Direct photocatalysis for organic synthesis by using plasmonic-metal nanoparticles irradiated with visible light

Recent advances in direct-use plasmonic-metal nanoparticles (NPs) as photocatalysts to drive organic synthesis reactions under visible-light irradiation have attracted great interest. Plasmonic-metal NPs are characterized by their strong interaction with visible light through excitation of the localized surface plasmon resonance (LSPR). Herein, we review recent developments in direct photocatalysis using plasmonic-metal NPs and their applications. We focus on the role played by the LSPR of the metal NPs in catalyzing organic transformations and, more broadly, the role that light irradiation plays in catalyzing the reactions. Through this, the reaction mechanisms that these light-excited energetic electrons promote will be highlighted. This review will be of particular interest to researchers who are designing and fabricating new plasmonic-metal NP photocatalysts by identifying important reaction mechanisms that occur through light irradiation.

Efficient photocatalytic Suzuki cross-coupling reactions on Au-Pd alloy nanoparticles under visible light irradiation

We report herein highly efficient photocatalysts comprising supported nanoparticles (NPs) of gold (Au) and palladium (Pd) alloys, which utilize visible light to catalyse the Suzuki cross-coupling reactions at ambient temperature. The alloy NPs strongly absorb visible light, energizing the conduction electrons of NPs which produce highly energetic electrons at the surface sites. The surface of the energized NPs activates the substrates and these particles exhibit good activity on a range of typical Suzuki reaction combinations. The photocatalytic efficiencies strongly depend on the Au:Pd ratio of the alloy NPs, irradiation light intensity and wavelength. The results show that the alloy nanoparticles efficiently couple thermal and photonic energy sources to drive Suzuki reactions. Results of the density functional theory (DFT) calculations indicate that transfer of the light-excited electrons from the nanoparticle surface to the reactant molecules adsorbed on the nanoparticle surface activates the reactants. The knowledge acquired in this study may inspire further studies of new efficient photocatalysts and a wide range of organic syntheses driven by sunlight.

Viable photocatalysts under solar-spectrum irradiation: Nonplasmonic metal nanoparticles

Supported nanoparticles (NPs) of nonplasmonic transition metals (Pd, Pt, Rh, and Ir) are widely used as thermally activated catalysts for the synthesis of important organic compounds, but little is known about their photocatalytic capabilities. We discovered that irradiation with light can significantly enhance the intrinsic catalytic performance of these metal NPs at ambient temperatures for several types of reactions. These metal NPs strongly absorb the light mainly through interband electronic transitions. The excited electrons interact with the reactant molecules on the particles to accelerate these reactions. The rate of the catalyzed reaction depends on the concentration and energy of the excited electrons, which can be increased by increasing the light intensity or by reducing the irradiation wavelength. The metal NPs can also effectively couple thermal and light energy sources to more efficiently drive chemical transformations.

Electrochemical mechanism of eugenol at a Cu doped gold nanoparticles modified glassy carbon electrode and its analytical application in food samples

A simple one-step electrodeposition method was used to construct a glassy carbon electrode (GCE), which has been modified with Cu doped gold nanoparticles (GNPs), i.e. a Cu@AuNPs/GCE. This electrode was characterized with the use of scanning electron microscopy (SEM) and X-ray diffraction (XRD) techniques. The eugenol was electrocatalytically oxidized at the Cu@AuNPs/GCE. At this electrode, in comparison with the behavior at the GCE alone, the corresponding oxidation peak current was enhanced and the shift of the oxidation potentials to lower values was observed. Electrochemical behavior of eugenol at the Cu@AuNPs/GCE was investigated with the use of the cyclic voltammetry (CV) technique, and additionally, in order to confirm the electrochemical reaction mechanism for o-methoxy phenols, CVs for catechol, guaiacol and vanillin were investigated consecutively. Based on this work, an electrochemical reaction mechanism for o-methoxy phenols was suggested, and in addition, the above Cu@AuNPs/GCE was successfully employed for the analysis of eugenol in food samples.

