Enhanced Hardness-Toughness Balance Induced by Adaptive Adjustment of the Matrix Microstructure in In Situ Composites

With the development of high-speed and heavy-haul railway transportation, the surface failure of rail turnouts has become increasingly severe due to insufficient high hardness-toughness combination. In this work, in situ bainite steel matrix composites with WC primary reinforcement were fabricated via direct laser deposition (DLD). With the increased primary reinforcement content, the adaptive adjustments of the matrix microstructure and in situ reinforcement were obtained at the same time. Furthermore, the dependence of the adaptive adjustment of the composite microstructure on the composites’ balance of hardness and impact toughness was evaluated. During DLD, the laser induces an interaction among the primary composite powders, which leads to obvious changes in the phase composition and morphology of the composites. With the increased WC primary reinforcement content, the dominant sheaves of the lath-like bainite and the few island-like retained austenite are changed into needle-like lower bainite and plenty of block-like retained austenite in the matrix, and the final reinforcement of Fe3W3C and WC is obtained. In addition, with the increased primary reinforcement content, the microhardness of the bainite steel matrix composites increases remarkably, but the impact toughness decreases. However, compared with conventional metal matrix composites, the in situ bainite steel matrix composites manufactured via DLD possess a much better hardness-toughness balance, which can be attributed to the adaptive adjustment of the matrix microstructure. This work provides a new insight into obtaining new materials with a good combination of hardness and toughness

Ultra-broadband metamaterial absorber in long wavelength Infrared band based on resonant cavity modes

International audienc

Dual functionality metamaterial enables ultra-compact, highly sensitive uncooled infrared sensor

Cointegration and coupling a perfect metamaterial absorber (PMA) together with a film bulk acoustic wave resonator (FBAR) in a monolithic fashion is introduced for the purpose of producing ultracompact uncooled infrared sensors of high sensitivity. An optimized ultrathin multilayer stack was implemented to realize the proposed device. It is experimentally demonstrated that the resonance frequency of the FBAR can be used efficiently as a sensor output as it downshifts linearly with the intensity of the incident infrared irradiation. The resulting sensor also achieves a high absorption of 88% for an infrared spectrum centered at a wavelength of 8.2 μm. The structure is compact and can be easily integrated on a CMOS-compatible chip since both the FBAR and PMA utilize and share the same stack of metal and dielectric layers

Dual functionality metamaterial enables ultra-compact, highly sensitive uncooled infrared sensor

International audienceCointegration and coupling a perfect metamaterial absorber (PMA) together with a film bulk acoustic wave resonator (FBAR) in a monolithic fashion is introduced for the purpose of producing ultracompact uncooled infrared sensors of high sensitivity. An optimized ultrathin multilayer stack was implemented to realize the proposed device. It is experimentally demonstrated that the resonance frequency of the FBAR can be used efficiently as a sensor output as it downshifts linearly with the intensity of the incident infrared irradiation. The resulting sensor also achieves a high absorption of 88% for an infrared spectrum centered at a wavelength of 8.2 μm. The structure is compact and can be easily integrated on a CMOS-compatible chip since both the FBAR and PMA utilize and share the same stack of metal and dielectric layers

The Seventh Visual Object Tracking VOT2019 Challenge Results

The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).Funding Agencies|Slovenian research agencySlovenian Research Agency - Slovenia [J2-8175, P2-0214, P2-0094]; Czech Science Foundation Project GACR [P103/12/G084]; MURI project - MoD/DstlMURI; EPSRCEngineering &amp; Physical Sciences Research Council (EPSRC) [EP/N019415/1]; WASP; VR (ELLIIT, LAST, and NCNN); SSF (SymbiCloud); AIT Strategic Research Programme; Faculty of Computer Science, University of Ljubljana, Slovenia</p