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Trash to treasure: recovery of transition metal phosphates for (electro-)catalytical applications
(2022)
Wastewaters containing high concentrations of NH4+, PO43- and transition metals are environmentally harmful and toxic pollutants. At the same time phosphorous and transition metals constitute valuable resources. Here, we report the synthesis routes for Co- and Ni-struvites (NH4MPO4∙6H2O, M = Ni2+, Co2+) out of aqueous solutions resembling synthetic/industrial waste water compositions, and allowing for P, ammonia and metal co-precipitation. Furthermore, the as-obtained struvites were further up-cycled. When heated, these transition metal phosphates (TMPs) demonstrate significant changes in the degree of crystallinity/coordination environment involving a high amount of amorphous phases and importantly develop mesoporosity (Figure 1). In this regard, amorphous and mesoporous TMPs are known to be highly promising (electro-)catalysts.
Amorphous phases do not represent a simple “disordered” crystal but more a complex system with a broad range of compositions and physicochemical properties, which remain mostly unknown. Consequently, we investigated the recrystallization and amorphization process during thermal treatment and a resolved the complex amorphous/crystalline structures (Figure 2). As a proof-of-principle for their applicational use, the as-obtained TMPs demonstrate significant proton conductivity properties similar to apatite-like structures from room to high temperatures (>800°C).
Hence, we have developed a promising recycling route in which environmental harmful contaminants like PO43-, NH4+ and 3d metals would be extracted out of waste waters in the form of precursor raw materials. These raw materials can be then further up-cycled through a simple thermal treatment for their specific application in electrocatalysis.
The successful shift to NDE 4.0 will not only require developing and embracing new technologies associated with the fourth industrial revolution or becoming an integral part of the overall Industry 4.0, but also developing and adopting new ways of working. It is undoubtful that people will remain in charge of the inspections. However, it is arguable if the current “procedure-following” “level I-III” paradigm can withstand the changes that come along NDE 4.0. With the increased autonomy and interconnectedness expected with NDT 4.0, the majority of traditional NDE tasks will no longer be needed. Instead, different skills, such as that of programming and adapting systems, as well as problem solving, will become vital for the inspections. Therefore, we suggest that a new paradigm is needed—one in which inspector roles and, thus, also the requirements will have to be reinvented. We expect the inspectors to be relieved from the tedious and error prone aspects of the current system and to take responsibility for increasingly complex automated systems and work in closer collaboration with other experts. Thus, we propose that the traditional inspector roles will be transformed into that of the system developer, caretaker and problem solver, each requiring a specific set of skills and assuming different responsibilities. In this talk, we will present the new roles and discuss the challenges that may arise with them.
Typically, the near-eutectic Al-Si alloys consist of highly interconnected three-dimensional network of the eutectic Silicon (Si) and intermetallics embedded into Aluminium (Al) matrix. For further improvement of the mechanical properties of such alloys, often, one single ceramic reinforcement phase, e.g. silicon carbide (SiC) or aluminium oxide (Al2O3) in the form of fibres or particles is added. However, hybrid reinforcements (fibres and particles) can further improve wear resistance and fracture toughness, and additionally, reduce anisotropy of the material. The engineering of metal matrix composites (MMC) for specific application requirements benefits from a comprehensive knowledge of the failure behaviour. Therefore, damage evolution under compression was investigated on:
- pure near-eutectic AlSi12CuMgNi matrix alloy
- type I: matrix reinforced with random-planar oriented Al2O3 short fibres (15 vol.%)
- type II: matrix reinforced with random-planar oriented Al2O3 short fibres (7 vol.%) and additional SiC particles (15 vol.%)
The analysis of damage mechanism was carried out in two rather independent but complementary studies. First, selected sister samples of every material were exposed to quasi-static compression (traverse control). The compression tests were interrupted at different strain levels. Miniature cylinders with a diameter of 1mm were extracted from the pre-strained samples and investigated by synchrotron computed tomography (SX-µCT) with a spatial resolution of about 0.7 µm. For the pure matrix alloy, microcracks are confined to the intermetallic particles and to the eutectic Si, hence no damage was observed in the Aluminium. The composite type II revealed a more effective strain accumulation (less damage) than type I at low plastic strain (up to 5 %), but a more catastrophic damage development due to cracking of the SiC clusters at higher strain levels.
