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- 2020 (4) (entfernen)
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- Englisch (4)
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- MALDI-TOF MS (2)
- Polylactide (2)
- Bending modulus (1)
- CONSENS (1)
- Carbon nanotubes (1)
- Cyclization (1)
- Fiber toxicology (1)
- Flexural rigidity (1)
- Iterative real-time optimization (1)
- Modifier adaptation (1)
Organisationseinheit der BAM
In this work the flexural rigidity of individual large diameter multi-walled carbon nanotubes (MWCNTs) was investigated. The bending modulus were obtained by detecting the resonance frequencies of mechanically excited cantilevered carbon nanotubes using the so-called dynamic scanning electron microscopy technique, and applying the Euler–Bernoulli beam theory. For the nanotubes studied, we determined a modulus of up to 160 GPa. This agrees with values reported by other authors for MWCNTs produced by catalytic chemical vapor deposition, however, it is 6-8 times smaller than values reported for single and multi-walled carbon nanotubes produced by arc-discharge synthesis. Toxicological studies with carbon nanotubes have been showing that inhaled airborne nanofibers that reach the deep airways of the respiratory system may lead to serious, asbestos-like lung diseases. These studies suggested that their toxicity critically depends on the fiber flexural rigidity, with high rigidity causing cell lesions. To complement the correlation between observed toxicological effects and fiber rigidities, reliable and routinely applicable measurement techniques for the flexural rigidity of nanofibers are required.
Ring–Ring Equilibration in Solid, Even-Numbered Cyclic Poly(l-lactide)s and their Stereocomplexes
(2020)
Even-numbered cyclic poly(d-lactide) and poly(l-lactide) are prepared by ringexpansion polymerization. The cyclic pol(l-lactide) is annealed either at 120 or at 160 °C for several days. The progress of transesterification in the solid state is monitored by the formation of odd-numbered cycles via matrix-assisted laser desorption/ionization-time of flight mass spectrometry. The changes of the crystallinity are monitored by differential scanning calorimetry, wideand small-angle x-ray scattering (WAXS and SAXS) measurements. Despite total even-odd equilibration at 160 °C, the crystallinity of poly(l-lactide) is not reduced. Furthermore, the crystallinity of the stereocomplexes of both cyclic polylactides do not decrease or vanish, as expected, when a blocky or random stereosequence is formed by transesterification. This conclusion is confirmed by 13C NMR spectroscopy. These measurements demonstrate that transesterification is a ring–ring equilibration involving the loops on the surfaces of the lamellar crystallites thereby improving crystallinity and 3D packing of crystallites without significant broadening of the molecular weight distribution.
A new kind of high melting (HTm) pol(L-lactide) was discovered when cyclic poly(L-lactide)s were prepared by ring-expansion polymerization with cyclic tin catalysts at 130–160 °C in bulk. By DSC measurements with 10 K min−1 melting temperatures (Tm) in the range of 190–196 °C were found. The WAXS and SAXS measurements evidenced that not a new crystal lattice but a well-ordered morphology and a higher perfection of the crystallites are responsible for the high Tm values and high crystallinities. Under identical reaction conditions SnOct2-catalyzed and alcohol-initiated ROPs do not yield these crystallites.
Furthermore, it was found that the standard crystallites are kinetically favored upon rapid crystallization, whereas the high melting form of poly(L-lactide) is thermodynamically more stable.
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.