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    Wyświetlanie 1-3 z 3
    Tytuł:
    On the imaginary part of coupling resonance points
    Autorzy:
    Azamov, Nurulla
    Daniels, Tom
    Powiązania:
    https://bibliotekanauki.pl/articles/255376.pdf
    Data publikacji:
    2019
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    scattering matrix
    scattering phase
    resonance point
    Breit-Wigner formula
    Opis:
    We prove for rank one perturbations that the imaginary part of a coupling resonance point is inversely proportional by a factor of —2 to the rate of change of the scattering phase, as a function of the coupling variable, evaluated at the real part of the resonance point. This equality is analogous to the Breit-Wigner formula from quantum scattering theory. For more general relatively trace class perturbations, we also give a formula for the spectral shift function in terms of coupling resonance points, non-real and real.
    Źródło:
    Opuscula Mathematica; 2019, 39, 5; 611-621
    1232-9274
    2300-6919
    Pojawia się w:
    Opuscula Mathematica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The heat equation on time scales
    Autorzy:
    Cuchta, Tom
    Ferreira, Rui A. C.
    Powiązania:
    https://bibliotekanauki.pl/articles/29519378.pdf
    Data publikacji:
    2023
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    heat equation
    time scales
    Fourier transform
    Opis:
    We present the use of a Fourier transform on time scales to solve a dynamic heat IVP. This is done by inverting a certain exponential function via contour integral. We include some specific examples and directions for further study.
    Źródło:
    Opuscula Mathematica; 2023, 43, 4; 475-491
    1232-9274
    2300-6919
    Pojawia się w:
    Opuscula Mathematica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The use of generative models to speed up the discovery of materials
    Autorzy:
    Coto, Andrea Gregores
    Precker, Christian Eike
    Andersson, Tom
    Laukkanen, Anssi
    Suhonen, Tomi
    Rodriguez, Pilar Rey
    Muíños-Landín, Santiago
    Powiązania:
    https://bibliotekanauki.pl/articles/29520053.pdf
    Data publikacji:
    2023
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    artificial intelligence
    materials science
    high-performance material
    generative model
    Opis:
    Material Science is a key factor in the evolution of many industrial sectors. Fields such as the aeronautics, automotive, construction, and biotechnology industries have experienced tremendous development with the introduction of advanced, high-performance materials. Such materials not only provide new functionalities to products, but also significant consequences in terms of economic and environmental sustainability of the products and processes triggered by the more efficient use of energy that they provide. Under this scenario, materials that provide such high performance, such as high entropy alloys (HEAs) or polymer derived ceramics (PDCs), have captured the attention of both industry and researchers in recent years. However, the remarkable number of resources required to develop such materials, from its design phase to its synthesis and characterization, means that the discovery of new high-performance materials is moving at a relatively low pace. This fact places emergent strategies based on artificial intelligence (AI) for the design of materials in a good position to be used to accelerate the whole process, providing an impulse in the initial phases of materials design. The enormous number of combinations of elements and the complexity of synthesizability conditions of HEAs and PDCs respectively, paves the way to the deployment of AI techniques such as Generative Models addressed in this work to create synthetic HEAs and PDCs for highly intensive industrial processes. A specific conditional tabular generative adversarial network (CTGAN) was developed to be used on tabular data to generate novel synthetic compounds for each kind of material. The generated synthetic data was based on the conventional parametric design parameters used for HEAs and PDCs, with specific datasets created for them. The real and generated data are compared, calculation of phase diagrams (CALPHAD) simulations are provided to evaluate the performance of the generated samples and a verification of the novel generated compositions is done in open materials databases available in the literature.
    Źródło:
    Computer Methods in Materials Science; 2023, 23, 1; 13-26
    2720-4081
    2720-3948
    Pojawia się w:
    Computer Methods in Materials Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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