novel benzoxaborole class compound that has been selected as a lead compound for the treatment of HAT, and has demonstrated effective clearance of both early and late stage trypanosomiasis in vivo. The compound is currently awaiting phase III clinical trials and could lead to a novel oral therapeutic for the treatment of HAT. However, the mode of action of AN5568 in T. brucei is unknown. This study aimed to investigate the mode of action of AN5568 against T. brucei, using a combination of molecular and metabolomics-based approaches.Treatment of blood-stage trypanosomes with AN5568 led to significant perturbations in parasite metabolism. In particular, elevated levels of metabolites involved in the metabolism of S-adenosyl-L-methionine, an essential methyl group donor, were found. Further comparative metabolomic analyses using an S-adenosyl-L-methionine-dependent methyltransferase inhibitor, sinefungin, showed the presence of several striking metabolic phenotypes common to both treatments. Furthermore, several metabolic changes in AN5568 treated parasites resemble those invoked in cells treated with a strong reducing agent, dithiothreitol, suggesting redox imbalances could be involved in the killing mechanism

Array-based vapor sensing using chemically sensitive, polymer composite resistors

We describe herein the construction of simple, low-power, broadly responsive vapor sensors. Insulating polymer-conductor composites have been shown to swell reversibly upon exposure to vapors. Thin films of polymer composites have been deposited across two metallic leads, with swelling-induced resistance changes of the films signaling the presence of vapors. To identify and classify vapors, arrays of such vapor-sensing elements have been constructed, with each element containing either carbon black or poly(pyrrole) as the conducting phase mixed with one of several different organic polymers as the insulating phase. A convenient chemical polymerization of poly(pyrrole) which allows a high degree of processibility is also described. The differing gas-solid partition coefficients for the various polymers of the sensor array produce a pattern of resistance changes that can be used to classify vapors and vapor mixtures. This type of sensor array has been shown to resolve common organic solvents, including molecules of different classes (such as aromatics from alcohols) as well as those within a particular class (such as benzene from toluene and methanol from ethanol). The response of an individual composite to varying concentrations of solvent is shown to be consistent with the predictions of percolation theory. Accordingly, significant increases in the signals of array elements have been observed for carbon black-polymer composites that were operated near their percolation thresholds