Generalized uncertainty principle and self-adjoint operators

In this work we explore the self-adjointness of the GUP-modified momentum and Hamiltonian operators over different domains. In particular, we utilize the theorem by von-Neumann for symmetric operators in order to determine whether the momentum and Hamiltonian operators are self-adjoint or not, or they have self-adjoint extensions over the given domain. In addition, a simple example of the Hamiltonian operator describing a particle in a box is given. The solutions of the boundary conditions that describe the self-adjoint extensions of the specific Hamiltonian operator are obtained.     

Modeling viscoelastic properties of triblock copolymers: A DPD simulation study

Gel systems based on self‐assembled, amphiphilic ABA triblock copolymers in midblock‐selective solvent form stable, spatially extended networks with controllable morphology and tunable viscoelastic behavior. In this work, we systematically evaluate the mechanical properties of these gels using morphology calculations, and a nonequilibrium oscillatory shear technique based on the dissipative particle dynamics (DPD) method. Our simulations demonstrate that low molecular weight triblock copolymers with incompatible blocks self‐assemble into micelles connected with bridges and loop‐like chains comprised of the solvent‐selective polymer midblocks. The fraction of bridges, ?_b, generally increases with increasing relative volume of the midblock, x, defined as the ratio of midblock and endblock volumes ( ). For our model, ?_b reaches a plateau at approximately x > 9 for a strongly selective solvent. At this limit, the value of ?_b increases from 0.40 to about 0.66 as the copolymer concentration, c, increases from 0.2 to 0.5; however, this increase is less significant at higher concentrations. The elastic response of the gel studied here is comparable with the Rouse modulus. The elastic modulus increases with polymer concentration, and it exhibits a broad peak within 6 < x < 12. Finally, we present an approximate method to predict the elastic modulus of unentangled ABA triblock copolymers based solely on the morphology of the micellar gel, which can be gleaned from equilibrium DPD simulations. We demonstrate that our simulation results are in good qualitative agreement with other theoretical predictions and experimental data. © 2009 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 48: 15–25, 2010     

Nanoparticles in solutions of adsorbing polymers: pair interactions, percolation, and phase behavior

We study the polymer adsorption characteristics, pair-interaction potentials, and phase and percolation behavior in nanoparticle-polymer mixtures. We propose a "saturable" adsorption model to capture the effect of the finite surface saturation capacity for adsorption, and use polymer self-consistent field theory in combination with a McMillan-Mayer framework [McMillan, W. G., Jr.; Mayer, J. E. J. Chem. Phys. 1945, 13, 276] to compute the pair-interaction potentials. Our results demonstrate novel size effects that distinguish the adsorption characteristics of nanoparticles from that of larger particles. Specifically, we predict that the nanoparticle regime is characterized by a significant adsorbance of polymers, albeit distributed predominantly in the form of tails. We also demonstrate that an interplay between the surface saturation, polymer-to-particle size ratios, and the polymer concentrations governs the overall effective interactions between nanoparticles in the presence of an adsorbing polymer. We use simple, mean-field models to relate these characteristics to the phase and percolation behavior in such systems. Our results show that the percolation thresholds for smaller particles are significantly smaller (and, overall, correspond only to a few volume percent) compared to that of the larger particles. Further, with a decrease in the size of the particles, we also predict a considerable increase in the miscibility of the polymer-particle mixtures. Our results are qualitatively in accord with many experimental observations in the nanoparticle regime.     

Polymer-bridged gels of nanoparticles in solutions of adsorbing polymers

We use a combination of polymer mean field theory and Monte Carlo simulations to study the polymer-bridged gelation, clustering behavior, and elastic moduli of polymer-nanoparticle mixtures. Polymer self-consistent field theory is first numerically implemented to quantify both the polymer induced interparticle interaction potentials and the conformational statistics of polymer chains between two spherical particles. Subsequently, the formation and structure of polymer-bridged nanoparticle gels are examined using Monte Carlo simulations. Our results indicate a universality in the fractal structure for the polymer-bridged networks over a wide range of parametric conditions. Explicitly, near the gelation transition, the fractal dimension d(f) ranges between 2.2 and 2.5, and above the gelation thresholds, the elastic moduli are found to follow a universal power law G(') proportional, variant(eta-eta(c))(nu(eta) ) with a critical exponent nu(eta) approximately 1.82. The latter suggests strong similarities between polymer-bridging induced percolation and classical elastic resistor network percolation. Our results show a very good agreement with the experimental results for polymer-particle mixtures and suggest a possible framework for experimentally distinguishing the origins of gelation phenomena observed in polymer-particle mixtures.     

