发表机构
Kiel University; Ruhr University Bochum; Fraunhofer Institute for Electronic Nano Systems ENAS（基尔大学; 波鸿鲁尔大学; 弗劳恩霍夫电子纳米系统研究所（ENAS））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究建立多尺度框架，结合超5万器件统计与模拟，揭示Cu嵌入SiO_x忆阻器件行为源于概率缺陷级联，提出氧空位密度为潜在描述符，将视角转向概率缺陷态设计以控制功能变异性。
AI 中文摘要
氧化物基器件中的电阻开关行为普遍受随机缺陷过程控制，然而，制造条件与功能行为之间的预测性联系仍然难以捉摸。在此，我们建立了一个多尺度框架，将等离子体定义的沉积条件与溅射SiO$_x$/Cu/SiO$_x$基体系的宏观器件功能联系起来。通过结合对超过50,000个实验表征器件的的大规模统计分析以及基于物理的等离子体和原子模拟，我们表明器件行为并非源于确定性的工艺-性能映射，而是源于跨越缺陷形成、缺陷态演化和功能态涌现的概率级联。数据驱动的聚类揭示了一个由可操作开关类型组成的连续功能状态空间，而逆向建模则识别出重构的氧空位密度作为一个有效的潜在描述符，该描述符捕捉了结构无序和缺陷拓扑的综合影响。这一潜在描述符与Cu再分布和电响应强烈耦合，将原本隐藏的材料特性与可观测的器件特征联系起来。此外，宏观开关行为被认为源于跨空间异质子域的系综整合，这为大面积器件显著的变异性提供了物理解释。这些发现将视角从确定性缺陷工程转向概率缺陷态设计，并为理解和控制此类氧化物基系统（如忆阻或电阻开关器件）中的功能变异性建立了一个基于物理的框架。
英文摘要
Resistive switching in oxide-based devices is widely governed by stochastic defect processes, yet a predictive link between fabrication conditions and functional behavior remains elusive. Here, we establish a multiscale framework connecting plasma-defined deposition conditions to macroscopic device functionality in sputtered SiO$_x$/Cu/SiO$_x$-based systems. By combining large-scale statistical analysis of more than 50,000 experimentally characterized devices with physics-based plasma and atomistic simulations, we show that device behavior does not emerge from deterministic process-to-performance mappings, but from a probabilistic cascade spanning defect formation, defect-state evolution, and functional-regime emergence. Data-driven clustering reveals a continuous functional state space composed of operational switching types, while inverse modeling identifies the reconstructed oxygen-vacancy density as an effective latent descriptor capturing the combined influence of structural disorder and defect topology. This latent descriptor is strongly coupled to both Cu redistribution and electrical response, linking otherwise hidden material properties to observable device characteristics. Furthermore, macroscopic switching behavior is argued to arise from ensemble integration across spatially heterogeneous subdomains, providing a physical explanation for the pronounced variability of large-area devices. These findings shift the perspective from deterministic defect engineering toward probabilistic defect-state design and establish a physically grounded framework for understanding and controlling functional variability in such oxide-based systems, such as memristive or resistive-switching devices.
