Improvement of Dried Distillers’ Grains with Solubles Utilizing Pretreatments and Fungal Fermentation

Limited inclusion of distillers’ grains in animal feed is primarily due to low protein and high fiber content. Other elements, such as phytate phosphorus levels in DDGS are still an issue for monogastric animals such as swine, poultry, and fish. Furthermore, unabsorbed phytic acid in manure poses a high risk for environmental pollution, because bacteria can hydrolyze phytic acid into free phosphorus that can result in algal blooms and eutrophication of surface or ground water. The objective of this thesis was to improve the nutritional value of corn dried distillers’ grains with solubles (DDGS). This was done utilizing submerged fungal fermentation, enzymatic hydrolysis, and a combination of extrusion pretreatment and fungal fermentation/enzymatic hydrolysis. All treatments served as a means of degrading fiber and phytic acid while improving protein content for animal feed applications. Initially, fungal fermentations at 5, 10, and 20% solid loading rates (SLR, dry weight basis) were used to assess four fungal strains (T. reesei, N. crassa, R. oligosporus, and A. pullulans). Flask trials were incubated for 120 h at 30℃ and 150 rpm. Uninoculated control flasks were also included. Flasks were sampled at 24 h intervals, with solids recovered by centrifugation. A solubilization effect was observed at the 0 h sampling for all SLRs, as DDGS solubles fractionated into the centrate stream, while insoluble fractions such as protein and fiber were concentrated in the pellet. An increase in protein content ~5% and crude fiber ~1.5% is seen at the 5% SLR in the uninoculated control; at higher SLR the increase in protein drops to ~3% and crude fiber increases about 0.5-1%. After fermentation N. crassa (NRRL-2332) at a SLR of 20% resulted in the greatest reduction in fiber (-0.5% equal to original grain), while increasing protein (+5%) and lowering phytic acid levels (~0.3g/100g). An increase in fiber was seen in all other fungal and SLR combinations. Higher SLR resulted in better protein content for each of the fungi. Enzymatic hydrolysis under submerged conditions (10% SLR) was also tested to determine if fibrous components of the DDGS could be degraded into simple sugars. Trials were conducted in 250 ml flasks incubated for 24 h at 55℃ and 150 rpm. Four commercially available enzymes (cellulase, xylanase, phytase, pectinase) at four dosages were tested at the recommended pH levels for individual testing. Trials were also conducted to assess synergistic effects of various enzyme combinations. The greatest reduction in crude fiber for the individual enzyme was seen in the cellulase 1 and 2 mg/g dosages while the greatest reduction in NDF and ADF seen in all four dosages of pectinase. When all four enzymes were combined the greatest reduction in all fibers (crude, NDF, and ADF) was achieved. The combination of 1mg/g of xylanase, phytase, and pectinase had the most effective releases of glucose and total sugars of all individual enzymes and combinations. Overall the most effective treatments were 1m/g of cellulase, xylanase, phytase, and pectinase and 1m/g of xylanase, phytase, and pectinase. To increase the fiber hydrolysis, the use of extrusion pretreatment prior to fungal fermentation was examined. Extrusion was conducted using DDGS at a 12% moisture content, with a barrel compression ratio of 3:1 and length to diameter of 20:1 at 90-100℃ Extruded DDGS was then blended with water to a 15% SLR, autoclaved, and inoculated with T. reesei, N. crassa, R. oligosporus, or A. pullulans. Extrusion reduced crude fiber content and increased protein concentration. However, after the addition of water to create the submerged fermentation the fibers were increased. After 120h of fermentation crude fiber was significantly increased in N. crassa and A. pullulans trials. Protein was concentrated during fermentation by removal of the soluble fraction, but N. crassa was able to increase the protein ~10% from the original grain and ~5% from the un-inoculated control at 48 h. A. pullulans was also able to increase the protein significantly while T. ressei and R. oligosporus were not significantly different from the control. Lastly, the use of fungal fermentation was conducted on DDGS that was pretreated via extrusion (12% moisture, barrel temperature 90-100℃, compression ratio 3:1, barrel length to diameter 20:1) and hydrolyzed via the combination of cellulase, xylanase, pectinase, and phytase, each at dosage of 1 mg protein/dry gram of DDGS and fermented using N. crassa using sequential (4h of hydrolysis then N. crassa) or simultaneous addition. Irrespective of extrusion the use of simultaneous addition of enzyme and fungi had the greatest reduction in fiber

Magnetic Characterization of the Nugget Microstructure at Resistance Spot Welding

