Krajewski Logan C, Rodgers Ryan P, Marshall Alan G
Department of Chemistry and Biochemistry, Florida State University , 95 Chieftain Way, Tallahassee, Florida 32306, United States.
Anal Chem. 2017 Nov 7;89(21):11318-11324. doi: 10.1021/acs.analchem.7b02004. Epub 2017 Oct 11.
Here, we present atmospheric pressure photoionization (APPI) Fourier transform ion cyclotron resonance (FTICR) mass analysis of a volcanic asphalt sample by acquiring data for 20 Da wide mass segments across a 1000 Da range, stitched into a single composite mass spectrum, and compare to a broad-band mass spectrum for the same sample. The segmented spectrum contained 170 000 peaks with magnitude greater than 6σ of the root-mean-square (rms) baseline noise, for which 126 264 unique elemental compositions could be assigned. Approximately two-thirds of those compositions represent monoisotopic (i.e., chemically different) species. That complexity is higher than that for any previously reported mass spectrum and almost 3 times greater than that obtained from the corresponding broad-band spectrum (59 015). For the segmented mass spectrum, the signal-to-noise ratio (S/N) was significantly higher throughout the spectrum, but especially at the lower and upper ends of mass distribution relative to that of the near-Gaussian broad-band mass distribution. Despite this S/N improvement, mass measurement accuracy was noticeably improved only at lower masses. The increased S/N did, however, yield a higher number of peaks and higher dynamic range throughout the entire segmented spectrum relative to the conventional broad-band spectrum. The additional assigned peaks include higher heteroatom species, as well as additional radicals and isotopologues. Segmenting can require a significant investment in data acquisition and analysis time over broad-band spectroscopy (∼1775% in this case) making it best suited for targeted analysis and/or when complete compositional coverage is important. Finally, the present segmented spectrum contains, to our knowledge, more assigned peaks than any spectrum of any kind (e.g., UV-vis, infrared, microwave, magnetic resonance, etc.).
在此,我们通过获取1000 Da范围内20 Da宽质量段的数据,对火山沥青样品进行了大气压光电离(APPI)傅里叶变换离子回旋共振(FTICR)质谱分析,将这些数据拼接成一个单一的复合质谱,并与同一样品的宽带质谱进行比较。分段质谱包含170000个峰,其幅度大于均方根(rms)基线噪声的6σ,其中126264个独特的元素组成可以被确定。这些组成中大约三分之二代表单同位素(即化学性质不同)的物种。这种复杂性高于任何先前报道的质谱,几乎是从相应宽带质谱(59015个)获得的复杂性的3倍。对于分段质谱,整个谱图中的信噪比(S/N)显著更高,尤其是在质量分布的低端和高端相对于近高斯宽带质量分布而言。尽管信噪比有所提高,但质量测量精度仅在较低质量处有明显改善。然而,相对于传统宽带质谱,信噪比的提高确实在整个分段谱图中产生了更多的峰和更高的动态范围。额外确定的峰包括更高的杂原子物种,以及额外的自由基和同位素异构体。与宽带光谱相比,分段分析可能需要在数据采集和分析时间上投入大量精力(在这种情况下约为1775%),这使得它最适合于靶向分析和/或当完整的成分覆盖很重要时。最后,据我们所知,目前的分段质谱包含的确定峰比任何类型的谱图(如紫外可见光谱、红外光谱、微波光谱、磁共振光谱等)都要多。