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The goal of this work is to identify the optimal operating input for a lithiation reaction that is performed in a highly innovative pilot scale continuous flow chemical plant in an industrial environment, taking into account the process and safety constraints. The main challenge is to identify the optimum operation in the absence of information about the reaction mechanism and the reaction kinetics. We employ an iterative real-time optimization scheme called modifier adaptation with quadratic approximation (MAWQA) to identify the plant optimum in the presence of plant-model mismatch and measurement noise. A novel NMR PAT-sensor is used to measure the concentration of the reactants and of the product at the reactor outlet. The experiment results demonstrate the capabilities of the iterative optimization using the MAWQA algorithm in driving a complex real plant to an economically optimal operating point in the presence of plant-model mismatch and of process and measurement uncertainties.
A two-step separation procedure for the quantification of Pd and Pt in automotive exhaust emissions using isotope dilution mass spectrometry was established using a combination of cation and anion exchange chemistry. AG 50W-X12 was used as cation exchange resin and DGA as weakly basic anion exchange resin. This procedure enabled the effective separation of Pd and Pt from the matrix and from interfering elements. Additionally Pd and Pt were collected in separate chromatographic fractions, which increased the precision of the isotope ratio determination by separate measurements using single collector sector field ICPMS. The analytical procedure was validated by analysing the synthetically prepared samples and the certified reference materials BCR-723 (road dust) and IAEA-450 (algae). For the SI-traceable results complete uncertainty budgets were calculated yielding relatively expanded uncertainties (k = 2) of ≈1% for analyte masses in the ng range. Procedure blanks of 55 pg Pd and 3 pg Pt were obtained. The detection limits were calculated as 12 pg for Pd and 7 pg for Pt. Additionally, Pd and Pt blank levels of different filter materials are presented as well as the first results for automotive exhaust particles collected on cellulose filters.
Ring-expansion polymerizations (REPs) catalyzed by two cyclic tin catalysts (2-stanna-1.3-dioxa-4,5,6,7-dibenzazepine [SnBiph] and
2,2-dibutyl-2-stanna-1,3-dithiolane [DSTL]) are performed at 140 °C in bulk.
Small amounts (4 vol%) of chlorobenzene or other solvents are added to
facilitate transesterification reactions (ring–ring equilibration) in the solid poly(l-lactide)s. In the mass range up to m/z 13 000 crystalline PLAs displaying a so-called saw-tooth pattern in the MALDI-TOF mass spectra are obtained indicating the formation of extended-ring crystals. The characteristics of extended-ring crystallites and folded-ring crystallites are discussed. Furthermore, extremely high melting temperatures (Tm’s up to 201.2 °C) and melting enthalpies (𝚫Hm’s up to 106 J g−1)) are found confirming that 𝚫Hm max, the 𝚫Hm of a perfect crystal, is around or above 115 J g−1 in contrast to literature data.
Alcohol-initiated ROPs of L-Lactide were performed at 140 ◦C in bulk with variation of the initiator/catalyst ratio and time. Lower ratios favor the formation of cycles which upon annealing display a change of the MALDI mass peak distribution towards a new maximum with a “saw-tooth pattern” of the mass peaks representing the cycles.
Such a pattern was not observed for the mass peak of the linear chains. The coexistence of these patterns indicate that linear and cyclic poly (L-lactide)s (PLA) crystallize in separate crystals, and that the crystallites of the cycles are made up by extended rings. High Tm and ΔHm values confirm that these extended-ring crystallites represent a thermodynamically optimized form of PLA. Experiments with preformed cyclic and linear PLAs support this interpretation.
