Gramatte Simon, Politano Olivier, Jakse Noel, Cancellieri Claudia, Utke Ivo, Jeurgens Lars P H, Turlo Vladyslav
Laboratory for Advanced Materials Processing, Empa - Swiss Federal Laboratories for Materials Science and Technology, Feuerwerkerstrasse 39, Thun, CH-3602 Switzerland.
Laboratoire Interdisciplinaire Carnot de Bourgogne ICB UMR 6303, Université Bourgogne Europe, CNRS, Dijon, FR-21000 France.
NPJ Comput Mater. 2025;11(1):170. doi: 10.1038/s41524-025-01676-5. Epub 2025 Jun 6.
Advancing hydrogen-based technologies requires detailed characterization of hydrogen chemical states in amorphous materials. As experimental probing of hydrogen is challenging, interpretation in amorphous systems demands accurate structural models. Guided by experiments on atomic layer deposited alumina, a fast atomistic simulation technique is introduced using an ab initio-based machine learning interatomic potential to generate amorphous structures with realistic hydrogen contents. As such, the annealing of highly defective crystalline hydroxide structures at atomic layer deposition temperatures reproduces experimental density and structure, enabling accurate prediction of Al Auger parameter chemical shifts. Our analysis shows that higher hydrogen content favors OH ligands, whereas lower hydrogen content leads to diverse chemical states and hydrogen bonding, consistent with charge density and partial Bader charge calculations. Our approach offers a robust route to link hydrogen content with experimentally accessible chemical shifts, aiding the design of next-generation hydrogen-related materials.
推进基于氢的技术需要详细表征非晶材料中的氢化学状态。由于对氢进行实验探测具有挑战性，因此在非晶体系中的解释需要准确的结构模型。在原子层沉积氧化铝的实验指导下，引入了一种快速原子模拟技术，该技术使用基于从头算的机器学习原子间势来生成具有实际氢含量的非晶结构。因此，在原子层沉积温度下对高度缺陷的结晶氢氧化物结构进行退火处理，可以再现实验密度和结构，从而能够准确预测铝俄歇参数化学位移。我们的分析表明，较高的氢含量有利于形成OH配体，而较低的氢含量会导致多种化学状态和氢键，这与电荷密度和部分巴德电荷计算结果一致。我们的方法提供了一条将氢含量与实验可获取的化学位移联系起来的可靠途径，有助于下一代氢相关材料的设计。
