Real-time monitoring of plasma synthesis of functional materials by high power impulse magnetron sputtering and other PVD processes: towards a physics-constrained digital twin
Real-time monitoring of plasma synthesis of functional materials by high power impulse magnetron sputtering and other PVD processes: towards a physics-constrained digital twin
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通过高功率脉冲磁控溅射和其他 PVD 工艺实时监测功能材料的等离子体合成：走向物理约束的数字孪生
DOI：
10.1088/1361-6463/aca25a
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Ehiasarian A
中科院分区：
文献类型：
--
作者：
Ehiasarian A
通过物理气相沉积(PVD)的等离子体合成薄膜，能够创造出推动现代生活中重大创新的材料。对更严格的质量控制和更好的资源利用的高价值制造需求可以通过能够实时模拟沉积过程的数字孪生兄弟来满足。光学发射光谱(OES)与工艺参数相结合来监测高功率脉冲磁控溅射和常规磁控溅射工艺的所有阶段，以提供确定工艺重复性的可靠方法和出于质量保证目的的工艺控制的可靠手段。开发了实时监测CrAlYN/CrN纳米多层膜的涂层厚度、成分、晶体结构和形貌发展的策略和基于物理的模型。基片上的离子中性比和金属氮比的当量由容易获得的参数得到，包括Cri，N2(C-B)和Ar I线的光发射强度，以及由基片和阴极电流密度之比得到的等离子体扩散系数。这些光学导出的等效参数确定了沉积通量条件，该条件触发了从X射线衍射极图中观察到的主要晶体织构从(111)向(220)的转变，以及在一定范围的磁控磁场配置下，涂层形貌从小平面向致密的发展。制定了基于OES的策略，以监控腔室排空、衬底清洁和预防性腔壁清洁的进度，以支持工艺优化和设备利用。这项工作为实施机器学习协议铺平了道路，以监测和控制这些和其他加工活动，包括涂层开发和使用替代沉积技术。这项工作为创建PVD工艺的数字孪生兄弟提供了基本要素，以实时监控和预测工艺结果，如薄膜厚度、纹理和形态。
Plasma synthesis of thin films by physical vapour deposition (PVD) enables the creation of materials that drive significant innovations in modern life. High value manufacturing demand for tighter quality control and better resource utilisation can be met by a digital twin capable of modelling the deposition process in real time. Optical emission spectroscopy (OES) was combined with process parameters to monitor all stages of both high power impulse magnetron sputtering and conventional magnetron sputtering processes to provide a robust method of determining process repeatability and a reliable means of process control for quality assurance purposes. Strategies and physics-based models for the in-situ real-time monitoring of coating thickness, composition, crystallographic and morphological development for a CrAlYN/CrN nanoscale multilayer film were developed. Equivalents to the ion-to-neutral ratio and metal-to-nitrogen ratios at the substrates were derived from readily available parameters including the optical emission intensities of Cr I, N 2 (C–B) and Ar I lines in combination with the plasma diffusivity coefficient obtained from the ratio of substrate and cathode current densities. These optically-derived equivalent parameters identified the deposition flux conditions which trigger the switch of dominant crystallographic texture from (111) to (220) observed in XRD pole figures and the development of coating morphology from faceted to dense for a range of magnetron magnetic field configurations. OES-based strategies were developed to monitor the progress of chamber evacuation, substrate cleaning and preventative chamber wall cleaning to support process optimisation and equipment utilisation. The work paves the way to implementation of machine learning protocols for monitoring and control of these and other processing activities, including coatings development and the use of alternative deposition techniques. The work provides essential elements for the creation of a digital twin of the PVD process to both monitor and predict process outcomes such as film thickness, texture and morphology in real time.