Optimal design of nanoplasmonic materials using genetic algorithms as a multiparameter optimization tool

An optimal control approach based on multiple parameter genetic algorithms is applied to the design of plasmonic nanoconstructs with predetermined optical properties and functionalities. We first develop nanoscale metallic lenses that focus an incident plane wave onto a prespecified, spatially confined spot. Our results illustrate the mechanism of energy flow through wires and cavities. Next we design a periodic array of silver particles to modify the polarization of an incident, linearly polarized plane wave in a desired fashion while localizing the light in space. The results provide insight into the structural features that determine the birefringence properties of metal nanoparticles and their arrays. Of the variety of potential applications that may be envisioned, we note the design of nanoscale light sources with controllable coherence and polarization properties that could serve for coherent control of molecular, electronic, or electromechanical dynamics in the nanoscale.     

Ligand-protein docking using a quantum stochastic tunneling optimization method

A novel hybrid optimization method called quantum stochastic tunneling has been recently introduced. Here, we report its implementation within a new docking program called EasyDock and a validation with the CCDC/Astex data set of ligand-protein complexes using the PLP score to represent the ligand-protein potential energy surface and ScreenScore to score the ligand-protein binding energies. When taking the top energy-ranked ligand binding mode pose, we were able to predict the correct crystallographic ligand binding mode in up to 75% of the cases. By using this novel optimization method run times for typical docking simulations are significantly shortened.     

Modeling and optimization of methane dry reforming over Ni-Cu/Al_2O_3 catalyst using Box-Behnken design

In this work the effects of the contents of nickel(5,7.5,10 wt%)and copper(0,1,2 wt%)and reaction temperature(650,700,750°C)on the catalytic performance of Ni–Cu/Al_2O_3catalyst in methane dry reforming were evaluated using Box–Behnken design in order to optimize methane conversion,H_2/CO ratio and the catalyst deactivation.Different catalysts were prepared by co-impregnation method and characterized by XRD,BET,H_2-TPR,FESEM and TG/DTA analyses.The results revealed that copper addition improved the catalyst reducibility.Promoted catalyst with low amounts of Cu gave higher activity and stability with high resistance to coke deposition and agglomeration of active phase especially during the reaction.However catalysts with high amounts of Cu were less active and rather deactivated due to the active sites sintering as well as Ni covering by Cu-enriched phase.The optimal conditions were determined by desirability function approach as 10 wt%of Ni,0.83 wt%of Cu at 750°C.CH_4conversion of95.1%,H_2/CO ratio of 1 and deactivation of 1.4%were obtained experimentally under optimum conditions,which were in close agreement with the values predicted by the developed model.     

Heterogeneous Baylis-Hillman using a polystyrene-bound 4-(N-benzyl-N-methylamino)pyridine as reusable catalyst

An insoluble Merrifield type resin having 4-aminopyridine units is a suitable and reusable heterogeneous catalyst for the Baylis-Hillman coupling of aromatic aldehydes and alpha,beta-unsaturated ketones.     

Ultrasound-assisted synthesis of ethyl hexanoate using heterogeneous catalyst: Optimization using Box-Behnken design

Ultrasound-assisted synthesis of ethyl hexanoate was studied in a solvent-free system using Amberlyst-15 as a heterogeneous catalyst. The effect of reaction parameters was evaluated by employing Box Behnken Design. Maximum conversion was obtained as 83.9% experimentally with operating temperature 60 °C, ethanol to hexanoic acid molar ratio as 3, 60% duty cycle, 11% catalyst loading, 10% molecular sieves, and 80 W input power which were optimized through one parameter at a time. The optimal conditions for maximum 86.66% conversion obtained by Box Behnken Design operated in Response Surface Methodology were 62.8 °C temperature, 3.31 ethanol to hexanoic acid molar ratio, and 51.58% duty cycle. The absence of external mass transfer resistances was proved by evaluating Mear's criterion. Thiele modulus and effectiveness factor were determined to study the influence of internal mass transfer resistance qualitatively. The kinetics of the heterogeneous reaction was modeled using Langmuir-Hinshelwood model. The activation energy was calculated as 24.61 kJ/mol.     

