权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Broadband Spectral Interferometric Polarized Coherent anti-Stokes Raman Scattering - a non-linear approach to fast all-optical chemical fingerprinting

宽带光谱干涉偏振相干反斯托克斯拉曼散射 - 一种快速全光学化学指纹识别的非线性方法

基本信息

批准号：
2188482
负责人：
金额：
--
依托单位：
King's College London
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2188482
关键词：
Broadband Spectral Interferometric Polarized Coherent

项目摘要

Development in coherent anti-Stokes Raman spectroscopy (CARS) techniques has expanded greatly in the past two decades with research geared towards faster and more sensitive data acquisition, simplified experimental requirements and robust computational/optical methods to remove the associated non-resonant background (NRB) with CARS. Following on from research conducted by David Richards' group at KCL, this project aims to further expand the capabilities of the broadband CARS technique developed and patented by the group, spectral interferometric polarized CARS (SIPCARS), as well as work on broadband CARS in general. There are two main strands as to which this will be achieved; experimental studies and data analysis of hyperspectral CARS data.The experimental strand will encompass both developments to the SIPCARS system and the usage of complex biological samples to characterise and demonstrate the validity and usefulness of SIPCARS as a means for obtaining rapid and accurate spectral data of biological specimen. The data analysis strand will primarily focus on analysing hyperspectral data obtained from SIPCARS measurements. Typically, analysis of hyperspectral data is carried out using clustering techniques. Essentially, the purpose of this strand in the research programme will be to provide tools to extract information from biological hyperspectral data, thus creating a fully comprehensive system capable of measuring and analysing hyperspectral Raman data of complex biological samples with rapid acquisition rates and a high level of accuracy.

相干反斯托克斯拉曼光谱（汽车）技术的发展在过去的二十年中已经大大扩展，研究面向更快和更灵敏的数据采集，简化的实验要求和鲁棒的计算/光学方法以去除与汽车相关的非共振背景（NRB）。继大卫理查兹的小组在KCL进行的研究之后，该项目旨在进一步扩大该小组开发和专利的宽带汽车技术的能力，光谱干涉偏振汽车（SIPCARS），以及宽带汽车的一般工作。这项工作主要分两个方面：实验研究和高光谱汽车数据分析，实验方面将包括SIPCARS系统的开发和复杂生物样品的使用，以验证SIPCARS作为获取生物样品快速准确光谱数据的手段的有效性和实用性。数据分析股将主要侧重于分析从SIPCARS测量中获得的高光谱数据。通常，使用聚类技术进行高光谱数据的分析。从本质上讲，研究方案中这一部分的目的将是提供从生物高光谱数据中提取信息的工具，从而建立一个能够以快速采集速度和高准确度测量和分析复杂生物样本的高光谱拉曼数据的全面系统。