Analysis of four-way two-dimensional liquid chromatography-diode array data: application to metabolomics

Two-dimensional liquid chromatography (2D-LC) is rapidly gaining popularity for the analysis of very complex mixtures, including proteomic and metabolomic samples. It provides an effective strategy for separating such samples, because the resolving power of 2D-LC is far superior to that of traditional single-dimension separations. The present work focuses on the development of data analysis methods for the extremely large data sets, on the order of 10 million data points, generated by 2D-LC with diode-array detection (DAD). Specifically, we have applied and adapted chemometric methods to the analysis of maize seedling digests, focusing on compounds related to the biosynthetic pathways of indole-3-acetic acid, the primary growth regulator in plants. The chemometric techniques of window target testing factor analysis (WTTFA), along with parallel factor analysis - alternating least squares (PARAFAC-ALS) were used to analyze 2D-LC-DAD chromatograms of a sample composed of 26 indolic standards, 2 extracts of mutant orange pericarp maize seedlings, 2 extracts of wild-type maize seedlings, and a blank sample. The indolic compounds studied belonged to six spectrally unique groups, and WTTFA was able to specifically identify the presence or absence of any of the 26 indolic standards in the mutant and wild-type samples. A PARAFAC-ALS algorithm and an ALS algorithm with flexible constraints were successfully applied to resolve the spectrally rank deficient data and to demonstrate the quantitative potential of multivariate curve resolution methods. Using this procedure, 95 total peaks were resolved in the data set analyzed. Of those 95 peaks, 45 were found in both the mutant and wild-type maize samples, 16 peaks were unique to the mutant maize samples, 13 peaks were unique to the wild-type maize samples, and 15 peaks were unique to the standard chromatograms. Of the 26 standards included in the data set, several indole acetic acid conjugates were identified and quantified in the maize samples at levels of approximately 0.3-2 microg/g plant material.     

Self-assembly of charged microclusters of CdSe/ZnS core/shell nanodots and nanorods into hierarchically ordered colloidal arrays

A thermodynamically driven self-organization of microclusters of semiconductor nanocrystals with a narrow size distribution into periodic two-dimensional (2D) arrays is an attractive low-cost technique for the fabrication of 2D photonic crystals. We have found that CdSe/ZnS core/shell quantum dots or quantum rods, transferred in aqueous phase after capping with the bifunctional surface-active agent DL-cysteine, form on a poly-L-lysine coated surface homogeneously sized micro-particles, droplet-like spheroid clusters and hexagon-like colloidal crystals self-organized into millimetre-sized 2D?hexagonal assemblies. The presence of an organic molecular layer around the micro-particles prevents immediate contact between them, forming an interstitial space which may be varied in thickness by changing the origin of the molecular layer capping nanocrystals. Due to the high refractive index of CdSe and the low refractive index of the interstitial spaces, these structures are expected to have deep gaps in their photonic band, forming hierarchically ordered 2D arrays of potentially photonic materials.     

Separation of the first-order image of the particle field in off-axis focused-image holography

The separation of multiple images is considered in the context of designing holographic image-focused particle diagnostic systems. Two techniques have been employed to determine the minimal directional cosine of the reference wave that ensures the separation of the first-order image of the particle field from the higher-order undesired images. The first approach is based on tracing the rays through the reconstructed images of the particles situated within the sample volume, whereas the second approach relies upon the analysis of the spectra of the reconstructed waves in the spatial-frequency domain. The results obtained by these techniques are compared and discussed.     

All-nanoparticle thin-film coatings

All-nanoparticle thin-film coatings that exhibit antireflection, antifogging (superhydrophilicity), and self-cleaning properties have been prepared via layer-by-layer deposition of TiO(2) and SiO(2) nanoparticles. The porosity and chemical composition of the coatings were determined using a simple method that is based on ellipsometry and does not require any assumptions about the refractive indices of the constituent nanoparticles. The presence of nanopores in the TiO(2)/SiO(2) nanoparticle coatings results in superhydrophilicity as well as antireflection properties. The superhydrophilicity of contaminated coatings could also be readily recovered and retained after ultraviolet irradiation.     

