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- Heparin (3)
- Bacillaceae (2)
- Biotechnological application (2)
- Butanol (2)
- Chemometrics (2)
- IR spectroscopy (2)
- NMR spectroscopy (2)
- Principal component analysis (2)
- Standardization (2)
- Subtilases (2)
The investigation of the possibility to determine various characteristics of powder heparin (n = 115) was carried out with infrared spectroscopy. The evaluation of heparin samples included several parameters such as purity grade, distributing company, animal source as well as heparin species (i.e. Na-heparin, Ca-heparin, and heparinoids). Multivariate analysis using principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), and partial least squares – discriminant analysis (PLS-DA) were applied for the modelling of spectral data. Different pre-processing methods were applied to IR spectral data; multiplicative scatter correction (MSC) was chosen as the most relevant.
Obtained results were confirmed by nuclear magnetic resonance (NMR) spectroscopy. Good predictive ability of this approach demonstrates the potential of IR spectroscopy and chemometrics for screening of heparin quality. This approach, however, is designed as a screening tool and is not considered as a replacement for either of the methods required by USP and FDA.
The molecular weight properties of lignins are one of the key elements that need to be analyzed for a successful industrial application of these promising biopolymers. In this study, the use of 1H NMR as well as diffusion-ordered spectroscopy (DOSY NMR), combined with multivariate regression methods, was investigated for the determination of the molecular weight (Mw and Mn) and the polydispersity of organosolv lignins (n = 53, Miscanthus x giganteus, Paulownia tomentosa, and Silphium perfoliatum). The suitability of the models was demonstrated by cross validation (CV) as well as by an independent validation set of samples from different biomass origins (beech wood and wheat straw). CV errors of ca. 7–9 and 14–16% were achieved for all parameters with the models from the 1H NMR spectra and the DOSY NMR data, respectively. The prediction errors for the validation samples were in a similar range for the partial least squares model from the 1H NMR data and for a multiple linear regression using the DOSY NMR data. The results indicate the usefulness of NMR measurements combined with multivariate regression methods as a potential alternative to more time-consuming methods such as gel permeation chromatography.
Although several successful applications of benchtop nuclear magnetic resonance (NMR) spectroscopy in quantitative mixture analysis exist, the possibility of calibration transfer remains mostly unexplored, especially between high- and low-field NMR. This study investigates for the first time the calibration transfer of partial least squares regressions [weight average molecular weight (Mw) of lignin] between high-field (600 MHz) NMR and benchtop NMR devices (43 and 60 MHz). For the transfer, piecewise direct standardization, calibration transfer based on canonical correlation analysis, and transfer via the extreme learning machine auto-encoder method are employed. Despite the immense resolution difference between high-field and low-field NMR instruments, the results demonstrate that the calibration transfer from high- to low-field is feasible in the case of a physical property, namely, the molecular weight, achieving validation errors close to the original calibration (down to only 1.2 times higher root mean square errors). These results introduce new perspectives for applications of benchtop NMR, in which existing calibrations from expensive high-field instruments can be transferred to cheaper benchtop instruments to economize.
The Kremer-Grest (KG) bead-spring model is a near standard in Molecular Dynamic simulations of generic polymer properties. It owes its popularity to its computational efficiency, rather than its ability to represent specific polymer species and conditions. Here we investigate how to adapt the model to match the universal properties of a wide range of chemical polymers species. For this purpose we vary a single parameter originally introduced by Faller and Müller-Plathe, the chain stiffness. Examples include polystyrene, polyethylene, polypropylene, cis-polyisoprene, polydimethylsiloxane, polyethyleneoxide and styrene-butadiene rubber. We do this by matching the number of Kuhn segments per chain and the number of Kuhn segments per cubic Kuhn volume for the polymer species and for the Kremer-Grest model. We also derive mapping relations for converting KG model units back to physical units, in particular we obtain the entanglement time for the KG model as function of stiffness allowing for a time mapping. To test these relations, we generate large equilibrated well entangled polymer melts, and measure the entanglement moduli using a static primitive-path analysis of the entangled melt structure as well as by simulations of step-strain deformation of the model melts. The obtained moduli for our model polymer melts are in good agreement with the experimentally expected moduli.