The second approach to study the damage initiation and accumulation in the materials subjected to compressive load was Acoustic Emission (AE) analysis. In this case the in-situ monitoring of the acoustic emission signal was performed during compression tests on specimens with dimension of several mm. For all three material types, AE activity set at 2% strain. Differences in AE behaviour of the three materials was proven based on AE hitrate, signal peak amplitudes as well as weighted peak frequencies (WPF). Future work focuses on combination of AE and SX-µCT aiming for more detailed knowledge on damage mechanism of metal matrix composites.
Nanomaterials bring various benefits and have become a part of our daily lives. However, the risks emerging from nanotechnology need to be minimized and controlled at the regulatory level and therefore, there is a need for nanorisk governance. One of the prerequisites for successful nanorisk governance is the availability of high-quality data on nanomaterials and their impact with the human body and the environment. In recent decades, a countless number of publications and studies on nanomaterials and their properties have been produced due to the fast development of nanotechnology. Despite such a vast amount of data and information, there are certain knowledge gaps hindering an efficient nanorisk governance process. Knowing the state of the available data and information is an important requirement for any decision maker in dealing with risks. In the specific case of nanotechnology, where most of the risks are complex, ambiguous, and uncertain in nature, it is essential to obtain complete data and metadata, to fill knowledge gaps, and to transform the available knowledge into functional knowledge. This can become possible using a novel approach developed within the NANORIGO project (Grant agreement No. 814530) – the Knowledge Readiness Level (KaRL). In analogy to NASA’s Technology Readiness Levels (TRLs), we define KaRLs as a categorization system of data, information, and knowledge which enables transformation of data and information into functional knowledge for nanorisk governance. Our approach goes beyond the technical curation of data and metadata and involves quality and completeness filters, regulatory compliance requirements, nanorisk-related tools, and most importantly, human input (inclusion of all stakeholder groups). With the KaRL approach we also address key issues in nanotechnology such as societal and ethical concerns, circular economies and sustainability, the Green Deal, and the traceability of data, knowledge, and decisions. The KaRL approach could be used for nanorisk governance by a nanorisk governance council (NRGC), which is currently under development by three EU projects (NANORIGO, GOV4NANO, and RISKGONE).
Nanomaterials bring various benefits and have become a part of our daily lives. However, the risks emerging from nanotechnology need to be minimized and controlled at the regulatory level and therefore, there is a need for nanorisk governance. One of the prerequisites for successful nanorisk governance is the availability of high-quality data on nanomaterials and their impact with the human body and the environment. In recent decades, a countless number of publications and studies on nanomaterials and their properties have been produced due to the fast development of nanotechnology. Despite such a vast amount of data and information, there are certain knowledge gaps hindering an efficient nanorisk governance process. Knowing the state of the available data and information is an important requirement for any decision maker in dealing with risks. In the specific case of nanotechnology, where most of the risks are complex, ambiguous, and uncertain in nature, it is essential to obtain complete data and metadata, to fill knowledge gaps, and to transform the available knowledge into functional knowledge. This can become possible using a novel approach developed within the NANORIGO project (Grant agreement No. 814530) – the Knowledge Readiness Level (KaRL). In analogy to NASA’s Technology Readiness Levels (TRLs), we define KaRLs as a categorization system of data, information, and knowledge which enables transformation of data and information into functional knowledge for nanorisk governance. Our approach goes beyond the technical curation of data and metadata and involves quality and completeness filters, regulatory compliance requirements, nanorisk-related tools, and most importantly, human input (inclusion of all stakeholder groups). With the KaRL approach we also address key issues in nanotechnology such as societal and ethical concerns, circular economies and sustainability, the Green Deal, and the traceability of data, knowledge, and decisions. The KaRL approach could be used for nanorisk governance by a nanorisk governance council (NRGC), which is currently under development by three EU projects (NANORIGO, GOV4NANO, and RISKGONE).
Regulatory decisions require reliable data and knowledge derived from this. Among stakeholders in nanotechnology, however, there is often uncertainty about the quality of data for regulatory purposes. In addition, the general public often finds itself excluded from nanoregulation and policy decisions. This creates uncertainty in the nanotechnology field and also in other branches of technology and leads to concerns among the society.
