@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{LindnerBurgerRutledgeetal.2022,
  author    = {Lindner, Simon and Burger, Ren{\´e} and Rutledge, Douglas N. and Do, Xuan Tung and Rumpf, Jessica and Diehl, Bernd W. K. and Schulze, Margit and Monakhova, Yulia},
  title     = {Is the calibration transfer of multivariate calibration models between high- and low-field NMR instruments possible? A case study of lignin molecular weight},
  series = {Analytical chemistry},
  volume    = {94},
  journal   = {Analytical chemistry},
  number    = {9},
  publisher = {ACS Publications},
  address   = {Washington, DC},
  isbn      = {1520-6882},
  doi       = {10.1021/acs.analchem.1c05125},
  pages     = {3997 -- 4004},
  year      = {2022},
  abstract  = {Although several successful applications of benchtop nuclear magnetic resonance (NMR) spectroscopy in quantitative mixture analysis exist, the possibility of calibration transfer remains mostly unexplored, especially between high- and low-field NMR. This study investigates for the first time the calibration transfer of partial least squares regressions [weight average molecular weight (Mw) of lignin] between high-field (600 MHz) NMR and benchtop NMR devices (43 and 60 MHz). For the transfer, piecewise direct standardization, calibration transfer based on canonical correlation analysis, and transfer via the extreme learning machine auto-encoder method are employed. Despite the immense resolution difference between high-field and low-field NMR instruments, the results demonstrate that the calibration transfer from high- to low-field is feasible in the case of a physical property, namely, the molecular weight, achieving validation errors close to the original calibration (down to only 1.2 times higher root mean square errors). These results introduce new perspectives for applications of benchtop NMR, in which existing calibrations from expensive high-field instruments can be transferred to cheaper benchtop instruments to economize.},
  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}
}