A novel fluorescent probe involving a graphene quantum dot-enzyme hybrid system for the analysis of hydroquinone in the presence of toxic resorcinol and catechol

An efficient method for the analysis of hydroquinone at trace levels in water samples has been developed in the form of a fluorescent probe based on graphene quantum dots (GQDs). The analytical variable, fluorescence quenching, was generated from the formation of benzoquinone intermediates, which formed during the catalytic oxidation of hydroquinone by horseradish peroxidase (HRP). In general, the reaction mechanism involved hydroquinone, as an electron acceptor, which affected the surface state of GQDs via an electron transfer effect. The water-soluble GQDs were directly prepared by the pyrolysis of citric acid and with the use of the mentioned hybrid enzyme system, the detection limit for hydroquinone was as low as 8.4 × 10−8 M. Furthermore, this analysis was almost unaffected by other phenol and quinine compounds, such as phenol, resorcinol and other quinines, and therefore, the developed GQD method produced satisfactory results for the analysis of hydroquinone in several different lake water samples.

Hybrid metaheuristic techniques for optimising sugarcane rail operations

Mixed integer programming and parallel-machine job shop scheduling are used to solve the sugarcane rail transport scheduling problem. Constructive heuristics and metaheuristics were developed to produce a more efficient scheduling system and so reduce operating costs. The solutions were tested on small and large size problems. High-quality solutions and improved CPU time are the result of developing new hybrid techniques which consist of different ways of integrating simulated annealing and Tabu search techniques.

Multipurpose nanoporous alumina-carbon nanowall bi-dimensional nano-hybrid platform via catalyzed and catalyst-free plasma CVD

Simple, rapid, plasma-assisted synthesis of large-area arrays of vertically-aligned carbon nanowalls on highly-porous, transparent bare and gold-coated alumina membranes with the two pore sizes is reported. It is demonstrated that the complex patterns of vertically aligned nanowalls can nucleate and form different morphologies in the low-temperature plasmas. The process is stable, and the twofold change in the gas flow (10 and 20 sccm) does not noticeably influence the morphology of the nanowall pattern. Application of a thin (5 nm) gold layer to nanoporous membrane prior to the nanowall growth allows controlling the network morphology.

The in vivo fate of nanoparticles and nanoparticle-loaded microcapsules after oral administration in mice: Evaluation of their potential for colon-specific delivery

Anti-cancer drug loaded-nanoparticles (NPs) or encapsulation of NPs in colon-targeted delivery systems shows potential for increasing the local drug concentration in the colon leading to improved treatment of colorectal cancer. To investigate the potential of the NP-based strategies for colon-specific delivery, two formulations, free Eudragit® NPs and enteric-coated NP-loaded chitosan–hypromellose microcapsules (MCs) were fluorescently-labelled and their tissue distribution in mice after oral administration was monitored by multispectral small animal imaging. The free NPs showed a shorter transit time throughout the mouse digestive tract than the MCs, with extensive excretion of NPs in faeces at 5 h. Conversely, the MCs showed complete NP release in the lower region of the mouse small intestine at 8 h post-administration. Overall, the encapsulation of NPs in MCs resulted in a higher colonic NP intensity from 8 h to 24 h post-administration compared to the free NPs, due to a NP ‘guarding’ effect of MCs during their transit along mouse gastrointestinal tract which decreased NP excretion in faeces. These imaging data revealed that this widely-utilised colon-targeting MC formulation lacked site-precision for releasing its NP load in the colon, but the increased residence time of the NPs in the lower gastrointestinal tract suggests that it is still useful for localised release of chemotherapeutics, compared to NP administration alone. In addition, both formulations resided in the stomach of mice at considerable concentrations over 24 h. Thus, adhesion of NP- or MC-based oral delivery systems to gastric mucosa may be problematic for colon-specific delivery of the cargo to the colon and should be carefully investigated for a full evaluation of particulate delivery systems.

Multimodal polymer nanoparticles with combined 19F magnetic resonance and optical detection for tunable, targeted, multimodal imagingin vivo

Understanding the complex nature of diseased tissue in vivo requires development of more advanced nanomedicines, where synthesis of multifunctional polymers combines imaging multimodality with a biocompatible, tunable, and functional nanomaterial carrier. Here we describe the development of polymeric nanoparticles for multimodal imaging of disease states in vivo. The nanoparticle design utilizes the abundant functionality and tunable physicochemical properties of synthetically robust polymeric systems to facilitate targeted imaging of tumors in mice. For the first time, high-resolution 19F/1H magnetic resonance imaging is combined with sensitive and versatile fluorescence imaging in a polymeric material for in vivo detection of tumors. We highlight how control over the chemistry during synthesis allows manipulation of nanoparticle size and function and can lead to very high targeting efficiency to B16 melanoma cells, both in vitro and in vivo. Importantly, the combination of imaging modalities within a polymeric nanoparticle provides information on the tumor mass across various size scales in vivo, from millimeters down to tens of micrometers.

