當(dāng)前位置：Artificial intelligence-enhanced atom probe microscopy: Local chemical ordering analysis
Artificial intelligence-enhanced atom probe microscopy: Local chemical ordering analysis
Chemical short-range order (CSRO), describing preferential local ordering of elements within the disordered matrix, can change the mechanical and functional properties of materials. CSRO is typically characterized indirectly, using volume-averaged (e.g. X-ray/neutron scattering) or through projection microscopy techniques that fail to capture the complex, three-dimensional atomistic architectures. Quantitative assessment of CSRO and concrete structure-property relationships have remained so far unachievable. Here, we present a machine-learning enhanced approach to break the inherent resolution limits of atom probe tomography to reveal three-dimensional analytical imaging of the size and morphology of multiple CSRO. We showcase our approach by addressing a long-standing question encountered in a body-centred-cubic Fe-18Al and Fe-19Ga (at.%) alloy that sees anomalous property changes upon heat treatment, supported by electron diffraction and synchrotron X-ray scattering techniques. The proposed strategy can be generally employed to investigate short/medium/long-range ordering phenomena in a vast array of materials and help design future high-performance materials.
Dr Yue Li, Alexander von Humboldt Fellow (2021-2024), Postdoc (2019-2021) at the Max Planck Institute for Sustainable Materials, Germany. Li received his doctorate degree in materials science and engineering from University of Science and Technology Beijing in 2019. His research interest is on machine learning enhanced atom probe microscopy, smart design of aluminum-rich alloys. Li has published 18 papers in well-known SCI journals as the first/corresponding author (such as Adv. Mater., Nat. Commun., Acta Mater., Prog. Mater. Sci.), and delivered more than 10 (invited) presentations in international conferences.
李躍博士，2019年畢業(yè)于北京科技大學(xué)，獲博士學(xué)位，2019年至今于德國(guó)馬普學(xué)會(huì)可持續(xù)材料研究所（原馬普鋼鐵所）從事博士后研究，德國(guó)洪堡學(xué)者。主要從事機(jī)器學(xué)習(xí)輔助的三維原子探針表征、輕質(zhì)合金的智能設(shè)計(jì)等相關(guān)研究。截至目前作為第一或通訊作者發(fā)表知名SCI論文18篇, 包括Adv. Mater., Nat. Commun., Acta Mater.和Prog. Mater. Sci.等，并作10多次國(guó)際會(huì)議的邀請(qǐng)報(bào)告。
