761 resultados para Justin Trudeau
Resumo:
Electron beam-induced deposition (EBID) is a direct write process where an electron beam locally decomposes a precursor gas leaving behind non-volatile deposits. It is a fast and relatively in-expensive method designed to develop conductive (metal) or isolating (oxide) nanostructures. Unfortunately the EBID process results in deposition of metal nanostructures with relatively high resistivity because the gas precursors employed are hydrocarbon based. We have developed deposition protocols using novel gas-injector system (GIS) with a carbon free Pt precursor. Interconnect type structures were deposited on preformed metal architectures. The obtained structures were analysed by cross-sectional TEM and their electrical properties were analysed ex-situ using four point probe electrical tests. The results suggest that both the structural and electrical characteristics differ significantly from those of Pt interconnects deposited by conventional hydrocarbon based precursors, and show great promise for the development of low resistivity electrical contacts.
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Germanium (Ge) nanowires are of current research interest for high speed nanoelectronic devices due to the lower band gap and high carrier mobility compatible with high K-dielectrics and larger excitonic Bohr radius ensuing a more pronounced quantum confinement effect [1-6]. A general way for the growth of Ge nanowires is to use liquid or a solid growth promoters in a bottom-up approach which allow control of the aspect ratio, diameter, and structure of 1D crystals via external parameters, such as precursor feedstock, temperature, operating pressure, precursor flow rate etc [3, 7-11]. The Solid-phase seeding is preferred for more control processing of the nanomaterials and potential suppression of the unintentional incorporation of high dopant concentrations in semiconductor nanowires and unrequired compositional tailing of the seed-nanowire interface [2, 5, 9, 12]. There are therefore distinct features of the solid phase seeding mechanism that potentially offer opportunities for the controlled processing of nanomaterials with new physical properties. A superior control over the growth kinetics of nanowires could be achieved by controlling the inherent growth constraints instead of external parameters which always account for instrumental inaccuracy. The high dopant concentrations in semiconductor nanowires can result from unintentional incorporation of atoms from the metal seed material, as described for the Al catalyzed VLS growth of Si nanowires [13] which can in turn be depressed by solid-phase seeding. In addition, the creation of very sharp interfaces between group IV semiconductor segments has been achieved by solid seeds [14], whereas the traditionally used liquid Au particles often leads to compositional tailing of the interface [15] . Korgel et al. also described the superior size retention of metal seeds in a SFSS nanowire growth process, when compared to a SFLS process using Au colloids [12]. Here in this work we have used silver and alloy seed particle with different compositions to manipulate the growth of nanowires in sub-eutectic regime. The solid seeding approach also gives an opportunity to influence the crystallinity of the nanowires independent of the substrate. Taking advantage of the readily formation of stacking faults in metal nanoparticles, lamellar twins in nanowires could be formed.
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Conductive AFM and in situ methods were used to determine contact resistance and resistivity of individual Sb2S3 nanowires. Nanowires were deposited on oxidized Si surface for in situ measurements and on Si surface with macroelectrodes for conductive AFM (C-AFM) measurements. Contact resistance was determined by measurement of I(V) characteristics at different distances from the nanowire contact with the macroelectrode and resistivity of nanowires was determined. Sb2S3 is a soft material with low adhesion force to the surface and therefore special precautions were taken during measurements.
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Species invasions are more prevalent than ever before. While the addition of a species can dramatically change critical ecosystem processes, factors that mediate the direction and magnitude of those impacts have received less attention. A better understanding of the factors that mediate invasion impacts on ecosystem functioning is needed in order to target which exotic species will be most harmful and which systems are most vulnerable. The role of invasion on nitrogen (N) cycling is particularly important since N cycling controls ecosystem services that provision human health, e.g. nutrient retention and water quality.