P[N(i-Bu)CH(2)CH(2)](3)N: nonionic Lewis base for promoting the room-temperature synthesis of α,β-unsaturated esters, fluorides, ketones, and nitriles using Wadsworth-Emmons phosphonates

The bicyclic triaminophosphine P(RNCH(2)CH(2))(3)N (R = i-Bu, 1c) serves as an effective promoter for the room-temperature stereoselective synthesis of α,β-unsaturated esters, fluorides, and nitriles from a wide array of aromatic, aliphatic, heterocyclic, and cyclic aldehydes and ketones, using a range of Wadsworth-Emmons (WE) phosphonates. Among the analogues of 1c [R = Me (1a), i-Pr (1b), Bn (1d)], 1a and 1b performed well, although longer reaction times were involved, and 1d led to poorer yields than 1c. Functionalities such as cyano, chloro, bromo, methoxy, amino, ester, and nitro were well tolerated. We were able to isolate and characterize (by X-ray means; see above) the reactive WE intermediate species formed from 2b and 1c.     

Aluminum chloride as a solid is not a strong Lewis acid

Aluminum chloride is used extensively as Lewis acid catalyst in a variety of industrial processes, including Friedel-Crafts and Cl/F exchange reactions. There is a common misconception that pure AlCl3 is itself a Lewis acid. In the current study, we use experimental and computational methods to investigate the surface structure and catalytic properties of solid AlCl3. The catalytic activity of AlCl3 for two halide isomerization reactions is studied and compared with different AlF3 phases. It is shown that pure solid AlCl3 does not catalyze these reactions. The (001) surface of crystalline AlCl(3) is the natural cleavage plane and its structure is predicted via first principles calculations. The chlorine ions in the outermost layer of the material mask the Al3+ ions from the external gas phase. Hence, the experimentally found catalytic properties of pure solid AlCl3 are supported by the predicted surface structure of AlCl3.     

TRANSFORM-ANN for online optimization of complex industrial processes: Casting process as case study

Artificial Neural Networks (ANNs) are well known for their credible ability to capture non-linear trends in scientific data. However, the heuristic nature of estimation of parameters associated with ANNs has prevented their evolution into efficient surrogate models. Further, the dearth of optimal training size estimation algorithms for the data greedy ANNs resulted in their overfitting. Therefore, through this work, we aim to contribute a novel ANN building algorithm called TRANSFORM aimed at simultaneous and optimal estimation of ANN architecture, training size and transfer function. TRANSFORM is integrated with three standalone Sobol sampling based training size determination algorithms which incorporate the concepts of hypercube sampling and optimal space filling. TRANSFORM was used to construct ANN surrogates for a highly non-linear industrially validated continuous casting model from steel plant. Multiobjective optimization of casting model to ensure maximum productivity, maximum energy saving and minimum operational cost was performed by ANN assisted Non-dominated Sorting Genetic Algorithms (NSGA-II). The surrogate assisted optimization was found to be 13 times faster than conventional optimization, leading to its online implementation. Simple operator's rules were deciphered from the optimal solutions using Pareto front characterization and K-means clustering for optimal functioning of casting plant. Comprehensive studies on (a) computational time comparisons between proposed training size estimation algorithms and (b) predictability comparisons between constructed ANNs and state of art statistical models, Kriging Interpolators adds to the other highlights of this work. TRANSFORM takes physics based model as the only input and provides parsimonious ANNs as outputs, making it generic across all scientific domains.     

One-pot synthesis of fluorine containing 3-cyano/ethoxycarbonyl-2-methyl-benzo[b]furans

Fluoro-substituted 3-cyano-2-methyl-benzo[b]furans and ethyl 2-methyl-benzo[b]furan-3-carboxylates are conveniently prepared in a single step in good yield by the microwave induced tandem intramolecular Wittig and Claisen rearrangement reactions of the corresponding [(aryloxyacetyl) (cyano) methylene] triphenylphosphorane and [(aryloxyacetyl) (ethoxycarbonyl) methylene] triphenylphosphoranes, respectively.     

Antioxidants and a new germacrane sesquiteroene from Carissa spinarum

A new germacrane derivative, care none (1) was isolated from the stems of a well-known medicinal plant, Carissa spinarum L. together with a new ester, 3'-(4'-methoxyphenyl)-3-oxo-ropionyl hexadecanoate (2). Their structures were established using 1D, 2D NMR spectroscopic and synthetic methods. The chloroform extract of the plant displayed strong antioxidant (DPPH) activity. Several other known compounds were also isolated for the first time from this active extract. The antioxidant activity of major lignans was studied.