To address these issues, NANORIGO elaborates a framework to support decision making as well as data, information and knowledge sharing and use. We refer to “reliability” of data and knowledge as a degree of readiness or maturity. According to these criteria we worked out a 9-level scale in analogy to TRL (technology readiness level), the KaRL system (Knowledge, Data and Information Readiness Level). KaRL allows assessment of knowledge readiness for decision making by applying defined quality criteria for each level. It also provides guidance on how to enhance the readiness level by the help of available tools and procedures. KaRL addresses SEIN[1] principles, circular economy and thus involves the public concerns in regulation. A specialized nanorisk governance council (being under development in NANORIGO) is suggested to perform quality check of an actionable document, thus, aiding in consensus on the reliability (maturity) of knowledge for decision making. Moreover, KaRL facilitates traceability of knowledge before its use in decision making. This enables the transparency demanded by all stakeholders.
Monitoring of reinforced concrete structures to ensure their stability and increase their service-life is a crucial element of a modern infrastructural concept. With classical methods of non-destructive testing and inspection, repeated measurements under comparable conditions are difficult to conduct. Therefore, DFG research unit FOR 2825 CoDA researches the assessment of concrete damage using ultrasound coda wave interferometry and embedded sensors. Embedding the sensors into the monitoring target reduces human and non-human factors influencing repeatability. Using Coda Wave Interferometry (CWI), small velocity changes in the material can be detected by comparison of repeated measurements. The technique is sensitive to damaging changes like cracking as well as to reversible influences like material temperature. The understanding of these different influences on the signal is crucial for the analysis of long-term monitoring data to make an educated assessment of the structure and its integrity. With several laboratory experiments in a climate chamber and a long-term experiment recording an annual cycle in a large model on an outdoor test site in Horstwalde close to Berlin, we try to understand the influence of temperature on the CWI results. The results show that the velocity change calculated by CWI does closely follow the trend of concrete temperature. After one year of data recording with the large model being exposed to environmental variations only, the calculated velocity change resembles the annual temperature curve. The data shows a linear dependency between velocity and temperature change in a range of -0.03 percent per °K to -0.06 percent per °K - regardless of specimen size. An approach to remove temperature influence from the yearly cycle recorded in the large-scale experiment using this linear relation is unable to remove high-frequency variations - especially daily influences. Low-pass filtering the data can eliminate these variations while preserving permanent shifts caused by damages. Although we have shown that the influence of temperature on long term monitoring can be removed to a significant extent, there is still an influence of environmental changes remaining in the data. Possible nonlinear effects and influences not related to temperature need to be investigated in the future.
In the field of non-destructive testing (NDT) in civil engineering, a large number of measurement data are collected. Although they serve as a basis for scientific analyses, there is still no uniform representation of the data. An analysis of various distributed data sets across different test objects is therefore only possible with high manual effort.
We present a system architecture for an integrated data management of distributed data sets based on Semantic Web technologies. The approach is essentially based on a mathematical model - the so-called ontology - which represents the knowledge of our domain NDT. The ontology developed by us is linked to data sources and thus describes the semantic meaning of the data. Furthermore, the ontology acts as a central concept for database access. Non-domain data sources can be easily integrated by linking them to the NDT construction ontology and are directly available for generic use in the sense of digitization. Based on an extensive literature research, we outline the possibilities that this offers for NDT in civil engineering, such as computer-aided sorting, analysis, recognition and explanation of relationships (explainable AI) for several million measurement data.
The expected benefits of this approach of knowledge representation and data access for the NDT community are an expansion of knowledge through data exchange in research (interoperability), the scientific exploitation of large existing data sources with data-based methods (such as image recognition, measurement uncertainty calculations, factor analysis, material characterization) and finally a simplified exchange of NDT data with engineering models and thus with the construction industry.
Ontologies are already the core of numerous intelligent systems such as building information modeling or research databases. This contribution gives an overview of the range of tools we are currently creating to communicate with them.
X-ray back scatter imaging is rarely applied compared to classical X-ray projection imaging. 20 years ago the company Philips developed “COMSCAN”, a first application case in the aircraft industry, which allowed even a depth resolution using back scatter imaging. The company AS&E in Boston offers back scatter imaging solutions for the security market. Their principle is to scan the object with a highly collimated X-ray needle beam from one side only and detect the backscattered radiation by a large area detector side by side with the collimation wheel. A new prototype is investigated at BAM for application and optimization in non-destructive testing. As modern industrial application field in-situ testing in additive manufacturing is targeted. The accessibility of the printed part during the production process is very limited. This prevent the application of a two sided X-ray inspection or Computed Tomography, were an rotation of the object is required to acquire projections from 360 degrees. An important advantage for the X-ray back scatter technique are also the materials used in additive manufacturing (polymers, ceramics, light metals like Aluminum or Titanium). These materials with lower density and lower Z values give better scatter signals than metals with higher densities and Z values. The back scatter intensity decreases with increasing density and Z value of the material. But the requirements on spatial resolution and contrast sensitivity are more stringent for non-destructive testing of additive manufactured parts compared to the security area. In NDT sizes of indications smaller than 1 mm have to be detected clearly. The investigation of these limits on a stateof-the-art prototype for X-ray back scattering using rotating collimated X-ray needle beams is a part of the BAM project “ProMoAM”. The contribution shows first results of the optimization for NDT and the achieved application limits for several example cases.
