Evaluation of the pore morphology formation of the Freeze Foaming process by in situ computed tomography

The so-called Freeze Foaming method aims at manufacturing ceramic cellular scaffolds for diverse applications. One application is dedicated to potential bone replacement material featuring open, micro and interconnected porosity. However, the main challenges of this foaming method is to achieve a homogeneous pore morphology. In a current project, the authors throw light on the bubble/pore and strut formation of this process by in situ computed tomography. This allows for evaluating varying process parameter’s effects on the growth of the ceramic foam during the foaming process. As first result and basis for CT analysis, a stable and reproducible model suspension was developed which resulted in reproducible foam structures. In dependence of selected process parameters like pressure reduction rate or air content in the ceramic suspension resulting Freeze Foams became adjustable with regard to their pore morphology. Pore size and distribution data as well as the porosity were characterized and evaluated accordingly.     

Flash Sintering using Controlled Current Ramp

In conventional flash sintering, the current rises nonlinearly to a set current limit, accompanied by a spike in the power density. This sudden power spike may cause hot spot formation, in which current preferentially channels through a small area, causing localized melting while other areas remain unsintered. By using a controlled current ramp early on the sudden power spike can be avoided. In addition, by changing the ramp rate material properties such as porosity, grain size and conductivity can be tuned.     

Sintering behavior,microstructure and thermoelectric properties of calcium cobaltite thick films for transversal thermoelectric multilayer generators

The sintering behavior and the thermoelectric performance of Ca₃Co₄O₉ multilayer laminates were studied, and a multilayer thermoelectric generator was fabricated. Compacts and multilayer samples with anisotropic microstructure and residual porosity were obtained after conventional sintering at 920 °C, whereas dense and isotropic multilayer samples were prepared by firing at 1200 °C and reoxidation at 900 °C. A hot-pressed sample has a dense and anisotropic microstructure. Samples sintered at 920 °C exhibit low electrical conductivity due to the low density, whereas the Seebeck coefficient is not sensitive to preparation conditions. However, thermal conductivity of multilayers is very low, and, hence acceptable ZT values are obtained. A transversal multilayer thermoelectric generator (TMLTEG) was fabricated by stacking layers of Ca₃Co₄O₉ green tapes, AgPd conductor printing, and co-firing at 920 °C. The TMLTEG has a power output of 3 mW at ΔT = 200 K in the temperature interval of 25 °C to 300 °C.     

Post‐polymerization modification of bio‐based polymers: maximizing the high functionality of polymers derived from biomass

The renaissance of the bio‐based chemical industry over the last 20 years has seen an ever growing interest in the synthesis of new bio‐based polymers. The building blocks of these new polymers, so called platform molecules, contain significantly more chemical functionality than their petrochemical counterparts (such as ethene, propene and para‐xylene). As a result bio‐based polymers often contain greater residual chemical functionality in their chains, with groups such as alkenes and hydroxyls commonly observed. These functional groups can act as sites for post‐polymerization modification (PPM), thus further extending the range of applications for bio‐based polymers by tailoring the polymers' final properties. This mini‐review highlights some of the most recent and compelling examples of how to make use of bio‐based polymers with residual functional groups for PPM. It also looks at how the emerging interdisciplinary field of enzymatic polymer synthesis allows for increased functionality in polymers by avoiding side‐reactions as a result of milder reaction conditions, and additionally offers an alternative means of polymer surface modification. © 2018 Society of Chemical Industry     

In vitro model to assess the adsorption of oral veterinary drugs to mycotoxin binders in a feed- and aflatoxin B1-containing buffered matrix