Conventional resistance spot welds are not visible from the outside. Therefore, it is not straightforward to evaluate the joint quality non-destructively. The pulse-echo method of manual ultrasonic is widely used for non-destructive testing. Another option is the passive magnetic flux density testing, which is being developed at Technische Universität Dresden, Germany. The spot weld is magnetized in the normal direction and the residual magnetic flux density is measured on top of the surface of the joint. This method is suitable for spot welds on typical car body steels. Previous investigations show that the magnetic properties of the materials influence the test result. In order to develop this new non-destructive testing method further, it is necessary to know the magnetic properties of the different microstructure regions of a spot weld. This article focuses on methods to measure and evaluate the magnetic properties of these regions, especially of the base material and the weld. Different measuring methods and approaches are presented and compared with each other. Based on the results, recommendations for future measurements for magnetic characterizations are given

Suppression of polaron self-localization by correlations

We investigate self-localization of a polaron in a homogeneous Bose-Einstein condensate in one dimension. This effect, where an impurity is trapped by the deformation that it causes in the surrounding Bose gas, has been first predicted by mean field calculations, but has not been seen in experiments. We study the system in one dimension, where, according to the mean field approximation, the self-localization effect is particularly robust, and present for arbitrarily weak impurity-boson interactions. We address the question whether self-localization is a real effect by developing a variational method which incorporates impurity-boson correlations non-perturbatively and solving the resulting inhomogeneous correlated polaron equations. We find that correlations inhibit self-localization except for very strongly repulsive or attractive impurity-boson interactions. Our prediction for the critical interaction strength for self-localization agrees with a sharp drop of the inverse effective mass to almost zero found in quantum Monte Carlo simulations of polarons in one dimension.Comment: 12 pages, 5 figure

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Selbstlokalisierung eines Fremdteilchens in einem Bose-Einstein-Kondensat in einer Dimension

In this thesis, we study the ground state of an impurity atom in a Bose-Einstein condensate in one dimension. Our goal is to investigate the existence of "self-localized" impurities, characterized by a localized impurity density that breaks translational symmetry, as proposed by mean-field calculations in 3D [F.M. Cucchietti and E. Timmermans, PRL 96, 210401 (2006)] as well as in 2D and 1D [M. Bruderer et al., EPL 82, 30004 (2008)]. To improve upon the mean-field results, we derive a variational method that includes correlations between the impurity and a boson of the condensate, while still allowing the wave function to break translational symmetry: Using the Rayleigh-Ritz variational method, we derive two coupled equations for the impurity density and the impurity-boson correlation function, and iteratively calculate the ground state solution using an imaginary time propagation algorithm. In contrast to the mean-field results, we find no indication of self-localization for weak and moderately strong impurity-boson interactions in 1D. In this regime, the impurity density is constant and the impurity-boson correlation function depends only on the distance between the impurity and the boson, consistent with translational invariance. Only for very strong interactions do we obtain localized impurity densities, but we still find that the impurity-boson correlations cannot be neglected. We calculate our results using a narrow Gaussian impurity-boson interaction potential. In addition, we include working algorithms for the implementation of a contact potential, which compute stable solutions if the impurity-boson interactions are not too strong, and the impurity density is delocalized.submitted by Lilith ZschetzscheAbweichender Titel laut Übersetzung der Verfasserin/des VerfassersMasterarbeit Universität Linz 202

Magnetic Characterization of the Nugget Microstructure at Resistance Spot Welding

Conventional resistance spot welds are not visible from the outside. Therefore, it is not straightforward to evaluate the joint quality non-destructively. The pulse-echo method of manual ultrasonic is widely used for non-destructive testing. Another option is the passive magnetic flux density testing, which is being developed at Technische Universität Dresden, Germany. The spot weld is magnetized in the normal direction and the residual magnetic flux density is measured on top of the surface of the joint. This method is suitable for spot welds on typical car body steels. Previous investigations show that the magnetic properties of the materials influence the test result. In order to develop this new non-destructive testing method further, it is necessary to know the magnetic properties of the different microstructure regions of a spot weld. This article focuses on methods to measure and evaluate the magnetic properties of these regions, especially of the base material and the weld. Different measuring methods and approaches are presented and compared with each other. Based on the results, recommendations for future measurements for magnetic characterizations are given

Quality monitoring of projection welding using machine learning with small data sets

Capacitor discharge welding is an efficient, cost-effective and stable process. It is mostly used for projection welding. Real-time monitoring is desired to ensure quality. Until this point, measured process quantities were evaluated through expert systems. This method takes much time for developing, is strongly restricted to specific welding tasks and needs deep understanding of the process. Another possibility is quality prediction based on process data with machine learning. This method can overcome the downsides of expert systems. But it requires classified welding experiments to achieve a high prediction probability. In industrial manufacturing, it is rarely possible to generate big sets of this type of data. Therefore, semi-supervised learning will be investigated to enable model development on small data sets. Supervised learning is used to develop machine learning models on large amounts of data. These models are used as a comparison to the semi-supervised models. The time signals of the process parameters are evaluated in these investigations. A total of 389 classified weld tests were performed. With semi-supervised learning methods, the amount of training data necessary was reduced to 31 classified data sets