Realization of thermally durable close-packed 2D gold nanoparticle arrays using self-assembly and plasma etching

Realization of thermally and chemically durable, ordered gold nanostructures using bottom-up self-assembly techniques are essential for applications in a wide range of areas including catalysis, energy generation, and sensing. Herein, we describe a modular process for realizing uniform arrays of gold nanoparticles, with interparticle spacings of 2 nm and above, by using RF plasma etching to remove ligands from self-assembled arrays of ligand-coated gold nanoparticles. Both nanoscale imaging and macroscale spectroscopic characterization techniques were used to determine the optimal conditions for plasma etching, namely RF power, operating pressure, duration of treatment, and type of gas. We then studied the effect of nanoparticle size, interparticle spacing, and type of substrate on the thermal durability of plasma-treated and untreated nanoparticle arrays. Plasma-treated arrays showed enhanced chemical and thermal durability, on account of the removal of ligands. To illustrate the application potential of the developed process, robust SERS (surface-enhanced Raman scattering) substrates were formed using plasma-treated arrays of silver-coated gold nanoparticles that had a silicon wafer or photopaper as the underlying support. The measured value of the average SERS enhancement factor (2 x 10(5)) was quantitatively reproducible on both silicon and paper substrates. The silicon substrates gave quantitatively reproducible results even after thermal annealing. The paper-based SERS substrate was also used to swab and detect probe molecules deposited on a solid surface.

Multilayer assemblies of polyelectrolyte-gold nanoparticles for the electrocatalytic oxidation and detection of arsenic(III)

Multilayers of poly(diallyldimethylammonium chloride) (PDDA) and citrate capped Au nanoparticles (AuNPs) anchored on sodium 3-mercapto-1-propanesulfonate modified gold electrode by electrostatic layer-by-layer assembly (LbL) technique are shown to be an excellent architecture for the direct electrochemical oxidation of As(III) species. The growth of successive layers in the proposed LbL architecture is followed by atomic force microscopy, UV-vis spectroscopy, quartz crystal microbalance with energy dissipation, and electrochemistry. The first bilayer is found to show rather different physico-chemical characteristics as compared to the subsequent bilayers, and this is attributed to the difference in the adsorption environments. The analytical utility of the architecture with five bilayers is exploited for arsenic sensing via the direct electrocatalytic oxidation of As(III), and the detection limit is found to be well below the WHO guidelines of 10 ppb. When the non-redox active PDDA is replaced by the redoxactive Os(2,2'-bipyridine)(2)Cl-poly(4-vinylpyridine) polyelectrolyte (PVPOs) in the LbL assembly, the performance is found to be inferior, demonstrating that the redox activity of the polyelectrolyte is futile as far as the direct electro-oxidation of As(III) is concerned. (C) 2012 Elsevier Inc. All rights reserved.

Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences

Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.

Diffusion mechanism in the gold-copper system

Interdiffusion study is conducted in the Au-Cu system, which has complete solid solution in the higher temperature range and ordered phases in the lower temperature range. First experiments are conducted at higher temperatures, where atoms can diffuse randomly. Higher values of interdiffusion coefficients are found in the range of 40-50 at.% Cu. This trend is explained with the help of thermodynamic factor and possible concentration of vacancies. Following an experiment is conducted at 623 K (350 degrees C), where the ordered phases are grown. The interdiffusion coefficients at this temperature are compared after extrapolating the data calculated at higher temperatures.

Effect of high gold salt concentrations on the size and polydispersity of gold nanoparticles prepared by an extended Turkevich-Frens method

The Turkevich-Frens synthesis starting conditions are expanded, ranging the gold salt concentrations up to 2 mM and citrate/gold(III) molar ratios up to 18:1. For each concentration of the initial gold salt solution, the citrate/gold(III) molar ratios are systematically varied from 2:1 to 18:1 and both the size and size distribution of the resulting gold nanoparticles are compared. This study reveals a different nanoparticle size evolution for gold salt solutions ranging below 0.8 mM compared to the case of gold salt solutions above 0.8 mM. In the case of Au3+]<0.8 mM, both the size and size distribution vary substantially with the citrate/gold(III) ratio, both displaying plateaux that evolve inversely to Au3+] at larger ratios. Conversely, for Au3+]>= 0.8 mM, the size and size distribution of the synthesized gold nanoparticles continuously rise as the citrate/gold(III) ratio is increased. A starting gold salt concentration of 0.6 mM leads to the formation of the most monodisperse gold nanoparticles (polydispersity index<0.1) for a wide range of citrate/gold(III) molar ratios (from 4:1 to 18:1). Via a model for the formation of gold nanoparticles by the citrate method, the experimental trends in size could be qualitatively predicted:the simulations showed that the destabilizing effect of increased electrolyte concentration at high initial Au3+] is compensated by a slight increase in zeta potential of gold nanoparticles to produce concentrated dispersion of gold nanoparticles of small sizes.

Mining sentiments from songs using latent dirichlet allocation

Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.

