SLS Processing Studies of Nylon 11 Nanocomposites

Selective Laser Sintering (SLS) is widely used for rapid prototyping/manufacturing of nylon 11 and nylon 12 parts. This processing technique has not been explored for nylon nanocomposites. This study investigates the technicalities of processing nylon 11-clay and nylon-carbon nanofiber nanocomposites with SLS. Microstructural analyses of the SLS powders and parts were conducted under SEM. Results suggest that SLS processing is possible with the new nylon 11 nanocomposites. Yet the SLS parts built have inferior properties relative to those of injection molding, suggesting that more fine tuning for the processing is required.Mechanical Engineerin

Polyamide Nanocomposites for Selective Laser Sintering

Current polyamide 11 and 12 are lacking in fire retardancy and high strength/high heat resistance characteristics for a plethora of finished parts that are desired and required for performance driven applications. It is anticipated that nanomodification of polyamide 11 and 12 will result in enhanced polymer performance, i.e., fire retardancy, high strength and high heat resistance for polyamide 11 and 12. It is expected that these findings will expand the market opportunities for polyamide 11 and 12 resin manufacturers. The objective of this research is to develop improved polyamide 11 and 12 polymers with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing (RM). A nanophase was introduced into the polyamide 11 and 12 via twin screw extrusion to provide improved material properties of the polymer blends. Arkema RILSAN® polyamide 11 molding polymer pellets and Degussa VESTAMID® L1670 polyamide 12 were examined with three types of nanoparticles: chemically modified montmorillonite (MMT) organoclays, surface modified nanosilica, and carbon nanofibers (CNFs) to create polyamide 11 and 12 nanocomposites. Wide angle X-ray diffraction (WAXD) and transmission electron microscopy (TEM) were used to determine the degree of dispersion. Injection molded test specimens were fabricated for physical, thermal, mechanical properties, and flammability tests. Thermal stability of these polyamide 11 and 12 nanocomposites was examined by TGA. Mechanical properties such as tensile, flexural, and elongation at break were measured. Flammability properties were also obtained using the Cone Calorimeter at an external heat flux of 50 kW/m2. TEM micrographs, physical, mechanical, and flammability properties are included in the paper. Polyamide 11 and 12 nanocomposites properties are compared with polyamide 11 and 12 baseline polymers. Based on flammability and mechanical material performance, selective polymers including polyamide 11 nanocomposites and control polyamide 11 were cryogenically ground into fine powders and fabricated into SLS parts.Mechanical Engineerin

Innovative Selective Laser Sintering Rapid Manufacturing using Nanotechnology

The objective of this research is to develop an improved nylon 11 (polyamide 11) polymer with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing (RM). A nanophase was introduced into nylon 11 via twin screw extrusion to provide improved material properties of the polymer blends. Atofina (now known as Arkema) RILSAN® nylon 11 injection molding polymer pellets was used with three types of nanoparticles: chemically modified montmorillonite (MMT) organoclays, nanosilica, and carbon nanofibers (CNF) to create nylon 11 nanocomposites. Wide angle X-ray diffraction (WAXD) and transmission electron microscopy (TEM) were used to determine the degree of dispersion. Fifteen nylon 11 nanocomposites and control nylon 11 were fabricated by injection molding. Flammability properties (using a cone calorimeter with a radiant flux of 50 kW/m2 ) and mechanical properties such as tensile strength and modulus, flexural modulus, elongation at break were determined for the nylon 11 nanocomposites and compared with the baseline nylon 11. Based on flammability and mechanical material performance, five polymers including four nylon 11 nanocomposites and a control nylon 11 were cryogenically ground into fine powders for SLS RM. SLS specimens were fabricated for flammability, mechanical, and thermal properties characterization. Nylon 11-CNF nanocomposites exhibited the best overall properties for this study.Mechanical Engineerin

Polyamide 11-Carbon Nanotubes Nanocomposites: Preliminary Investigation

The objective of this research is to develop an improved polyamide 11 (PA11) polymer with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing. In the present study, a nanophase was introduced into polyamide 11 via twin screw extrusion. Arkema Rilsan® polyamide 11 molding polymer pellets were used with 1, 3, 5, and 7 wt% loadings of Arkema’s GraphistrengthTM multi-wall carbon nanotubes (MWNTs) to create a family of PA11-MWNT nanocomposites. Transmission electron microscopy and scanning electron microscopy were used to determine the degree and uniformity of dispersion. Injection molded test specimens were fabricated for physical, thermal, mechanical properties, and flammability measurements. Thermal stability of these polyamide 11-MWNT nanocomposites was examined by TGA. Mechanical properties such as ultimate tensile strength, rupture tensile strength, and elongation at rupture were measured. Flammability properties were also obtained using the UL 94 test method. All these different methods and subsequent polymer characteristics are discussed in this paper.Mechanical Engineerin

Comparison of chemical profiles and effectiveness between Erxian decoction and mixtures of decoctions of its individual herbs : a novel approach for identification of the standard chemicals

Acknowledgements This study was partially supported by grants from the Seed Funding Programme for Basic Research (Project Number 201211159146 and 201411159213), the University of Hong Kong. We thank Mr Keith Wong and Ms Cindy Lee for their technical assistances.Peer reviewedPublisher PD