The Kremer–Grest (KG) polymer model is a standard model for studying generic polymer properties in molecular dynamics simulations. It owes its popularity to its simplicity and computational efficiency, rather than its ability to represent specific polymers species and conditions. Here we show that by tuning the chain stiffness it is possible to adapt the KG model to model melts of real polymers. In particular, we provide mapping relations from KG to SI units for a wide range of commodity polymers. The connection between the experimental and the KG melts is made at the Kuhn scale, i.e., at the crossover from the chemistry-specific small scale to the universal large scale behavior. We expect Kuhn scale-mapped KG models to faithfully represent universal properties dominated by the large scale conformational statistics and dynamics of flexible polymers. In particular, we observe very good agreement between entanglement moduli of our KG models and the experimental moduli of the target polymers.
The feasibility of light-addressed detection and manipulation of pH gradients inside an electrochemical microfluidic cell was studied. Local pH changes, induced by a light-addressable electrode (LAE), were detected using a light-addressable potentiometric sensor (LAPS) with different measurement modes representing an actuator-sensor system. Biosensor functionality was examined depending on locally induced pH gradients with the help of the model enzyme penicillinase, which had been immobilized in the microfluidic channel. The surface morphology of the LAE and enzyme-functionalized LAPS was studied by scanning electron microscopy. Furthermore, the penicillin sensitivity of the LAPS inside the microfluidic channel was determined with regard to the analyte’s pH influence on the enzymatic reaction rate. In a final experiment, the LAE-controlled pH inhibition of the enzyme activity was monitored by the LAPS.
Poly(N-isopropylacrylamide) (PNIPAAm) hydrogel films with incorporated graphene oxide (GO) were developed and tested as light-stimulated actuators. GO dispersions were synthesized via Hummers method and characterized toward their optical properties and photothermal energy conversion. The hydrogels were prepared by means of photopolymerization. In addition, the influence of GO within the hydrogel network on the lower critical solution temperature (LCST) was investigated by differential scanning calorimetry (DSC). The optical absorbance and the response to illumination were determined as a function of GO concentration for thin hydrogel films. A proof of principle for the stimulation with light was performed.
As a low-input crop, Miscanthus offers numerous advantages that, in addition to agricultural applications, permits its exploitation for energy, fuel, and material production. Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ. Here, a comparative study is presented between lignins isolated from M. x giganteus, M. sinensis, M. robustus and M. nagara using a catalyst-free organosolv pulping process. The lignins from different plant constituents are also compared regarding their similarities and differences regarding monolignol ratio and important linkages. Results showed that the plant genotype has the weakest influence on monolignol content and interunit linkages. In contrast, structural differences are more significant among lignins of different harvest time and/or season. Analyses were performed using fast and simple methods such as nuclear magnetic resonance (NMR) spectroscopy. Data was assigned to four different linkages (A: β-O-4 linkage, B: phenylcoumaran, C: resinol, D: β-unsaturated ester). In conclusion, A content is particularly high in leaf-derived lignins at just under 70% and significantly lower in stem and mixture lignins at around 60% and almost 65%. The second most common linkage pattern is D in all isolated lignins, the proportion of which is also strongly dependent on the crop portion. Both stem and mixture lignins, have a relatively high share of approximately 20% or more (maximum is M. sinensis Sin2 with over 30%). In the leaf-derived lignins, the proportions are significantly lower on average. Stem samples should be chosen if the highest possible lignin content is desired, specifically from the M. x giganteus genotype, which revealed lignin contents up to 27%. Due to the better frost resistance and higher stem stability, M. nagara offers some advantages compared to M. x giganteus. Miscanthus crops are shown to be very attractive lignocellulose feedstock (LCF) for second generation biorefineries and lignin generation in Europe.
