Helium diffusion, clustering and bubble nucleation and growth is modelled using the finite element method. The existing model from Faney et al. (Model Simul Mater Sci Eng 22:065010, 2018; Nucl Fusion ...55:013014, 2015) is implemented with FEniCS and simplified in order to greatly reduce the number of equations. A parametric study is performed to investigate the influence of exposure conditions on helium inventory, bubbles density and size. Temperature is varied from 120 K to 1200 K and the implanted flux of 100 eV He is varied from Formula: see text to Formula: see text. Bubble mean size increases as a power law of time whereas the bubble density reaches a maximum. The maximum He content in bubbles was approximately Formula: see text He at Formula: see text. After 1 h of exposure, the helium inventory varies from Formula: see text at low flux and high temperature to Formula: see text at high flux and low temperature. The bubbles inventory varies from Formula: see text bubbles mFormula: see text to Formula: see text bubbles mFormula: see text. Comparison with experimental measurements is performed. The bubble density simulated by the model is in quantitative agreement with experiments.
A new temperature controlled material probe was designed for the exposure of tungsten samples to helium plasma in the LHD. Samples were exposed to estimated fluences of ∼1023 m−2 and temperatures ...ranging from 65 to 600 °C. Transmission Electron Microscopy analysis allowed the study of the impact of He irradiation under high temperatures on tungsten micro structure for the first time in real-plasma exposure conditions. Both dislocation loops and bubbles appeared from low to medium temperatures and saw an impressive increase of size (factor 4 to 6) most probably by coalescence as the temperature reaches 600 °C, with 500 °C appearing as a threshold for bubble growth. Annealing of the samples up to 800 C highlighted the stability of the dislocation damages formed by helium irradiation at high surface temperature, as bubbles and dislocation loops seem to conserve their characteristics. Additional studies on cross-sections showed that bubbles were formed much deeper (70–100 nm) than the heavily damaged surface layer (10–20 nm), raising concern about the impact on the material mechanical properties conservation and potential additional trapping of hydrogen isotopes.
•Design and test of a temperature-controlled sample holder to expose samples in LHD.•Dislocation loops and bubbles created in W even at low fluences and temperatures.•Heavily damaged layer (10–20 nm thick) very rich in damages formed at the surface.•He bubbles observed much deeper than implantation range (until 100 nm).•He effects not only at the surface, raising concerns for properties conservation.
While being the main potential beneficiaries of therapeutic fasting's health benefits, the elderly are frequently thought of as being too fragile to fast. The main objective of our survey was to ...review the knowledge, practices, and acceptability of therapeutic fasting in subjects aged 65 years and over. From September 2020 to March 2021, an online questionnaire was sent to subjects aged 65 and over, using the mailing list of local organizations working in the field of aging. The mean age of the 290 respondents was 73.8 ± 6.5 years, 75.2% were women and 54.1% had higher education. Among the respondents, 51.7% had already fasted and 80.7% deemed therapeutic fasting interesting, 83.1% would be willing to fast if it was proven beneficial for their health, and 77.2% if it was proven to decrease the burden of chronic diseases. Subjects aged 65 to 74 years considered themselves as having the greatest physical and motivational abilities to perform therapeutic fasting. People aged 65 years, or more, are interested in therapeutic fasting and a large majority would be ready to fast if such practice was proven beneficial. These results pave the way for future clinical trials evaluating therapeutic fasting in elderly subjects.
Abstract Fusion energy is a promising, safe, and reliable green energy solution to the increasing energy demand. However, there are several materials challenges that need to be overcome to increase ...the technical readiness to a level that enables a fusion pilot plant on the grid. This focus issue aims to identify and address a set of such key impediments for realizing deuterium-tritium (D–T) fusion power in a tokamak reactor and highlight the most recent progress on those research frontiers. The main emphasis of this collection is on materials development challenges resulting from helium irradiation, neutron-induced degradation, thermomechanical loading, and the corrosive environment faced by the divertor and first-wall materials, commonly known as plasma-facing components, and blanket systems for tokamak fusion reactors.