The WelDX research project aims to foster the exchange of scientific data inside the welding community by developing and establishing a new open source file format suitable for documentation of experimental welding data and upholding associated quality standards. In addition to fostering scientific collaboration inside the national and international welding community an associated advisory committee will be established to oversee the future development of the file format. The proposed file format will be developed with regards to current needs of the community regarding interoperability, data quality and performance and will be published under an appropriate open source license.
By using the file format objectivity, comparability and reproducibility across different institutes and experimental setups can be improved.
The detection of cracks before the failure is highly significant when it comes to safety-relevant structures. Crack detection in metallic samples at high surface temperature is one of the challenging situation in manufacturing industries. Laser thermography has already proved its detection capability of surface cracks in metallic samples at room temperature. In this work a continuous wave (CW) laser use to generate a laser, which is using to scan the metal surface with notch. The corresponding heat distribution on the surface monitored using infrared thermal (IR) camera. A simplified 3D model for laser thermography is developed and validated with experimental results. A dedicated image processing algorithm developed to improve the detectability of the cracks. To understand the dependency of surface temperature, laser power, laser scanning speed etc. in defect detection, we carried out parametric studies with our validated model. Here we report the capability of laser thermography in crack detection at elevated temperature.
The compatible solute and osmolyte ectoine is an effective protectant of biomolecules and whole cells against heating, freezing and high salinity. The protection of cells (human Keratinocytes) by ectoine against ultraviolet radiation was also reported by various authors, although the underlying mechanism is not yet understood. We present results on the irradiation of biomolecules (DNA) with ionizing radiation (high energy electrons) in fully aqueous environment in the presence of ectoine and high salt concentrations. The results demonstrate an effective radiation protection of DNA by ectoine against the induction of single strand breaks by ionizing radiation. The effect is explained by an increased in low-energy electron scattering at the enhanced free-vibrational density of states of water due to ectoine, as well as the action of ectoine as an OH-radical scavenger. This was demonstrated by Raman spectroscopy, electron paramagnetic resonance (EPR) and Monte-Carlo simulations (Geant4).
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.
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.
Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction characterization and process control. Robust field integration of NMR systems have to face explosion protection or integration into process control systems with short set-up times. This paves the way for industrial automation in real process environments.
The design of failsafe, temperature and pressure resistant flow through cells along with their NMR-specific requirements is an essential cornerstone to enter industrial production plants and fulfill explosion safety requirements. Additionally, if fast reactions are monitored, suitable mixing devices need to be placed in close vicinity to the measuring volume to mix the reactants properly.
NMR-specific requirements aim at full quantitative pre-magnetization and acquisition with maximum sensitivity while reducing sample transfer times and dwell-times. All parameters are individually dependent on the applied NMR instrument.
Luckily, an increasing number of applications are reported together with an increasing variety of commercial equipment. However, these contributions have to be reviewed thoroughly.
The performance of sample flow cells commonly used in online analytics and especially for low-field NMR spectroscopy was experimentally and theoretically investigated by 1H-NMR experiments and numerical simulations. Especially, the applicability of 3D printed zirconium dioxide for innovative flow cell designs was of interest. Here, we demonstrate and discuss an automated test method to determine the critical parameters of flow through cells for quantitative online NMR spectroscopy. The setup is based on randomized setpoints of flow rates in order to reduce temperature related effects. Five flow cells and tubing were assessed and compared for high-field as well as low-field NMR spectrometers.
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).
Process analytical techniques are extremely useful tools for chemical production and manufacture and are of particular interest to the pharmaceutical, food and (petro-) chemical industries.
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.
A major advantage of NMR spectroscopy is that the method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method which is independent of the matrix. This is an important prerequisite for robust data evaluation strategies within a control concept and reduces the need for extensive maintenance of the evaluation model over the time of operation. Additionally, NMR spectroscopy provides orthogonal, but complimentary physical information to conventional, e.g., optical spectroscopy. It increases the accessible information for technical processes, where aromatic-to-aliphatic conversions or isomerizations occur and conventional methods fail due to only minor changes in functional groups.
