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 - TY - JOUR A1 - Kern, Simon A1 - Liehr, Sascha A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Müller, S. A1 - Maiwald, Michael A1 - Kowarik, Stefan T1 - Artificial neural networks for quantitative online NMR spectroscopy N2 - Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger Training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data. KW - Online NMR spectroscopy KW - Real-time process monitoring KW - Artificial neural networks KW - Automation KW - Process industry PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-507508 DO - https://doi.org/10.1007/s00216-020-02687-5 SN - 1618-2642 VL - 412 IS - 18 SP - 4447 EP - 4459 PB - Springer CY - Berlin AN - OPUS4-50750 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Balderas-Xicohtencatl, R. A1 - Villajos Collado, José Antonio A1 - Casabán, J. A1 - Wong, D. A1 - Maiwald, Michael A1 - Hirscher, M. T1 - ZIF‑8 Pellets as a Robust Material for Hydrogen Cryo-Adsorption Tanks N2 - Cryoadsorption on the inner surface of porous materials is a promising solution for safe, fast, and reversible hydrogen storage. Within the class of highly porous metal−organic frameworks, zeolitic imidazolate frameworks (ZIFs) show high thermal, chemical, and mechanical stability. In this study, we selected ZIF-8 synthesized mechanochemically by twin-screw extrusion as powder and pellets. The hydrogen storage capacity at 77 K and up to 100 bar has been analyzed in two laboratories applying three different measurement setups showing a high reproducibility. Pelletizing ZIF-8 increases the packing density close to the corresponding value for a single crystal without loss of porosity, resulting in an improved volumetric hydrogen storage capacity close to the upper limit for a single crystal. The high volumetric uptake combined with a low and constant heat of adsorption provides ca. 31 g of usable hydrogen per liter of pellet assuming a temperature−pressure swing adsorption process between 77 K − 100 bar and 117 K − 5 bar. Cycling experiments do not indicate any degradation in storage capacity. The excellent stability during preparation, handling, and operation of ZIF-8 pellets demonstrates its potential as a robust adsorbent material for technical application in pilot- and full-scale adsorption vessel prototypes. KW - Hydrogen adsorption storage KW - Metal−organic frameworks KW - ZIF-8 KW - Cryoadsorption KW - Hydrogen Storage KW - MefHySto PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-569473 DO - https://doi.org/10.1021/acsaem.2c03719 SN - 2574-0962 SP - 1 EP - 8 PB - ACS Publications CY - Washington DC AN - OPUS4-56947 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bornemann-Pfeiffer, Martin A1 - Kern, Simon A1 - Maiwald, Michael A1 - Meyer, Klas T1 - Calibration-Free Chemical Process and Quality Control Units as Enablers for Modular Production N2 - Modular chemical production is a tangible translation of the digital transformation of the process industry for specialty chemicals. In particular, it enables the speeding-up of process development and thus a quicker time to market by flexibly connecting and orchestrating standardised physical modules and bringing them to life (i.e., parameterising them) with digitally accumulated process knowledge. We focus on the specific challenges of chemical process and quality control, which in its current form is not well suited for modular production and provide possible approaches and examples of the change towards direct analytical methods, analytical model transfer or machine-supported processes. KW - Modular Production KW - Chemical Process Control KW - Process Analytical Technology KW - Digital Transformation KW - Industry 4.0 PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-517264 DO - https://doi.org/10.1002/cite.202000150 SN - 1522-2640 VL - 93 IS - 1-2 SP - 62 EP - 70 PB - Wiley-VCH CY - Weinheim AN - OPUS4-51726 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Paul, Andrea A1 - Ruiken, J.-P. A1 - Westad, Frank A1 - Illner, M. A1 - Müller, D. A1 - Esche, E. A1 - Repke, J.-U. A1 - Maiwald, Michael T1 - Online Spectroscopy in Microemulsions – A Process Analytical Approach for a Hydroformylation Mini-plant N2 - Within the Collaborative Research Center InPROMPT a novel process concept for the hydroformylation of long-chained olefins is studied in a mini-plant, using a rhodium complex as catalyst in the presence of syngas. Recently, the hydroformylation in micro¬emulsions, which allows for the efficient recycling of the expensive rhodium catalyst, was found to be feasible. However, the high sensitivity of this multi-phase system with regard to changes in temperature and composition demands a continuous observation of the reaction to achieve a reliable and economic plant operation. For that purpose, we tested the potential of both online NMR and Raman spectroscopy for process control. The lab-scale experiments were supported by off-line GC-analysis as a reference method. A fiber optic coupled probe of a process Raman spectrometer was directly integrated into the reactor. 25 mixtures with varying concentrations of olefin (1-dodecene), product (n-tridecanal), water, n-dodecane, and technical surfactant (Marlipal 24/70) were prepared according to a D-optimal design. Online NMR spectroscopy was implemented by using a flow probe equipped with 1/16” PFA tubing serving as a flow cell. This was hyphenated to the reactor within a thermostated bypass to maintain process conditions in the transfer lines. Partial least squares regression (PLSR) models were established based on the initial spectra after activation of the reaction with syngas for the prediction of unknown concentrations of 1-dodecene and n-tridecanal over the course of the reaction in the lab-scale system. The obtained Raman spectra do not only contain information on the chemical composition but are further affected by the emulsion properties of the mixtures, which depend on the phase state and the type of micelles. Based on the spectral signature of both Raman and NMR spectra, it could be deduced that especially in reaction mixtures with high 1-dodecene content the formation