An Annular Plasmonic Lens Under Illumination of Circularly Polarized Light

In this paper, we consider a circular central aperture surrounded with annular depth-tuned grooves and investigate the beaming effect of the structure under illumination of a circularly polarized (CP) plane wave. As a CP plane wave is equivalent to the superposition of two linearly polarized plane waves (TM and TE) with a phase difference of π/2, the superposition of the electric field intensity, ( | E_x |² + | E_y |² ) \left( {{{\left| {E_x} \right|}^2} + {{\left| {E_y} \right|}^2}} \right) , is observed in the transmission field. In addition, two plasmonic modes are found at the resonant wavelengths λ ₁ and λ ₂ with each consisting of multiple wavelengths. At the wavelength λ ₁ = 420 nm, the significant near-field collimation is formed along the direction z, having a long propagation distance up to 1.75 μm (≈4λ) away from the exit plane of the new plasmonic lens.     

Spatial Distribution of Optical Near-Fields in Plasmonic Gold Sphere Segment Voids

We present a comprehensive experimental and computational study on the electromagnetic field distribution in sphere segment void arrays. Surface plasmon polaritons can be excited in these void arrays, resulting in greatly enhanced electromagnetic fields. With the scanning near-field optical microscope (SNOM) we are able to measure the electromagnetic field distribution at the sample surface. For this purpose, an array of relatively large voids with a sphere diameter of 900 nm was fabricated, allowing for an easy access of the scanning glass-fibre tip and yielding very detailed scans. Complementary, finite-difference time-domain (FDTD) calculations on a complete void array have been performed and compared with the SNOM intensity maps and experimental reflectivity data. We show in a direct way both the existence of extended and localised modes in the Au void array for three different void depths. We also show and discuss the changes that the modes undergo for the different void depths and excitation wavelengths. Moreover, since the simulations were performed for two different void geometries, one containing perfectly spherical void surfaces and another more realistic one, which considers the presence of interstitial wall holes and other imperfections, as observed in scanning electron micrographs, we were able to determine by comparison with the experiment under which conditions an array of idealised sphere segment voids is a meaningful model. This demonstrates that both SNOM and FDTD simulations are powerful tools for understanding the plasmonic response of metallic nanostructures, thus enabling, for instance, a design for applications in ultra-sensitive optical detection.     

Interferometric Control of Signal Light Intensity by Anomalous Refraction with Plasmonic Metasurface

We propose a new method of controlling signal light intensity by changing the polarization direction of pump light that is incident on a phase-gradient metasurface. Theoretical analyses and simulations demonstrate that, when the incident angles for signal and pump light sources conform to a certain relationship, the anomalous refraction of the pump light superposes with the signal light. The intensity of the signal light can be fully tuned across a broadband range by varying the polarization direction of the pump light. Our methods will contribute to the development of promising techniques to be used in photonics devices such as amplitude modulators and photoswitches.     

Illumination Dependent Optical Properties of Plasmonic Nanorods Coupled to Thin-Film Cavities

The scattering spectra and intensity of gold nanorods placed at varied distances above gold films have been simulated and measured under various conditions, demonstrating that scattering characteristics of the nanorod-film system are highly dependent on illumination conditions. Studying the surrounding electric fields of nanorods reveals that the illumination-dependent properties of the system are induced by the interference in the nanorod-film system. Both simulations and experiments show that optimising the nanorod-film distance can greatly enhance scattering magnitudes up to ~20 times for certain illumination conditions. We propose an application of the studied system in facilitating photo-thermal conversion.     

Design of a Structured Bulk Plasmon Illumination Source for Enhancing Plasmonic Cavity Superlens Imaging

Plasmonics - A structured bulk plasmon illumination (BPI) source is designed for achieving a uniform high spatial frequency illumination field. By employing the hyperbolic metamaterial (HMM)...     

Improving Imaging Contrast of Non-Contacted Plasmonic Lens by Off-Axis Illumination with High Numerical Aperture

Off-axis illumination plasmonic lens (OAIPL) is proposed and demonstrated to improve the imaging contrast in non-contacted application manner. The spatial Fourier components of light transmitted through the nano-patterns are greatly enhanced in the imaging process by shifting the wave vectors with high numerical aperture off-axis illumination. On the other hand, a reflector in the image area helps to tailor the ratio between electric field components in the tangential and normal directions. These two effects resultantly deliver significant improvement of imaging performance, including enhanced resolution, imaging contrast, and elongation of air gap thickness. In comparison to the case of normal illumination, the air gap thickness for 30 and 60 nm half-pitch resolution is extended to 25 and 100 nm by OAIPL with numerical aperture (NA)?=?1.55, respectively.     

