Surface Plasmon Enhancement on Infrared Photodetection

AbstractInAsSb based infrared photodetector is an alternative to the existing HgCdTe, PbSnTe, and InSb counterparts, but its room temperature performance is still relatively poor. One of the ways to improve its performance is through surface plasmon, which provides near field confinement that leads to enhancement in light matter interaction. In this work, the role of each parameter of two dimensional metallic hole arrays in plasmonic enhancement is studied in details, such as the periodicity of hole array, hole diameter and metal film thickness. The plasmonic resonances and their corresponding electric field distributions are comprehensively studied in finite difference time domain simulation, which also would serve as a guide for designing surface plasmon enhanced InAsSb infrared detector with high quantum efficiency and signal-to-noise ratio

PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions

Graph node embedding aims at learning a vector representation for all nodes given a graph. It is a central problem in many machine learning tasks (e.g., node classification, recommendation, community detection). The key problem in graph node embedding lies in how to define the dependence to neighbors. Existing approaches specify (either explicitly or implicitly) certain dependencies on neighbors, which may lead to loss of subtle but important structural information within the graph and other dependencies among neighbors. This intrigues us to ask the question: can we design a model to give the maximal flexibility of dependencies to each node's neighborhood. In this paper, we propose a novel graph node embedding (named PINE) via a novel notion of partial permutation invariant set function, to capture any possible dependence. Our method 1) can learn an arbitrary form of the representation function from the neighborhood, withour losing any potential dependence structures, and 2) is applicable to both homogeneous and heterogeneous graph embedding, the latter of which is challenged by the diversity of node types. Furthermore, we provide theoretical guarantee for the representation capability of our method for general homogeneous and heterogeneous graphs. Empirical evaluation results on benchmark data sets show that our proposed PINE method outperforms the state-of-the-art approaches on producing node vectors for various learning tasks of both homogeneous and heterogeneous graphs.Comment: 24 pages, 4 figures, 3 tables. arXiv admin note: text overlap with arXiv:1805.1118

Examining the Interactome of Huperzine A by Magnetic Biopanning

Huperzine A is a bioactive compound derived from traditional Chinese medicine plant Qian Ceng Ta (Huperzia serrata), and was found to have multiple neuroprotective effects. In addition to being a potent acetylcholinesterase inhibitor, it was thought to act through other mechanisms such as antioxidation, antiapoptosis, etc. However, the molecular targets involved with these mechanisms were not identified. In this study, we attempted to exam the interactome of Huperzine A using a cDNA phage display library and also mammalian brain tissue extracts. The drugs were chemically linked on the surface of magnetic particles and the interactive phages or proteins were collected and analyzed. Among the various cDNA expressing phages selected, one was identified to encode the mitochondria NADH dehydrogenase subunit 1. Specific bindings between the drug and the target phages and target proteins were confirmed. Another enriched phage clone was identified as mitochondria ATP synthase, which was also panned out from the proteome of mouse brain tissue lysate. These data indicated the possible involvement of mitochondrial respiratory chain matrix enzymes in Huperzine A's pharmacological effects. Such involvement had been suggested by previous studies based on enzyme activity changes. Our data supported the new mechanism. Overall we demonstrated the feasibility of using magnetic biopanning as a simple and viable method for investigating the complex molecular mechanisms of bioactive molecules

