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研究生: 林家君
Lin, Chia-Chun
論文名稱: 人工智能優化第一原理計算之尖晶石結構高熵氧化物於能源轉換之應用
Artificial Intelligence Optimized First-Principles Calculations Study of Spinel-Structured High-Entropy Oxides for Energy Conversion
指導教授: 蘇彥勳
Su, Yen-Hsun
共同指導: 關肇正
Kaun, Chao-Cheng
學位類別: 碩士
Master
系所名稱: 工學院 - 材料科學及工程學系
Department of Materials Science and Engineering
論文出版年: 2021
畢業學年度: 109
語文別: 中文
論文頁數: 106
中文關鍵詞: 第一原理計算尖晶石結構高熵氧化物機器學習產氫反應產氧反應
外文關鍵詞: First-principles calculation, Spinel structured high-entropy oxide, machine learning, hydrogen evolution reaction, oxygen evolution reaction
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  • 本研究著重於探討尖晶石結構高熵氧化物的性質及其應用,主要分為三個部分進行討論;第一部分是利用第一原理結合機器學習的概念研究(Co,Cr,Fe,Mn,Ni)3O4的物理性質,結果顯示尖晶石結構氧化物的物理性質與組成相關,晶格上的不同金屬陽離子不僅影響了材料晶胞的大小(晶格常數),亦影響了材料的穩定度(形成能),本研究結果表明當鉻金屬在材料中有較高的比例時,其晶格常數會呈現較大,且材料的結構也會隨著鉻金屬含量的提升而變得更加地穩定,此外尖晶石結構之位置也大大的影響材料之性質,本研究結果說明結構的形成能受B site的影響大於A site帶來的影響,總之藉由第一性原理計算和機器學習的串聯方法,可以大大節省計算時間和計算資源,有利於我們去探究這類型的材料。
    第二、三部分為尖晶石結構高熵氧化物應用之研究。在第二部分介紹了尖晶石結構高熵氧化物(Co,Cr,Fe,Mn,Ni)3O4用於產氫反應,基於第一原理的理論模擬針對不同的活性位點金屬進行研究,以位於尖晶石結構 (001) 面之A site上的Co,Fe,Mn和Ni金屬為研究目標,根據電子結構的計算結果說明以鐵為反應位點的結構將有利於介面電荷的轉移,且此狀態下的結構亦具有最低的過電位,說明此狀態具有最佳的HER催化活性,此外藉由能量變化圖的結果,可以得知在兩種常見的HER機制: Volmer-Heyrovsky及Volmer-Tafel中,Volmer-Heyrovsky機制主導了(Co,Cr,Fe,Mn,Ni)3O4用於產氫的催化反應,過程中又以氫脫附的過程為HER速率決定步驟。
    第三部分是關於(Co,Cr,Fe,Mn,Ni)3O4用於產氧反應的研究,利用第一原理分析尖晶石結構 (111) 面上活性位點的電子結構以及催化活性,計算結果顯示當(Co,Cr,Fe,Mn,Ni)3O4中的A site由鈷金屬所佔據,並以鎳金屬作為反應位點時有最低的過電位數值,亦即有最佳的OER之表現,由於OER過程的中間態之吸附情形決定了反應的速率,本研究亦針對產氧反應的中間態進行吸附狀態的計算,結果說明此材料的對於產氧反應的速率決定步大多為氧原子吸附之中間態至OOH基團吸附之中間態的過程。

    The development of environmentally friendly and low-cost materials has become the mainstream of products and technologies. High-entropy oxides (HEOx) is very promising.In this work, we investigate the geometric structure, physical properties, and applications of spinel-structured HEOx based on first-principles calculations. The coupling of first principles and machine learning can quickly and accurately obtain material information, thereby accelerating the discovery of stable components of materials. The structures containing Cr metal ions or containing a high ratio of Cr show a large lattice constant and have a lower formation energy, making the structures more stable. Furthermore, the B-site-dependence of the formation energy is stronger than the A-site-dependence. For HER, the Volmer-Heyrovsky mechanism dominates the HER process of HEOx, where the Heyrovsky reaction is the rate-determining step of the entire Volmer-Heyrovsky process. For OER, the process from *O to *OOH is the rate-determination step for most systems. The calculated HER and OER performance of the spinel structure HEOx shows the importance of Fe component and Ni component in the reaction process, respectively.

    摘要 i 誌謝 x 目錄 xi 表目錄 xiv 圖目錄 xv 第一章 緒論 1 1-1 前言 1 1-2 研究動機 3 第二章 基礎理論與文獻回顧 4 2-1基礎理論 4 2-1.1第一原理計算與應用 4 2-1.2薛丁格方程式 4 2-1.3 多電子系統與Hartree-Fock 近似 5 2-1.4 密度泛函理論(Density Functional Theory, DFT) 7 2-1.5 布洛赫定理 (Bloch theorem) 14 2-1.6 能態密度(Density of states) 15 2-1.7贋勢法(Pseudopotential method) 15 2-1.8 過渡態理論(Transition state theory)與CI-NEB 方法 (Climbing-image nudged elastic band method) 17 2-2文獻回顧 19 2-2.1高熵氧化物 (High entropy oxides, HEOx) 19 2-2.2尖晶石結構高熵氧化物 (Spinel-structured HEOx) 20 2-2.3 高熵氧化物之第一原理研究 22 2-2.4 機器學習 23 2-2.5 尖晶石結構HEOx的應用 26 2-2.5.1 產氫反應 (Hydrogen evolution reaction, HER) 28 2-2.5.2 產氧反應 (Oxygen evolution reaction, OER) 29 第三章 計算軟體介紹與計算參數 31 3-1 VASP 31 3-2 計算參數 32 第四章 結果與討論 33 4-1 第一性原理及機器學習預測尖晶石結構HEOx的物理性質 33 4-1.1 第一原理的計算 (First-principles calculations) 33 4-1.2 機器學習的決策流程 36 4-1.3 ML模型的選擇和low data test 39 4-1.4 未知數據的預測 42 4-1.5 ML預測結果的驗證 50 4-2 尖晶石結構HEOx於氫轉化的應用 53 4-2.1 HER催化劑之結構設計 53 4-2.2催化劑尖晶石結構HEOx之電子結構分析 55 4-2.3 Volmer 反應 57 4-2.4 Heyrovsky 反應 64 4-2.5 Tafel 反應 67 4-2.6 HER的總反應 (Overall reaction) 表現 74 4-3 尖晶石結構HEOx於氧轉化的應用 78 4-3.1 設計OER催化劑的模型 78 4-3.2 OER中間態之電子結構分析 79 4-3.3 OER的總反應表現 86 第五章 結論 92 5-1 耦合高熵氧化物的第一原理與機器學習計算尖晶石結構高熵氧化物 (Co,Cr,Fe,Mn,Ni)3O4 92 5-2 尖晶石結構高熵氧化物(Co,Cr,Fe,Mn,Ni)3O4於產氫反應的第一性原理研究 93 5-3 尖晶石結構高熵氧化物(Co,Cr,Fe,Mn,Ni)3O4於產氧反應的第一性原理研究 94 參考文獻 95

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