Lignocellulosic biorefinery: Process integration of hydrolysis and fermentation (SSF process)
(2011)
The aim of the present work is the process integration and the optimization of the enzymatic hydrolysis of wood and the following fermentation of the products to ethanol. The substrate is a fiber fraction obtained by organosolv pre-treatment of beech wood. For the ethanol production, a co-fermentation by two different yeasts (Saccharomyces cerevisiae and Pachysolen tannophilus) was carried out to convert glucose as well as xylose. Two approaches has been followed: 1. A two step process, in which the hydrolysis of the fiber fraction and the fermentation to product are separated from each other. 2. A process, in which the hydrolysis and the fermentation are carried out in one single process step as simultaneous saccharification and fermentation (SSF). Following the first approach, a yield of about 0.15 g ethanol per gram substrate can be reached. Based on the SSF, one process step can be saved, and additionally, the gained yield can be raised up to 0.3 g ethanol per gram substrate.
Electronic cigarettes (e-cigarettes) have become popular worldwide with the market growing exponentially in some countries. The absence of product standards and safety regulations requires urgent development of analytical methodologies for the holistic control of the growing diversity of such products. An approach based on low-field nuclear magnetic resonance (LF-NMR) at 80 MHz is presented for the simultaneous determination of key parameters: carrier solvents (vegetable glycerine (VG), propylene glycol (PG) and water), total nicotine as well as free-base nicotine fraction. Moreover, qualitative and quantitative determination of fourteen weak organic acids deliberately added to enhance sensory characteristics of e-cigarettes was possible. In most cases these parameters can be rapidly and conveniently determined without using any sample manipulation such as dilution, extraction or derivatization steps. The method was applied for 37 authentic e-cigarettes samples. In particular, eight different organic acids with the content up to 56 mg/mL were detected. Due to its simplicity, the method can be used in routine regulatory control as well as to study release behaviour of nicotine and other e-cigarettes constituents in different products.
The SG1-mediated solution polymerization of methyl methacrylate (MMA) and oligo(ethylene glycol) methacrylate (OEGMA, Mₙ = 300 g mol⁻¹) in the presence of a small amount of functional/reactive styrenic comonomer is investigated. Moieties such as pentafluorophenyl ester, triphenylphosphine, azide, pentafluorophenyl, halide, and pyridine are considered. A comonomer fraction as low as 5 mol% typically results in a controlled/living behavior, at least up to 50% conversion. Chain extensions with styrene for both systems were successfully performed. Variation of physical properties such as refractive index (for MMA) and phase transition temperature (for OEGMA) were evaluated by comparing to 100% pure homopolymers. The introduction of an activated ester styrene derivative in the polymerization of OEGMA allows for the synthesis of reactive and hydrophilic polymer brushes with defined thickness. Finally, using the example of pentafluorostyrene as controlling comonomer, it is demonstrated that functional PMMA-b-PS are able to maintain a phase separation ability, as evidenced by the formation of nanostructured thin films.
Meiotic functions of RAD18
(2011)
Elastomers are exceptional materials owing to their ability to undergo large deformations before failure. However, due to their very low stiffness, they are not always suitable for industrial applications. Addition of filler particles provides reinforcing effects and thus enhances the material properties that render them more versatile for applications like tyres etc. However, deformation behavior of filled polymers is accompanied by several nonlinear effects like Mullins and Payne effect. To this day, the physical and chemical changes resulting in such nonlinear effect remain an active area of research. In this work, we develop a heterogeneous (or multiphase) constitutive model at the mesoscale explicitly considering filler particle aggregates, elastomeric matrix and their mechanical interaction through an approximate interface layer. The developed constitutive model is used to demonstrate cluster breakage, also, as one of the possible sources for Mullins effect observed in non-crystallizing filled elastomers.