Impact of the helium plasma exposure on the surface modification in tungsten and reduced activation ferritic/martensitic (RAFM) steel have been investigated on the linear plasma device PSI-2 assuming ...the condition of DEMO first wall. In tungsten, a nanoscale undulating surface structure, which has a periodic arrangement, is formed under low temperature conditions below fuzz nanostructure formation threshold ∼1000 K. Interval and direction of the undulation shows dependence on the crystal orientation. A large variation in surface level up to 200 nm has been observed among grains at a fluence of 3 × 10 26 He m−2 showing dependence of the surface erosion rate on the crystal orientation. The {100} plane in which the undulating surface structure is not formed shows the highest erosion rate. This significant erosion is due to the multistage sputtering through impurity. In RAFM steel, sponge-like nanostructure is developed and it grows with increasing helium fluence beyond 1 m. In the sponge-like nanostructure, a composition change from the base material is observed in which the tungsten ratio increases while the iron ratio decreases showing differences in sputtering ratio depending on the atomic mass.
The International Thermonuclear Experimental Reactor (ITER) is an international project aimed at the production of carbon-free energy through the use of thermonuclear fusion. During ITER operation, ...in case of a loss-of-vacuum-accident, tungsten nanoparticles (W-NPs) could potentially be released into the environment and induce occupational exposure via inhalation. W-NPs toxicity was evaluated on MucilAir™, a 3D in vitro cell model of the human airway epithelium. MucilAir™ was exposed for 24 h to metallic ITER-like milled W-NPs, tungstate (WO42−) and tungsten carbide cobalt particles alloy (WC-Co). Cytotoxicity and its reversibility were assessed using a kinetic mode up to 28 days after exposure. Epithelial tightness, metabolic activity and interleukin-8 release were also evaluated. Electron microscopy was performed to determine any morphological modification, while mass spectrometry allowed the quantification of W-NPs internalization and of W transfer through the MucilAir™. Our results underlined a decrease in barrier integrity, no effect on metabolic activity or cell viability and a transient increase in IL-8 secretion after exposure to ITER-like milled W-NPs. These effects were associated with W-transfer through the epithelium, but not with intracellular accumulation. We have shown that, under our experimental conditions, ITER-like milled W-NPs have a minor impact on the MucilAir™ in vitro model.
Fuel retention monitoring in tokamak walls requires the development of remote composition analysis methods such as laser-induced breakdown spectroscopy (LIBS). The present study investigates the ...feasibility of the LIBS method to analyse the composition and fuel retention in three samples from WEST divertor erosion marker tiles after the experimental campaign C3. The investigated samples originated from tile regions outside of strong erosion and deposition regions, where the variation of thin deposit layers is relatively small and facilitates cross-comparison between different analysis methods. The depth profiles of main constituents W, Mo and C were consistent with depth profiles determined by other composition analysis methods, such as glow-discharge optical emission spectroscopy (GDOES) and secondary ion mass spectrometry (SIMS). The average LIBS depth resolution determined from depth profiles was 100 nm/shot. The averaging of the spectra collected from multiple spots of a same sample allowed us to improve the signal-to-noise ratio, investigate the presence of fuel D and trace impurities such as O and B. In the investigated tile regions with negligible erosion and deposition, these impurities were clearly detectable during the first laser shot, while the signal decreased to noise level after a few subsequent laser shots at the same spot. LIBS investigation of samples originating from the deposition regions of tiles may further clarify LIBS’ ability to investigate trace impurities.