Synchronous Tuning of Twined Resonance Modes with Controllable Spectral Separation in Plasmonic Gratings

We investigated angle-resolved tuning performance of the double resonance modes of waveguide metallic grating structures, where the incident angle was changed in the plane formed by the extending direction of the grating lines and the wave vector with the grating plane tilted with respect to the vertical axis. Double resonance modes were observed due to tilting of the grating, which were tuned simultaneously to the blue with increasing the angle of incidence. The spectral separation between the resonance modes can be adjusted simply by changing the tilting angle of the grating. Such a double resonance device is important for exploring multichannel optical filters, optical switching device, or sensors.     

Engineering the Optical Response of the Novel Plasmonic Binary Nanohole Array

The phenomenon of extraordinary optical transmission (EOT) due to its advantages has been considered by researchers in various applications, and in recent years, many efforts have been made to engineer these structures to get the best possible response for desired applications. In this work, the optical properties of novel binary gold nanohole arrays are investigated theoretically. We engineered the optical response of the system by adjusting the ratio of contribution of surface plasmon polariton (SPP) to localized surface plasmon resonance (LSPR) through the manipulation of the geometrical properties. The changes in the topology of this nanohole array affected the intensity and the wavelength of transmission peaks. The sensitivity of the optical response to the refractive index was also investigated. The designed structure is a good candidate for use as a polarization-independent optical label-free sensor.

     

Spectral Investigations on the Fluorescence Quenching of 1,4-dihydroxy-2,3-dimethylanthracene-9,10-dione by Plasmonic Silver Nanoparticles

Silver nanoparticles (Ag NPs) of different sizes have been prepared by Lee and Meisel’s method using trisodium citrate as reducing agent under ultra sonication. Optical absorption and fluorescence emission techniques were employed to investigate the interaction of 1,4-dihydroxy-2,3-dimethyl anthracene-9,10-dione (DHDMAD) with silver nanoparticles. In fluorescence spectroscopic study, we used the DHDMAD and Ag NPs as component molecules for construction of Förster Resonance Energy Transfer (FRET), whereas DHDMAD serve as donor and Ag NPs as acceptor. The surface plasmon resonance (SPR) peak of the prepared silver colloidal solution was observed from 419 nm to 437 nm. The synthesized silver nanoparticles at different heating time intervals were spherical in shape about the size of 25 nm and 55 nm. The fluorescence interaction between silver nanoparticles and DHDMAD confirms the FRET mechanism. According to Förster theory, the distance between silver nanoparticles and DHDMAD and the critical energy transfer distance were calculated and it is increase with heating time.     

Plasmonic Spectral Detection of Carcinoembryonic Antigen by Preventing the Direct Binding of Rhodamine 6G with Au Nanoparticles

Carcinoembryonic antigen (CEA) was used as a separator to prevent the Rhodamine 6G (R6G)-induced aggregation of colloidal gold nanoparticles. The destroyed aggregation has been monitored by measuring the absorption and resonance light scattering peaks corresponding to the longitudinal surface plasmon resonance (SPR) of the chain-like aggregated gold nanoparticles (AuNPs). It was found that the pre-adding of CEA with different concentrations to the gold colloids before mixing them with R6G could lead to the longitudinal SPR peak decrease and blue shift. By analysing the intensity changing and wavelength shifting of the absorption spectra, CEA could be detected in a linear range from 0.2 to 4 ng/mL, and the limit of detection reaches to 0.1 ng/mL. The sensitivity of the CEA concentration dependent shifting and quenching of the plasmonic absorption and scattering corresponding to the AuNPs aggregation presents a well potential application of biologic spectral sensing.     

Spectral Engineering of Semitransparent Polymer Solar Cells for Greenhouse Applications

In this study, a wavelength selective semitransparent polymer solar cell (ST‐PSC) with a proper transmission spectrum for plant growth is proposed for greenhouse applications. A ternary strategy combining a wide bandgap polymer donor with a near‐infrared absorbing nonfullerene acceptor and a high electron mobility fullerene acceptor is introduced to achieve PSCs with power conversion efficiency (PCE) over 10%. The addition of PC₇₁BM into J52:IEICO‐4F binary blend contributes to the suppressed trap‐assisted recombination, enhanced charge extraction, and improved open‐circuit voltage simultaneously. ST‐PSC based on the J52:IEICO‐4F:PC₇₁BM ternary blend shows an optimized performance with PCE of 7.75% and a defined crop growth factor of 24.8%. Such high‐performance ST‐PSC is achieved by carefully engineering the absorption spectrum of the light harvesting materials. As a result, the transmission spectra of the semitransparent devices are well‐matched with the absorption spectra of the photoreceptors, such as chlorophylls, in green plants, which provides adequate lighting conditions for photosynthesis and plant growth, and therefore making it a competitive candidate for photovoltaic greenhouse applications.     

