Putting A Spin On Machine Learning, Atom by Atom

逐个原子地推进机器学习

• 批准号: EP/T033568/1
• 负责人: Philip Moriarty
• 金额: $ 228.96万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FT033568%2F1
• 关键词: Putting; Spin; Machine; Learning; Atom

There is nothing quite like the magic of magnets. And yet even Richard Feynman, an incredibly gifted science communicator, struggled to explain just how magnetism works. (The video in question is easily found on YouTube. Feynman's slight tetchiness with the interviewer who raises the subject of magnetic forces is not entirely unrelated to the difficulty in explaining their fundamental origin at a level that a non-physicist -- or, indeed, a physicist -- can readily grasp.) Scientists are now at the point, however, where not only can we measure forces on an atom-by-atom basis, but we can harness and exploit those self-same forces to manipulate magnetism right down to the atomic level (and beyond). The instrument that allows this exquisite level of control of magnetic forces is the scanning probe microscope. A technique that will shortly reach its fortieth birthday, probe microscopy is conceptually rather straight-forward -- its experimental realisation rather less so. An exceptionally sharp tip, terminated in a single atom or molecule, is brought extremely close to a surface such that the tip-surface separation is of the order of the diameter of an atom or less. This atomically sharp probe can then be used in a number of modes to explore, interrogate, and modify the underlying sample surface on an atom-by-atom basis. Some of the most exciting and ground-breaking science ever carried out has involved the scanning probe microscope's unparalleled ability to not only image, but manipulate, matter at the single atom level. Probe microscopes are not just limited to the imaging and control of atoms; they can go much further. With an appropriately modified tip apex, even the quantum mechanical spin of electrons -- which, ultimately, is the source of magnetism -- is detectable either via the tiny electrical current that flows between the probe and the sample, or, incredibly, via measurement of the minuscule magnetic force between single atoms. Just a couple of months ago (in Oct. 2019), Chris Lutz' group at the IBM Almaden Research Centre reported that they have achieved, in collaboration with researchers in Korea and Oxford, the most precise and coherent control of the spin state of individual atoms ever attempted with SPM. (It's worth noting that IBM is the birthplace of both the scanning probe microscope itself, which was invented by Binnig, Rohrer and co-workers in the Ruschlikon, Zurich research labs, and of SPM-driven single atom manipulation, due to the inspiring efforts of Don Eigler and colleagues at IBM Almaden.) But the deep, dark secret of the probe microscopist is that a very large percentage of their time is spent coercing and cajoling the probe into providing atomic resolution. Yet even that's not enough -- when that resolution is achieved, the microscopist very often has to maintain the ability to image, move, and spectroscopically interrogate single atoms at the same time, while always being on the look-out for tip-derived artefacts. The component at the core of probe microscopy -- the probe itself -- therefore represents a major, and infuriating, bottleneck in the technique. This project integrates artificial intelligence, surface science, and nanoscience to take the pain out of probe microscopy. We will develop a machine learning framework that, in essence, "auto focuses" a probe microscope and then takes the SPM to the point where it can learn how to build magnetic nanostructures atom-by-atom and spin-by-spin. By itself. This AI-enabled probe microscope will then be used to carry out a programme of exceptionally challenging experiments whose common theme is the control of magnetism at the most fundamental levels: single domains, single molecules, single atoms, and single spins.

