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Optimizing the Geometry of Photoacoustically Active Gold Nanoparticles for Biomedical Imaging
Photoacoustics is an upcoming modality for biomedical imaging, which promises minimal invasiveness at high penetration depths of several centimeters. For superior photoacoustic contrast, imaging probes with high photothermal conversion efficiency are required. Gold nanoparticles are among the best performing photoacoustic imaging probes. However, the geometry and size of the nanoparticles determine their photothermal efficiency. We present a systematic theoretical analysis to determine the optimum nanoparticle geometry with respect to photoacoustic efficiency in the near-infrared spectral range, for superior photoacoustic contrast. Theoretical predictions are illustrated by experimental results for two of the most promising nanoparticle geometries, namely, high aspect ratio gold nanorods and gold nanostars. Copyright © 2020 American Chemical Society.
Present and future of surface-enhanced Raman scattering
The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.
Electron Transport across Vertical Silicon/MoS2/Graphene Heterostructures: Towards Efficient Emitter Diodes for Graphene Base Hot Electron Transistors
Heterostructures comprising silicon, molybdenum disulfide (MoS2), and graphene are investigated with respect to the vertical current conduction mechanism. The measured current-voltage (I-V) characteristics exhibit temperature-dependent asymmetric current, indicating thermally activated charge carrier transport. The data are compared and fitted to a current transport model that confirms thermionic emission as the responsible transport mechanism across devices. Theoretical calculations in combination with the experimental data suggest that the heterojunction barrier from Si to MoS2 is linearly temperature-dependent for T = 200-300 K with a positive temperature coefficient. The temperature dependence may be attributed to a change in band gap difference between Si and MoS2, strain at the Si/MoS2 interface, or different electron effective masses in Si and MoS2, leading to a possible entropy change stemming from variation in density of states as electrons move from Si to MoS2. The low barrier formed between Si and MoS2 and the resultant thermionic emission demonstrated here make the present devices potential candidates as the emitter diode of graphene base hot electron transistors for future high-speed electronics. Copyright © 2020 American Chemical Society.
Unveiling Relations in the Industry 4.0 Standards Landscape Based on Knowledge Graph Embeddings
Industry 4.0 (I4.0) standards and standardization frameworks have been proposed with the goal of empowering interoperability in smart factories. These standards enable the description and interaction of the main components, systems, and processes inside of a smart factory. Due to the growing number of frameworks and standards, there is an increasing need for approaches that automatically analyze the landscape of I4.0 standards. Standardization frameworks classify standards according to their functions into layers and dimensions. However, similar standards can be classified differently across the frameworks, producing, thus, interoperability conflicts among them. Semantic-based approaches that rely on ontologies and knowledge graphs, have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks. Albeit informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. Thus, graph-based analytical methods able to exploit knowledge encoded by these approaches, are required to uncover alignments among standards. We study the relatedness among standards and frameworks based on community analysis to discover knowledge that helps to cope with interoperability conflicts between standards. We use knowledge graph embeddings to automatically create these communities exploiting the meaning of the existing relationships. In particular, we focus on the identification of similar standards, i.e., communities of standards, and analyze their properties to detect unknown relations. We empirically evaluate our approach on a knowledge graph of I4.0 standards using the Trans∗ family of embedding models for knowledge graph entities. Our results are promising and suggest that relations among standards can be detected accurately.
Segregated Network Polymer Composites with High Electrical Conductivity and Well Mechanical Properties based on PVC, P(VDFTFE), UHMWPE, and rGO
The formation of a segregated network structure (wittingly uneven distribution of a filler) is one of the most promising strategies for the fabrication of electrically conductive polymer composites at present. However, the simultaneous achievement of high values of electrical conductivity with the retention of well mechanical properties within this approach remains a great challenge. Here, by means of X-ray photoelectron spectra (XPS), near-edge X-ray absorption fine structure (NEXAFS) spectra, scanning electron microscopy (SEM), dielectric spectroscopy, and compression engineering stress-strain curve analysis, we have studied the effect of a segregated network structure on the electrical conductivity and mechanical properties of a set of polymer composites. The composites were prepared by applying graphene oxide (GO) with ultralarge basal plane size (up to 150 μm) onto the surface of polymer powder particles, namely, poly(vinyl chloride) (PVC), poly(vinylidene fluoride-co-tetrafluoroethylene) (P(VDF-TFE)), and ultrahigh-molecular-weight poly(ethylene) (UHMWPE) with the subsequent GO reduction and composite hot pressing. A strong dependence of the segregated network polymer composites' physical properties on the polymer matrix was demonstrated. Particularly, 12 orders of magnitude rise of the polymers' electrical conductivity up to 0.7 S/m was found upon the incorporation of the reduced GO (rGO). A 17% increase in the P(VDF-TFE) elastic modulus filled by 1 wt % of rGO was observed. Fracture strength of PVC/rGO at 0.5 wt % content of the filler was demonstrated to decrease by fourfold. At the same time, the change in strength was not significant for P(VDF-TFE) and UHMWPE composites in comparison with pure polymers. Our results show a promise to accelerate the development of new composites for energy applications, such as metal-free supercapacitor plates and current collectors of lithium-ion batteries, bipolar plates of proton-exchange membrane fuel cells, antistatic elements of various electronic devices, etc. © 2020 American Chemical Society.
