The photocatalyst β-TaON is of interest due to promising properties, such as stability, suitable band gap for visible light, and carrier mobility. We implemented a combinatorial, material discovery approach that used pulsed laser deposition (PLD) for thin-film growth, X-ray diffraction (XRD) for phase determination, and machine learning for data reduction. A lateral compositional gradient of TaO_xN_y was grown across the surface of an α-Al₂O₃ (012) wafer. After annealing, XRD scattering patterns were collected across the lateral gradient. Unsupervised machine learning separated the XRD data into four clusters (phases); one of which turned out to be the desired monoclinic β-TaON phase. Using high-resolution XRD, we determined that the β-TaON region of the film was a 260 Å thick single-crystal epitaxial with the substrate, having out-of-plane β-TaON (100)//α-Al₂O₃ (012) and in-plane β-TaON (010)//α-Al₂O₃ (21̅0). X-ray reflectivity (XRR) analysis of the β-TaON region of the film showed an electron density matching that expected for β-TaON. X-ray photoelectron spectroscopy (XPS) showed a Ta⁵⁺ valence state in the β-TaON region of the film. This combinatorial approach, which produces a library of phases on a single wafer, proved to be very efficient for the growth of a material’s phase of interest.

中文翻译：

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用于单晶生长TAON组合方法：外延β-TAON（100）/α-Al系₂ ö ₃（012）

由于有希望的性质，例如稳定性，可见光的合适带隙和载流子迁移率，光催化剂β-TaON是令人关注的。我们实施了一种组合的材料发现方法，该方法使用脉冲激光沉积（PLD）进行薄膜生长，使用X射线衍射（XRD）进行相确定以及使用机器学习进行数据缩减。横向组分梯度的的TaO _X Ñ _ý被跨越的表面生长的α-Al ₂ ö ₃（012）晶片。退火后，沿横向梯度收集XRD散射图。无监督机器学习将XRD数据分为四个集群（阶段）；结果证明其中之一是所需的单斜β-TaON相。使用高分辨率XRD，我们确定膜的β-TAON区域是一个260埃厚的单晶外延与衬底，具有外的平面β-TAON（100）//的α-Al ₂ ö ₃（012）和面内β-TAON（010）//的α-Al ₂ ö ₃（210）。膜的β-TaON区域的X射线反射率（XRR）分析显示，电子密度与β-TaON所期望的匹配。X射线光电子能谱（XPS）显示Ta ⁵⁺薄膜的β-TaON区域的化合价态。这种组合方法可在单个晶片上产生相库，事实证明，这种方法对于生长所关注材料的相非常有效。