22 research outputs found

    Reversible Non-Volatile Electronic Switching in a Near Room Temperature van der Waals Ferromagnet

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    The ability to reversibly toggle between two distinct states in a non-volatile method is important for information storage applications. Such devices have been realized for phase-change materials, which utilizes local heating methods to toggle between a crystalline and an amorphous state with distinct electrical properties. To expand such kind of switching between two topologically distinct phases requires non-volatile switching between two crystalline phases with distinct symmetries. Here we report the observation of reversible and non-volatile switching between two stable and closely-related crystal structures with remarkably distinct electronic structures in the near room temperature van der Waals ferromagnet Fe5−δ_{5-\delta}GeTe2_2. From a combination of characterization techniques we show that the switching is enabled by the ordering and disordering of an Fe site vacancy that results in distinct crystalline symmetries of the two phases that can be controlled by a thermal annealing and quenching method. Furthermore, from symmetry analysis as well as first principle calculations, we provide understanding of the key distinction in the observed electronic structures of the two phases: topological nodal lines compatible with the preserved global inversion symmetry in the site-disordered phase, and flat bands resulting from quantum destructive interference on a bipartite crystaline lattice formed by the presence of the site order as well as the lifting of the topological degeneracy due to the broken inversion symmetry in the site-ordered phase. Our work not only reveals a rich variety of quantum phases emergent in the metallic van der Waals ferromagnets due to the presence of site ordering, but also demonstrates the potential of these highly tunable two-dimensional magnets for memory and spintronics applications

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    The association between Personality Traits and General Anxiety Disorder

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    Effect of Steel Slag on Hydration Kinetics and Rheological Properties of Alkali-Activated Slag Materials: A Comparative Study with Fly Ash

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    The effects of steel slag (SS) and fly ash (FA) on hydration heat, fluidity, setting time and rheological properties of alkali-activated slag (AAS) pastes with different silicate modulus (Ms) values were comparatively investigated. The results show that the incorporation of SS shortens the induction period, increases the cumulative hydration heat, improves the initial fluidity and decreases the setting time at low Ms, but the opposite trend is found at high Ms. FA significantly retards the reaction, reduces the hydration heat, increases the fluidity and prolongs the setting time. The addition of SS or FA reduces the yield stress and plastic viscosity of AAS paste. SS improves the rheological properties of AAS paste more significantly than that of FA at high Ms. The yield stress and plastic viscosity of AAS paste with SS or FA rise with the increasing Ms and decline with the increasing water/binder (w/b) ratio

    Effect of Steel Slag on the Properties of Alkali-Activated Slag Material: A Comparative Study with Fly Ash

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    Slag and fly ash (FA) are mostly used as precursors for the production of alkali-activated materials (AAMs). FA is the waste discharged by power plants, while slag and steel slag (SS) both belong to the iron and steel industry. The effects of SS and FA on the strength, microstructure, and volume stability of alkali-activated slag (AAS) materials with different water glass modulus (Ms) values were comparatively investigated. The results show that adding SS or FA decreases the compressive strength of AAS mortar, and the reduction effect of SS is more obvious at high Ms. SS or FA reduce the non-evaporable water content (Wn) of AAS paste. However, SS increases the long-term Wn of AAS paste at low Ms. The cumulative pore volume and porosity increase after adding SS or FA, especially after adding FA. The hydration products are mainly reticular C-(A)-S-H gels. Adding SS increases the Ca/Si ratio of C-(A)-S-H gel but decreases the Al/Si ratio. However, by mixing FA, the Ca/Si ratio is reduced and the Al/Si ratio is almost unchanged. The incorporation of SS or FA reduces the drying shrinkage of AAS mortar, especially when SS is added. Increasing Ms increases the compressive strength and improves the pore structure, and it significantly increases the drying shrinkage of all samples. This study provides theoretical guidance for the application of steel slag in the alkali-activated slag material

    A particle swarm optimization algorithm based on diversity-driven fusion of opposing phase selection strategies

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    Abstract Opposition-based learning (OBL) is often embedded in intelligent optimization algorithms to solve practical engineering and mathematical problems, but the combinatorial problems among different OBL variants are rarely studied. To this end, we propose a novel OBL variant based on the principle of optical imaging, which combines two novel types of quasi-opposite learning and extended opposite learning, called diversity-driven fused opposition learning (SQOBL). First, a density center based on a neighborhood model is proposed. Based on the rapid convergence of the centroid, combined the advantages of density and centroid to construct a double mean center (DMC) to replace the original center point in quasi-opposite learning based on the principle of refraction. Secondly, an extended opposite learning method based on optical refraction imaging is proposed. Diversity is then exploited to drive different opposing learning strategies at different stages of evolution, thus controlling the exploration and utilization of the algorithm. Finally, SQOBL was embedded in the PSO with eight others representative OBL variants to find the most optimal solution for a test suite. In addition, 8 novel intelligent optimization algorithms and the first three algorithms were selected to evaluate the performance of the latest CEC2022 benchmark test set and realistic constrained optimization problems. Experiments with 56 test functions and 3 real-world constraint optimization problems show that the proposed SQOBL has good integrative properties in CEC2015, CEC2017, CEC2020, and CEC2022 test suites
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