Mid-wavelength infrared photodetection and surface plasmon enhancement

Infrared (IR) photodetectors with peak sensitivity wavelength in mid-wavelength infrared (MWIR) spectral window (3-5 μm) have attracted extensive interests due to the highest atmospheric transmission in this range. Traditional photodetectors operating in this wavelength range are mainly based on HgCdTe, PbSnTe and InSb, which either have difficulties in repeatable growth of uniform composition bulk crystals and epitaxial layers or need low temperature environment, which lead to the development of alternative material systems, such as InAs/GaSb type-II superlattice (SL) and InAsSb based material system. To improve high temperature performance of photodetectors, a concept of surface plasmon polariton (SPP) enhancement has been proposed in recent years. By placing a plasmonic structure which has strong light focusing capability in sub-wavelength regime, close to absorption region of a detector, tight spatial confinement and high local field intensity of surface plasmons enable to enhance light-matter interaction and thus to improve the performance of light detection. A practical and efficient way is to integrate a sub-wavelength metallic two-dimensional hole array (2DHA) and an absorption structure. Simulation and analysis of extraordinary optical transmission (EOT) through sub-wavelength metallic 2DHA, the underlying physics and mechanism of plasmonic enhanced photodetection have been studied. Possible variables and parameters which may affect the transmission and enhancement of photodetector performance have been analyzed. These include periodicity of hole array, hole diameter, refractive index of substrate, thickness of metal film, hole shape and light incident direction. The simulation results provide a good guide for design of 2DHA photodetectors. The origin of Wood’s anomaly in optical transmission through metallic hole array has been analyzed. Here, the contradiction of the existence of Wood’s anomaly in EOT and the generally observed broadband performance enhancement of photodetector via 2DHA is successfully explained. It is interpreted that at Wood’s anomaly wavelength, the extremely low transmission results from excitation of incident light as SPP, which has a low efficiency of being decoupled from the metal-dielectric interface and doesn’t contribute to transmission. Also, how this theory can be applied to illustrate the broadband photoresponse enhancement of integrated structure of photodetector and metallic hole array is described. A n-i-p based mid-infrared InAs/GaSb type-II superlattice (SL) photodetector working at 220 K has been designed and fabricated. According to characterization results, the grown SL structure has very high quality. At 220 K, the 50% cutoff wavelength of the photoresponse is about 4.66 µm, the R0A is as high as 14.9 Ω·cm2, and the dark current is very low. The peak detectivity of the photodetector is 2.23×10^10 Jones at 3.0 µm under zero bias, which is the highest for the InAs/GaSb SL photodetector operating at 220 K. High performance InAsSb based photodetector operating at room temperature has been fabricated and investigated. The InAsSb material is grown on the GaSb substrate by molecular beam epitaxy (MBE) and photoconductive detector is made by them. The grown materials show high quality and slight lattice mismatch to the substrate. The photoconductors fabricated based on the InAsSb/GaSb structure show spectral response ranging from near infrared (NIR) to MWIR range. They can work well at low voltage bias and the measured blackbody detectivities are ~2.4×10^7 Jones and ~6.1×10^9 Jones at room temperature and 77 K, respectively. Photodetection performance of n-GaSb/n-InAsSb heterostructure at different temperatures and biases has been investigated. The devices were found to be capable of dual color photodetection at fixed large forward biases at different temperatures and the maximum responsivity occurs at room temperature. As the forward bias decreases, a turning bias exists at which the photocurrent changes its direction and the voltage value varies with temperature. At reverse biases, the absorption of GaSb dominates the photocurrent and the maximum photocurrent occurs at about 205 K. All the observation can be explained by the proposed model. Plasmonic enhanced infrared photodetection based on n-GaSb/n-InAsSb heterostructure is realized and investigated. By integrating properly designed sub-wavelength metallic 2DHA on top, the room temperature photocurrent and detectivity of the photodiode is enhanced by ~2 times. Besides, the dark current of the heterostructure is not adversely affected by 2DHA fabricated on top. The performance enhancement is due to higher quantum efficiency of the 2DHA-heterostructure, resulting from electric field concentration at the metal-dielectric interface.Doctor of Philosophy (EEE

Solid Dispersions of Genistein via Solvent Rotary Evaporation for Improving Solubility, Bioavailability, and Amelioration Effect in HFD-Induced Obesity Mice

Genistein (GEN) is an active pharmaceutical ingredient that presents the challenges of poor water solubility and low oral bioavailability. To tackle these challenges, a GEN solid dispersion was prepared by solvent rotary evaporation using polyvinylpyrrolidone K30 (PVP K30) as a carrier. The optimal formulation was determined by drug loading efficiency and in vitro release. The physical state of the solid dispersion was characterized by DSC, XRD, SEM and FT-IR. And the results of the in vitro release study indicate that the drug release of SD (1:7) increased 482-fold that of pure GEN at 60 min. Following oral administration to rats, the Cmax and AUC0–24 of SD (1:7) was increased 6.86- and 2.06-fold to that of pure GEN. The adipose fat index and body weight of the SD (1:7) group were significantly lower than those of the GEN group (p p < 0.05). All experiments revealed that solid dispersion could be a promising formulation approach to improve the dissolution rate, oral bioavailability, and effect on the reduction of lipid accumulation in high-fat diet-induced obesity mice

Study of dual color infrared photodetection from n-GaSb/n-InAsSb heterostructures

We report detailed investigation of n-GaSb/n-InAsSb heterostructure photodetectors for infrared photodetection at different temperatures and biases. Our results show that the heterostructure photodetectors are capable of dual color photodetections at a fixed forward bias with its highest responsivity occurred at room temperature; With the decrease of the forward bias, a turning point, at which the photocurrent changes its direction, exist and the corresponding voltage values increases with the decrease of temperature; At all reverse biases, the photocurrents flow in the same direction but the maximum current occurs at about 205 K. A new model is proposed, which can well explain all the observations.ASTAR (Agency for Sci., Tech. and Research, S’pore)MOE (Min. of Education, S’pore)Published versio

Transgenic Cotton Plants Expressing the HaHR3 Gene Conferred Enhanced Resistance to Helicoverpa armigera and Improved Cotton Yield

RNA interference (RNAi) has been developed as an efficient technology. RNAi insect-resistant transgenic plants expressing double-stranded RNA (dsRNA) that is ingested into insects to silence target genes can affect the viability of these pests or even lead to their death. HaHR3, a molt-regulating transcription factor gene, was previously selected as a target expressed in bacteria and tobacco plants to control Helicoverpa armigera by RNAi technology. In this work, we selected the dsRNA-HaHR3 fragment to silence HaHR3 in cotton bollworm for plant mediated-RNAi research. A total of 19 transgenic cotton lines expressing HaHR3 were successfully cultivated, and seven generated lines were used to perform feeding bioassays. Transgenic cotton plants expressing dsHaHR3 were shown to induce high larval mortality and deformities of pupation and adult eclosion when used to feed the newly hatched larvae, and 3rd and 5th instar larvae of H. armigera. Moreover, HaHR3 transgenic cotton also demonstrated an improved cotton yield when compared with controls

PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions

Graph node embedding aims at learning a vector representation for all nodes given a graph. It is a central problem in many machine learning tasks (e.g., node classification, recommendation, community detection). The key problem in graph node embedding lies in how to define the dependence to neighbors. Existing approaches specify (either explicitly or implicitly) certain dependencies on neighbors, which may lead to loss of subtle but important structural information within the graph and other dependencies among neighbors. This intrigues us to ask the question: can we design a model to give the maximal flexibility of dependencies to each node's neighborhood. In this paper, we propose a novel graph node embedding (named PINE) via a novel notion of partial permutation invariant set function, to capture any possible dependence. Our method 1) can learn an arbitrary form of the representation function from the neighborhood, withour losing any potential dependence structures, and 2) is applicable to both homogeneous and heterogeneous graph embedding, the latter of which is challenged by the diversity of node types. Furthermore, we provide theoretical guarantee for the representation capability of our method for general homogeneous and heterogeneous graphs. Empirical evaluation results on benchmark data sets show that our proposed PINE method outperforms the state-of-the-art approaches on producing node vectors for various learning tasks of both homogeneous and heterogeneous graphs.This is a pre-print of the article Gui, Shupeng, Xiangliang Zhang, Pan Zhong, Shuang Qiu, Mingrui Wu, Jieping Ye, Zhengdao Wang, and Ji Liu. "Pine: Universal deep embedding for graph nodes via partial permutation invariant set functions." arXiv preprint arXiv:1909.12903 (2019). Posted with permission.</p