Tribo-Mechanical and Electrical Properties of Boron-Containing Coatings

Le développement de nouveaux revêtements protecteurs durs ayant une performance de pointe est très important pour le progrès scientifique relié à de plusieurs domaines industriels. L’application de revêtements protecteurs durs peut augmenter significativement la performance de pièces et composantes, étendre leur durée de vie ainsi que sauver de l’énergie dans maintes industries incluant l’aérospatial, l’automobile, les manufactures et bien d’autres. De plus, la multifonctionnalité des revêtements représente une valeur ajoutée dans d’autres domaines tels que l’optique, la microélectronique, le biomédical, le stockage magnétique de données, etc. Ainsi, les revêtements protecteurs avec des propriétés tribo-mécaniques améliorées et une résistance à la corrosion augmentée sont très en demande. Les caractéristiques des revêtements peuvent être ajustées en contrôlant leur microstructure sur une échelle répandue dans différents ordres de grandeur. Par exemple, les films avec des nanostructures, comme les super-réseaux, les nanocolonnes et les systèmes nanocomposites, montrent des caractéristiques très distinctes par rapport aux matériaux à une seule phase. Ils montrent des propriétés tribo-mécaniques supérieures grâce à la présence d’interfaces internes rigides et différentes fonctions peuvent être accomplies avec un matériau multi-phase. Les matériaux contenant du bore ont d’excellentes propriétés mécaniques et des caractéristiques électroniques très intéressantes, ce qui en fait de bons candidats pour les revêtements protecteurs fonctionnels durs. Par exemple, le nitrure de bore cubique (c-BN), le carbure de bore (B1−xCx) et le diborure de titane (TiB2) sont très connus pour leur grande dureté, leur haute stabilité thermique et leur caractère chimique inerte. Un exemple intéressant est le nitrure de carbure de bore (BCN) qui possède plusieurs propriétés attrayantes grâce à la similarité structurale avec le carbone (graphite et diamant) ainsi que le nitrure de bore (BN en phase hexagonal ou cubique). L’objectif principal de cette recherche est de développer plus en détail la famille de revêtements contenant du bore, incluant le B1−xCx, le Ti−B−C et le BCN déposés par pulvérisation magnétron, pour améliorer leur performance sur mesure et obtenir de nouvelles fonctions en contrôlant leur microstructure à l’échelle nanométrique.----------Abstract The development of new hard protective coatings with advanced performance is very important for progress in a variety of scientific and industrial fields. Application of hard protective coatings can significantly improve the performance of parts and components, extend their service life, and save energy in many industrial applications including aerospace, automotive, manufacturing, and other industries. In addition, the multifunctionality of protective coatings is also required in many other application fields such as optics, microelectronics, biomedical, magnetic storage media, etc. Therefore, protective coatings with enhanced tribo-mechanical and corrosion properties as well as other functions are in demand. The coating characteristics can be adjusted by controlling the microstructure at different scales. For example, films with nanostructures, such as superlattice, nanocolumn, and nanocomposite systems, exhibit distinctive characteristics compared to single-phase materials. They show superior tribo-mechanical properties due to the presence of strong interfaces, and different functions can be achieved due to the multi-phase characteristics. Boron-containing materials with their excellent mechanical properties and interesting electronic characteristics are good candidates for functional hard protective coatings. For instance, cubic boron nitride (c-BN), boron carbide (B1−xCx), and titanium diboride (TiB2) are well known for their high hardness, high thermal stability, and high chemical inertness. An interesting example is the boron carbon nitride (BCN) compound that possesses many attractive properties because its structure is similar to that of carbon (graphite and diamond) and of boron nitride (BN in hexagonal and cubic phases). The main goal of this work is to further develop the family of Boron-containing films including B1−xCx, Ti−B−C, and BCN films fabricated by magnetron sputtering, and to enhance their performance by controlling their microstructure on the nanoscale. Their tribo-mechanical, corrosion, and electrical properties are studied in relation to the composition and microstructure, aiming at enhancing their performance for multi-functional protective coating applications via microstructural design

