TY - CONF A1 - Maiwald, Michael A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Kern, Simon T1 - Sustainable and Flexible Production of High Quality Chemicals and Pharmaceuticals Using Smart Sensors and Modular Production Units N2 - The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. The talk introduces a smart online NMR sensor module provided in an explosion proof housing as example. This sensor was developed for an intensified industrial process (pharmaceutical lithiation reaction step) funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs. The talk also generally covers current aspects of high-field and low-field online NMR spectroscopy for reaction monitoring and process control and gives also an overview on direct dissolution studies of API cocrystals. T2 - Chemistry Group Seminar Pfizer Inc. CY - La Jolla, California, USA DA - 09.03.2018 KW - Process Monitoring KW - Online NMR Spectroscopy KW - Smart Sensors KW - Indirect Hard Modeling KW - Modular Production KW - CONSENS PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-444382 AN - OPUS4-44438 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Quantitative NMR Spectroscopy Uncertainty Analysis Workshop N2 - qNMR provides the most universally applicable form of direct concentration or purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties. The workshop presents basic terms of statistics and uncertainty analysis, which are the basis for qNMR spectroscopy and data analysis such as, e.g., standard deviations, linear regression, significance tests, etc. and gives typical examples of applications in qNMR spectroscopy. T2 - Practical Applications of NMR in Industry Conference ​(PANIC) Validation Workshop 2018 CY - La Jolla, California, USA DA - 08.03.2018 KW - qNMR KW - NMR Validation KW - Basic Statistics KW - Linear Regression PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-444395 AN - OPUS4-44439 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Wander, Lukas A1 - Meyer, Klas A1 - Paul, Andrea T1 - Already Producing or Still Calibrating? – Advances of Model-Based Data Evaluation Concepts for Quantitative Online NMR Spectroscopy N2 - The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example. Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs. 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 Modelling and Quantum Mechanical calculations). Based on concentration measurements of reagents and products by the NMR analyzer a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (“Integrated CONtrol and SENsing”, www.consens-spire.eu). T2 - Practical Applications of NMR in Industry Conference (PANIC) 2018 CY - La Jolla, California, USA DA - 04.03.2018 KW - Process Monitoring KW - Process Control KW - Process analytical technology KW - Spectral Modeling KW - Smart Sensors KW - CONSENS KW - Industrie 4.0 PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-444357 AN - OPUS4-44435 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -