Maxwell-Hydrodynamic Model for Simulating Nonlinear Terahertz Generation from Plasmonic Metasurfaces

The interaction between the electromagnetic field and plasmonic nanostructures leads to both the strong linear response and inherent nonlinear behavior. In this paper, a time-domain hydrodynamic model for describing the motion of electrons in plasmonic nanostructures is presented, in which both surface and bulk contributions of nonlinearity are considered. A coupled Maxwell-hydrodynamic system capturing full-wave physics and free electron dynamics is numerically solved with the parallel finite-difference time-domain (FDTD) method. The validation of the proposed method is presented to simulate linear and nonlinear responses from a plasmonic metasurface. The linear response is compared with the Drude dispersion model and the nonlinear terahertz emission from a difference-frequency generation process is validated with theoretical analyses. The proposed scheme is fundamentally important to design nonlinear plasmonic nanodevices, especially for efficient and broadband THz emitters.Comment: 8 pages, 7 figures, IEEE Journal on Multiscale and Multiphysics Computational Techniques, 201

Full Hydrodynamic Model of Nonlinear Electromagnetic Response in Metallic Metamaterials

Applications of metallic metamaterials have generated significant interest in recent years. Electromagnetic behavior of metamaterials in the optical range is usually characterized by a local-linear response. In this article, we develop a finite-difference time-domain (FDTD) solution of the hydrodynamic model that describes a free electron gas in metals. Extending beyond the local-linear response, the hydrodynamic model enables numerical investigation of nonlocal and nonlinear interactions between electromagnetic waves and metallic metamaterials. By explicitly imposing the current continuity constraint, the proposed model is solved in a self-consistent manner. Charge, energy and angular momentum conservation laws of high-order harmonic generation have been demonstrated for the first time by the Maxwell-hydrodynamic FDTD model. The model yields nonlinear optical responses for complex metallic metamaterials irradiated by a variety of waveforms. Consequently, the multiphysics model opens up unique opportunities for characterizing and designing nonlinear nanodevices.Comment: 11 pages, 14 figure

Nonlinearity in the Dark: Broadband Terahertz Generation with Extremely High Efficiency

Plasmonic metamaterials and metasurfaces offer new opportunities in developing high performance terahertz emitters and detectors beyond the limitations of conventional nonlinear materials. However, simple meta-atoms for second-order nonlinear applications encounter fundamental trade-offs in the necessary symmetry breaking and local-field enhancement due to radiation damping that is inherent to the operating resonant mode and cannot be controlled separately. Here we present a novel concept that eliminates this restriction obstructing the improvement of terahertz generation efficiency in nonlinear metasurfaces based on metallic nanoresonators. This is achieved by combining a resonant dark-state metasurface, which locally drives nonlinear nanoresonators in the near field, with a specific spatial symmetry that enables destructive interference of the radiating linear moments of the nanoresonators, and perfect absorption via simultaneous electric and magnetic critical coupling of the pump radiation to the dark mode. Our proposal allows eliminating linear radiation damping, while maintaining constructive interference and effective radiation of the nonlinear components. We numerically demonstrate a giant second-order nonlinear susceptibility around Hundred-Billionth m/V, a one order improvement compared with the previously reported split-ring-resonator metasurface, and correspondingly, a 2 orders of magnitude enhanced terahertz energy extraction should be expected with our configuration under the same conditions. Our study offers a paradigm of high efficiency tunable nonlinear metadevices and paves the way to revolutionary terahertz technologies and optoelectronic nanocircuitry.Comment: 6 pages, 4 figure

Fish-T1K (Transcriptomes of 1,000 Fishes) Project: Large-Scale Transcriptome Data for Fish Evolution Studies

Ray-finned fishes (Actinopterygii) represent more than 50 % of extant vertebrates and are of great evolutionary, ecologic and economic significance, but they are relatively underrepresented in ‘omics studies. Increased availability of transcriptome data for these species will allow researchers to better understand changes in gene expression, and to carry out functional analyses. An international project known as the “Transcriptomes of 1,000 Fishes” (Fish-T1K) project has been established to generate RNA-seq transcriptome sequences for 1,000 diverse species of ray-finned fishes. The first phase of this project has produced transcriptomes from more than 180 ray-finned fishes, representing 142 species and covering 51 orders and 109 families. Here we provide an overview of the goals of this project and the work done so far

Understanding the Spatial Structure of Urban Commuting Using Mobile Phone Location Data: A Case Study of Shenzhen, China