Osteoarticular infections are major disabling diseases that can occur after orthopedic implant surgery in patients. The management of these infections is very complex and painful, requiring surgical ...intervention in combination with long-term antibiotic treatment. Therefore, early and accurate diagnosis of the causal pathogens is essential before formulating chemotherapeutic regimens. Although culture-based microbiology remains the most common diagnosis of osteoarticular infections, its regular failure to identify the causative pathogen as well as its long-term modus operandi motivates the development of rapid, accurate, and sufficiently comprehensive bacterial species-specific diagnostics that must be easy to use by routine clinical laboratories. Based on these criteria, we reported on the feasibility of our DendrisCHIP® technology using DendrisCHIP®OA as an innovative molecular diagnostic method to diagnose pathogen bacteria implicated in osteoarticular infections. This technology is based on the principle of microarrays in which the hybridization signals between oligoprobes and complementary labeled DNA fragments from isolates queries a database of hybridization signatures corresponding to a list of pre-established bacteria implicated in osteoarticular infections by a decision algorithm based on machine learning methods. In this way, this technology combines the advantages of a PCR-based method and next-generation sequencing (NGS) while reducing the limitations and constraints of the two latter technologies. On the one hand, DendrisCHIP®OA is more comprehensive than multiplex PCR tests as it is able to detect many more germs on a single sample. On the other hand, this method is not affected by the large number of nonclinically relevant bacteria or false positives that characterize NGS, as our DendrisCHIP®OA has been designed to date to target only a subset of 20 bacteria potentially responsible for osteoarticular infections. DendrisCHIP®OA has been compared with microbial culture on more than 300 isolates and a 40% discrepancy between the two methods was found, which could be due in part but not solely to the absence or poor identification of germs detected by microbial culture. We also demonstrated the reliability of our technology in correctly identifying bacteria in isolates by showing a convergence (i.e., same bacteria identified) with NGS superior to 55% while this convergence was only 32% between NGS and microbial culture data. Finally, we showed that our technology can provide a diagnostic result in less than one day (technically, 5 h), which is comparatively faster and less labor intensive than microbial cultures and NGS.
Dermatophytosis is a superficial fungal infection with an ever-increasing number of patients. Culture-based mycology remains the most commonly used diagnosis, but it takes around four weeks to ...identify the causative agent. Therefore, routine clinical laboratories need rapid, high throughput, and accurate species-specific analytical methods for diagnosis and therapeutic management. Based on these requirements, we investigated the feasibility of DendrisCHIP® technology as an innovative molecular diagnostic method for the identification of a subset of 13 pathogens potentially responsible for dermatophytosis infections in clinical samples. This technology is based on DNA microarray, which potentially enables the detection and discrimination of several germs in a single sample. A major originality of DendrisCHIP® technology is the use of a decision algorithm for probability presence or absence of pathogens based on machine learning methods. In this study, the diagnosis of dermatophyte infection was carried out on more than 284 isolates by conventional microbial culture and DendrisCHIP®DP, which correspond to the DendrisCHIP® carrying oligoprobes of the targeted pathogens implicated in dermatophytosis. While convergence ranging from 75 to 86% depending on the sampling procedure was obtained with both methods, the DendrisCHIP®DP proved to identify more isolates with pathogens that escaped the culture method. These results were confirmed at 86% by a third method, which was either a specific RT-PCR or genome sequencing. In addition, diagnostic results with DendrisCHIP®DP can be obtained within a day. This faster and more accurate identification of fungal pathogens with DendrisCHIP®DP enables the clinician to quickly and successfully implement appropriate antifungal treatment to prevent the spread and elimination of dermatophyte infection. Taken together, these results demonstrate that this technology is a very promising method for routine diagnosis of dermatophytosis.
Clinical microbiology is experiencing the emergence of the syndromic approach of diagnosis. This paradigm shift will require innovative technologies to detect rapidly, and in a single sample, ...multiple pathogens associated with an infectious disease. Here, we report on a multiplex technology based on DNA-microarray that allows detecting and discriminating 11 bacteria implicated in respiratory tract infection. The process requires a PCR amplification of bacterial 16S rDNA, a 30 min hybridization step on species-specific oligoprobes covalently linked on dendrimers coated glass slides (DendriChips
) and a reading of the slides by a dedicated laser scanner. A diagnostic result is delivered in about 4 h as a predictive value of presence/absence of pathogens using a decision algorithm based on machine-learning method, which was constructed from hybridization profiles of known bacterial and clinical isolated samples and which can be regularly enriched with hybridization profiles from clinical samples. We demonstrated that our technology converged in more than 95% of cases with the microbiological culture for bacteria detection and identification.
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