Single crystalline ultrathin gold nanowires: Promising nanoscale interconnects

Using first principles based density functional calculation we study the mechanical, electronic and transport properties of single crystalline gold nanowires. While nanowires with the diameter less than 2 nm retain hexagonal cross-section, the larger diameter wires show a structural smoothening leading to circular cross-section. These structural changes significantly affect the mechanical properties of the wires, however, strength remains comparable to the bulk. The transport calculations reveal that the conductivity of these wires are in good agreement with experiments. The combination of good mechanical, electronic and transport properties make these wires promising as interconnects for nano devices. Copyright 2013 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.4796188]

IceCube: efficient targeted mining in data cubes

We address the problem of mining targeted association rules over multidimensional market-basket data. Here, each transaction has, in addition to the set of purchased items, ancillary dimension attributes associated with it. Based on these dimensions, transactions can be visualized as distributed over cells of an n-dimensional cube. In this framework, a targeted association rule is of the form {X -> Y} R, where R is a convex region in the cube and X. Y is a traditional association rule within region R. We first describe the TOARM algorithm, based on classical techniques, for identifying targeted association rules. Then, we discuss the concepts of bottom-up aggregation and cubing, leading to the CellUnion technique. This approach is further extended, using notions of cube-count interleaving and credit-based pruning, to derive the IceCube algorithm. Our experiments demonstrate that IceCube consistently provides the best execution time performance, especially for large and complex data cubes.

Green synthesis of polysaccharide/gold nanoparticle nanocomposite: An efficient ammonia sensor

A low cost eco-friendly method for the synthesis of gold nanoparticles (AuNPs) using guar gum (GG) as a reducing agent is reported. The nanoparticles obtained are characterized by UV-vis spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD). Based on these results, a potential mechanism for this method of AuNPs synthesis is discussed. GG/AuNPs nanocomposite (GG/AuNPs NC) was exploited for optical sensor for detection of aqueous ammonia based on surface plasmon resonance (SPR). It was found to have good reproducibility, response times of similar to 10 s and excellent sensitivity with a detection limit of 1 ppb (parts-per-billion). This system allows the rapid production of an ultra-low-cost GG/AuNPs NC-based aqueous ammonia sensor.

Ultrafast photoinduced enhancement of nonlinear optical response in 15-atom gold clusters on indium tin oxide conducting film

We show that the third order optical nonlinearity of 15-atom gold clusters is significantly enhanced when in contact with indium tin oxide (ITO) conducting film. Open and close aperture z-scan experiments together with non-degenerate pump-probe differential transmission experiments were done using 80 fs laser pulses centered at 395 nm and 790 nm on gold clusters encased inside cyclodextrin cavities. We show that two photon absorption coefficient is enhanced by an order of magnitude as compared to that when the clusters are on pristine glass plate. The enhancement for the nonlinear optical refraction coefficient is similar to 3 times. The photo-induced excited state absorption using pump-probe experiments at pump wavelength of 395 nm and probe at 790 nm also show an enhancement by an order of magnitude. These results attributed to the excited state energy transfer in the coupled gold cluster-ITO system are different from the enhancement seen so far in charge donor-acceptor complexes and nanoparticle-conjugate polymer composites.

Algorithm for mining outliers in categorical data through ranking

The rapid growth in the field of data mining has lead to the development of various methods for outlier detection. Though detection of outliers has been well explored in the context of numerical data, dealing with categorical data is still evolving. In this paper, we propose a two-phase algorithm for detecting outliers in categorical data based on a novel definition of outliers. In the first phase, this algorithm explores a clustering of the given data, followed by the ranking phase for determining the set of most likely outliers. The proposed algorithm is expected to perform better as it can identify different types of outliers, employing two independent ranking schemes based on the attribute value frequencies and the inherent clustering structure in the given data. Unlike some existing methods, the computational complexity of this algorithm is not affected by the number of outliers to be detected. The efficacy of this algorithm is demonstrated through experiments on various public domain categorical data sets.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Tunability of electronic states in ultrathin gold nanowires

The electronic state in ultrathin gold nanowires is tuned by careful engineering of the device architecture via a chemical methodology. The electrons are localized to an insulating state (showing variable range hopping transport) by simply bringing them close to the substrate, while the insertion of an interlayer leads to a Tomonaga Luttinger liquid state.

Organogels from Dimeric Bile Acid Esters: In Situ Formation of Gold Nanoparticles

A new class of steroid dimers (bile acid derivatives) linked through ester functionalities were synthesized, which gelled various aromatic solvents. The organogels formed by the three dimeric ester molecules showed birefringent textures and fibrous nature by polarizing optical microscopy and scanning electron microscopy, respectively. A detailed rheological study was performed to estimate the mechanical strengths of two sets of organogels. In these systems, the storage modulus varied in the range of 0.8-3.5 X 10(4) at 1% w/v of the organogelators. The exponents of scaling of the storage modulus and yield stress of the two systems agreed well with those expected for viscoelastic soft colloidal gels with fibrillar flocs. The nanofibers in the organogel were utilized to engineer gold nanoparticles of different sizes and shapes and generate new gel-nanoparticle hybrid materials.

Engineering Gold Nanoparticle Interaction by PAMAM Dendrimer

Bare faceted gold nanoparticles (AuNPs) have a tendency to aggregate through a preferred attachment of the 111] surfaces. We have used fully atomistic classical molecular dynamics simulations to obtain a quantitative estimate of this surface interaction using umbrella sampling (US) at various temperatures. To tune this surface interaction, we use polyamidoamine (PAMAM) dendrimer to coat the gold surface under various conditions. We observe a spontaneous adsorption of the protonated as well as nonprotonated PAMAM dendrimer on the AuNP surface. The adsorbed dendrimer on the nanoparticle surface strongly alters the interaction between the nanoparticles. We calculate the interaction between dendrimercoated AuNPs using US and show how the interaction between two bare faceted AuNPs can be tuned as a function of dendrimer concentration and charge (pH dependent) With appropriate choice of the dendrimer concentration and charge, two strongly interacting AuNPs can be made effectively noninteracting. Our simulation results demonstrate a strategy to tune the nanoparticle interaction, which can help in engineering self-assembly of such nanoparticles.