A comparison of constitutive models for describing the flow of uncured styrene-butadiene rubber

Uncured styrene-butadiene rubber (SBR) can be modelled as a viscoelastic material with at least two different relaxation mechanisms. In this paper we compare multi-mode constitutive models combining two viscoelastic modes (linear and/or nonlinear) in three possible ways. Our particular choice of the two modes was inspired by models originally developed to describe the response of asphalt binders. We select the model that best fits the experimental data obtained from a modified stress relaxation experiment in the torsional configuration of the plate-plate rheometer. The optimisation of the five model parameters for each model is achieved by minimising the weighted least-squares distance between experimental observations and the computer model output using a tree-structured Parzen estimator algorithm to find an initial guess, followed by further optimisation using the Nelder-Mead simplex algorithm. The results show that the model combining the linear mode and the nonlinear mode is the most suitable variant to describe the observed behavior of SBR in the given regime. The predictive capabilities of the three models are further examined in changed experimental and numerical configurations. Full data and code to produce the figures in this article are included as supplementary material

Experimental separation of the onset of slip and sharkskin melt instabilities during the extrusion of silica‑filled, styrene–butadiene rubber compounds

The flow curves of polymers often reveal the onset of melt instabilities such as sharkskin, stick–slip, or gross melt fracture, in order of increasing shear rates. The focus of this work lies in the application of the Göttfert sharkskin option to the investigation of flow curves of styrene-butadiene rubber (SBR) compounds. The sharkskin option consists of highly sensitive pressure transducers located inside a slit die of a capillary rheometer. This tool allows the detection of in-situ pressure fluctuation characteristics of different melt instabilities. It is shown that the change of slope of the transition region in the flow curves is only linked to slip. Dynamic Mechanical Analysis (DMA) measurements furthermore show that the shear rate at which the change of slope can be observed shows the same temperature dependency as the viscous and elastic properties of the compounds

Investigation of the Sharkskin melt instability using optical Fourier analysis

An optical method allowing the characterization of melt flow instabilities typically occurring during an extrusion process of polymers and polymer compounds is presented. It is based on a camera‐acquired image of the extruded compound with a reference length scale. Application of image processing and transformation of the calibrated image to the frequency domain yields the magnitude spectrum of the instability. The effectiveness of the before mentioned approach is shown on Styrene‐butadiene rubber (SBR) compounds, covering a wide range of silica filler content, extruded through a Göttfert capillary rheometer. The results of the image‐based analysis are compared with the results from the sharkskin option, a series of highly sensitive pressure transducers installed inside the rheometer. A simplified version of the code used to produce the optical analysis results is included as supplementary material

Structure and domain dynamics of human lactoferrin in solution and the influence of Fe(III)-ion ligand binding

BackgroundHuman lactoferrin is an iron-binding protein of the innate immune system consisting of two connected lobes, each with a binding site located in a cleft. The clefts in each lobe undergo a hinge movement from open to close when Fe3+ is present in the solution and can be bound. The binding mechanism was assumed to relate on thermal domain fluctuations of the cleft domains prior to binding. We used Small Angle Neutron Scattering and Neutron Spin Echo Spectroscopy to determine the lactoferrin structure and domain dynamics in solution.ResultsWhen Fe3+ is present in solution interparticle interactions change from repulsive to attractive in conjunction with emerging metas aggregates, which are not observed without Fe3+. The protein form factor shows the expected change due to lobe closing if Fe3+ is present. The dominating motions of internal domain dynamics with relaxation times in the 30–50 ns range show strong bending and stretching modes with a steric suppressed torsion, but are almost independent of the cleft conformation. Thermally driven cleft closing motions of relevant amplitude are not observed if the cleft is open.ConclusionThe Fe3+ binding mechanism is not related to thermal equilibrium fluctuations closing the cleft. A likely explanation may be that upon entering the cleft the iron ion first binds weakly which destabilizes and softens the hinge region and enables large fluctuations that then close the cleft resulting in the final formation of the stable iron binding site and, at the same time, stable closed conformation

Molecularly defined diffuse leptomeningeal glioneuronal tumor (DLGNT) comprises two subgroups with distinct clinical and genetic features

Diffuse leptomeningeal glioneuronal tumors (DLGNT) represent rare CNS neoplasms which have been included in the 2016 update of the WHO classification. The wide spectrum of histopathological and radiological features can make this enigmatic tumor entity difficult to diagnose. In recent years, large-scale genomic and epigenomic analyses have afforded insight into key genetic alterations occurring in multiple types of brain tumors and provide unbiased, complementary tools to improve diagnostic accuracy. Through genome-wide DNA methylation screening of > 25,000 tumors, we discovered a molecularly distinct class comprising 30 tumors, mostly diagnosed histologically as DLGNTs. Copy-number profiles derived from the methylation arrays revealed unifying characteristics, including loss of chromosomal arm 1p in all cases. Furthermore, this molecular DLGNT class can be subdivided into two subgroups [DLGNT methylation class (MC)-1 and DLGNT methylation class (MC)-2], with all DLGNT-MC-2 additionally displaying a gain of chromosomal arm 1q. Co-deletion of 1p/19q, commonly seen in IDH-mutant oligodendroglioma, was frequently observed in DLGNT, especially in DLGNT-MC-1 cases. Both subgroups also had recurrent genetic alterations leading to an aberrant MAPK/ERK pathway, with KIAA1549:BRAF fusion being the most frequent event. Other alterations included fusions of NTRK1/2/3 and TRIM33:RAF1, adding up to an MAPK/ERK pathway activation identified in 80% of cases. In the DLGNT-MC-1 group, age at diagnosis was significantly lower (median 5 vs 14 years, p < 0.01) and clinical course less aggressive (5-year OS 100, vs 43% in DLGNT-MC-2). Our study proposes an additional molecular layer to the current histopathological classification of DLGNT, of particular use for cases without typical morphological or radiological characteristics, such as diffuse growth and radiologic leptomeningeal dissemination. Recurrent 1p deletion and MAPK/ERK pathway activation represent diagnostic biomarkers and therapeutic targets, respectively—laying the foundation for future clinical trials with, e.g., MEK inhibitors that may improve the clinical outcome of patients with DLGNT

Amphiphilic beads as depots for sustained drug release integrated into fibrillar scaffolds

Native extracellular matrix (ECM) is a complex fibrous structure loaded with bioactive cues that affects the surrounding cells. A promising strategy to mimicking native tissue architecture for tissue engineering applications is to engineer fibrous scaffolds using electrospinning. By loading appropriate bioactive cues within these fibrous scaffolds, various cellular functions such as cell adhesion, proliferation and differentiation can be regulated. Here, we report on the encapsulation and sustained release of a model hydrophobic drug (dexamethasone (Dex)) within beaded fibrillar scaffold of poly(ethylene oxide terephthalate)-poly(butylene terephthalate) (PEOT/PBT), a polyether-ester multiblock copolymer to direct differentiation of human mesenchymal stem cells (hMSCs). The amphiphilic beads act as depots for sustained drug release that is integrated into the fibrillar scaffolds. The entrapment of Dex within the beaded structure results in sustained release of the drug over the period of 28days. This is mainly attributed to the diffusion driven release of Dex from the amphiphilic electrospun scaffolds. In vitro results indicate that hMSCs cultured on Dex containing beaded fibrillar scaffolds exhibit an increase in osteogenic differentiation potential, as evidenced by increased alkaline phosphatase (ALP) activity, compared to the direct infusion of Dex in the culture medium. The formation of a mineralized matrix is also significantly enhanced due to the controlled Dex release from the fibrous scaffolds. This approach can be used to engineer scaffolds with appropriate chemical cues to direct tissue regenerationAKG, SMM, LM and AK conceived the idea and designed the experiments. AKG and SMM fabricated electrospun scaffolds and performed the structural (SEM, FTIR), mechanical, and in vitro studies. AAK and AKGperformedDex release study. AKGand AP performed thermal analysis. AKG analyzed experimental data. AKG, SMM, LMand AK wrote the manuscript. ADL and CvB provided the polymers and corrected the manuscript. AKK, AP, MG and RLR revised the paper. All authors discussed the results and commented on the manuscript. Authors would like to thank Shilpaa Mukundan, Poornima Kulkarni and Dr. Arghya Paul for help with image analysis, drug release modeling and technical discussion respectively. AKG would like to thank Prof. Robert Langer for access to equipment and acknowledge financial support from MIT Portugal Program (MPP-09Call-Langer-47). SMMthanks the Portuguese Foundation for Science and Technology (FCT) for the personal grant SFRH/BD/42968/2008 (MIT-Portugal Program). This research was funded by the office of Naval Research Young National Investigator Award (AK), the Presidential Early Career Award for Scientists and Engineers (PECASE) (AK), the NIH (EB009196; DE019024; EB007249; HL099073; AR057837), the National Science Foundation CAREER award (DMR 0847287; AK), and the Dutch Technology Foundation (STW # 11135; LM, CvB, and AD)

Melt Instability Identification Using Unsupervised Machine Learning Algorithms

In industrial extrusion processes, increasing shear rates can lead to higher production rates. However, at high shear rates, extruded polymers and polymer compounds often exhibit melt instabilities ranging from stick-slip to sharkskin to gross melt fracture. These instabilities result in challenges to meet the specifications on the extrudate shape. Starting with an existing published data set on melt instabilities in polymer extrusion, we assess the suitability of clustering, unsupervised machine learning algorithms combined with feature selection, to extract and identify hidden and important features from this data set, and their possible relationship with melt instabilities. The data set consists of both intrinsic features of the polymer as well as extrinsic features controlled and measured during an extrusion experiment. Using a range of commonly available clustering algorithms, it is demonstrated that the features related to only the intrinsic properties of the data set can be reliably divided into two clusters, and that in turn, these two clusters may be associated with either the stick-slip or sharkskin instability. Furthermore, using a feature ranking on both the intrinsic and extrinsic features of the data set, it is shown that the intrinsic properties of molecular weight and polydispersity are the strongest indicators of clustering