As a technically relevant example, the catalytic hydrogenation of 2-butyne-1,4-diol and further pharmaceutical reactions were studied using an online NMR sensor based on a commercially available low-field NMR spectrometer within the framework of the EU project CONSENS (Integrated Control and Sensing).
The recent developments of inovative compact NMR spectrometers are therefore remarkable due to their possible application in process analytical technology (PAT) in an industrial environment without high maintenance requirements. spectroscopic methods, NMR spectroscopy offers some unique features for online reaction monitoring. However, those benefits have not been exploited for PAT applications so far. Within the CONSENS Project, the challenge to adapt a commercially available benchtop NMR spectrometer to the full requirements of an automated chemical production environment was tackled successfully. was provided in an explosion proof housing and involves a compact NMR spectrometer together with an automated data acquisition and evaluation unit, flow control, as well as data communication.
For reaction monitoring using NMR instruments, in particular, after acquisition of the FID the data needs to be corrected in real-time for common effects using automated methods. When it comes to NMR data evaluation under industrial process conditions, the shape of signals can change drastically due to nonlinear effects. However, the structural and quantitative information is still present but needs to be extracted by applying predictive models. Acquired raw spectra were processed with the following tools:
· Phase correction using the Entropy minimization method
· Baseline correction using a low-order Polynomial fit
· Alignment (icoshift) Pure component models based on Pseudo-Voigt functions can be derived via peak fitting of measured pure components or by the use of spin calculations.
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, which was developed for an intensified industrial process 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.
Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which are calibration intensive. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process monitoring and control.
Within the European Union’s Research Project CONSENS (Integrated CONtrol and SENsing, www.consens-spire.eu) by development and integration of a smart NMR module for process monitoring was designed and delivers online spectra of various reactions. The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation.
For reaction monitoring and process control using NMR instruments 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 Modelling and Quantum Mechanical calculations). 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.
Simple calibration concept of an online NMR module demonstrated in a modularised production plant
(2017)
Monitoring specific information (such as physico-chemical properties, chemical re-actions, etc.) is the key to chemical process control. Within the CONSENS Project, the challenge to adapt a commercially available benchtop NMR spectrometer to the full requirements of an automated chemical production environment was tack-led. The developed online NMR module was provided in an explosion proof housing and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit, a programmable logic controller for automated triggering, flow con-trol, as well as data communication.
First results of an aromatic coupling reaction in lab scale showed a general feasibil-ity according to the signal information in the acquired NMR spectra even though with a considerable overlap. Due to the comparatively low field strength of the NMR spectrometer multivariate methods had to be considered for the prediction of con-centration profiles based on spectral data. Typically, for industrial application of those methods, e.g. Partial Least Squares Regression (PLS-R) as well as Indirect Hard Modeling, large amount of calibration data is demanded, which must be ac-quired in time consuming lab-scale experiments and offline analytics. When it comes to changes in raw materials (e.g., varying functional groups, additional stabi-lizing agents) calibration experiments and data evaluation models are developed again. Here we present an approach of automated data analysis tools for low field NMR spectra with minimal calibration effort. The algorithms are based on Indirect Hard Modeling, whereby each component in each mixture spectra can be rep-resented by several flexible peak functions (pure component models). This means, that only pure component NMR spectra are needed to generate a first evaluation model. The flexibility of peak functions in the spectral model can be adjusted via constraints of peak parameters. The area of any pure component model can either be converted to concentrations based on a one-point calibration on raw material concentration or even neat solvent signals. In several cases it has been shown, the IHM works almost independently of the matrix of the real samples. Such a calibration can be repeated daily in the beginning of each process run with minimal time effort. Moreover, additional pure components can be added to the model or even substitut-ed while keeping the previously adjusted peak function constraints. The proposed method exhibited good agreement of resulting concentration data from low field NMR spectra, when compared to an online high field NMR spectrometer as refer-ence instrument.
Monitoring chemical reactions is the key to process control. Today, mainly optical online methods are applied, which are calibration intensive. NMR spectroscopy has a high potential for direct loop process control while cutting the calibration and validation needs to an minimum and thus exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process monitoring and control.
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. Data analysis techniques are available but currently mostly used for off-line data analysis to detect the causes of variations in the product quality.
