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Adaptive control of tip-enhanced near-field optical signals in carbon nanotubes

Adaptive control of tip-enhanced near-field optical signals in carbon nanotubes
碳纳米管尖端增强近场光信号的自适应控制
批准号:
137747659
负责人:
Professor Dr. Achim Hartschuh
金额:
$0.0万
依托单位:
依托单位国家:
德国
项目类别:
Priority Programmes
财政年份:
2009
资助国家:
德国
项目状态:
已结题
起止时间:
2008-12-31 至 2013-12-31

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中文摘要
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英文摘要
Ultrafast laser spectroscopy enables real time observations of photo-induced processes and the exploration of their dynamics and reaction pathways on attosecond time-scales. By shaping the spectral amplitude and phase of ultrashort laser pulses the contributing electronically and vibronically excited states can even be controlled coherently. Optimum control is achieved by adaptive pulse shaping using learning-loop techniques fine-tuning branching ratios and reaction yields. Near-field optics, on the other hand, aims at surpassing the resolution limit of conventional microscopy imposed by diffraction reaching about 10 nm at present. We propose to develop a novel technique by combining ultrafast adaptive control and tip-enhanced near-field optical microscopy (UAC-TENOM) using carbon nanotubes as model nanostructures. Specifically, we will achieve the adaptive control of near-field interference and pulse compression in tunable metal-particle configurations using polarization shaped laser pulses. Merging ultrafast adaptive control and tip-enhanced techniques offers substantial added value by further increasing spatial resolution and signal enhancement of TENOM. Our results will form important steps towards full spatio-temporal and coherent control of excited states in single nanostructures and will have a major impact on other nanoscale spectroscopies.
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DOI: 10.1364/josab.31.001118
发表时间: 2014-01
期刊: Journal of The Optical Society of America B-optical Physics
影响因子: 1.9
作者: [A. Comin;R. Ciesielski;G. Piredda;Kevin Donkers;A. Hartschuh]
通讯作者: A. Comin;R. Ciesielski;G. Piredda;Kevin Donkers;A. Hartschuh
Optical probing and control of heat propagation at the nanoscale
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    426728715
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    Research Grants
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    $0.0万
  • 财政年份:
    2019
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    2008
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