Nanodevice for Imaging Normal Stress Distribution with Application in Sensing Texture and 'Feel' by Touching
Nanodevice for Imaging Normal Stress Distribution with Application in Sensing Texture and 'Feel' by Touching
批准号:
0534812
负责人:
Ravi Saraf
金额:
$0.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-08-30 至 2008-08-31
中文摘要
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英文摘要
Touch is one of the five senses designed by nature for survival. 'Touch' may (partially) be characterized as a sensory operation for measuring texture and softness of an object by mechanical contact. We propose to design, fabricate, study and develop, a novel, large-area, touch sensor made from nanoparticles. The nanodevice is a self-assembled thin-film sensor that will convert static or dynamic (compressive) normal stress distribution to, (i) visible-light , and/or, (ii) electrical current or voltage. The optical and/or electrical signal is proportional to the magnitude of local stress on the sensor's active area. By detecting the light intensity distribution and/or, probing the current distribution on the active area using an electrode array, potentially, the stress distribution can be obtained in less than millisecond speeds at spatial resolution of 1 mm spot. Importantly, the dynamic range and the sensitivity of the sensor can be tuned. Due to high speed (especially for electrical signal), the external stimulus (i.e., stress distribution) may be mechanical force, pressure or ultrasound radiation. The structure of the device will be a suitable test-bed to study physics and characteristics of electronic transport across nanoparticle/nanoparticle and nanoparticle/insulator junctions, both at single particle resolution. This fundamental study will potentially lead to design rules to optimize the device performance of the proposed sensor, also dubbed 'Artificial Skin'. The thin-film device may be supported or directly self-assembled on flexible or rigid substrate. The sensor will have broad range of other applications such as, ultrasound medical imaging/diagnostics, smart materials, and non-destructive diagnostics of large structures.
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