Focused-ion-beam-induced deposition of superconducting nanowires

Superconducting nanowires, with a critical temperature of 5.2 K, have been synthesized using an ion-beam-induced deposition, with a Gallium focused ion beam and Tungsten Carboxyl, W(CO)6, as precursor. The films are amorphous, with atomic concentrations of about 40, 40, and 20 % for W, C, and Ga, respectively. Zero Kelvin values of the upper critical field and coherence length of 9.5 T and 5.9 nm, respectively, are deduced from the resistivity data at different applied magnetic fields. The critical current density is Jc= 1.5 10^5 A/cm2 at 3 K. This technique can be used as a template-free fabrication method for superconducting devices.Comment: Accepted for publication in Applied Physics Letter

Electrical transport properties of small diameter single-walled carbon nanotubes aligned on ST-cut quartz substrates

A method is introduced to isolate and measure the electrical transport properties of individual single-walled carbon nanotubes (SWNTs) aligned on an ST-cut quartz, from room temperature down to 2 K. The diameter and chirality of the measured SWNTs are accurately defined from Raman spectroscopy and atomic force microscopy (AFM). A significant up-shift in the G-band of the resonance Raman spectra of the SWNTs is observed, which increases with increasing SWNTs diameter, and indicates a strong interaction with the quartz substrate. A semiconducting SWNT, with diameter 0.84 nm, shows Tomonaga-Luttinger liquid and Coulomb blockade behaviors at low temperatures. Another semiconducting SWNT, with a thinner diameter of 0.68 nm, exhibits a transition from the semiconducting state to an insulating state at low temperatures. These results elucidate some of the electrical properties of SWNTs in this unique configuration and help pave the way towards prospective device applications

Embedding a Carbon Nanotube across the Diameter of a Solid State Nanopore

A fabrication method for positioning and embedding a single-walled carbon nanotube (SWNT) across the diameter of a solid state nanopore is presented. Chemical vapor deposition (CVD) is used to grow SWNTs over arrays of focused ion beam (FIB) milled pores in a thin silicon nitride membrane. This typically yields at least one pore whose diameter is centrally crossed by a SWNT. The final diameter of the FIB pore is adjusted to create a nanopore of any desired diameter by atomic layer deposition, simultaneously embedding and insulating the SWNT everywhere but in the region that crosses the diameter of the final nanopore, where it remains pristine and bare. This nanotube-articulated nanopore is an important step towards the realization of a new type of detector for biomolecule sensing and electronic characterization, including DNA sequencing.Engineering and Applied SciencesMolecular and Cellular BiologyPhysic

Direct Patterning of Boron-doped Amorphous Carbon Using Focused Ion Beam-assisted Chemical Vapor Deposition

The deposition of boron-doped amorphous carbon thin films on SiO2 substrate was achieved via a focused ion beam-assisted chemical vapor deposition of triphenyl borane (C18H15B) and triphenyl borate (C18H15BO3). The existence of boron in the deposited film from triphenyl borane, with a precursor temperature of 90 {\deg}C, was confirmed by a core level X-ray photoelectron spectroscopy analysis. The film exhibited a semiconducting behavior with a band gap of 285 meV. Although the band gap was decreased to 197 meV after an annealing process, the film was still semiconductor. Additionally, a drastic reduction of the resistance on the deposited film by applying pressures was observed from an in-situ electrical transport measurements using a diamond anvil cell

Development of Bioinformatics Infrastructure for Genomics Research in H3Africa

Background: Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet’s role has evolved in response to changing needs from the consortium and the African bioinformatics community. Objectives: H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Methods and Results: Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. Conclusions: For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa

On the visual detection of non-natural records in streamflow time series: challenges and impacts

Large datasets of long-term streamflow measurements are widely used to infer and model hydrological processes. However, streamflow measurements may suffer from what users can consider anomalies, i.e. non-natural records that may be erroneous streamflow values or anthropogenic influences that can lead to misinterpretation of actual hydrological processes. Since identifying anomalies is time consuming for humans, no study has investigated their proportion, temporal distribution, and influence on hydrological indicators over large datasets. This study summarizes the results of a large visual inspection campaign of 674 streamflow time series in France made by 43 evaluators, who were asked to identify anomalies falling under five categories, namely, linear interpolation, drops, noise, point anomalies, and other. We examined the evaluators' individual behaviour in terms of severity and agreement with other evaluators, as well as the temporal distributions of the anomalies and their influence on commonly used hydrological indicators. We found that inter-evaluator agreement was surprisingly low, with an average of 12 % of overlapping periods reported as anomalies. These anomalies were mostly identified as linear interpolation and noise, and they were more frequently reported during the low-flow periods in summer. The impact of cleaning data from the identified anomaly values was higher on low-flow indicators than on high-flow indicators, with change rates lower than 5 % most of the time. We conclude that the identification of anomalies in streamflow time series is highly dependent on the aims and skills of each evaluator, which raises questions about the best practices to adopt for data cleaning.</p