of isomers as a competitive reaction was dominating. Similar trends were also observed during some of the process runs in the mini-plant. The multivariate calibration allowed for the estimation of reactants and products of the hydroformylation reaction in both laboratory setup and mini-plant. T2 - 4th European Conference on Process Analytics and Control Technology (EuroPACT 2017) CY - Potsdam, Germany DA - 10.05.2017 KW - Microemulsions KW - Process Analytical Technology KW - Reaction Monitoring KW - Online NMR Spectroscopy KW - Online Raman Spectroscopy PY - 2017 SP - 64 EP - 64 CY - Frankfurt a. M. AN - OPUS4-40228 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Paul, Andrea A1 - Wander, Lukas A1 - Gräßer, Patrick A1 - Maiwald, Michael T1 - Design and Validation of a Compact NMR Analyser N2 - Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and relatively inexpensive analysers, which feature advantages like low cost, low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, sufficient robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack. Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. If these are not available, there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Unionʼs Research Project CONSENS (Integrated Control and Sensing) by development and integration of smart sensor modules for process monitoring and control within such modular plant setups. The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling (IHM) was selected for data analysis of the low-field NMR spectra. A set-up for monitoring continuous reactions in a thermostated 1/8” tubular reactor using automated syringe pumps was used to validate the IHM models by using high-field NMR spectroscopy as analytical reference method. T2 - 4th European Conference on Process Analytics and Control Technology (EuroPACT 2017) CY - Potsdam, Germany DA - 10.05.2017 KW - Prozessanalytik KW - Reaction Monitoring KW - Online NMR Spectrsocopy KW - Process Analytical Technology KW - Industrie 4.0 KW - EuroPACT PY - 2017 SP - 72 EP - 73 CY - Frankfurt a. M. AN - OPUS4-40229 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Maiwald, Michael A1 - Sperling, M. A1 - Huber, C. A1 - Hayen, H. A1 - Teutenberg, T. A1 - Belder, D. A1 - Karst, U. A1 - Hagenhoff, B. A1 - Vogel, M. T1 - Prozessanalytik: Spektroskopie und Miniaturisierung N2 - Forderungen nach höherer Geschwindigkeit und die Komplexität der Fragen geben der analytischen Chemie neue Impulse. So nutzt die Prozessanalytik gepulste Ramanspektrometer, die Elemente Arsen und Quecksilber dominieren die Forschung in der Speziesanalytik, und die Omics-Techniken entwickeln sich zu Multi-Omics-Ansätzen. Ambiente MS-Techniken benötigen keine aufwendige Probenvorbereitung, multidimensionale Trenntechniken werden verstärkt in der Routine eingesetzt, und Chip-basierte Trennungen fallen durch Schnelligkeit auf. Molekülspektroskopie und Massenspektrometrie dominieren die bildgebenden Verfahren, und die Lateralauflösung der ToF-Sekundärionenmassenspektrometrie hat sich bei Oberflächenuntersuchungen verbessert. KW - Prozessanalytik KW - Quanten-Kaskadenlaser KW - Photonendichtewellen-Spektroskopie KW - Gepulste Ramanspektrometer KW - Partikelmesstechnik KW - Prozesssensoren PY - 2016 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-361371 UR - http://onlinelibrary.wiley.com/doi/10.1002/nadc.20164046080/abstract DO - https://doi.org/10.1002/nadc.20164046080 SN - 1868-0054 VL - 64 IS - 5 SP - 497 EP - 508 PB - Wiley-VCH Verlag GmbH & Co. KGaA CY - Weinheim AN - OPUS4-36137 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Zientek, Nicolai A1 - Meyer, Klas A1 - Kern, Simon T1 - Low field NMR spectroscopy for online monitoring N2 - Online NMR spectroscopy is an excellent tool to study complex reacting multicomponent mixtures and gain process insight and understanding. For online studies under process conditions, flow NMR probes can be used in a wide range of temperature and pressure. This paper compiles the most important aspects towards quantitative process NMR spectroscopy in complex multicomponent mixtures and provides examples. After NMR spectroscopy is introduced as an online method and for technical samples without sample preparation in deuterated solvents, influences of the residence time distribution, pre-magnetization, and cell design are discussed. NMR acquisition and processing parameters as well as data preparation methods are presented and the most practical data analysis strategies are introduced. T2 - Sonderkolloquium der INVITE-GmbH CY - Leverkusen, Germany DA - 07.09.2016 KW - Industrie 4.0 KW - CONSENS KW - Prozessanalytik KW - Online NMR spectroscopy PY - 2015 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-361417 AN - OPUS4-36141 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Zientek, Nicolai A1 - Laurain, Clement A1 - Meyer, Klas A1 - Paul, Andrea A1 - Engel, D. A1 - Kraume, M. A1 - Guthausen, G. T1 - Automated Data Evaluation and Modeling of Simultaneous 19F-1 H Benchtop NMR Spectra for Online Reactin Monitoring N2 - Benchtop nuclear magnetic resonance spectroscopy currently develops to an important analytical tool for both quality control and process monitoring. In contrast to high resolution online NMR (HR-NMR), benchtop NMR can be operated under rough environmental conditions. A continuous re-circulating stream of reaction mixture from the reaction vessel to the NMR spectrometer enables a non-invasive, volume integrating online analyses of reactants and products. Here we investigated the esterification of 2,2,2-trifluoroethanol with acetic acid to 2,2,2-trifluoroethyl acetate both by 1H HR-NMR (500 MHz) and 1H and 19F MR NMR (43 MHz and 40 MHz) as a model system. The parallel online measurement was realized by splitting the flow, which allowed the adjustment of quantitative and independent flow rates, both in the benchtop NMR probe as well as in the HR-NMR probe, in ad-dition to a fast bypass line back to the reactor. T2 - SMASH 2015 (Small Molecules NMR Conference) CY - Baveno, Italy DA - 20.09.2015 PY - 2015 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-351645 AN - OPUS4-35164 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -