Periodicity-controlled two-dimensional crystalline colloidal arrays

We developed a convenient and fast approach to preparing close-packed two-dimensional (2-D) particle arrays on mercury surfaces. Addition of cosolvents, such as alcohols, to aqueous colloidal particle suspensions induces spreading and self-assembly of the particles into 2-D arrays on top of the mercury surface. We can fabricate large-area close-packed 2-D arrays (>70 cm(2)) within 30 s. We attached these 2-D arrays to functional hydrogel films such that the 2-D array spacings were altered by the hydrogel volume response to the environment. We directly observed the hydrogel volume induced 2-D array spacing changes by using confocal laser scanning microscopy to monitor the spacings of fluorescent polystyrene particle 2-D arrays in response to changes in pH, solvent composition, temperature, etc.     

Wafer-scale periodic nanohole arrays templated from two-dimensional nonclose-packed colloidal crystals

This communication reports a simple yet versatile nonlithographic approach for fabricating wafer-scale periodic nanohole arrays from a large variety of functional materials, including metals, semiconductors, and dielectrics. Spin-coated two-dimensional (2D) nonclose-packed colloidal crystals are used as first-generation shadow masks during physical vapor deposition to produce isolated nanohole arrays. These regular nanoholes can then be used as second-generation etching masks to create submicrometer void arrays in the substrates underneath. Complex patterns with micrometer-scale resolution can be made by standard microfabrication techniques for potential device applications. These 2D-ordered nanohole arrays may find important technological applications ranging from subwavelength optics to interferometric biosensors.     

A novel efficient way to estimate the chemical rank of high-way data arrays

A novel method, a subspace projection of pseudo high-way data array (SPPH), was developed for estimating the chemical rank of high-way data arrays. The proposed method determines the chemical rank through performing singular value decomposition (SVD) on the slice matrices of original high-way data array to produce a pseudo high-way data array and employing the idea of the difference of the original truncated data set and the pseudo one. Compared with traditional methods, it uses the information from eigenvectors combined with the projection residual to estimate the rank of the three-way data arrays instead of using the eigenvalue. In order to demonstrate the excellent performance of the new method, simulated and real three-way data arrays were carried out by the proposed method. The results showed that the proposed method could accurately and quickly determine the chemical rank to fit the trilinear model. Moreover, the newly proposed method was compared with the other four factor-determining methods, i.e. factor indicator function (IND), ADD-ONE-UP, core consistency diagnostic (CORCONDIA) and two-mode subspace comparison (TMSC) approaches. It was found that the proposed method can deal with more complex situations with existence of severe collinearity and trace concentration than many other methods can and performs well in practical applications.     

Quantifying uncertainty in chemical systems modeling

This study compares two techniques for uncertainty quantification in chemistry computations, one based on sensitivity analysis and error propagation, and the other on stochastic analysis using polynomial chaos techniques. The two constructions are studied in the context of H₂? O₂ ignition under supercritical‐water conditions. They are compared in terms of their prediction of uncertainty in species concentrations and the sensitivity of selected species concentrations to given parameters. The formulation is extended to one‐dimensional reacting‐flow simulations. The computations are used to study sensitivities to both reaction rate pre‐exponentials and enthalpies, and to examine how this information must be evaluated in light of known, inherent parametric uncertainties in simulation parameters. The results indicate that polynomial chaos methods provide similar first‐order information to conventional sensitivity analysis, while preserving higher‐order information that is needed for accurate uncertainty quantification and for assigning confidence intervals on sensitivity coefficients. These higher‐order effects can be significant, as the analysis reveals substantial uncertainties in the sensitivity coefficients themselves. © 2005 Wiley Periodicals, Inc. Int J Chem Kinet 37: 368–382, 2005     

Self-assembling two-dimensional nanophotonic arrays for reflectivity-based sensing

We propose a nanoplasmonic platform that can be used for sensing trace levels of heavy metals in solutions via simple optical reflectivity measurements. The considered example is a lead sensor, which relies on the lead-mediated assembly of glutathione-functionalized gold nanoparticles (NPs) at a self-healing water/DCE liquid | liquid interface (LLI). Capillary forces tend to trap each NP at the LLI while the negatively charged ligands prevent the NPs settling too close to each other. In the presence of lead, due to chelation between the lead ion and glutathione ligand, the NPs assemble into a dense quasi-2D interfacial array. Such a dense assembly of plasmonic NPs can generate a remarkable broad-band reflectance signal, which is absent when NPs are adsorbed at the interface far apart from each other. The condensing effect of the LLI and the plasmonic coupling effect among the NP array gives rise to a dramatic enhancement of the reflectivity signals. Importantly, we show that our theory of the optical reflectivity from such an array of NPs works in perfect harmony with the physics and chemistry of the system with the key parameter being the interparticle distance at the interface. As a lead sensor, the system is fast, stable, and can achieve detection limits down to 14 ppb. Future alternative recognizing ligands can be used to build sister platforms for detecting other heavy metals.

