论文标题
朝着具有自动扫描液滴细胞的耐腐蚀合金涂料的自动设计
Towards automated design of corrosion resistant alloy coatings with an autonomous scanning droplet cell
论文作者
论文摘要
我们提出了一个自主扫描液滴电池平台，旨在研究多组分合金的耐腐蚀性特性，旨在进行按需合金电沉积和实时电化学表征。自动化和机器学习目前正在以高通量和自主材料设计和发现的高速创新。我们提出了两个合金设计案例研究：一个侧重于多物体耐腐蚀的抗合金优化，以及一个案例研究，强调了为了洞悉推动观察到的材料行为的基本结构和化学因子所需的多模式表征的复杂性。这激发了自主研究平台与科学机器学习方法之间的紧密耦合，该方法将机械模型和黑匣子机器学习模型融合在一起。这个新兴研究领域为加速材料综合，评估以及发现和设计提供了新的机会。
We present an autonomous scanning droplet cell platform designed for on-demand alloy electrodeposition and real-time electrochemical characterization for investigating the corrosion-resistance properties of multicomponent alloys. Automation and machine learning are currently driving rapid innovation in high throughput and autonomous materials design and discovery. We present two alloy design case studies: one focusing on a multi-objective corrosion resistant alloy optimization, and a case study highlighting the complexity of the multimodal characterization needed to provide insight into the underlying structural and chemical factors that drive observed material behavior. This motivates a close coupling between autonomous research platforms and scientific machine learning methodology that blends mechanistic physical models and black box machine learning models. This emerging research area presents new opportunities to accelerate materials synthesis, evaluation, and hence discovery and design.