A poly(L-lactide) with a trifluoroethyl ester end group and an average degree of polymerization (DP) of 50 was synthesized by ROP of L-lactide initiated with trifluoroethanol. Small-angle X-ray scattering (SAXS) in combination with differential scanning calorimetry (DSC) measurements revealed an average crystal thickness of 13 nm, corresponding to 45 repeat units. This suggests that most crystallites were formed by extended PLA chains, and both flat surfaces were covered by CF3 groups. The crystalline PLAs were annealed at 140 or 160 °C in the presence of two catalysts: tin(II) 2-ethylhexanoate, (SnOct2) or dibutyltin bis(pentafluorophenoxide) (BuSnPhF). The chemical reactions, such as polycondensation and cyclization, proceeded in the solid state and were monitored by matrix-assisted laser desorption/ionization time-offlight (MALDI TOF) mass spectrometry and gel permeation chromatography (GPC) measurements. Under optimal conditions a large fraction of linear chains was transformed into crystallites composed of extended cycles. Additionally, MALDI TOF MS analysis of GPC fractions from samples annealed for 28 or 42 days detected chain elongation of the linear species up to a factor of 20.
The usefulness of seven different Tin catalysts, Bismuth subsalicylate and Titan tetra(ethoxide) for the polycondensation of ethyl L-lactate (ELA) was examined at 150 °C/6 d. Dibutyltin bis(phenoxides) proved to be particularly effective. Despite the low reactivity of ELA, weight average molecular masses (Mw) up to 12 500 were found along with partial crystallization. Furthermore, polylactides (PLAs) of similar molecular masses were prepared via ELA-initiated ROPs of L-lactide by means of the four most effective polycondensation catalysts. The crystalline linear PLAs were annealed at 140 or 160 °C in the presence of these catalysts. The consequences of the transesterification reactions in the solid PLAs were studied by means of matrix-assisted laser desorption/ionization (MALDI TOF) mass spectrometry, gel permeation chromatography (GPC) and small-angle X-ray scattering (SAXS). The results indicate that polycondensation and formation of cycles proceed in the solid state via formation of loops on the surface of the crystallites. In summary, five different transesterification reactions are required to explain all results.
Modular plants using intensified continuous processes represent an appealing concept to produce pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes, and it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and includes a compact Nuclear Magnetic Resonance (NMR) spectrometer for online quality monitoring as well as a new model-based control approach. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including ro-bust evaluation of sensor data.
Here, we present alternatives for the quantitative determination of the analytes using modular, physically motivated models. These models can be adapted to new substances solely by the use of their corresponding pure component spectra, which can either be derived from experimental spectra as well as from quantum mechanical models or NMR predictors. Modular means that spec-tral models can simply be exchanged together with alternate reagents and products. Beyond that, we comprehensively calibrated an NIR spectrometer based on online NMR process data for the first time within an industrial plant. The integrated solution was developed for a metal organic reac-tion running on a commercial-scale modular pilot plant and it was tested under industrial conditions.
A big problem with the chemistry literature is that it is not standardized with respect to precise operational parameters, and real time corrections are hard to make without expert knowledge. This lack of context means difficult reproducibility because many steps are ambiguous, and hence depend on tacit knowledge. Here we present the integration of online NMR into an automated chemical synthesis machine (CSM aka. “Chemputer” which is capable of small-molecule synthesis using a universal programming language) to allow automated analysis and adjustment of reactions on the fly. The system was validated and benchmarked by using Grignard reactions which were chosen due to their importance in synthesis. The system was monitored in real time using online-NMR, and spectra were measured continuously during the reactions. This shows that the synthesis being done in the Chemputer can be dynamically controlled in response to feedback optimizing the reaction conditions according to the user requirements.
Im Zuge der Digitalisierung der Prozessindustrie werden zunehmend modellbasiere Echtzeitoptimierungsverfahren eingesetzt, sog. „Advanced Process Control“. Mithilfe der sogenannten Modifier-Adaptation ist eine iterative Betriebspunktoptimierung auch mit ungenauen Modellen möglich, sofern zuverlässige Prozessdaten zur Verfügung stehen. Am Beispiel eines smarten Online-NMR-Sensors, der in einem EU-Projekt von der BAM entwickelt wurde, konnte das Konzept in einer modularen Produktionsanlage zur Herstellung eines pharmazeutischen Wirkstoffs erfolgreich getestet werden.