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Classification of spectroscopically encoded resins by Raman mapping and infrared hyperspectral imaging

机译:通过拉曼映射和红外高光谱成像对光谱编码的树脂进行分类

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摘要

Barcoded resins (BCRs) were recently introduced as a potential platform for pre-encoded multiplexed synthesis, screening, and biomedical diagnostics. A key step toward the development of this strategy is the ability to rapidly interrogate and classify the BCRs in a high-throughput, noninvasive manner. Here, we describe a one-step strategy based on Raman mapping and Fourier transform infrared imaging to classify and spatially resolve randomly distributed BCRs. To illustrate this methodology, mixtures of up to 25 different BCRs were imaged and classified with 100% confidence. This strategy can be readily extended to a larger pool of resins, provided each BCR features a unique vibrational fingerprint (spectroscopic barcode). We have also established that reliable single-bead Raman spectra can be recorded in 10 ms, thus confirming that Raman mapping, in particular, could be a very fast method to classify the BCRs.
机译:条形码树脂(BCR)最近被引入作为预编码的多元合成,筛选和生物医学诊断的潜在平台。制定此策略的关键步骤是以高通量,无创方式对BCR进行快速查询和分类的能力。在这里,我们描述了一种基于拉曼映射和傅立叶变换红外成像的单步策略,以对随机分布的BCR进行分类和空间解析。为了说明这种方法,对多达25种不同BCR的混合物进行了成像,并以100%置信度进行了分类。如果每个BCR都具有独特的振动指纹(光谱条形码),则该策略可以很容易地扩展到更大的树脂库中。我们还建立了可以在10 ms内记录可靠的单珠拉曼光谱的方法,从而证实了拉曼作图尤其是对BCR进行分类的非常快速的方法。

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