TY - GEN A1 - Kern, Simon T1 - Reading between the lines – Automated data analysis for low field NMR spectra N2 - For reaction monitoring and process control using NMR instruments, in particular, after acquisition of the FID the data needs to be corrected in real-time for common effects using fast interfaces and automated methods. When it comes to NMR data evaluation under industrial process conditions, the shape of signals can change drastically due to nonlinear effects. Additionally, the multiplet structure becomes more dominant because of the comparably low-field strengths which results in overlapping of multiple signals. However, the structural and quantitative information is still present but needs to be extracted by applying predictive models. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modeling). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants, or derivatives and robust automation schemes. T2 - Small Molecule NMR Conference (SMASH) CY - Baveno, Italy DA - 17.09.2017 KW - Online NMR spectroscopy KW - Data analysis KW - Chemometrics KW - Indirect hard modeling KW - Spectral modeling KW - Line prediction KW - CONSENS KW - SMASH PY - 2017 UR - https://opus4.kobv.de/opus4-bam/frontdoor/index/index/docId/41949 AN - OPUS4-41949 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-419498 UR - http://www.smashnmr.org/conference/program AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany