@article{BurgerRumpfDoetal.2021,
  author    = {Burger, Ren{\´e} and Rumpf, Jessica and Do, Xuan Tung and Monakhova, Yulia and Diehl, Bernd W. K. and Rehahn, Matthias and Schulze, Margit},
  title     = {Is NMR combined with multivariate regression applicable for the molecular weight determination of randomly cross-linked polymers such as lignin?},
  series = {ACS Omega},
  volume    = {6},
  journal   = {ACS Omega},
  number    = {44},
  publisher = {ACS Publications},
  address   = {Washington, DC},
  issn      = {2470-1343},
  doi       = {10.1021/acsomega.1c03574},
  pages     = {29516 -- 29524},
  year      = {2021},
  abstract  = {The molecular weight properties of lignins are one of the key elements that need to be analyzed for a successful industrial application of these promising biopolymers. In this study, the use of 1H NMR as well as diffusion-ordered spectroscopy (DOSY NMR), combined with multivariate regression methods, was investigated for the determination of the molecular weight (Mw and Mn) and the polydispersity of organosolv lignins (n = 53, Miscanthus x giganteus, Paulownia tomentosa, and Silphium perfoliatum). The suitability of the models was demonstrated by cross validation (CV) as well as by an independent validation set of samples from different biomass origins (beech wood and wheat straw). CV errors of ca. 7-9 and 14-16\% were achieved for all parameters with the models from the 1H NMR spectra and the DOSY NMR data, respectively. The prediction errors for the validation samples were in a similar range for the partial least squares model from the 1H NMR data and for a multiple linear regression using the DOSY NMR data. The results indicate the usefulness of NMR measurements combined with multivariate regression methods as a potential alternative to more time-consuming methods such as gel permeation chromatography.},
  language  = {en}
}
@article{BurgerLindnerRumpfetal.2022,
  author    = {Burger, Ren{\´e} and Lindner, Simon and Rumpf, Jessica and Do, Xuan Tung and Diehl, Bernd W.K. and Rehahn, Matthias and Monakhova, Yulia and Schulze, Margit},
  title     = {Benchtop versus high field NMR: Comparable performance found for the molecular weight determination of lignin},
  series = {Journal of Pharmaceutical and Biomedical Analysis},
  volume    = {212},
  journal   = {Journal of Pharmaceutical and Biomedical Analysis},
  number    = {Article number: 114649},
  publisher = {Elsevier},
  address   = {New York, NY},
  isbn      = {0731-7085},
  doi       = {10.1016/j.jpba.2022.114649},
  year      = {2022},
  abstract  = {Lignin is a promising renewable biopolymer being investigated worldwide as an environmentally benign substitute of fossil-based aromatic compounds, e.g. for the use as an excipient with antioxidant and antimicrobial properties in drug delivery or even as active compound. For its successful implementation into process streams, a quick, easy, and reliable method is needed for its molecular weight determination. Here we present a method using 1H spectra of benchtop as well as conventional NMR systems in combination with multivariate data analysis, to determine lignin's molecular weight (Mw and Mn) and polydispersity index (PDI). A set of 36 organosolv lignin samples (from Miscanthus x giganteus, Paulownia tomentosa and Silphium perfoliatum) was used for the calibration and cross validation, and 17 samples were used as external validation set. Validation errors between 5.6\% and 12.9\% were achieved for all parameters on all NMR devices (43, 60, 500 and 600 MHz). Surprisingly, no significant difference in the performance of the benchtop and high-field devices was found. This facilitates the application of this method for determining lignin's molecular weight in an industrial environment because of the low maintenance expenditure, small footprint, ruggedness, and low cost of permanent magnet benchtop NMR systems.},
  language  = {en}
}