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PREDICTING MOLECULAR COLLISION CROSS-SECTION USING DIFFERENTIAL MOBILITY SPECTROMETRY
PREDICTING MOLECULAR COLLISION CROSS-SECTION USING DIFFERENTIAL MOBILITY SPECTROMETRY
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机译:使用差分移动光谱法预测分子碰撞截面
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摘要
A plurality of known compounds with known CCS values is analyzed using a DMS device. The DMS device determines how the intensities of their transmitted ions vary with different separation voltages (SVs) and compensation voltages (CVs). A machine learning algorithm builds a data model from the known m/z value, known CCS value, and measured pairs of CV and SV values that provide optimal transmission through the DMS device for each of the known compounds. An unknown compound with an unknown CCS value is then analyzed. The DMS device determines how the intensity of its ions varies with the same different SVs and CVs. Finally, the machine learning algorithm predicts the CCS value of the unknown compound from the data model, the known m/z of the unknown compound, and the measured pairs of CV and SV values that provide optimal transmission through the DMS device for the unknown compound.
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