没有什么比磁铁的魔力更神奇的了。然而，即使是理查德·费曼，一位极具天赋的科学传播者，也很难解释磁场是如何工作的。(有问题的视频很容易在YouTube上找到。费曼对提出磁力问题的采访者的轻微暴躁并非完全没有关系，因为他很难在非物理学家（实际上是物理学家）容易理解的层面上解释磁力的基本起源。)然而，科学家们现在不仅可以在原子的基础上测量力，而且可以控制和利用这些力来操纵磁性，直到原子水平（甚至更远）。这种精密的磁力控制仪器就是扫描探针显微镜。探针显微镜是一项即将迎来40岁生日的技术，它在概念上相当直截了当，而在实验上的实现却不那么直截了当。一个末端在单个原子或分子中的特别锋利的尖端，被带得非常靠近表面，使得尖端与表面的分离相当于或小于一个原子直径的数量级。然后，这种原子锋利的探针可以在许多模式下用于逐个原子地探索、询问和修改下层样品表面。一些最激动人心、最具突破性的科学研究都涉及到扫描探针显微镜无与伦比的能力，它不仅能成像，还能在单原子水平上操纵物质。探针显微镜不仅限于对原子的成像和控制；他们可以走得更远。通过适当修改尖端，即使是电子的量子力学自旋——这最终是磁性的来源——也可以通过在探针和样品之间流动的微小电流来检测，或者通过测量单个原子之间微小的磁力来检测，这令人难以置信。就在几个月前（2019年10月），IBM阿尔马登研究中心的克里斯·卢茨（Chris Lutz）团队报告说，他们与韩国和牛津大学的研究人员合作，实现了有史以来用SPM对单个原子自旋状态最精确、最连贯的控制。（值得注意的是，IBM是扫描探针显微镜本身的诞生地，扫描探针显微镜是由宾尼、罗勒及其同事在苏黎世的Ruschlikon研究实验室发明的，而spm驱动的单原子操纵技术也是由IBM阿尔马登的唐·埃格勒及其同事的鼓舞人心的努力发明的。）但是，探针显微镜家的一个深刻而黑暗的秘密是，他们大部分时间都花在强迫和哄骗探针提供原子分辨率上。然而，即使这还不够——当达到这样的分辨率时，显微镜学家往往必须同时保持成像、移动和对单个原子进行光谱分析的能力，同时还要时刻注意尖端衍生的人工制品。因此，探针显微镜的核心组件——探针本身——代表了这项技术的一个主要的、令人恼火的瓶颈。该项目整合了人工智能、表面科学和纳米科学，以消除探针显微镜的痛苦。我们将开发一个机器学习框架，从本质上讲，它可以“自动聚焦”探针显微镜，然后将SPM带到可以学习如何一个原子一个原子地构建磁性纳米结构的位置。本身。这种人工智能探针显微镜将被用于执行一项极具挑战性的实验计划，其共同主题是在最基本的层面上控制磁性：单畴、单分子、单原子和单自旋。

项目成果

Improving the segmentation of scanning probe microscope images using convolutional neural networks

• DOI: 10.1088/2632-2153/abc81c
• 发表时间: 2021-03-01
• 期刊: MACHINE LEARNING-SCIENCE AND TECHNOLOGY
• 影响因子: 6.8
• 作者: Farley, Steff;Hodgkinson, Jo E. A.;Hunsicker, Eugenie
• 通讯作者: Hunsicker, Eugenie

Gender issues in fundamental physics: Strumia's bibliometric analysis fails to account for key confounders and confuses correlation with causation

基础物理学中的性别问题：斯特鲁米亚的文献计量分析未能解释关键的混杂因素，并混淆了相关性与因果关系

• DOI: 10.1162/qss_a_00117
• 发表时间: 2021
• 期刊: Quantitative Science Studies
• 影响因子: 6.4
• 作者: Ball P

Origin of C$_{60}$ surface reconstruction resolved by atomic force microscopy

原子力显微镜解析 C$_{60}$ 表面重建的起源

• DOI: 10.48550/arxiv.2110.15838
• 发表时间: 2021
• 作者: Forcieri L

Self-assembly and tiling of a prochiral hydrogen-bonded network: bi-isonicotinic acid on coinage metal surfaces

前手性氢键网络的自组装和平铺：造币金属表面上的双异烟酸

• DOI: 10.1080/00268976.2023.2192824
• 发表时间: 2023
• 期刊: Molecular Physics
• 影响因子: 1.7
• 作者: Allen A

Origin of C 60 surface reconstruction resolved by atomic force microscopy

原子力显微镜解析 C 60 表面重建的起源

• DOI: 10.1103/physrevb.104.205428
• 发表时间: 2021
• 期刊: Physical Review B
• 影响因子: 3.7
• 作者: Forcieri L