Etude numérique du régime transitoire dans un modèle thermique d'évaporation

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Cross-architecture Kalman filter benchmarks on modern hardware platforms

The 2020 upgrade of the LHCb detector will vastly increase the rate of collisions the online system needs to process in software in order to filter events in real-time. 30 million collisions per second will pass through a selection chain where each step is executed conditional to its prior acceptance. The Kalman filter is a process of the event reconstruction that, due to its time characteristics and early execution in the selection chain, consumes 40% of the whole reconstruction time in the current trigger software. This makes it a time-critical component as the LHCb trigger evolves into a full software trigger in the upgrade. The algorithm Cross Kalman allows performance tests across a variety of architectures, including multi and many-core platforms, and has been successfully integrated and validated in the LHCb codebase. Since its inception, new hardware architectures have become available exposing features that require fine-grained tuning in order to fully utilize their resources. In this paper we present performance benchmarks and explore the Intel® Skylake and Intel® Knights Landing architectures in depth. We determine the performance gain over previous architectures and show that the efficiency of our implementation is close to the maximum attainable given the mathematical formulation of our problem

Etude numérique du régime transitoire dans un modèle thermique d'évaporation

International audienc

Imprinting isolated single iron atoms onto mesoporous silica by templating with metallosurfactants

International audienceHypothesisOne of the main drawbacks of metal-supported materials, traditionally prepared by the impregnation of metal salts onto pre-synthesized porous supports, is the formation of large and unevenly dispersed particles. Generally, the larger are the particles, the lower is the number of catalytic sites. Maximum atom exposure can be reached within single-atom materials, which appear therefore as the next generation of porous catalysts.ExperimentsHerein, we designed single iron atom-supported silica materials through sol-gel hydrothermal treatment using mixtures of a non-ionic surfactant (Pluronic P123) and a metallosurfactant (cetyltrimethylammoniumtrichloromonobromoferrate, CTAF) as porogens. The ratio between the Pluronic P123 and the CTAF enables to control the silica structural and textural properties. More importantly, CTAF acts as an iron source, which amount could be simply tuned by varying the non-ionic/metallo surfactants molar ratio.FindingsThe fine distribution of iron atoms onto the silica mesopores results from the iron distribution within the mixed micelles, which serve as templates for the polymerization of the silica matrix. Several characterization methods were used to determine the structural and textural properties of the silica material (XRD, N2 sorption isotherms and TEM) and the homogeneous distribution and lack of clustering of iron atoms in the resulting materials (elemental analysis, magnetic measurements, pair distribution function (PDF), MAS-NMR and TEM mapping). The oxidation and spin state of single-iron atoms determined from their magnetic properties were confirmed by DFT calculations. This strategy might find straightforward applications in preparing versatile single atom catalysts, with improved efficiency compared to nanosized ones