Publications by authors named "Kaiyan Cao"

Tactile-based sensing technology represents one of the most promising methods for interacting with their surrounding environment. Consequently, flexible tactile sensing has garnered significant attention from researchers worldwide. In this study, triboelectricity and piezoelectricity were combined to propose a multifunctional self-powered tactile sensor (MSPTS).

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The structure of a material is an important factor in determining its physical properties. Here, we adjust the structure of the NiMnGa spun ribbons by changing the wheel speed to regulate the exchange bias effect of the material. The characterization results of micromorphology and structure show that as the wheel speed increases, the martensite lath decreases from 200 nm to 50 nm, the structure changed from the NM to a NM and 10M mixed martensitic structure containing mainly NM, then changed to NM and 10M where 10M and NM are approaching.

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The discovery and identification of gene families by using wide-genome and public databases is an effective way to gain initial insight into gene function, which also is one of the current hot spots of research. Chlorophyll ab-binding proteins (LHC) are important for photosynthesis and widely involved in plant adversity stress. However, the study in wheat has not been reported.

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A giant exchange bias (EB) of 9600 Oe was observed in polycrystalline Fe3O4/CoO layers at 10 K after 20 kOe field cooling, and was attributed to the strong exchange coupling formed by the interfacial spins between the polycrystalline Fe3O4 and the CoO layer. It was found that at 10 K, the magnetic-moment difference (ΔM) between the zero field cooling curves and field cooling curves first increases and then decreases with the change of the field, and it reaches the maximum value at a field of 20 kOe, which suggests that the interfacial spins can be tuned by the cooling field. Furthermore, other magnetic properties, including field dependence, temperature dependence, and training effects, were investigated, which further confirmed that the interfacial spins play an important role in the EB effect.

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Hamiltonian parameters estimation is crucial in condensed matter physics, but is time- and cost-consuming. High-resolution images provide detailed information of underlying physics, but extracting Hamiltonian parameters from them is difficult due to the huge Hilbert space. Here, a protocol for Hamiltonian parameters estimation from images based on a machine learning (ML) architecture is provided.

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With the development of magnetic refrigerant technology, magnetic substances with a large magnetocaloric effect (MCE) and nearly zero thermal hysteresis are desired. Although Ni-Mn based Heusler alloys have been found to produce large MCEs and have attracted increasing attention recently, the occurrence of thermal hysteresis accompanying MCE due to the nature of first-order phase transition limits its applications with magnetic refrigeration. Up to now, an effective theory or method to eliminate this thermal hysteresis is still lacking.

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We report the magnetocaloric effect in a Tb Dy Co compound which exhibits a wide working temperature window around the Curie temperature (T ) and delivers a large refrigerant capacity (RC) with near-zero thermal hysteresis. Specifically, the wide full width at half maxima ([Formula: see text]) can reach up to 62 K and the RC value changes from 216.5 to 274.

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