المؤلفون: Gergő Róth (11534005), Tibor Nagy (425445), Ákos Kuki (1968994), Mahir Hashimov (8443188), Zsófia Vonza (11534008), István Timári (2035315), Miklós Zsuga (1968991), Sándor Kéki (1968988)

مصطلحات موضوعية: Biochemistry, Medicine, Physiology, Space Science, Chemical Sciences not elsewhere classified, quick visual recognition, polymer chain lengths, homemade software enables, ethylene oxide contents, average molecular weights, average molecular weight, approximately 4000 g, novel copolymer quantity, composition drift curves, copolymer mass spectra, copolymer composition, mass spectrometry, compositional drift, triblock copolymer, visualization methods, species present, small variations, robust algorithm, relative abundance, relation allows, paramount importance, e ., determined number, data processing, compositional assignment

Relation: https://figshare.com/articles/journal_contribution/Polydispersity_Ratio_and_Its_Application_for_the_Characterization_of_Poloxamers/16764271

الاتاحة: https://doi.org/10.1021/acs.macromol.1c01552.s001

المؤلفون: Gergő Róth (11534005), Tibor Nagy (425445), Ákos Kuki (1968994), Mahir Hashimov (8443188), Zsófia Vonza (11534008), István Timári (2035315), Miklós Zsuga (1968991), Sándor Kéki (1968988)

مصطلحات موضوعية: Biochemistry, Medicine, Physiology, Space Science, Chemical Sciences not elsewhere classified, quick visual recognition, polymer chain lengths, homemade software enables, ethylene oxide contents, average molecular weights, average molecular weight, approximately 4000 g, novel copolymer quantity, composition drift curves, copolymer mass spectra, copolymer composition, mass spectrometry, compositional drift, triblock copolymer, visualization methods, species present, small variations, robust algorithm, relative abundance, relation allows, paramount importance, e ., determined number, data processing, compositional assignment

Relation: https://figshare.com/articles/dataset/Polydispersity_Ratio_and_Its_Application_for_the_Characterization_of_Poloxamers/16764274

الاتاحة: https://doi.org/10.1021/acs.macromol.1c01552.s002