Understanding commuting patterns has been a classic research topic in the fields of geography, transportation and urban planning, and it is significant for handling the increasingly serious urban traffic congestion and air pollution and their impacts on the quality of life. Traditional studies have used travel survey data to investigate commuting from the aspects of commuting mode, efficiency and influence factors. Due to the limited sample size of these data, it is difficult to examine the large-scale commuting patterns of urban citizens, especially when exploring the spatial structure of commuting. This study attempts to understand the spatial structure characteristics generated by human commutes to work by using massive mobile phone datasets. A three-step workflow was proposed to accomplish this goal, which includes extracting the home and work locations of phone users, detecting the communities from the commuting network, and identifying the commuting convergence and divergence areas for each community. A case study of Shenzhen, China was implemented to determine the commuting structure. We found that there are thirteen communities detected from the commuting network and that some of the communities are in accordance with urban planning; moreover, spatial polycentric polygons exist in each community. These findings can be referenced by urban planners or policy-makers to optimize the spatial layout of the urban functional zones. Document type: Articl

A Convergent Differential Evolution Algorithm with Hidden Adaptation Selection for Engineering Optimization

Many improved differential Evolution (DE) algorithms have emerged as a very competitive class of evolutionary computation more than a decade ago. However, few improved DE algorithms guarantee global convergence in theory. This paper developed a convergent DE algorithm in theory, which employs a self-adaptation scheme for the parameters and two operators, that is, uniform mutation and hidden adaptation selection (haS) operators. The parameter self-adaptation and uniform mutation operator enhance the diversity of populations and guarantee ergodicity. The haS can automatically remove some inferior individuals in the process of the enhancing population diversity. The haS controls the proposed algorithm to break the loop of current generation with a small probability. The breaking probability is a hidden adaptation and proportional to the changes of the number of inferior individuals. The proposed algorithm is tested on ten engineering optimization problems taken from IEEE CEC2011

TIPE2 Suppresses Malignancy of Pancreatic Cancer Through Inhibiting TGFβ1 Mediated Signaling Pathway

Pancreatic cancer is one of the major reasons of cancer-associated deaths due to poor diagnosis, high metastasis and drug resistance. Therefore, it is important to understand the cellular and molecular mechanisms of pancreatic cancer to identify new targets for the treatment. TIPE2 is an essential regulator of tumor apoptosis, inflammation and immune homeostasis. However, the role of TIPE2 is still not fully understood in pancreatic cancer. In this study, we found the expression of TIPE2 was decreased in pancreatic cancer tissues compare to paracancerous tissues, which was negatively correlated with tumor size in patients. Overexpression of TIPE2 significantly decreased cell proliferation, metastasis and increased apoptotic events in pancreatic cancer cell lines. Moreover, the results obtained from real time PCR and western blot revealed that TIPE2 was also involved in inhibiting MMPs and N-Cadherin expression while increasing Bax expression in pancreatic cancer cells. Similarly, TIPE2 could inhibit tumor growth in vivo, decrease the expression of Ki-67 and N-Cadherin, and increase the expression of Bax by IHC analysis in tumor tissues isolated from tumor-bearing mice. Mechanistic studies exhibited that TIPE2 might suppress pancreatic cancer development through inhibiting PI3K/AKT and Raf/MEK/ERK signaling pathways triggered by TGFβ1. Moreover, the tumor-infiltrating lymphocytes from tumor-bearing mice were analyzed by flow cytometry, and showed that TIPE2 could promote T cell activation to exert an anti-tumor effect possibly through activation of DCs in a TGFβ1 dependent manner. In general, we described the multiple regulatory mechanisms of TIPE2 in pancreatic tumorigenesis and tumor microenvironment, which suggested TIPE2 may act as a potential therapeutic target in pancreatic cancer

Macroscopic helical chirality and self-motion of hierarchical self-assemblies induced by enantiomeric small molecules

Transfer of molecular chirality to supramolecular chirality at nanoscale and microscale by chemical self-assembly has been studied intensively for years. However, how such molecular chirality further transfers to the macroscale along the same path remains elusive. Here we reveal how the chirality from molecular level transfers to macroscopic level via self-assembly. We assemble a macrostripe using enantiomeric camphorsulfonic acid (CSA)-doped polyaniline with hierarchical order. The stripe can twist into a single-handed helical ribbon via helical self-motion. A multi-scale chemo-mechanical model is used to elucidate the mechanism underlying its chirality transfer and induction. The molecular origin of this macroscopic helical chirality is verified. Results provide a comprehensive understanding of hierarchical chirality transfer and helical motion in self-assembled materials and even their natural analogues. The stripe exhibits disparate actuation behaviour under stimuli of enantiomeric amines and integrating such chiral perception with helical self-motion may motivate chiral biomimetic studies of smart materials