We propose a nanoplasmonic platform that can be used for sensing trace levels of heavy metals in solutions via simple optical reflectivity measurements at the liquid–liquid interface.     

Hierarchical assembly of two-dimensional homochiral nanocavity arrays

We demonstrate the rational design of nanoporous two-dimensional supramolecular structures by the hierarchical assembly of organic molecules and transition metal atoms at surfaces. Single-molecule level observations with scanning tunneling microscopy monitor the successive aufbau of structures with increasing complexity. From the primary components secondary mononuclear chiral complexes are formed, which represent antecedents for tertiary polynuclear metal-organic nanogrids. These nanogrids represent the constituents of the eventually evolving two-dimensional networks comprising homochiral nanocavity arrays. Our findings visualize the evolution of complex matter in an exemplary way: from per se achiral species via chiral intermediates to mesoscale dissymmetric structures.     

Surface patterning with two-dimensional porphyrin supramolecular arrays

Monolayer arrays of a series of meso-tetra-substituted porphyrins containing octadecyloxy and carboxyl (or pyridyl) groups were prepared on the highly oriented pyrolytic graphite surface at the liquid/solid interface. It was found by means of scanning tunneling microscopy that some porphyrins from this family assemble into various patterns. Specifically, slightly undulated rows are obtained from 5,10,15-tris(4-octadecyloxyphenyl)-20-(4-pyridyl)porphyrin. Meanwhile, rows with more pronounced kinks result from 5-(4-carboxyphenyl)-10,15,20-tris(4-octadecyloxyphenyl)porphyrin. The occurrence of the kinks is dependent on the arrangement of surrounding porphyrin molecules and is determined by intricate interplay between directional hydrogen-bonding interactions and packing forces, including molecule-molecule and molecule-substrate interactions. A double-layer structure is obtained from 5,10-bis(4-carboxyphenyl)-15,20-bis(4-octadecyloxyphenyl)porphyrin, probably through cyclic hydrogen bond formation. This work proves the concept that programmed surface patterning is possible by using porphyrins incorporating directional intermolecular interaction sites.     

Polarizabilities of solvents from the chemical composition

From the experimental polarizability values, alpha, of a large set of solvents containing 426 compounds with very different chemical characteristics, an additive model for the estimation of the polarizability is proposed. The derived average atomic polarizability of 10 elements, C, H, O, N, S, P, F, Cl, Br, and I, allows the calculation of the molecular polarizability of solvents from their chemical composition alone, without any other structural consideration. The average errors are 2.31% and 1.93% for the working set of 340 solvents and the prediction set of 86 solvents, respectively. Semiempirical quantum methods, such as, AM1, PM3, and MNDO, gave errors of about 35%. The density functional theory (DFT) calculations give better results than the semiempirical ones but poorer results than those obtained by the additive approach.     

Inversion of two-dimensional potentials from frequency-resolved spectroscopic data

We report the first successful reconstruction of two-dimensional potential energy surfaces (PES) using the magnitudes and positions of a set of frequency-resolved fluorescence (or absorption) lines. The inversion proceeds by first extracting the phases of the transition-dipole matrix elements, yielding, together with the (ground) PES to (from) which emission (absorption) occurs, a point by point reconstruction of the two-dimensional excited state PES. The inversion procedure is highly accurate even for PES with multiple minima and many missing lines, with typical RMS errors <0.002 cm(-1) in the classically allowed region and <0.018 cm(-1) in the classically forbidden region.     

Three-dimensional colloidal crystal-assisted lithography for two-dimensional patterned arrays

In this paper, we report our recent work on preparing two-dimensional patterned microstructure arrays using three-dimensional colloidal crystals as templates, namely, colloidal crystal-assisted lithography. Two alternative processes are described and involved in colloidal crystal-assisted lithography. One is based upon imprinting the polymer films with three-dimensional silica colloidal crystals, and the other is based upon chemically depositing Ag microstructures on Au substrates covered by polymer colloidal crystals. By varying the experimental conditions in the colloidal crystal-assisted lithography process, we can intentionally control the morphologies of the resulting microstructures. The resultant Ag-coated Au substrates can be used as surface-enhanced Raman scattering substrates, and they would provide an ideal system for the mechanism study of surface-enhanced Raman scattering. We expect that colloidal crystal-assisted lithography will be a versatile approach which can be applied to patterning other materials such as functional molecules, polymers, oxides, and metals.     

Light-induced coherent interactions between silver nanoparticles in two-dimensional arrays

Silver nanoparticles arranged in two-dimensional arrays experience quadrupolar coupling of plasmon resonances when irradiated with visible light. This coupling leads to the formation of the coherent plasmon mode characterized by an intense narrow resonance in the blue spectral range in the extinction spectrum. The coupling and the intensity of this mode can be effectively controlled by varying the distance between particles. The interparticle distance was varied by biaxial stretching of the arrays prepared in transparent elastomeric film of poly(dimethylsiloxane). The observed phenomenon exemplifies a generic approach in which new optical properties of materials can be engineered by organizing metal nanoparticles in various one-, two-, and three-dimensional structures. Further development of this approach will result in the discovery of novel principles of both fundamental and practical importance.     

