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<!DOCTYPE html>
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<title>Project a05</title>
<meta charset="utf-8"/>
<meta name="robots" content="noindex">
<link href="app_1.1.2.css" rel="stylesheet"/>
<link href="theme-3c.css" rel="stylesheet"/>
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<body>
<div id="site">
<h1>2026</h1><!--Kuhn_2026aa-->
<p style="margin-bottom: 0.2em"><strong>Kühn, Patrick ; Yang, Yangyiwei ; Chen, Guanyu ; Foster, Shanelle N. ; <a class="link" href="https://www.jku.at" target="_top">Egger, Herbert</a> ; <a class="link" href="https://www.tu-darmstadt.de" target="_top">Xu, Bai-Xiang</a></strong>
(2026):
<em>Microstructural influence on hysteresis and eddy-current losses of additively manufactured electrical steel: A multiphysical approach.</em>
In: Computational Materials Science, pp. 114408, ISSN: 0927-0256, DOI: <a class="link" href="https://doi.org/10.1016/j.commatsci.2025.114408" target="_top">10.1016/j.commatsci.2025.114408</a>, ARXIV: <a class="link" href="https://arxiv.org/abs/2502.01559" target="_top">2502.01559</a>.
[Article]</p>
<h1>2024</h1><!--Peng_2024aa-->
<p style="margin-bottom: 0.2em"><strong>Peng, Xiang-Long ; Fathidoost, Mozhdeh ; Lin, Binbin ; Yang, Yangyiwei ; <a class="link" href="https://www.tu-darmstadt.de" target="_top">Xu, Bai-Xiang</a></strong>
(2024):
<em>What Can Machine Learning Help with Microstructure-Informed Materials Modeling and Design?</em>
In: <span class="bibtex-protected">MRS</span> Bulletin, ISSN: 0883-7694, DOI: <a class="link" href="https://doi.org/10.1557/s43577-024-00797-4" target="_top">10.1557/s43577-024-00797-4</a>.
[Article]</p>
<!--Yang_2024aa-->
<p style="margin-bottom: 0.2em"><strong>Yang, Yangyiwei ; Kühn, Patrick ; Fathidoost, Mozhdeh ; Adabifiroozjaei, Esmaeil ; Xie, Ruiwen ; Foya, Eren ; Ohmer, Dominik ; Skokov, Konstantin ; Molina-Luna, Leopoldo ; Gutfleisch, Oliver ; Zhang, Hongbin ; <a class="link" href="https://www.tu-darmstadt.de" target="_top">Xu, Bai-Xiang</a></strong>
(2024):
<em>Coercivity influence of nanostructure in <span class="bibtex-protected">SmCo</span>-1:7 magnets: <span class="bibtex-protected">Machine</span> learning of high-throughput micromagnetic data.</em>
Cornell University, ARXIV: <a class="link" href="https://arxiv.org/abs/2408.03198" target="_top">2408.03198</a>.
[Preprint].</p>
<h1>2023</h1><!--Yang_2023aa-->
<p style="margin-bottom: 0.2em"><strong>Yang, Yangyiwei ; Kühn, Patrick ; Fathidoost, Mozhdeh ; <a class="link" href="https://www.tu-darmstadt.de" target="_top">Xu, Bai-Xiang</a></strong>
(2023):
<em>Micromagnetics and Multiscale Hysteresis Simulations of Permanent Magnets.</em>
In: <span class="bibtex-protected">COMPEL</span>: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 42(5), pp. 993–1006, ISSN: 0332-1649, DOI: <a class="link" href="https://doi.org/10.1108/COMPEL-12-2022-0424" target="_top">10.1108/COMPEL-12-2022-0424</a>.
[Article]</p>
<!--Yang_2023ab-->
<p style="margin-bottom: 0.2em"><strong>Yang, Yangyiwei ; Oyedeji, Timileyin David ; Zhou, Xiandong ; Albe, Karsten ; <a class="link" href="https://www.tu-darmstadt.de" target="_top">Xu, Bai-Xiang</a></strong>
(2023):
<em>Tailoring magnetic hysteresis of additive manufactured <span class="bibtex-protected">Fe</span>-<span class="bibtex-protected">Ni</span> permalloy via multiphysics-multiscale simulations of process-property relationships.</em>
In: npj Computational Materials 9(1), pp. 103, ISSN: 2057-3960, DOI: <a class="link" href="https://doi.org/10.1038/s41524-023-01058-9" target="_top">10.1038/s41524-023-01058-9</a>.
[Article]</p>
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