Improve the Plasmonic Spectral Detection of Alpha-Fetoprotein: the Effect of Branch Length on the Coagulation of Gold Nanostars

Plasmonics - A sensitive spectral sensing method for detection of alpha-fetoprotein (AFP) was proposed based on the intense aggregation of colloidal gold nanostars. It has been found that the...     

基因工程改良淀粉品质

淀粉对人类生活十分重要,它不仅是人们的能量和营养来源,而且还是重要的工业原材料。对于淀粉合成过程及淀粉的加工、使用一直是淀粉研究的重点内容。淀粉的合成在最后阶段涉及到３个关键性的酶是：ＡＤＰＧ焦磷酸化酶、淀粉合成酸以及淀粉分支酶。它们分别催化ＡＤＰ－葡萄糖的形成、葡聚糖链的延伸以及分支链的形成。另外淀粉去分支酶对淀粉最终结构的形成也起到重要作用。本文将介绍上述４个酶近年来的生物化学和分子生物学研究     

微生物发酵法生产L-色氨酸的代谢工程研究

L-色氨酸作为人体内的一种必需氨基酸,广泛应用于医药、食品与饲料等行业.工业上采用的色氨酸生产方法有化学合成法、转化法及微生物发酵法.近年来,随着代谢工程在色氨酸菌种选育中的成功运用,微生物发酵法逐渐成为主要的色氨酸生产方法.系统综述了微生物发酵法生产色氨酸所涉及的代谢工程策略,包括生物合成色氨酸的代谢调控机制以及途径...     

Plasmonic Enhancement of Dye Sensitized Solar Cells via a Tailored Size-Distribution of Chemically Functionalized Gold Nanoparticles

A substantial and stable increase of the current density J_sc of ruthenium (Ru) dye sensitized solar cells (DSC) of up to 16.18% and of the power efficiency of up to 25.5% is demonstrated in this article via plasmonic enhancement. The key aspect of this work is the use of a tailored bimodal size distribution of functionalized gold nanoparticles (AuNPs) that have been chemically immobilized onto the mesoporous titanium dioxide (TiO₂) layer via short, stable dithiodibutyric acid linkers. The size distribution of the AuNPs is a result of theoretical calculations that aimed at the perfection of the absorption characteristics of the complete solar cell system over a wide range of wavelengths. The functionalization of the AuNPs serves to bind them at a close but defined distance to TiO₂-particles and additionally to chemically protect them against potential corrosion by the electrolyte. Simulations of near field (enhanced absorption) and far field (scattering) contributions have been used to tailor a complex AuNPs bimodal size distribution that had subsequently demonstrated experimentally a close to optimum improvement of the absorbance over a wide wavelength range (500–675 nm) and therefore an impressive DSC efficiency enhancement. Finally, the modified DSCs are exhibiting pronounced longevity and stable performance as confirmed via long time measurements. In summary, the presented systems show increased performance compared to non plasmonic enhanced cells with otherwise identical composition, and are demonstrating a previously unpublished longevity for iodide electrolyte/AuNPs combinations.     

Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks

Peptide and protein identification remains challenging in organisms with poorly annotated or rapidly evolving genomes, as are commonly encountered in environmental or biofuels research. Such limitations render tandem mass spectrometry (MS/MS) database search algorithms ineffective as they lack corresponding sequences required for peptide-spectrum matching. We address this challenge with the spectral networks approach to (1) match spectra of orthologous peptides across multiple related species and then (2) propagate peptide annotations from identified to unidentified spectra. We here present algorithms to assess the statistical significance of spectral alignments (Align-GF), reduce the impurity in spectral networks, and accurately estimate the error rate in propagated identifications. Analyzing three related Cyanothece species, a model organism for biohydrogen production, spectral networks identified peptides from highly divergent sequences from networks with dozens of variant peptides, including thousands of peptides in species lacking a sequenced genome. Our analysis further detected the presence of many novel putative peptides even in genomically characterized species, thus suggesting the possibility of gaps in our understanding of their proteomic and genomic expression. A web-based pipeline for spectral networks analysis is available at http://proteomics.ucsd.edu/software.Microorganisms have evolved their cellular metabolism to generate energy for life in unusual environments (1), and their capabilities are of great interest in the production of renewable bioenergy and could contribute toward managing the world''s current energy and climate crisis (2). Genomics studies have increased the number of sequenced bioenergy-related microbial genomes and revealed the possible biological reactions involved in bioenergy production (3). Studies of photosynthetic microorganisms, for example, have yielded insights into how they harvest solar energy and use it to produce bioenergy products (4). Despite this importance of microorganisms, the characterization of diverse microbial phenotypes by proteomics tandem mass spectrometry (MS/MS) has been limited. The dominant approaches for MS/MS analysis heavily rely on the availability of completely annotated genomes (i.e. accurate protein databases) (5–7), yet most microorganisms populating the planet have unsequenced or poorly annotated genomes. Thus it remains challenging to identify proteins from environmental and unculturable organisms.One solution to protein identification in a species with no sequenced genome is to use the genomes of closely related species (8). This requires matching MS/MS data to slightly different peptides in amino acid sequences (polymorphic, orthologous peptides); but matching shifted masses of peptides and their fragment ions is computationally expensive and challenging. Moreover, different species-specific post-translational modifications (PTMs)¹ can make the cross-species identification more complex. The common computational approach is tolerantly matching de novo sequences derived from MS/MS data to the database while allowing for amino acid mutations and modifications (9–11). However, this approach critically depends on good de novo interpretations, which are nearly always partially incorrect and yield high-quality subsequences only for a small fraction of all spectra. The blind database search approach, developed to identify peptides with unexpected modifications, can also be used to directly match MS/MS data from unknown species to a database of closely related species, but its utilization is limited because of its exceptionally large search space (12–18). These spectrum-database matching approaches to cross-species identification pose significant challenges in its speed and sensitivity with a huge database, which leads to a much longer search time and more false positive identifications (19, 20).As a complementary approach to spectrum-database matching, spectral library searching is an emerging and promising approach (21). A spectral library is a large collection of identified MS/MS spectra, and an unknown query spectrum can then be identified by direct spectral matching to the library. The great advantage of this approach is the reduction of search space and the use of fragmentation patterns of peptides. The spectral networks approach expands this concept to the identification of modified peptides in MS/MS data sets (22, 23). Spectral networks do not directly search a database, but groups MS/MS spectra by computing the pairwise similarity between MS/MS spectra of peptide variants and then constructs networks where each spectrum defines a node and each significant spectral pair, highly correlated in the fragmentation pattern, defines an edge (Fig. 1). In spectral networks, identification of spectra belonging to the same subnetwork should be related and thus the peptide sequence for an identified spectrum can be propagated to neighboring unidentified spectra.Open in a separate windowFig. 1.Overview of multi-species spectral networks. Nodes represent individual spectra and edges between nodes represent significant pairwise alignment between spectra; edges are labeled with amino acid mutations (dotted edges) or parent mass differences (solid edges). In spectral networks, a peptide and its related variants are ideally grouped into a single subnetwork. If at least one spectrum in a subnetwork is annotated (filled node), all the neighboring spectra (unfilled nodes) can potentially become identified by propagating the annotation over network edges. For example, all spectra in the subnetwork of “peptide A” (top left, blue network) can be annotated via up to three iterative propagations, first from A to {A₁, A₂, A₃}, second from {A₂, A₃} to {A₄, A₅}, and third from {A₄, A₅} to A₆. This paradigm can be equally applied to cross-species data analysis, as “peptide L” identified in species 1 (top middle, olive-colored network) is propagated to a node unidentified in species 2, identifying its orthologous “peptide l”, with a serine to alanine polymorphism. Thus, spectral networks enable the detection of orthologous peptide pairs between different species.We recently reported that a vast number of polymorphic, orthologous peptides across species are present in MS/MS data sets (24). We propose a new approach in cross-species proteomics research that aggregates MS/MS of multiple related species followed by spectral networks analysis of the pooled data to capitalize on pairs of spectra from orthologous peptides, as shown in Fig. 1. This approach does not require advance knowledge of the genomes for all species, and enables the identification of novel, polymorphic peptides across species via interspecies propagation. Compared with previous approaches, cross-species spectral network analysis has two major advantages. First, by matching spectra to spectra instead of spectra to database sequences, spectral networks only consider the sequence variability of peptides present in the samples instead of considering all possible variability across the whole database of related species; thus the performance of spectral networks is independent of database size. Second, the analysis of the set of highly related spectra increases the reliability in identifying polymorphic peptides in that multiple different spectra can support the same novel identification. The utility of spectral networks can be also expanded to the proteomic analysis of microbial communities that often contain hundreds of distinct organisms (25, 26). But despite the success of spectral networks in low complexity data sets (22, 23), the analysis of large multi-species proteomics data requires significantly higher reliability in spectral similarity scores because the number of pairwise spectral comparisons grows quadratically with the number of spectra.In this work, we present algorithmic and statistical advances to spectral networks to improve its utility with large and diverse spectral data sets. To statistically assess the significance of spectral alignments in pairing millions of spectra, we propose Align-GF (generating function for spectral alignment) to compute rigorous p values of a spectral pair based on the complete score histogram of all possible alignments between two spectra. We show that Align-GF successfully addressed the reliability challenge in a large data set analysis and demonstrated its utility by leading to a 4-fold increase in the sensitivity of spectral pairs. Even with this dramatically improved accuracy, a very small number of incorrect pairs in a network can still complicate propagation of annotations. To further progress toward the ideal scenario where each subnetwork consists of only spectra from a single peptide family, we introduce new procedures to split mixed networks from different peptide families and show that these effectively eliminate many false spectral pairs. Finally, we propose the first approach to calculation of false discovery rate (FDR) for spectral networks propagation of identifications from unmodified to progressively more modified peptides. The proposed FDR estimation was conservative and was more rigorous for highly modified peptides, and thus now makes propagation results comparable to other peptide identification approaches.The cross-species spectral networks techniques proposed here enabled the proteomic analysis of three different Cyanothece species, including a strain where the genome sequence is not known. Cyanobacteria are one of the most diverse and widely distributed microorganisms and have received significant consideration as satisfying various demands required in bioenergy generation (27). We show that spectral networks can improve peptide identification by up to 38% compared with mainstream approaches, including many polymorphic and modified peptides. Spectral networks could identify peptides with highly divergent sequences (with 7 amino acid mutations) by leveraging networks of variant peptides, and one example subnetwork of species-specific variants of phycobilisome proteins reflects the diversity of photosynthetic light-harvesting strategies (28). Our approach thus demonstrates the potential gains in multi-species proteomics and sets the stage for related developments in higher-complexity metaproteomics samples. Finally, spectral networks revealed many unidentified subnetworks containing only unidentified spectra, thus strongly suggesting the presence of novel peptides that are missing from current protein databases. Although we illustrate the potential of our approach on a specific set of bioenergy-related species, we note that the proposed approach is generic and should be applicable to any other set of related species. The diversity of biologically important protein families could be studied by comparing closely and more remotely related species.     

