C-V characterization of the trap-rich layer in a novel Double-BOX structure

IF 1.4 4区 物理与天体物理 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Solid-state Electronics Pub Date : 2024-05-09 DOI:10.1016/j.sse.2024.108951
Yang Huang , Fanyu Liu , Sorin Cristoloveanu , Shiqi Ma , Massinissa Nabet , Yiyi Yan , Bo Li , Binhong Li , Bich-Yen Nguyen , Zhengsheng Han , Jean-Pierre Raskin
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Abstract

A new Double-BOX structure is introduced to explore the electrical properties of the trap-rich layer used to enhance the performance of radio frequency Silicon-on-Insulator substrates. Capacitance-voltage (C-V) measurements reveal anomalous behavior with a “shoulder” emerging in the electron accumulation region and a shift towards negative gate voltage in hysteresis. TCAD simulation shows that these features are related to trap states at the grain boundary in the trap-rich polycrystalline silicon (polysilicon) layer. These traps form a potential barrier and affect the C-V curves. To determine the traps density in polysilicon, a three-element circuit model is used. The effective density of fast traps is evaluated from the corrected C-V curve, while the hysteresis of double-sweep C-V measurement yields the slow traps density at the grain boundary in polysilicon.

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新型双 BOX 结构中陷阱丰富层的 C-V 特性分析
为了探索用于提高射频绝缘体上硅衬底性能的富陷阱层的电气特性,我们引入了一种新的双 BOX 结构。电容-电压(C-V)测量结果表明,电子积聚区出现了 "肩",滞后中的栅极电压趋向于负值。TCAD 模拟显示,这些特征与多晶硅(多晶硅)层中富含陷阱的晶界陷阱态有关。这些陷阱形成了势垒,影响了 C-V 曲线。为了确定多晶硅中的陷阱密度,我们使用了一个三元素电路模型。根据校正后的 C-V 曲线评估快速陷阱的有效密度,而根据双扫 C-V 测量的滞后性得出多晶硅晶界处的慢速陷阱密度。
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来源期刊
Solid-state Electronics
Solid-state Electronics 物理-工程:电子与电气
CiteScore
3.00
自引率
5.90%
发文量
212
审稿时长
3 months
期刊介绍: It is the aim of this journal to bring together in one publication outstanding papers reporting new and original work in the following areas: (1) applications of solid-state physics and technology to electronics and optoelectronics, including theory and device design; (2) optical, electrical, morphological characterization techniques and parameter extraction of devices; (3) fabrication of semiconductor devices, and also device-related materials growth, measurement and evaluation; (4) the physics and modeling of submicron and nanoscale microelectronic and optoelectronic devices, including processing, measurement, and performance evaluation; (5) applications of numerical methods to the modeling and simulation of solid-state devices and processes; and (6) nanoscale electronic and optoelectronic devices, photovoltaics, sensors, and MEMS based on semiconductor and alternative electronic materials; (7) synthesis and electrooptical properties of materials for novel devices.
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