Temporal and spatial resolutions of optical time stretch imaging with dispersive grating pair

Optical time stretch imaging (OTSI), providing the capability of capturing the dynamics of fast single-shot or random events, overcomes the fundamental trade-off between imaging speed and sensitivity in ultrafast imaging regions. Lying at the heart of the OTSI is dispersive Fourier transformation, being capable of using large chromatic dispersion to map the spectrum of a broadband ultrashort optical pulse into a stretched time-domain waveform. Dispersive grating pair (DGP) is a unique solution to generate large chromatic dispersion for dispersive Fourier transformation at the wavebands, in which dispersion compensation fibers commonly suffer from high dispersion-to-loss ratio. Here we characterize the performances of DGP-based OTSI modality and analyze the crucial parameters that strongly impact on the temporal as well as spatial resolutions, and further discuss its merits and challenges. Our results demonstrate DGP-based OTSI, allowing creation of high resolution images, is an effective modality compared to fiber-based OTSI

Curcumol Synergizes with Cisplatin in Osteosarcoma by Inhibiting M2-like Polarization of Tumor-Associated Macrophages

Osteosarcoma is the most prevalent bone cancer, and chemotherapy is still an indispensable treatment in its clinical practice. Cisplatin (CDDP) has become the most commonly used agent for osteosarcoma, although the outcomes of CDDP chemotherapy remain unsatisfactory because of frequent resistance. Here, we report on a promising combination therapy where curcumol, a bioactive sesquiterpenoid, enhanced CDDP-induced apoptosis to eradicate osteosarcoma cells, and revealed that M2-like macrophages might be the underlying associated mechanisms. First, we observed that curcumol enhanced the CDDP-mediated inhibition of cell proliferation and augmented the apoptosis in osteosarcoma cell lines. Curcumol contributed to preventing the migration of osteosarcoma cells when combined with CDDP. Moreover, this drug combination showed more potent tumor-growth suppression in the orthotopic transplantation of osteosarcoma K7M2 WT cells. We then estimated chemotherapy-associated drug-resistant genes, including ABCB1, ABCC1 and ABCG2, and found that curcumol significantly reversed the mRNA levels of CDDP-induced ABCB1, ABCC1 and ABCG2 genes in the tumor tissue. Moreover, M2-like macrophages were enriched in osteosarcoma tissues, and were largely decreased after curcumol and CDDP treatment. Taken together, these findings suggest that curcumol inhibits the polarization of M2-like macrophages and could be a promising combination strategy to synergize with CDDP in the osteosarcoma

News Recommendation With Word-Related Joint Topic Prediction

As the problem of information overload becomes more severe, it has become increasingly difficult for users to browse news that they are interested in. News recommendation is an effective method to alleviate this problem. In news recommendation, accurately obtaining rich semantic news representations and modeling user’s historical interests are long-standing challenges. Based on these two issues, we propose a News recommendation approach with Word-related joint Topic prediction(NWT). The core of our approach is the topic perceptron and the news encoder that emphasizes word relevance. The topic information and word relevance information are fused through joint training, enhancing the abilities of topic prediction and news representation. In the news encoder, we employ multi-head self-attention network to emphasize word relevance, capturing the semantic relationships between any two words in the news title and enhancing the representation of the news. In the topic perceptron, we use the enhanced word relevance-based news representation as input and learn the topic information in the news by assigning weights to different topics. During joint training, the overall news recommendation module obtains the news topic information. Additionally, the user encoder learns the user’s topic preferences and utilizes attention networks to highlight news articles that are more representative of the user’s interests, thereby acquiring a more accurate user representation. We conduct extensive experiments on the MIND dataset, and the results demonstrate that NWT outperforms most existing baseline methods across various evaluation metrics