This is addressed within the EU’s Research Project CONSENS by the development and integration of a smart NMR module for process monitoring. The presented NMR module is provided in a mobile explosion proof housing and involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation. Such “smart sensors” provide the basis for the future project “Industrie 4.0”, and Industrial Internet of Things (IIoT), along with current requirements to process control, model based control, or soft sensing. The module transforms the acquired online spectra of various technically relevant reactions to either conventional 4‒20 mA signals as well as WiFi based OPC-UA communication protocols, which enables NMR-based advanced process control and funny discussions with plant managers along with automation and safety engineers.
Assessment and validation of various flow cell designs for quantitative online NMR spectroscopy
(2017)
Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction and process control. Robust field integration of NMR systems have to face explosion protection or integration into process control systems with short set-up times. This paves the way for industrial automation in real process environments.
The design of failsafe, temperature and pressure resistant flow through cells along with their NMR-specific requirements is an essential cornerstone to enter industrial production plants and fulfill explosion safety requirements. NMR-specific requirements aim at full quantitative pre-magnetization and acquisition with maximum sensitivity while reducing sample transfer times and dwell-times. All parameters are individually dependent on the applied NMR instrument. Luckily, an increasing number of applications are reported together with an increasing variety of commercial equipment. However, these contributions have to be reviewed thoroughly.
The performance of sample flow cells commonly used in online analytics and especially for low-field NMR spectroscopy was experimentally and theoretically investigated by 1H-NMR experiments and numerical simulations. Here, we demonstrate and discuss an automated test method to determine the critical parameters of flow through cells for quantitative online NMR spectroscopy. The setup is based on randomized setpoints of flow rates in order to reduce temperature related effects. Five flow cells and tubings were assessed and compared for high-field as well as low-field NMR spectrometers.
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.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors will simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. This is particularly important for concepts like self-diagnostics, self-calibration and self-configuration/parameterization. Intelligent field devices as parts of digital field networks, Inter-net Protocol (IP)-based connectivity and web interfaces, as well as advanced data analysis soft-ware will provide the basis for future projects like Industrie 4.0, Factory of the Future, or Industrial Internet of Things (IIoT). The talk summarizes the currently discussed general requirements for process sensors 4.0 and introduces an online NMR sensor as example. This sensor was developed to provide integrated control and sensing for sustainable operation of flexible intensified processes (CONSENS) funded by the European Union’s Horizon 2020 research and innovation programme.
Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which are calibration intensive. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process monitoring and control.
Within the European Union’s Research Project CONSENS (Integrated CONtrol and SENsing by development and integration of a smart NMR module for process monitoring was designed and delivers online spectra of various reactions. The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation.
For reaction monitoring and process control using NMR instruments 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 Modelling and Quantum Mechanical calculations). 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.
Smart functions of sensors simplify their use and enable plug-and-play, even though they are more complex. This is particularly important for, self-diagnostics, self-calibration and self-configuration/parameterization. Intelligent field devices, digital field networks, Internet Protocol (IP)-enabled connectivity and web services, historians, and advanced data analysis software are providing the basis for the future project “Industrie 4.0” and Industrial Internet of Things (IIoT).
Important smart features include connectivity and communication ability according to a unified protocol (OPC-UA currently most widely discussed), maintenance and operating functions, traceability and compliance, virtual description to support a continuous engineering, and well as interaction capabilities between sensors. This is a prerequisite for the realization of Cyber Physical Systems (CPS) within these future automation concepts for the process industry. Therefore, smart process sensors enable new business models for users, device manufacturers, and service providers.
The departure from current automation to smart sensor has already begun. Further development is based on the actual situation over several steps. Possible perspectives will be via additional communication channels to mobile devices, bidirectional communication, integration of the cloud and virtualization. The integration of virtual runtime environments can provide a more flexible topology for process control environments.
The talk summarizes the currently discussed requirements to process sensors 4.0 and introduces an online NMR sensor as an example, which was developed in the EU project CONSENS.
The talk reflects how PAT could be applied in future developments ofpharma manufacturing. It shows the benefits, increase quality, size and increasing speed of production with significant reduction of quality costs, which are possible. Using Smart Sensors and model based data evaluation methods are the key to reduce set-up times and costs. Industry 4.0 will help shape the Pharmaceutical industry of tomorrow. This is demonstrated by an example using modular production units for Continuous Manufacturing. The development of a smart online NMR analyser is shown.
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 Union’s 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.