Effects of Growth Solutions Ageing Time to the Formation of Gold Nanorods via Two-Step Approach for Plasmonic Applications

Plasmonics - We demonstrate the structural reorganization of gold nanorods (GNRs) that could fine-tune localized surface plasmon resonance (LSPR) by using modified wet chemical synthesis on the...     

Reverse Engineering of Bacterial Chemotaxis Pathway via Frequency Domain Analysis

Chemotaxis is defined as a behavior involving organisms sensing attractants or repellents and leading towards or away from them. Therefore, it is possible to reengineer chemotaxis network to control the movement of bacteria to our advantage. Understanding the design principles of chemotaxis pathway is a prerequisite and an important topic in synthetic biology. Here, we provide guidelines for chemotaxis pathway design by employing control theory and reverse engineering concept on pathway dynamic design. We first analyzed the mathematical models for two most important kinds of E. coli chemotaxis pathway—adaptive and non-adaptive pathways, and concluded that the control units of the pathway de facto function as a band-pass filter and a low-pass filter, respectively, by abstracting the frequency response properties of the pathways. The advantage of the band-pass filter is established, and we demonstrate how to tune the three key parameters of it—A (max amplification), ω₁ (down cut-off frequency) and ω₂ (up cut-off frequency) to optimize the chemotactic effect. Finally, we hypothesized a similar but simpler version of the dynamic pathway model based on the principles discovered and show that it leads to similar properties with native E. coli chemotactic behaviors. Our study provides an example of simulating and designing biological dynamics in silico and indicates how to make use of the native pathway''s features in this process. Furthermore, the characteristics we discovered and tested through reverse engineering may help to understand the design principles of the pathway and promote the design of artificial chemotaxis pathways.