The resistance of piezoresistive materials can change as they are deformed, and consequently, they can be applied in the motion detection of micro-/nano-electromechanical systems and the pressure sensors. For the bulk, however, its piezoresistive coefficient is quite low, and furthermore, its resistance can be restored immediately when the strain of materials disappears, resulting into a limiting of application scope. In this project, the traps of one-dimensional (1D) nanostructured semiconductors will be modulated by doping. Not only a giant piezoresistive effect will be achieved, but also the resistance of 1D nanostructures will orderly vary with strain. Especially, the resistance can remain a variation after the stress is removed and the strain disappears, and moreover, the variation value is dependent of the as-applied strain. Thus, these materials can store stress information. Additionally, the resistance variation induced by the strain can be restored by a relatively high outside electric field, and thus the stored stress information can be erased. As a consequence, the nanostructured materials not only can be applied in nonvolatile stress-related devices, such as pressure sensors and data storage devices. Eventually, the rewritable nonvolatile stress sensors and stress-writing data storage devices are fabricated based on an individual nanowire and composite nanostructures with the giant piezoresistive performance. The influence of species, concentration, and depth of defects and traps on the piezoresistive coefficient and the stress storing and restoring of nanostructures will be explored. The mechanisms associated with defect, strain and resistance will be revealed, and the constitutive equation will be established among them. The theoretical model of stress-storing information will be created, and the prototype devices of rewritable nonvolatile stress sensors and stress-writing data memories will be built based on a single nanowire and composite nanostrucutres. The theoretical, based on the performance modulation of nanostructures, will be established, and moreover, it will be provided the technical support for stress sensors and stress-writing memories based on nanostructures.
压阻材料的阻值随着材料形变而变化的特性使其在微纳机电系统的运动探测及压力传感中有着重要的应用前景。然而,常规块体材料的压阻系数较低,且阻值会随着应变的消失而恢复,成为制约其广泛应用的瓶颈。针对此关键问题,本项目拟采用掺杂等手段对一维纳米结构半导体的电荷陷阱进行可控调制,不仅实现巨压阻效应,而且阻值在应力撤除后仍存在决于所施加应变量的变化,另外变化的阻值可通过外界高电场的作用而恢复,实现对应力信息的记忆和擦除功能。然后,利用此材料的单一及复合纳米结构来构建可循环擦写的非易失性应力传感及应力写入型数据存储器。研究纳米结构中掺杂形成的缺陷陷阱种类、浓度和深度对压阻系数及应力记忆功能的影响规律;揭示缺陷-应变-电阻三者之间的关联机制,确立它们之间的本构方程;建立应力存储信息的理论模型,并构建出原型器件。为纳米结构的半导体性能调控奠定理论基础,也为实现基于纳米结构的新型应力传感及存储器提供技术支持。
压阻材料的阻值随着材料形变而变化的特性使其在微纳机电系统的运动探测及压力传感中有着重要的应用前景。然而,常规块体材料的压阻系数较低,且阻值会随着应变的消失而恢复,成为制约其广泛应用的瓶颈。针对此问题,我们提出纳米结构陷阱,特别是表面空间电荷区中的陷阱是影响纳米结构应力响应的主导因素。基于此,我们采用掺杂、组成和结构异质化、以及超纳复合结构构建等手段对一维纳米结构半导体的陷阱进行可控调制,不仅实现巨压阻效应,而且其阻值在应力撤除后仍存在取决于所施加应变量的变化,另外变化的阻值可通过外界高电场的作用而恢复,实现对应力信息可擦除的的非易失性感知与记忆功能。然后,利用此材料不仅构建出具有高灵敏度的瞬时应力传感器件,而且进一步构建出可循环擦写的非易失性应力感知与记忆型数据存储器见。通过深入的研究,得出了巨压阻效应源于压/张应力导致陷阱中心势垒高度的下降/上升,形成巨压阻效应。所有应力作用后都会导致陷阱中捕获载流子数目的下降,而高偏压下空出的陷阱能被填充,且这些状态在室温和低偏压下能被维持,从而产生可擦写的非易失性应力感知与记忆特性。我们提出了陷阱机制,建立了应力存储信息的理论模型,然后合成出相应结构材料,最终构建出高性能的原型器件。该工作为纳米结构的半导体性能调控奠定理论基础,也为实现基于纳米结构的新型应力传感及存储器提供技术支持。
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数据更新时间:2023-05-31
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