RESUMEN
Lateral transition-metal dichalcogenide and their heterostructures have attracted substantial attention, but there lacks a simple approach to produce large-scaled optoelectronic devices with graded composition. In particular, the incorporation of substitution and doping into heterostructure formation is rarely reported. Here, we demonstrate growth of a composition graded doped lateral WSe2/WS2 heterostructure by ambient pressure chemical vapor deposition in a single heat cycle. Through Raman and photoluminescence spectroscopy, we demonstrate that the monolayer heterostructure exhibits a clear interface between two domains and a graded composition distribution in each domain. The coexistence of two distinct doping modes, i.e., interstitial and substitutional doping, was verified experimentally. A distinct three-stage growth mechanism consisting of nucleation, epitaxial growth, and substitution was proposed. Electrical transport measurements reveal that this lateral heterostructure has representative characteristics of a photodiodes. The optoelectronic device based on the lateral WSe2/WS2 heterostructure shows improved photodetection performance in terms of a reasonable responsivity and a large photoactive area.
RESUMEN
BACKGROUND: Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. METHOD: We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. RESULTS: We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. CONCLUSIONS: The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a significant breakthrough for the process of drug discovery against schistosomiasis in particular and can be extended to other helmintic diseases which together afflict a large part of humankind.