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 inexpensive analysers, which feature advantages like 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, 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. Otherwise there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS 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 with a module size of 57 x 57 x 85 cm 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.
The Royal Society of Chemistry NMR Discussion Group and Molecular Spectroscopy Group would like to invite you to the 2017 Spring Meeting, which will be held at GlaxoSmithKline (GSK), Stevenage. The theme for the meeting is “Low level detection and quantification by NMR” and different NMR technologies, including solution state NMR, solid state NMR and benchtop/low field NMR will be discussed. The presentations will cover a range of NMR related disciplines, including conventional low level detection and quantification, the use of cryoprobes, quantification of polymorphism using ssNMR and also methods for spectral simplification. Recent developments and applications of hyperpolarisation techniques, within both solution state and solid state NMR, will be presented in conjunction with the effect these sensitivity enhancements have with respect to quantification and limits of detection.
Process analytical techniques are extremely useful tools for chemical production and manufacture and are of particular interest to the pharmaceutical, food and (petro-) chemical industries.
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.
A major advantage of NMR spectroscopy is that the method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method which is independent of the matrix. This is an important prerequisite for robust data evaluation strategies within a control concept and reduces the need for extensive maintenance of the evaluation model over the time of operation. Additionally, NMR spectroscopy provides orthogonal, but complimentary physical information to conventional, e.g., optical spectroscopy. It increases the accessible information for technical processes, where aromatic-to-aliphatic conversions or isomerisation’s occur and conventional methods fail due to only minor changes in functional groups.
As a technically relevant example, the catalytic hydrogenation of 2-butyne-1,4-diol and further pharmaceutical reactions were studied using an online NMR sensor based on a commercially available low-field NMR spectrometer within the framework of the EU project CONSENS (Integrated Control and Sensing).
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. Conventionally, sensors have to be calibrated in a first step to find a response curve between the sensor signal and physical or chemical properties of the sample. In a second step, a model of the response between these parameters (e.g., concentrations) and the targeted quality specifications is needed. Thanks to the direct proportionality of the molar concentrations and the NMR signal, it could directly be used in the near future to relate the process target quality specification to sensor data – also in combination with multiple other sensor or process information.
Low field NMR spectroscopy for sustainable and flexible production of high quality chemical products
(2017)
The main development goal of process industries is to advance the continuous production of high-value products that meet high quality demands in flexible intensified continuous plants by introducing novel online sensing equipment and closed-loop control (CONSENS – integrated control and sensing- is funded from the European Union’s Horizon 2020 research and innovation programme). Therefore, we present the field integration of a benchtop NMR instrument into a modular production environment, focussing on suitable equipment for operation in hazardous areas with risk of explosive atmospheres.
We investigated a pharmaceutical reaction step in order to describe challenges for the experimental design, the evaluation of complex NMR spectra and demonstrate automated data analysis tools.
Process monitoring of an intensified continuous production unit with compact NMR spectroscopy
(2017)
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 inexpensive analysers, which feature advantages like 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, 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. Otherwise there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS 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 with a module size of 57 x 57 x 85 cm 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.
Process monitoring of an intensified continuous
production unit with compact NMR spectroscopy
(2017)
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 inexpensive analysers, which feature advantages like 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, 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. Otherwise there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS 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 with a module size of 57 x 57 x 85 cm 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.
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 Union’s Research Project CONSENS (Integrated Control and Sensing [3]) 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.
Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction and process control. An increasing number of applications are reported. Robust field integration of NMR systems have to face explosion protection or integration into process control systems with short set-up times. Tis paves the way for industrial automation in real process environments.
Automated data preparation and analysis are cornerstones for a breakthrough of NMR techniques for process control. Particularly, robust chemometrics as well as automated signal processing methods have to be (further) developed especially for NMR spectroscopy in process control. This becomes even more important for so called “smart sensors” providing the basis for the future project “Industrie 4.0”, and Industrial Internet of Things (IIoT), along with current requirements to process control, model based control, or soft sensing. Data analysis techniques are available but currently mostly used for off-line data analysis to detect the causes of variations in the product quality.
The talk presents current research activities towards process control with compact NMR and reflects “cultural differences” between the interdisciplinary parties involved.
Process monitoring of an intensified continuous production unit with compact NMR spectroscopy
(2016)
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 analyzers, 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. Recently, promising benchtop NMR instruments with acceptable performance came to market and process integrated sensors developed on basis of such laboratory instruments are on their way.