Hashtag as hybrid forum: The case of #agchatoz

This chapter imports Michel Callon’s model of the ‘hybrid forum’ (Callon et al, 2009, p. 18) into social media research, arguing that certain kinds of hashtag publics can be mapped onto this model. It explores this idea of the hashtag as hybrid forum through the worked example of #agchatoz—a hashtag used as both ‘meetup’ organizer for Australian farmers and other stakeholders in Australian agriculture, and as a topic marker for general discussion of related issues. Applying the principles and techniques of digital methods (Rogers, 2013), we employ a standard suite of analytics to a longitudinal dataset of #agchatoz tweets. The results are used not only to describe various elements and dynamics of this hashtag, but also to experiment with the articulation of such approaches with the theoretical model of the hybrid forum, as well as exploring the ways that controversies animate and transform such forums as part of the emergence and cross-pollination of issue publics.

A three-dimensional hybrid smoothed finite element method (H-SFEM) for nonlinear solid mechanics problems

This paper presents a novel three-dimensional hybrid smoothed finite element method (H-SFEM) for solid mechanics problems. In 3D H-SFEM, the strain field is assumed to be the weighted average between compatible strains from the finite element method (FEM) and smoothed strains from the node-based smoothed FEM with a parameter α equipped into H-SFEM. By adjusting α, the upper and lower bound solutions in the strain energy norm and eigenfrequencies can always be obtained. The optimized α value in 3D H-SFEM using a tetrahedron mesh possesses a close-to-exact stiffness of the continuous system, and produces ultra-accurate solutions in terms of displacement, strain energy and eigenfrequencies in the linear and nonlinear problems. The novel domain-based selective scheme is proposed leading to a combined selective H-SFEM model that is immune from volumetric locking and hence works well for nearly incompressible materials. The proposed 3D H-SFEM is an innovative and unique numerical method with its distinct features, which has great potential in the successful application for solid mechanics problems.

A hybrid cellular automata model of multicellular tumour spheroid growth in hypoxic microenvironment

A three-dimensional hybrid cellular automata (CA) model is developed to study the dynamic process of multicellular tumour spheroid (MTS) growth by introducing hypoxia as an important microenvironment factor which influences cell migration and cell phenotype expression. The model enables us to examine the effects of different hypoxic environments on the growth history of the MTS and to study the dynamic interactions between MTS growth and chemical environments. The results include the spatial distribution of different phenotypes of tumour cells and associated oxygen concentration distributions under hypoxic conditions. The discussion of the model system responses to the varied hypoxic conditions reveals that the improvement of the resistance of tumour cells to a hypoxic environment may be important in the tumour normalization therapy.

Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method

The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.

Biophysical response of living cells to boron nitride nanoparticles: Uptake mechanism and bio-mechanical characterization

Boron nitride nanomaterials have attracted significant interest due to their superior chemical and physical properties. Despite these novel properties, investigation on the interaction between boron nitride nanoparticle (BN NP) and living systems has been limited. In this study, BN NP (100–250 nm) is assessed as a promising biomaterial for medical applications. The toxicity of BN NP is evaluated by assessing the cells behaviours both biologically (MTT assay, ROS detection etc.) and physically (atomic force microscopy). The uptake mechanism of BN NP is studied by analysing the alternations in cellular morphology based on cell imaging techniques. The results demonstrate in vitro cytocompatibility of BN NP with immense potential for use as an effective nanoparticle for various bio-medical applications.

Hybrid game strategies for MO problems in aerospace design

Game strategies have been developed in past decades and used in the field of economics, engineering, computer science and biology due to their efficiency in solving design optimisation problems. In addition, research on Multi-Objective (MO) and Multidisciplinary Design Optimisation (MDO) has focused on developing robust and efficient optimisation method to produce quality solutions with less computational time. In this paper, a new optimisation method Hybrid Game Strategy for MO problems is introduced and compared to CMA-ES based optimisation approach. Numerical results obtained from both optimisation methods are compared in terms of computational expense and model quality. The benefits of using Game-strategies are demonstrated.