Mechanistic Understanding of the Heterogeneous, Rhodium-Cyclic (Alkyl)(Amino)Carbene-Catalyzed (Fluoro-)Arene Hydrogenation
Recently, chemoselective methods for the hydrogenation of fluorinated, silylated, and borylated arenes have been developed providing direct access to previously unattainable, valuable products. Herein, a comprehensive study on the employed rhodium-cyclic (alkyl)(amino)carbene (CAAC) catalyst precursor is disclosed. Mechanistic experiments, kinetic studies, and surface-spectroscopic methods revealed supported rhodium(0) nanoparticles (NP) as the active catalytic species. Further studies suggest that CAAC-derived modifiers play a key role in determining the chemoselectivity of the hydrogenation of fluorinated arenes, thus offering an avenue for further tuning of the catalytic properties. Copyright © 2020 American Chemical Society.
Labour Market Information Driven, Personalized, OER Recommendation System for Lifelong Learners
In this paper, we suggest a novel method to aid lifelong learners to access relevant OER based learning content to master skills demanded on the labour market. Our software prototype 1) applies Text Classification and Text Mining methods on vacancy announcements to decompose jobs into meaningful skills components, which lifelong learners should target; and 2) creates a hybrid OER Recommender System to suggest personalized learning content for learners to progress towards their skill targets. For the first evaluation of this prototype we focused on two job areas: Data Scientist, and Mechanical Engineer. We applied our skill extractor approach and provided OER recommendations for learners targeting these jobs. We conducted in-depth, semi-structured interviews with 12 subject matter experts to learn how our prototype performs in terms of its objectives, logic, and contribution to learning. More than 150 recommendations were generated, and 76.9% of these recommendations were treated as us eful by the interviewees. Interviews revealed that a personalized OER recommender system, based on skills demanded by labour market, has the potential to improve the learning experience of lifelong learners.
Biochemical Characterization of Mouse Retina of an Alzheimer's Disease Model by Raman Spectroscopy
The presence of biomarkers characteristic for Alzheimer's disease in the retina is a controversial topic. Raman spectroscopy offers information on the biochemical composition of tissues. Thus, it could give valuable insight into the diagnostic value of retinal analysis. Within the present study, retinas of a double transgenic mouse model, that expresses a chimeric mouse/human amyloid precursor protein and a mutant form of human presenilin 1, and corresponding control group were subjected to ex vivo Raman imaging. The Raman data recorded on cross sections of whole eyes highlight the layered structure of the retina in a label-free manner. Based on the Raman information obtained from en face mounted retina samples, a discrimination between healthy and Alzheimer's disease retinal tissue can be done with an accuracy of 85.9%. For this a partial least squares-linear discriminant analysis was applied. Therefore, although no macromolecular changes in form of, i.e., amyloid beta plaques, can be noticed based on Raman spectroscopy, subtle biochemical changes happening in the retina could lead to Alzheimer's disease identification. ©
Gas-Phase Fluorination on PLA Improves Cell Adhesion and Spreading
For the regeneration or creation of functional tissues, biodegradable biomaterials including polylactic acid (PLA) are widely preferred. Modifications of the material surface are quite common to improve cell-material interactions and thereby support the biological outcome. Typical approaches include a wet chemical treatment with mostly hazardous substances or a functionalization with plasma. In the present study, gas-phase fluorination was applied to functionalize the PLA surfaces in a simple and one-step process. The biological response including biocompatibility, cell adhesion, cell spreading, and proliferation was analyzed in cell culture experiments with fibroblasts L929 and correlated with changes in the surface properties. Surface characterization methods including surface energy and isoelectric point measurements, X-ray photoelectron spectroscopy, and atomic force microscopy were applied to identify the effects of fluorination on PLA. Gas-phase fluorination causes the formation of C-F bonds in the PLA backbone, which induce a shift to a more hydrophilic and polar surface. The slightly negatively charged surface dramatically improves cell adhesion and spreading of cells on the PLA even with low fluorine content. The results indicate that this improved biological response is protein-but not integrin-dependent. Gas-phase fluorination is therefore an efficient technique to improve cellular response to biomaterial surfaces without losing cytocompatibility. Copyright © 2020 American Chemical Society.
Translating the Concept of Goal Setting into Practice: What ‘else’ Does It Require than a Goal Setting Tool?
This conceptual paper reviews the current status of goal setting in the area of technology enhanced learning and education. Besides a brief literature review, three current projects on goal setting are discussed. The paper shows that the main barriers for goal setting applications in education are not related to the technology, the available data or analytical methods, but rather the human factor. The most important bottlenecks are the lack of students’ goal setting skills and abilities, and the current curriculum design, which, especially in the observed higher education institutions, provides little support for goal setting interventions.