Reference energy extremal optimization: a stochastic search algorithm applied to computational protein design

We adapt a combinatorial optimization algorithm, extremal optimization (EO), for the search problem in computational protein design. This algorithm takes advantage of the knowledge of local energy information and systematically improves on the residues that have high local energies. Power-law probability distributions are used to select the backbone sites to be improved on and the rotamer choices to be changed to. We compare this method with simulated annealing (SA) and motivate and present an improved method, which we call reference energy extremal optimization (REEO). REEO uses reference energies to convert a problem with a structured local-energy profile to one with more random profile, and extremal optimization proves to be extremely efficient for the latter problem. We show in detail the large improvement we have achieved using REEO as compared to simulated annealing and discuss a number of other heuristics we have attempted to date.     

Identifying clusters as low-lying mimina--efficiency of stochastic and genetic algorithms using inexpensive electronic structure levels

Molecular candidates possessing unconventional chemical bonding paradigms (e.g., boron wheels, molecular stars, and multicenter bonding) have attracted a great deal of attention by the computational community. The viability of such systems is necessarily assessed through the identification of the lowest lying energy forms of a given chemical composition on the potential energy surface (PES). Although dozens of search algorithms have been developed, only a few are general and simple enough to become standard everyday procedures for this purpose. The simple random search and genetic algorithm (GA) are among these: but how do these approaches perform on typical isomeric searches? The performance of three specific variants for the ab initio exploration of the PES of prototype planar tetracoordinated and hypercoordinated carbon-containing systems C₂Al₄ and CB₆²⁻ are compared. The advantages of preoptimizing with a low-cost semiempirical method (e.g., PM6) together with the most cost-efficient GA-based variant are discussed, and the trends verified by the isomer search of the larger Si₅Li₇⁺ clusters. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011     

Structural optimization of model colloidal clusters at the air-water interface using genetic algorithms

The structure of colloidal clusters observed at the air-water interface is studied theoretically in this paper using a recently developed global optimization routine based on a genetic algorithm. A model potential with a secondary minimum produced from the attractive van der Waals interaction and repulsive dipolar interaction is used for the colloid-colloid interaction. The structures predicted from the genetic algorithm are not always consistent with the experimental observations; the theoretical results predict the growth of cluster as a spreading of triangular networks, however, the experimental observations seem to suggest the formation of a circular shell structure. More thorough theoretical as well as experimental studies are called for in order to obtain more conclusive evidence regarding these matters.     

Calculation of homogeneous azeotropes in reactive and non-reactive mixtures using a stochastic optimization approach

In this paper we introduce an alternative strategy to find homogeneous azeotropes in reactive and non-reactive mixtures which is based upon the Simulated Annealing optimization technique. This stochastic optimization method is used to robustly solve a system of non-linear equations that results from the equalities of the orthogonal derivatives of the Gibbs energy and the Gibbs energy of mixing in the vapor and the liquid phases. For non-reactive systems, this equation system is solved by considering conventional composition variables while for reactive cases we use the transformed composition variables proposed by Ung and Doherty. Numerical performance of our approach is illustrated using several examples previously reported in the literature and results show that it is a suitable and robust strategy for the calculation of homogeneous azeotropes in mixtures with or without chemical reactions.     

Heterogeneous Suzuki and Stille coupling reactions using highly efficient palladium(0) immobilized MCM-41 catalyst

An efficient palladium(0) immobilized MCM-41 catalytic system for C-C cross-coupling reaction has been developed. Ligand-free Pd(0)-MCM-41 catalyst can be successfully used in coupling reaction between various aryl halides including deactivated chlorobenzene with aryl borane and organotin to give biaryls in excellent yields with high turnover frequency (TOF) (the maximal TOFs are up to 6990 for the reaction of bromobenzene with phenylboronic acid). The catalyst can be recycled and reused without any loss of catalytic activity.     

