Strong interface-induced spin-orbit coupling in graphene on WS2

Interfacial interactions allow the electronic properties of graphene to be modified, as recently demonstrated by the appearance of satellite Dirac cones in the band structure of graphene on hexagonal boron nitride (hBN) substrates. Ongoing research strives to explore interfacial interactions in a broader class of materials in order to engineer targeted electronic properties. Here we show that at an interface with a tungsten disulfide (WS2) substrate, the strength of the spin-orbit interaction (SOI) in graphene is very strongly enhanced. The induced SOI leads to a pronounced low-temperature weak anti-localization (WAL) effect, from which we determine the spin-relaxation time. We find that spin-relaxation time in graphene is two-to-three orders of magnitude smaller on WS2 than on SiO2 or hBN, and that it is comparable to the intervalley scattering time. To interpret our findings we have performed first-principle electronic structure calculations, which both confirm that carriers in graphene-on-WS2 experience a strong SOI and allow us to extract a spin-dependent low-energy effective Hamiltonian. Our analysis further shows that the use of WS2 substrates opens a possible new route to access topological states of matter in graphene-based systems.Comment: Originally submitted version in compliance with editorial guidelines. Final version with expanded discussion of the relation between theory and experiments to be published in Nature Communication

Chemically etched ultrahigh-Q wedge-resonator on a silicon chip

Ultrahigh-Q optical resonators are being studied across a wide range of fields, including quantum information, nonlinear optics, cavity optomechanics and telecommunications. Here, we demonstrate a new resonator with a record Q-factor of 875 million for on-chip devices. The fabrication of our device avoids the requirement for a specialized processing step, which in microtoroid resonators8 has made it difficult to control their size and achieve millimetre- and centimetre-scale diameters. Attaining these sizes is important in applications such as microcombs and potentially also in rotation sensing. As an application of size control, stimulated Brillouin lasers incorporating our device are demonstrated. The resonators not only set a new benchmark for the Q-factor on a chip, but also provide, for the first time, full compatibility of this important device class with conventional semiconductor processing. This feature will greatly expand the range of possible ‘system on a chip’ functions enabled by ultrahigh-Q devices

Protease-Activated Drug Development

In this extensive review, we elucidate the importance of proteases and their role in drug development in various diseases with an emphasis on cancer. First, key proteases are introduced along with their function in disease progression. Next, we link these proteases as targets for the development of prodrugs and provide clinical examples of protease-activatable prodrugs. Finally, we provide significant design considerations needed for the development of the next generation protease-targeted and protease-activatable prodrugs

Synergistic Antifungal Study of PEGylated Graphene Oxides and Copper Nanoparticles against Candida albicans

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).The coupling reactions of polyethylene glycol (PEG) with two different nano-carbonaceous materials, graphene oxide (GO) and expanded graphene oxide (EGO), were achieved by amide bond formations. These reactions yielded PEGylated graphene oxides, GO-PEG and EGO-PEG. Whilst presence of the newly formed amide links (NH-CO) were confirmed by FTIR stretches observed at 1732 cm−1 and 1712 cm−1, the associated Raman D- and G-bands resonated at 1311/1318 cm−1 and 1584/1595 cm−1 had shown the carbonaceous structures in both PEGylated products remain unchanged. Whilst SEM images revealed the nano-sheet structures in all the GO derivatives (GO/EGO and GO-PEG/EGO-PEG), TEM images clearly showed the nano-structures of both GO-PEG and EGO-PEG had undergone significant morphological changes from their starting materials after the PEGylated processes. The successful PEGylations were also indicated by the change of pH values measured in the starting GO/EGO (pH 2.6–3.3) and the PEGylated GO-PEG/EGO-PEG (pH 6.6–6.9) products. Initial antifungal activities of selective metallic nanomaterials (ZnO and Cu) and the four GO derivatives were screened against Candida albicans using the in vitro cut-well method. Whilst the haemocytometer count indicated GO-PEG and copper nanoparticles (CuNPs) exhibited the best antifungal effects, the corresponding SEM images showed C. albicans had, respectively, undergone extensive shrinkage and porosity deformations. Synergistic antifungal effects all GO derivatives in various ratio of CuNPs combinations were determined by assessing C. albicans viabilities using broth dilution assays. The best synergistic effects were observed when a 30:70 ratio of GO/GO-PEG combined with CuNPs, where MIC50 185–225 μm/mL were recorded. Moreover, the decreased antifungal activities observed in EGO and EGO-PEG may be explained by their poor colloidal stability with increasing nanoparticle concentrations.Peer reviewe

Multimodal sensor fusion for real-time location-dependent defect detection in laser-directed energy deposition

Real-time defect detection is crucial in laser-directed energy deposition (L-DED) additive manufacturing (AM). Traditional in-situ monitoring approach utilizes a single sensor (i.e., acoustic, visual, or thermal sensor) to capture the complex process dynamic behaviors, which is insufficient for defect detection with high accuracy and robustness. This paper proposes a novel multimodal sensor fusion method for real-time location-dependent defect detection in the robotic L-DED process. The multimodal fusion sources include a microphone sensor capturing the laser-material interaction sound and a visible spectrum CCD camera capturing the coaxial melt pool images. A hybrid convolutional neural network (CNN) is proposed to fuse acoustic and visual data. The key novelty in this study is that the traditional manual feature extraction procedures are no longer required, and the raw melt pool images and acoustic signals are fused directly by the hybrid CNN model, which achieved the highest defect prediction accuracy (98.5 %) without the thermal sensing modality. Moreover, unlike previous region-based quality prediction, the proposed hybrid CNN can detect the onset of defect occurrences. The defect prediction outcomes are synchronized and registered with in-situ acquired robot tool-center-point (TCP) data, which enables localized defect identification. The proposed multimodal sensor fusion method offers a robust solution for in-situ defect detection.Comment: 8 pages, 10 figures. This paper has been accepted to be published in the proceedings of IDETC-CIE 202

Weak localization of Dirac fermions in graphene beyond the diffusion regime

We develop a microscopic theory of the weak localization of two-dimensional massless Dirac fermions which is valid in the whole range of classically weak magnetic fields. The theory is applied to calculate magnetoresistance caused by the weak localization in graphene and conducting surfaces of bulk topological insulators.Comment: 5 pages, 2 figure