A novel experimental method for the measurement of the caloric curves of clusters

A novel experimental scheme has been developed in order to measure the heat capacity of mass selected clusters. It is based on controlled sticking of atoms on clusters. This allows one to construct the caloric curve, thus determining the melting temperature and the latent heat of fusion in the case of first-order phase transitions. This method is model-free. It is transferable to many systems since the energy is brought to clusters through sticking collisions. As an example, it has been applied to Na\_90\^+ and Na\_140\^+. Our results are in good agreement with previous measurements

Two-step melting of Na41+

The heat capacity of the mass selected Na41+ cluster has been measured using a differential nanocalorimetry method. A two-peak structure appears in the heat capacity curve of Na41+, whereas Schmidt and co-workers [ M. Schmidt, J. Donges, Th. Hippler, and H. Haberland, Phys. Rev. Lett. 90, 103401 (2003) ] observed, within their experimental accuracy, a smooth caloric curve. They concluded from the absence of any structure that there is a second order melting transition in Na41+ with no particular feature such as premelting. The observed difference with the latter results is attributed to the better accuracy of our method owing to its differential character. The two structures in the heat capacity are ascribed to melting and premelting of Na41+. The peak at lower temperature is likely due to an anti-Mackay to Mackay solid-solid transition

Critical role of surface chemical modifications induced by length shortening on multi-walled carbon nanotubes-induced toxicity.

International audienceABSTRACT: Given the increasing use of carbon nanotubes (CNT) in composite materials and their possible expansion to new areas such as nanomedicine which will both lead to higher human exposure, a better understanding of their potential to cause adverse effects on human health is needed. Like other nanomaterials, the biological reactivity and toxicity of CNT were shown to depend on various physicochemical characteristics, and length has been suggested to play a critical role.We therefore designed a comprehensive study that aimed at comparing the effects on murine macrophages of two samples of multi-walled CNT (MWCNT) specifically synthesized following a similar production process (aerosol-assisted CVD), and used a soft ultrasonic treatment in water to modify the length of one of them.We showed that modification of the length of MWCNT leads, unavoidably, to accompanying structural (i.e. defects) and chemical (i.e. oxidation) modifications that affect both surface and residual catalyst iron nanoparticle content of CNT. The biological response of murine macrophages to the two different MWCNT samples was evaluated in terms of cell viability, pro-inflammatory cytokines secretion and oxidative stress. We showed that structural defects and oxidation both induced by the length reduction process are at least as responsible as the length reduction itself for the enhanced pro-inflammatory and pro-oxidative response observed with short (oxidized) compared to long (pristine) MWCNT.In conclusion, our results stress that surface properties should be considered, alongside the length, as essential parameters in CNT-induced inflammation, especially when dealing with a safe design of CNT, for application in nanomedicine for example

Structure in Nascent Carbon Nanotubes Revealed by Spatially Resolved Raman Spectroscopy

The understanding of carbon nanotubes (CNT) growth is crucial for the control of their production. In particular, the identification of structural changes of carbon possibly occurring near the catalyst particle in the very early stages of their formation is of high interest. In this study, samples of nascent CNT obtained during nucleation step and samples of vertically aligned CNT obtained during growth step are analysed by combined spatially resolved Raman spectroscopy and X-Ray diffraction measurements. Spatially resolved Raman spectroscopy reveals that iron-based phases and carbon phases are co-localised at the same position, and indicates that sp2 carbon nucleates preferentially on iron-based particles during this nucleation step. Depth scan Raman spectroscopy analysis, performed on nascent CNT, highlights that carbon structural organisation is significantly changing from defective graphene layers surrounding the iron-based particles at their base up to multi-walled nanotube structures in the upper part of iron-based particles

Synchrotron X-ray diffraction experiments with a prototype hybrid pixel detector

International audienceA prototype X-ray pixel area detector (XPAD3.1) has been used for X-ray diffraction experiments with synchrotron radiation. The characteristics of this detector are very attractive in terms of fast readout time, high dynamic range and high signal-to-noise ratio. The prototype XPAD3.1 enabled various diffraction experiments to be performed at different energies, sample-to-detector distances and detector angles with respect to the direct beam, yet it was necessary to perform corrections on the diffraction images according to the type of experiment. This paper is focused on calibration and correction procedures to obtain high-quality scientific results specifically developed in the context of three different experiments, namely mechanical characterization of nanostructured multilayers, elastic-plastic deformation of duplex steel and growth of carbon nanotubes

