2,747 research outputs found
Recommended from our members
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
Recommended from our members
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 RILSANĀ® polyamide 11 molding polymer pellets and
Degussa VESTAMIDĀ® 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
Recommended from our members
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) RILSANĀ® 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
Recommended from our members
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 RilsanĀ® polyamide 11 molding polymer pellets were used
with 1, 3, 5, and 7 wt% loadings of Arkemaās 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
Recommended from our members
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
Recommended from our members
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 RILSANĀ® polyamide 11 molding polymer
pellets were examined with two types of nanoparticles: chemically modified
montmorillonite (MMT) organoclays, and carbon nanofibers (CNFs); and Clairantās
ExolitĀ® 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
- ā¦