Chiral catalyst optimization using both solid-phase and liquid-phase methods in asymmetric aza Diels-Alder reactions

[formula: see text] In the presence of 1-5 mol % of a chiral zirconium catalyst, aza Diels-Alder reactions of aldimines with Danishefsky's dienes proceeded smoothly to afford the corresponding piperidine derivatives in high yields with high enantioselectivities. For the catalyst optimization, solid-phase and liquid-phase methods were successfully used. In the solid-phase approach, polymer-supported (R)-1,1'-binaphthols (BINOLs) have been synthesized and rapid optimization using the solid-phase reactions has been achieved. On the other hand, novel chiral zirconium cyanides were developed as excellent catalysts using the liquid-phase approach.     

Evolutionary algorithms in computer-aided molecular design

Summary In recent years, search and optimisation algorithms inspired by evolutionary processes have been applied with marked success to a wide variety of problems in diverse fields of study. In this review, we survey the growing application of these evolutionary algorithms in one such area: computer-aided molecular design. In the course of the review, we seek to summarise the work to date and to indicate where evolutionary algorithms have met with success and where they have not fared so well. In addition to this, we also attempt to discern some future trends in both the basic research concerning these algorithms and their application to the elucidation, design and modelling of chemical and biochemical structures.     

Optimal control design of NMR and dynamic nuclear polarization experiments using monotonically convergent algorithms

Optimal control theory has recently been introduced to nuclear magnetic resonance (NMR) spectroscopy as a means to systematically design and optimize pulse sequences for liquid- and solid-state applications. This has so far primarily involved numerical optimization using gradient-based methods, which allow for the optimization of a large number of pulse sequence parameters in a concerted way to maximize the efficiency of transfer between given spin states or shape the nuclear spin Hamiltonian to a particular form, both within a given period of time. Using such tools, a variety of new pulse sequences with improved performance have been developed, and the NMR spin engineers have been challenged to consider alternative routes for analytical experiment design to meet similar performance. In addition, it has lead to increasing demands to the numerical procedures used in the optimization process in terms of computational speed and fast convergence. With the latter aspect in mind, here we introduce an alternative approach to numerical experiment design based on the Krotov formulation of optimal control theory. For practical reasons, the overall radio frequency power delivered to the sample should be minimized to facilitate experimental implementation and avoid excessive sample heating. The presented algorithm makes explicit use of this requirement and iteratively solves the stationary conditions making sure that the maximum of the objective is reached. It is shown that this method is faster per iteration and takes different paths within a control space than gradient-based methods. In the present work, the Krotov approach is demonstrated by the optimization of NMR and dynamic nuclear polarization experiments for various spin systems and using different constraints with respect to radio frequency and microwave power consumption.     

Factorial design evaluation of the Suzuki cross-coupling reaction using a magnetically recoverable palladium catalyst

A magnetically recoverable catalyst [Fe₃O₄@SiO₂-AEAPTMS-Pd(II)] was prepared, fully characterized and had its catalytic activity evaluated on the Suzuki cross-coupling reaction under microwave irradiation. The reaction conditions for the synthesis of biaryl compounds was optimized in two stages - an initial fractional design 2⁴, in which the parameters reaction time, temperature, solvent and catalyst loading were evaluated, followed by a Doehlert design. The factorial design proved to be a viable approach for obtaining the optimal reaction conditions based on a relatively small number of experiments. Additionally, the biaryl derivatives synthesized by this method were obtained with good to excellent yields (71–96%) and the recovery and reuse of the palladium catalyst was also evaluated.     