A comparative study on the enzymatic biodegradability of covalently functionalized double- and multi-walled carbon nanotubes

The assessment of the biodegradability potential of carbon nanotubes (CNTs) is a fundamental point towards their applications in materials science and biomedicine. Due to the continuous concerns about the fate of such type of nanomaterials, it is very important to understand if they can undergo degradation under certain conditions and if the morphology and structure of the nanotubes play a role in this process. For this purpose we have decided to undertake a comparative study on the enzymatic degradation of CNTs with concentric multilayers. Double-walled (DW) and multi-walled (MW) CNTs of various lengths, degrees of oxidation and functionalizations using different methods were treated with horseradish peroxidase (HRP). While all tested DWCNTs resulted resistant to the biodegradation, some of the MWCNTs were partially degraded by the enzyme. We have found that short oxidized multi-walled CNTs functionalized by amidation were reduced in length and presented a high amount of defects at the end of the period of treatment with HRP. This comparative study holds its importance in the understanding of the structural changes of different types of nanotubes towards the catalytic enzymatic degradation and will help to design safer CNTs for future applications

Archives d’auteurs contemporains et Humanités numériques : le cas des archives de Jean Duvignaud

Les archives d’auteurs contemporains (2ème ½ XXe - XXIe siècle) restent un domaine contraint et peu exploité, essentiellement pour des questions de droit. Pourtant, ces archives récentes sont une mémoire vive, et les sources directes constituées par leurs dépositaires peuvent être enrichies, expliquées, augmentées par des témoignages oraux. Ces fonds sont souvent denses, variés (en nature et supports de documents), riches en informations. Ils permettent un éclairage direct sur les questions qui entourent la biographie des auteurs, la génétique de leur œuvre et leurs processus créatifs, leur environnement social et de travail. Les humanités numériques peuvent permettre à travers le développement et l’usage d’outils d’exploitation et de médiation numérique, de faire redécouvrir l’œuvre de ces auteurs, et d’ouvrir leurs archives aux chercheurs et au grand public. C’est dans cette perspective que se place le projet de valorisation numérique de l’œuvre de l’auteur, sociologue et homme de théâtre Jean Duvignaud

TRH: Pathophysiologic and clinical implications

Thyrotropin releasing hormone is thought to be a tonic stimulator of the pituitary TSH secretion regulating the setpoint of the thyrotrophs to the suppressive effect of thyroid hormones. The peptide stimulates the release of normal and elevated prolactin. ACTH and GH may increase in response to exogenous TRH in pituitary ACTH and GH hypersecretion syndromes and in some extrapituitary diseases. The pathophysiological implications of extrahypothalamic TRH in humans are essentially unknown. The TSH response to TRH is nowadays widely used as a diganostic amplifier in thyroid diseases being suppressed in borderline and overt hyperthyroid states and increased in primary thyroid failure. In hypothyroid states of hypothalamic origin, TSH increases in response to exogenous TRH often with a delayed and/or exaggerated time course. But in patients with pituitary tumors and suprasellar extension TSH may also respond to TRH despite secondary hypothyroidism. This TSH increase may indicate a suprasellar cause for the secondary hypothyroidism, probably due to portal vessel occlusion. The TSH released in these cases is shown to be biologically inactive

Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning

We consider quantitative analyses of spectral data using laser-induced breakdown spectroscopy. We address the small size of training data available, and the validation of the predictions during inference on unknown data. For the purpose, we build robust calibration models using deep convolutional multitask learning architectures to predict the concentration of the analyte, alongside additional spectral information as auxiliary outputs. These secondary predictions can be used to validate the trustworthiness of the model by taking advantage of the mutual dependencies of the parameters of the multitask neural networks. Due to the experimental lack of training samples, we introduce a simulation-based data augmentation process to synthesise an arbitrary number of spectra, statistically representative of the experimental data. Given the nature of the deep learning model, no dimensionality reduction or data selection processes are required. The procedure is an end-to-end pipeline including the process of synthetic data augmentation, the construction of a suitable robust, homoscedastic, deep learning model, and the validation of its predictions. In the article, we compare the performance of the multitask model with traditional univariate and multivariate analyses, to highlight the separate contributions of each element introduced in the process.Comment: 35 pages, appendix with supplementary materia