A joint moment projection method and maximum entropy approach for simulation of soot formation and oxidation in diesel engines

A joint moment projection method and maximum entropy approach for treating the soot population balance equations is developed and presented in this work. The moment projection method is used to solve the population balance equations and generate moments that are supplied to the maximum entropy approach as a post-processing technique to reconstruct the soot particle size distribution. The particle size range required by the maximum entropy for particle size distribution reconstruction is determined based on the weighted particles generated in the moment projection method. The performance of the joint approach is first evaluated by solving a set of simplified population balance equations in Matlab, then it is implemented into a Stochastic Reactor Model engine code to simulate the formation and oxidation of soot particles in a single-cylinder direct injection diesel engine. Results suggest that the joint approach has the advantages of ease of implementation, high accuracy and low computational cost. It enables a detailed analysis on the soot formation and oxidation processes in diesel engines. Complete information on the soot particle size distribution can be provided with little CPU cost induced

Intumescent Flame Retardant Polyamide 11 Nanocomposites

Current polyamide 11 and 12 are lacking in fire retardancy and high strength/high heat resistance characteristics for a plethora of fabricated parts that are desired and required for performance driven applications. The introduction of selected nanoparticles such as surface modified montmorillonite (MMT) clay or carbon nanofibers (CNFs), combined with a conventional intumescent flame retardant (FR) additive into the polyamide 11/polyamide 12 (PA11/PA12) by melt processing conditions has resulted in the preparation of a family of intumescent polyamide nanocomposites. These intumescent polyamide 11 and 12 nanocomposites exhibit enhanced polymer performance characteristics, i.e., fire retardancy, high strength and high heat resistance and are expected to expand the market opportunities for polyamide 11 and polyamide 12 polymer manufacturers. The objective of this research is to develop improved polyamide 11 and 12 polymers with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing (RM). In the present study, a nanophase was introduced into the polyamide 11 and combining it with a conventional intumescent FR additive via twin screw extrusion. Arkema RILSAN® polyamide 11 molding polymer pellets were examined with two types of nanoparticles: chemically modified montmorillonite (MMT) organoclays, and carbon nanofibers (CNFs); and Clairant’s Exolit® OP 1230 intumescent FR additive were used to create a family of FR intumescent polyamide 11 nanocomposites. Transmission electron microscopy (TEM) was used to determine the degree of nanoparticles dispersion. Injection molded specimens were fabricated for physical, thermal, and flammability measurements. Thermal stability of these intumescent polyamide 11 nanocomposites was examined by TGA. Flammability properties were obtained using the Cone Calorimeter at an external heat flux of 35 kW/m 2 and UL 94 Test Method. Heat deflection temperatures (HDT) were also measured. TEM micrographs, physical, thermal, and flammability properties are presented. FR intumescent polyamide 11 nanocomposites properties are compared with polyamide 11 baseline polymer. Based on flammability and mechanical material performance, selective polymers including polyamide 11 nanocomposites and control polyamide 11 will be cryogenically ground into fine powders for SLS RM processing. SLS specimens will be fabricated for thermal, flammability, and mechanical properties characterization.Mechanical Engineerin

Targeted online liquid chromatography electron capture dissociation mass spectrometry for the localization of sites of in vivo phosphorylation in human Sprouty2

We demonstrate a strategy employing collision-induced dissociation for phosphopeptide discovery, followed by targeted electron capture dissociation (ECD) for site localization. The high mass accuracy and low background noise of the ECD mass spectra allow facile sequencing of coeluting isobaric phosphopeptides, with up to two isobaric phosphopeptides sequenced from a single mass spectrum. In contrast to the previously described neutral loss of dependent ECD method, targeted ECD allows analysis of both phosphotyrosine peptides and lower abundance phosphopeptides. The approach was applied to phosphorylation analysis of human Sprouty2, a regulator of receptor tyrosine kinase signaling. Fifteen sites of phosphorylation were identified, 11 of which are novel

Genetic Classification of Populations using Supervised Learning

There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are geographically separated, case--control studies and quality control (when participants in a study have been genotyped at different laboratories). This latter application is of particular importance in the era of large scale genome wide association studies, when collections of individuals genotyped at different locations are being merged to provide increased power. The traditional method for detecting structure within a population is some form of exploratory technique such as principal components analysis. Such methods, which do not utilise our prior knowledge of the membership of the candidate populations. are termed \emph{unsupervised}. Supervised methods, on the other hand are able to utilise this prior knowledge when it is available. In this paper we demonstrate that in such cases modern supervised approaches are a more appropriate tool for detecting genetic differences between populations. We apply two such methods, (neural networks and support vector machines) to the classification of three populations (two from Scotland and one from Bulgaria). The sensitivity exhibited by both these methods is considerably higher than that attained by principal components analysis and in fact comfortably exceeds a recently conjectured theoretical limit on the sensitivity of unsupervised methods. In particular, our methods can distinguish between the two Scottish populations, where principal components analysis cannot. We suggest, on the basis of our results that a supervised learning approach should be the method of choice when classifying individuals into pre-defined populations, particularly in quality control for large scale genome wide association studies.Comment: Accepted PLOS On