A fast algorithm for automated feature mining of synthetic (industrial) homopolymers or perfectly alternating copolymers was developed. Comprehensive two-dimensional liquid chromatography–mass spectrometry data (LC × LC–MS) was utilized, undergoing four distinct parts within the algorithm. Initially, the data is reduced by selecting regions of interest within the data. Then, all regions of interest are clustered on the time and mass-to-charge domain to obtain isotopic distributions. Afterward, single-value clusters and background signals are removed from the data structure. In the second part of the algorithm, the isotopic distributions are employed to define the charge state of the polymeric units and the charge-state reduced masses of the units are calculated. In the third part, the mass of the repeating unit ( i.e. , the monomer) is automatically selected by comparing all mass differences within the data structure. Using the mass of the repeating unit, mass remainder analysis can be performed on the data. This results in groups sharing the same end-group compositions. Lastly, combining information from the clustering step in the first part and the mass remainder analysis results in the creation of compositional series, which are mapped on the chromatogram. Series with similar chromatographic behavior are separated in the mass-remainder domain, whereas series with an overlapping mass remainder are separated in the chromatographic domain. These series were extracted within a calculation time of 3 min. The false positives were then assessed within a reasonable time. The algorithm is verified with LC × LC–MS data of an industrial hexahydrophthalic anhydride-derivatized propylene glycol-terephthalic acid copolyester. Afterward, a chemical structure proposal has been made for each compositional series found within the data.

Trapped ion-mobility spectrometry combined with quadrupole time-of-flight mass spectrometry (TIMS-QTOFMS) was evaluated as a tool for resolving linear and branched isomeric polyester oligomers. Solutions of polyester samples were infused directly into the ion source employing electrospray ionization (ESI). TIMS-MS provides both mobility and m / z data on the formed ions, allowing construction of extracted-ion mobilograms (EIMs). EIMs of polyester molecules showed multimodal patterns, indicating conformational differences among isomers. Subsequent TIMS-MS/MS experiments indicated mobility differences to be caused by (degree of) branching. These assignments were supported by liquid chromatography-TIMS-MS/MS analysis, confirming that direct TIMS-MS provided fast (500 ms/scan) distinction between linear and branched small oligomers. Observing larger oligomers (up to 3000 Da) using TIMS required additional molecular charging to ensure ion entrapment within the mobility window. Molecular supercharging was achieved using m -nitrobenzyl alcohol (NBA). The additional charges on the oligomer structures enhanced mobility separation of isomeric species but also added to the complexity of the obtained fragmentation mass spectra. This complexity could be partly reduced by post-TIMS analyte-decharging applying collision-induced dissociation (CID) prior to Q1 with subsequent isolation of the singly charged ions for further fragmentation. The as-obtained EIM profiles were still quite complex as larger molecules possess more possible structural isomers. Nevertheless, distinguishing between linear and symmetrically branched oligomers was possible based on measured differences in collisional cross sections (CCSs). The established TIMS-QTOFMS approach reliably allows branching information on isomeric polyester molecules up to 3000 Da to be obtained in less than 1 min analysis time.