THERMOELECTRIC CONVERSION ELEMENT
    3.
    发明申请

    公开(公告)号:US20200313062A1

    公开(公告)日:2020-10-01

    申请号:US16651914

    申请日:2018-08-13

    Abstract: A thermoelectric conversion element 10 includes an anomalous Nernst material 11 having the anomalous Nernst effect, in which: the anomalous Nernst material 11 includes at least an element having the inverse spin-Hall effect; and the element is spin-polarized. By applying, for example, a magnetic field to such the thermoelectric conversion element 10 in the x direction and a temperature gradient thereto in the z direction, thermoelectromotive force can be taken out from terminals 12.

    PORTABLE POWER SUPPLY
    4.
    发明申请

    公开(公告)号:US20220037576A1

    公开(公告)日:2022-02-03

    申请号:US17296392

    申请日:2019-11-14

    Abstract: A portable power supply according to the present invention is provided with a combustion device (20) and a heating container (30) that retains an object to be heated, wherein at least a part of a portion of the heating container, the portion being directly heated by the combustion device, is provided with a magnetic metal plate (32) that has spontaneous magnetization and that generates electromotive force due to an anomalous Nernst effect induced by the heating, and wherein electrodes (33a, 33b) for drawing power are provided. Thus, the heating container for generating electricity has a simple configuration, and furthermore the portable power supply is provided with both the heating container and the combustion device.

    RELATION SEARCH SYSTEM, INFORMATION PROCESSING DEVICE, METHOD, AND PROGRAM

    公开(公告)号:US20200034367A1

    公开(公告)日:2020-01-30

    申请号:US16493862

    申请日:2018-03-06

    Abstract: A relation search system includes: a storage means (1) which stores a data set which includes a first-type data group and a second-type data group which are two types of data group that are acquired by different methods; a data adaptation means (2) which either corrects or reconstructs either first data which belongs to the first-type data group or second data which belongs to the second-type data group and which is associated with the first data, such that a divergence which arises between the first data and the second data because of the difference in the methods for the acquisition thereof is reduced; and a learning means (3) which, using the data set which includes the corrected or reconstructed data, carries out machine learning.

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