Bioinspired catalyst design and artificial metalloenzymes

Many bioinspired transition-metal catalysts have been developed over the recent years. In this review the progress in the design and application of ligand systems based on peptides and DNA and the development of artificial metalloenzymes are reviewed with a particular emphasis on the combination of phosphane ligands with powerful molecular recognition and shape selectivity of biomolecules. The various approaches for the assembly of these catalytic systems will be highlighted, and the possibilities that the use of the building blocks of Nature provide for catalyst optimisation strategies are discussed.     

Heterogeneous Shvo-type ruthenium catalyst: dehydrogenation of alcohols without hydrogen acceptors

A Shvo-type diruthenium complex is heterogenized by a sol-gel process, which catalyzes the conversion of alcohols to carbonyl compounds and molecular hydrogen without any additive. The heterogeneous catalyst is recoverable by simple filtration, stable in the air, and reusable.     

Fast search algorithms for computational protein design

One of the main challenges in computational protein design (CPD) is the huge size of the protein sequence and conformational space that has to be computationally explored. Recently, we showed that state‐of‐the‐art combinatorial optimization technologies based on Cost Function Network (CFN) processing allow speeding up provable rigid backbone protein design methods by several orders of magnitudes. Building up on this, we improved and injected CFN technology into the well‐established CPD package Osprey to allow all Osprey CPD algorithms to benefit from associated speedups. Because Osprey fundamentally relies on the ability of to produce conformations in increasing order of energy, we defined new strategies combining CFN lower bounds, with new side‐chain positioning‐based branching scheme. Beyond the speedups obtained in the new ‐CFN combination, this novel branching scheme enables a much faster enumeration of suboptimal sequences, far beyond what is reachable without it. Together with the immediate and important speedups provided by CFN technology, these developments directly benefit to all the algorithms that previously relied on the DEE/ combination inside Osprey* and make it possible to solve larger CPD problems with provable algorithms. © 2016 Wiley Periodicals, Inc.     

Automated pharmacophore query optimization with genetic algorithms - a case study using the MC4R system

Due to the recent availability of high quality small molecule databases, such as ZINC and PubChem,1,2 virtual screening is playing an even more important role in identifying biologically relevant molecules in drug discovery campaigns. The success of pharmacophore-based virtual screening (PBVS) relies largely on the accuracy and specificity of the pharmacophore query employed. Deriving a pharmacophore query from a single structure inevitably introduces uncertainty, and the derived query is unlikely to be optimal against every collection of input compounds, especially when it is desired to discriminate among compounds with similar chemical structures. In this study, we present an optimization approach empowered by genetic algorithms (GA) to enhance the accuracy and specificity of a primary pharmacophore query. The example utilized is the human melanocortin type 4 receptor (hMC4R), for which the pharmacophore query was built on the basis of the structure of a rigid cyclic peptide agonist.(3) The optimized query is shown to be capable of identifying 37 positive hMC4R agonists with no false positives from a training set containing 55 agonists and 51 nonagonists. This represents a significant improvement from the initial query which exhibited a 37/32 hit rate. The final, optimized query is challenged with a testing set comprising of 55 hMC4R agonists and 50 nonagonists and achieves a hit rate of 33/8, that improved from 40/31. The impact of GA controlling parameters, including mutation rate, crossover rate, fitness function, population size, and convergence criterion, on performance of optimization are examined and discussed.     

Heterogeneous methane oxidative coupling using perovskites

Catalytic oxidative coupling of methane over perovskite CaTiO₃ prepared by modified ceramic method has been studied. The C₂ yield was 13% at 830 °C and promotion with Na₄P₂O₇ did not improve considerably the catalyst peformance. Regarding reactor test and mechanism studies it is believed that charge deficient, oxygen O^– generated by transforming oxygen adsorbed on surface defects and dissolved into bulk vacancies is responsible for activating methane (active site). Adsorbed oxygen generates the oxidizing sites for actived methane. Strict conditions are required for generation and regeneration of the activating sites in lattice.