Submolecular potential profiling across organic monolayers

Potential profiles across molecular layers are constructed by means of noncontact electrically stimulated photoelectron spectroscopy, probing for the first time the molecule-substrate interface potential and resolving local screening effects across inner phenyl groups.     

Enforced one-dimensional photoconductivity in core-cladding hexabenzocoronenes

Photoconductivity in contorted hexabenzocoronene liquid crystals is found to be exclusively one-dimensional. Spectroscopic measurements and density functional theory support the existence of two pi-systems attributed to a low-energy radialene-core and higher energy out-of-plane alkoxyphenyl rings. Persistent photocurrents, measured as a function of field, channel length, and intensity, fit a stretched exponential characteristic of intracolumnar transport, restricted through the radialene-core by the alkoxyphenyl-cladding. Bimolecular recombination is enhanced with increasing carrier concentration by the system's one-dimensionality.     

Sparsity-based single-shot subwavelength coherent diffractive imaging

Coherent Diffractive Imaging (CDI) is an algorithmic imaging technique where intricate features are reconstructed from measurements of the freely diffracting intensity pattern. An important goal of such lensless imaging methods is to study the structure of molecules that cannot be crystallized. Ideally, one would want to perform CDI at the highest achievable spatial resolution and in a single-shot measurement such that it could be applied to imaging of ultrafast events. However, the resolution of current CDI techniques is limited by the diffraction limit, hence they cannot resolve features smaller than one half the wavelength of the illuminating light. Here, we present sparsity-based single-shot subwavelength resolution CDI: algorithmic reconstruction of subwavelength features from far-field intensity patterns, at a resolution several times better than the diffraction limit. This work paves the way for subwavelength CDI at ultrafast rates, and it can considerably improve the CDI resolution with X-ray free-electron lasers and high harmonics.     

A highly elastic, capacitive strain gauge based on percolating nanotube networks

We present a highly elastic strain gauge based on capacitive sensing of parallel, carbon nanotube-based percolation electrodes separated by a dielectric elastomer. The fabrication, relying on vacuum filtration of single-walled carbon nanotubes and hydrophobic patterning of silicone, is both rapid and inexpensive. We demonstrate reliable, linear performance over thousands of cycles at up to 100% strain with less than 3% variability and the highest reported gauge factor for a device of this class (0.99). We further demonstrate use of this sensor in a robotics context to transduce joint angles.     

Adaptive Nonlinear System Identification in the Short-Time Fourier Transform Domain

In this paper, we introduce an adaptive algorithm for nonlinear system identification in the short-time Fourier transform (STFT) domain. The adaptive scheme consists of a parallel combination of a linear component, represented by crossband filters between subbands, and a quadratic component, which is modeled by multiplicative cross-terms. We adaptively update the model parameters using the least-mean-square (LMS) algorithm, and derive explicit expressions for the transient and steady-state mean-square error (MSE) in frequency bins for white Gaussian inputs. We show that estimation of the nonlinear component improves the MSE performance only when the power ratio of nonlinear to linear components is relatively high. Furthermore, as the number of crossband filters increases, a lower steady-state MSE may be obtained at the expense of slower convergence. Experimental results support the theoretical derivations.     

Continuous cardiac output monitoring by peripheral blood pressure waveform analysis

A clinical method for monitoring cardiac output (CO) should be continuous, minimally invasive, and accurate. However, none of the conventional CO measurement methods possess all of these characteristics. On the other hand, peripheral arterial blood pressure (ABP) may be measured reliably and continuously with little or no invasiveness. We have developed a novel technique for continuously monitoring changes in CO by mathematical analysis of a peripheral ABP waveform. In contrast to the previous techniques, our technique analyzes the ABP waveform over time scales greater than a cardiac cycle in which the confounding effects of complex wave reflections are attenuated. The technique specifically analyzes 6-min intervals of ABP to estimate the pure exponential pressure decay that would eventually result if pulsatile activity abruptly ceased (i.e., after the high frequency wave reflections vanish). The technique then determines the time constant of this exponential decay, which equals the product of the total peripheral resistance and the nearly constant arterial compliance, and computes proportional CO via Ohm's law. To validate the technique, we performed six acute swine experiments in which peripheral ABP waveforms and aortic flow probe CO were simultaneously measured over a wide physiologic range. We report an overall CO error of 14.6%.