Self-assembled two-dimensional ordered arrays of tripod-type molecules on graphite

Tripod-type molecules with long alkyl chains, 1,1,1-tris(4-alkoxyphenyl)ethanes with octadecyloxy or docosyloxy chains, self-assemble into two-dimensional crystallites on drop-casting onto the surface of highly oriented pyrolytic graphite. In the two-dimensional crystalline domain, the molecules are organized in a mortise-and-tenon motif, as revealed by scanning tunneling microscopy. The time evolution of the crystallite formation has been followed by the dynamic force mode atomic force microscopy. The tripods may be used as a basis for the extension of a two-dimensional order into three-dimensional molecular architectures.     

Sequential polymer lithography for chemical sensor arrays

A simple process for the deposition of up to six different polymers in selected areas to be used as sensitive layers in chemical sensor arrays is presented. The process is based on photolithographic processes and takes advantage of the balance between UV exposure dose, material tone and developers used. The sensing properties of the deposited films in the array were characterized by the in situ monitoring of volume expansion upon exposure to analytes using white light reflectance sspectroscopy. The swelling properties of processed films are compared to the unprocessed ones for the purpose of examining the variation induced by the processing steps (exposure and development circles). Additionally, the repeatability of the processes as well as the effect of analyte sequence is examined. This process offers good control of the lateral dimensions and the thickness of the polymeric films and allows for the parallel fabrication of sensors based on different transduction mechanisms including mass sensitive and stress induced bending chemical sensors.     

Conducting polymers in chemical sensors and arrays

The review covers main applications of conducting polymers in chemical sensors and biosensors. The first part is focused on intrinsic and induced receptor properties of conducting polymers, such as pH sensitivity, sensitivity to inorganic ions and organic molecules as well as sensitivity to gases. Induced receptor properties can be also formed by molecularly imprinted polymerization or by immobilization of biological receptors. Immobilization strategies are reviewed in the second part. The third part is focused on applications of conducting polymers as transducers and includes usual optical (fluorescence, SPR, etc.) and electrical (conductometric, amperometric, potentiometric, etc.) transducing techniques as well as organic chemosensitive semiconductor devices. An assembly of stable sensing structures requires strong binding of conducting polymers to solid supports. These aspects are discussed in the next part. Finally, an application of combinatorial synthesis and high-throughput analysis to the development and optimization of sensing materials is described.     

Use of pseudo-sample extraction and the projection technique to estimate the chemical rank of three-way data arrays

Determining the rank of a trilinear data array is a first step in subsequent trilinear component decomposition. Different from estimating the rank of bilinear data, it is more difficult to decide the significant number of component to fit the trilinear decompositions exactly. General methods of rank estimation utilize the information contained in the singular values but ignore information from eigenvectors. In this paper, a rank estimating method specifically for trilinear data arrays is proposed. It uses the idea of direct trilinear decomposition (DTLD) to compress the cube matrix into two pseudo sample matrices which are then decomposed by singular value decomposition. Two eigenvectors combined with the projection technique are used to estimate the rank of trilinear data arrays. Simulated trilinear data arrays with homoscedastic and heteroscedastic noise, different noise levels, high collinearity, and real three-way data arrays have been used to illustrate the feasibility of the proposed method. Compared with other factor-determining methods, for example use of the factor indication function (IND), residual percentage variance (RPV), and the two-mode subspace comparison approach (TMSC), the results showed that the new method can give more reliable answers under the different conditions applied.      

Estimating the chemical rank of three-way data arrays by a simple linear transform incorporating Monte Carlo simulation

Estimating an appropriate chemical rank of a three-way data array is very important to second-order calibration. In this paper, a simple linear transform incorporating Monte Carlo simulation approach (LTMC) to estimate the chemical rank of a three-way data array was suggested. The new method determines the chemical rank through performing a simple linear transform procedure on the original cube matrix to produce two subspaces by singular value decomposition. One of two subspaces is derived from the original three-way data array itself and the other is derived from a new three-way data array produced by the linear transformation of the original one. Projection technique incorporating the Monte Carlo approach acts as distinguishing criterion to choose the appropriate component number of the system. Simulated three-way trilinear data arrays with different noise types (homoscedastic and heteroscedastic), various noise level as well as high collinearity are used to illustrate the feasibility of the new method. The results have shown that the new method could yield accurate results with different conditions appended. The feasibility of the new method is also confirmed by two real arrays, HPLC-DAD data and excitation-emission fluorescent data. All the results are compared with the other three factor-determining methods: factor indicator function (IND), core consistency diagnostic (CORCONDIA) and two-mode subspace comparison (TMSC) approach. It shows that the newly proposed algorithm can objectively and quickly determine the chemical rank to fit the trilinear model.