Mycotoxin binders are feed additives which are mixed in the feed to adsorb mycotoxins and thereby reducing their toxic effects on animals. Interactions with orally administered veterinary medicinal products, such as antimicrobials or coccidiostats, have been reported previously. This paper describes an in vitro model to screen the interaction between mycotoxin binders and veterinary drugs with respect to the non-specific binding of drugs. It is designed as a static setup using a single concentration of drug and binder in a feed-containing or a feed-plus-mycotoxin-containing matrix, buffered at different pH values. The model was applied to two frequently used antimicrobials in veterinary medicine, doxycycline (DOX) and tylosin (TYL), one major mycotoxin, aflatoxin B1 (AFB1), and four mycotoxin binders. Proportions of feed, DOX or TYL, AFB1, and binder are equivalent to the in vivo situation for broiler chickens, while pH and volume of the buffer are representative of the gastrointestinal tract of chickens. A substantial binding of DOX (~ 88%) and TYL (~ 66%) to the feed-matrix was observed. For the mycotoxin binders, similar results were obtained for DOX and TYL; more specifically up to an inclusion rate of 20 g binder/kg feed, no significant binding was demonstrated, determined as the free concentration of DOX and TYL. A single exception was noticed for TYL and one specific bentonite-based mycotoxin binder, for which no significant interaction could be demonstrated up to 10 g binder/kg but there was an effect at 20 g/kg. In all cases, there was no competition between the tested drugs DOX or TYL and the mycotoxin AFB1 for binding to the bentonite-based mycotoxin binder.     

Anti-Inflammatory Treatment with FTY720 Starting after Onset of Symptoms Reverses Synaptic Deficits in an AD Mouse Model

Therapeutic approaches providing effective medication for Alzheimer’s disease (AD) patients after disease onset are urgently needed. Previous studies in AD mouse models suggested that physical exercise or changed lifestyle can delay AD-related synaptic and memory dysfunctions when treatment started in juvenile animals long before onset of disease symptoms, while a pharmacological treatment that can reverse synaptic and memory deficits in AD mice was thus far not identified. Repurposing food and drug administration (FDA)-approved drugs for treatment of AD is a promising way to reduce the time to bring such medication into clinical practice. The sphingosine-1 phosphate analog fingolimod (FTY720) was approved recently for treatment of multiple sclerosis patients. Here, we addressed whether fingolimod rescues AD-related synaptic deficits and memory dysfunction in an amyloid precursor protein/presenilin-1 (APP/PS1) AD mouse model when medication starts after onset of symptoms (at five months). Male mice received intraperitoneal injections of fingolimod for one to two months starting at five to six months. This treatment rescued spine density as well as long-term potentiation in hippocampal cornu ammonis-1 (CA1) pyramidal neurons, that were both impaired in untreated APP/PS1 animals at six to seven months of age. Immunohistochemical analysis with markers of microgliosis (ionized calcium-binding adapter molecule 1; Iba1) and astrogliosis (glial fibrillary acid protein; GFAP) revealed that our fingolimod treatment regime strongly down regulated neuroinflammation in the hippocampus and neocortex of this AD model. These effects were accompanied by a moderate reduction of Aβ accumulation in hippocampus and neocortex. Our results suggest that fingolimod, when applied after onset of disease symptoms in an APP/PS1 mouse model, rescues synaptic pathology that is believed to underlie memory deficits in AD mice, and that this beneficial effect is mediated via anti-neuroinflammatory actions of the drug on microglia and astrocytes.     

Applying Feature-Weighted Gradient Decent K-Nearest Neighbor to Select Promising Projects for Scientific Funding

Due to its outstanding ability in processing large quantity and high-dimensional data, machine learning models have been used in many cases, such as pattern recognition, classification, spam filtering, data mining and forecasting. As an outstanding machine learning algorithm, K-Nearest Neighbor (KNN) has been widely used in different situations, yet in selecting qualified applicants for winning a funding is almost new. The major problem lies in how to accurately determine the importance of attributes. In this paper, we propose a Feature-weighted Gradient Decent K-Nearest Neighbor (FGDKNN) method to classify funding applicants in to two types: approved ones or not approved ones. The FGDKNN is based on a gradient decent learning algorithm to update weight. It updatesthe weight of labels by minimizing error ratio iteratively, so that the importance of attributes can be described better. We investigate the performance of FGDKNN with Beijing Innofund. The results show that FGDKNN performs about 23%, 20%, 18%, 15% better than KNN, SVM, DT and ANN, respectively. Moreover, the FGDKNN has fast convergence time under different training scales, and has good performance under different settings.