Intensified continuous processes are in focus of current research. Compared to traditional batch processes, these are giving admittance to new and difficult to produce compounds, leading to better product uniformity, and dras-tically reducing the consumption of raw materials and energy. 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. Typically, such plants have smaller scale than big size facilities for production of basic chemicals but are still capable to produce kilograms to tons of specialty products each day. Such flexible (modular) plants can be provided in the size of 20 ft freight containers and represent a promising approach by their ability of easy transfer to production sites as well as the possibility of increasing production capacity by a simple numbering-up-approach.
However, full automation is a prerequisite to realize such benefits of intensified continuous production. In continu-ous flow processes steady automated measurements 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) prod-ucts. This is addressed in the European Union’s 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.
Ugly Spectra and Lousy interfaces – Challenges for Compact NMR Spectroscopy in Process Control
(2016)
With the introduction of advanced process analytical technology, the closeness of key process variables to their limits can be directly controlled and the product can be classified or even released in real time.
Compact NMR instruments can make NMR spectroscopy accessible in industrial and harsh environments for process control.
A robust and sensitive method for the detection of the explosive trinitrotoluene (TNT) was developed. The detection limit was determined to be around 0.5 µg/L. The fast signal response of less than 1 minute shows that this approach is suitable for security and other time-critcal applications. In addition, the very low cross-reactivity highly reduces the number of false-positives in relation to competing techniques, including sniffer dogs. Due to the multianalyte ability of the SAW system, several explosives might be detected in parallel.
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.
Online low-field NMR spectroscopy of an industrial lithiation reaction step for process control
(2016)
Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectroscopy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory.
Within the project CONSENS, the continuous production of high-value products in small production scale is advanced by introducing benchtop NMR spectroscopy. CONSENS is a research and innovation project on integrated control and sensing for sustainable operation of flexible intensified processes.
This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Furthermore, first online spectra of the lithiation reaction in batch mode were acquired in lab scale. The reaction was performed in a 25 mL glass reactor with thermal jackets for temperature control of the reaction mixture. The Li-HMDS was dosed stepwise by using a glass syringe. First spectra in the proton and fluorine domain were recorded online using a flowrate of 3.5 mL min–1 and a simple 5 mm polytetrafluoroethylene tube (PTFE) as a flow cell.
Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectroscopy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory.
Within the project CONSENS, the continuous production of high-value products in small production scale is advanced by introducing benchtop NMR spectroscopy. CONSENS is a research and innovation project on integrated control and sensing for sustainable operation of flexible intensified processes.
This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Furthermore, first online spectra of the lithiation reaction in batch mode were acquired in lab scale. The reaction was performed in a 25 mL glass reactor with thermal jackets for temperature control of the reaction mixture. The Li-HMDS was dosed stepwise by using a glass syringe. First spectra in the proton and fluorine domain were recorded online using a flowrate of 3.5 mL min–1 and a simple 5 mm polytetrafluoroethylene tube (PTFE) as a flow cell.
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.
Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectros-copy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical com-parison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory.
Wthin the project CONSENS (www.consens-spire.eu), the continuous production of high-value products in small production scale is advanced by introducing benchtop NMR spectroscopy. CONSENS is a research and innovation project on inte-grated control and sensing for sustainable operation of flexible intensified processes.
This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Furthermore, first online spectra of the lithiation reaction in batch mode were acquired in lab scale. The reaction was performed in a 25 mL glass reactor with thermal jackets for temperature control of the reaction mixture. The Li-HMDS was dosed stepwise by using a glass syringe. First spectra in the proton and fluorine domain were recorded online using a flowrate of 3.5 mL min–1 and a simple 5 mm polytetrafluoroethylene tube (PTFE) as a flow cell.
Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectroscopy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory.
Within the project CONSENS, the continuous production of high-value products in small production scale is advanced by introducing MR-NMR spectroscopy. CONSENS is a research and innovation project on integrated control and sensing for sustainable operation of flexible intensified processes.
This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Additionally, the first results of the lithiation reaction in lab scale regarding the pure components and reaction mixtures are going to be discussed.
Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectroscopy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory.
Within the project CONSENS, the continuous production of high-value products in small production scale is advanced by introducing MR-NMR spectroscopy. CONSENS is a research and innovation project on integrated control and sensing for sustainable operation of flexible intensified processes.
This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Additionally, the first results of the lithiation reaction in lab scale regarding the pure components and reaction mixtures are going to be discussed.