We conducted a meta-analysis and in-depth studies focused on the invasive grass species, Microstegium vimineum, to better understand how (i) plant characteristics, (ii) invader abundance and neighbor identity, and (iii) environmental conditions mediate the impacts of invasion on N pools and fluxes. The results of our global meta-analysis support the concept that invasive species and reference community traits such as leaf %N and leaf C:N are useful for understanding invasion impacts on soil N cycling, but that trait dissimilarities between invaded and reference communities are most informative. Regarding the in-depth studies of Microstegium, we did not find evidence to suggest that invasion increases net nitrification as other studies have shown. Instead, we found that an interaction between its abundance and the neighboring plant identify were important for determining soil nitrate concentrations and net nitrification rates in the greenhouse. In field, we found that variability in environmental conditions mediated the impact of Microstegium invasion on soil N pools and fluxes, primarily net ammonification, between sites through direct, indirect, and interactive pathways. Notably, we detected a scenario in which forest openness has a negative direct effect and indirect positive effect on ammonification in sites with high soil moisture and organic matter. Collectively, our findings suggest that dissimilarity in plant community traits, neighbor identity, and environmental conditions can be important drivers of invasion impacts on ecosystem N cycling and should be considered when evaluating the ecosystem impacts of invasive species across heterogeneous landscapes.
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X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.
A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.
Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.
The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).
First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.
Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.
Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.
The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.
To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.
The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.
The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.
Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.
The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.
In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.
Resumo:
Microwave annealing is an emerging technique for achieving ordered patterns of block copolymer films on substrates. Little is understood about the mechanisms of microphase separation during the microwave annealing process and how it promotes the microphase separation of the blocks. Here, we use controlled power microwave irradiation in the presence of tetrahydrofuran (THF) solvent, to achieve lateral microphase separation in high- lamellar-forming poly(styrene-b-lactic acid) PS-b-PLA. A highly ordered line pattern was formed within seconds on silicon, germanium and silicon on insulator (SOI) substrates. In-situ temperature measurement of the silicon substrate coupled to condition changes during "solvo-microwave" annealing allowed understanding of the processes to be attained. Our results suggest that the substrate has little effect on the ordering process and is essentially microwave transparent but rather, it is direct heating of the polar THF molecules that causes microphase separation. It is postulated that the rapid interaction of THF with microwaves and the resultant temperature increase to 55 degrees C within seconds causes an increase of the vapor pressure of the solvent from 19.8 to 70 kPa. This enriched vapor environment increases the plasticity of both PS and PLA chains and leads to the fast self-assembly kinetics. Comparing the patterns formed on silicon, germanium and silicon on insulator (SOI) and also an in situ temperature measurement of silicon in the oven confirms the significance of the solvent over the role of substrate heating during "solvo-microwave" annealing. Besides the short annealing time which has technological importance, the coherence length is on a micron scale and dewetting is not observed after annealing. The etched pattern (PLA was removed by an Ar/O-2 reactive ion etch) was transferred to the underlying silicon substrate fabricating sub-20 nm silicon nanowires over large areas demonstrating that the morphology is consistent both across and through the film.
Resumo:
Carbon nanotubes (CNTs) have recently emerged as promising candidates for electron field emission (FE) cathodes in integrated FE devices. These nanostructured carbon materials possess exceptional properties and their synthesis can be thoroughly controlled. Their integration into advanced electronic devices, including not only FE cathodes, but sensors, energy storage devices, and circuit components, has seen rapid growth in recent years. The results of the studies presented here demonstrate that the CNT field emitter is an excellent candidate for next generation vacuum microelectronics and related electron emission devices in several advanced applications.
The work presented in this study addresses determining factors that currently confine the performance and application of CNT-FE devices. Characterization studies and improvements to the FE properties of CNTs, along with Micro-Electro-Mechanical Systems (MEMS) design and fabrication, were utilized in achieving these goals. Important performance limiting parameters, including emitter lifetime and failure from poor substrate adhesion, are examined. The compatibility and integration of CNT emitters with the governing MEMS substrate (i.e., polycrystalline silicon), and its impact on these performance limiting parameters, are reported. CNT growth mechanisms and kinetics were investigated and compared to silicon (100) to improve the design of CNT emitter integrated MEMS based electronic devices, specifically in vacuum microelectronic device (VMD) applications.
Improved growth allowed for design and development of novel cold-cathode FE devices utilizing CNT field emitters. A chemical ionization (CI) source based on a CNT-FE electron source was developed and evaluated in a commercial desktop mass spectrometer for explosives trace detection. This work demonstrated the first reported use of a CNT-based ion source capable of collecting CI mass spectra. The CNT-FE source demonstrated low power requirements, pulsing capabilities, and average lifetimes of over 320 hours when operated in constant emission mode under elevated pressures, without sacrificing performance. Additionally, a novel packaged ion source for miniature mass spectrometer applications using CNT emitters, a MEMS based Nier-type geometry, and a Low Temperature Cofired Ceramic (LTCC) 3D scaffold with integrated ion optics were developed and characterized. While previous research has shown other devices capable of collecting ion currents on chip, this LTCC packaged MEMS micro-ion source demonstrated improvements in energy and angular dispersion as well as the ability to direct the ions out of the packaged source and towards a mass analyzer. Simulations and experimental design, fabrication, and characterization were used to make these improvements.
Finally, novel CNT-FE devices were developed to investigate their potential to perform as active circuit elements in VMD circuits. Difficulty integrating devices at micron-scales has hindered the use of vacuum electronic devices in integrated circuits, despite the unique advantages they offer in select applications. Using a combination of particle trajectory simulation and experimental characterization, device performance in an integrated platform was investigated. Solutions to the difficulties in operating multiple devices in close proximity and enhancing electron transmission (i.e., reducing grid loss) are explored in detail. A systematic and iterative process was used to develop isolation structures that reduced crosstalk between neighboring devices from 15% on average, to nearly zero. Innovative geometries and a new operational mode reduced grid loss by nearly threefold, thereby improving transmission of the emitted cathode current to the anode from 25% in initial designs to 70% on average. These performance enhancements are important enablers for larger scale integration and for the realization of complex vacuum microelectronic circuits.
Resumo:
Purpose
The objective of our study was to test a new approach to approximating organ dose by using the effective energy of the combined 80kV/140kV beam used in fast kV switch dual-energy (DE) computed tomography (CT). The two primary focuses of the study were to first validate experimentally the dose equivalency between MOSFET and ion chamber (as a gold standard) in a fast kV switch DE environment, and secondly to estimate effective dose (ED) of DECT scans using MOSFET detectors and an anthropomorphic phantom.
Materials and Methods
A GE Discovery 750 CT scanner was employed using a fast-kV switch abdomen/pelvis protocol alternating between 80 kV and 140 kV. The specific aims of our study were to (1) Characterize the effective energy of the dual energy environment; (2) Estimate the f-factor for soft tissue; (3) Calibrate the MOSFET detectors using a beam with effective energy equal to the combined DE environment; (4) Validate our calibration by using MOSFET detectors and ion chamber to measure dose at the center of a CTDI body phantom; (5) Measure ED for an abdomen/pelvis scan using an anthropomorphic phantom and applying ICRP 103 tissue weighting factors; and (6) Estimate ED using AAPM Dose Length Product (DLP) method. The effective energy of the combined beam was calculated by measuring dose with an ion chamber under varying thicknesses of aluminum to determine half-value layer (HVL).
Results
The effective energy of the combined dual-energy beams was found to be 42.8 kV. After calibration, tissue dose in the center of the CTDI body phantom was measured at 1.71 ± 0.01 cGy using an ion chamber, and 1.73±0.04 and 1.69±0.09 using two separate MOSFET detectors. This result showed a -0.93% and 1.40 % difference, respectively, between ion chamber and MOSFET. ED from the dual-energy scan was calculated as 16.49 ± 0.04 mSv by the MOSFET method and 14.62 mSv by the DLP method.
Resumo:
Gold nanoparticles (Au NPs) with diameters ranging between 15 and 150 nm have been synthesised in water. 15 and 30 nm Au NPs were obtained by the Turkevich and Frens method using sodium citrate as both a reducing and stabilising agent at high temperature (Au NPs-citrate), while 60, 90 and 150 nm Au NPs were formed using hydroxylamine-o-sulfonic acid (HOS) as a reducing agent for HAuCl4 at room temperature. This new method using HOS is an extension of the approaches previously reported for producing Au NPs with mean diameters above 40 nm by direct reduction. Functionalised polyethylene glycol-based thiol polymers were used to stabilise the pre-synthesised Au NPs. The nanoparticles obtained were characterised using uv-visible spectroscopy, dynamic light scattering (DLS) and transmission electron microscopy (TEM). Further bioconjugation on 15, 30 and 90 nm PEGylated Au NPs were performed by grafting Bovine Serum Albumin, Transferrin and Apolipoprotein E (ApoE).
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© 2016, Springer Science+Business Media New York.The present study examined the relative effects of mindful acceptance and reappraisal on metacognitive attitudes and beliefs in relation to rumination and negative experiences. A small but growing literature has compared the effects of these strategies on immediate emotional experience, but little work has examined the broader, metacognitive impact of these strategies, such as maladaptive beliefs about rumination. One hundred and twenty-nine participants who reported elevated symptoms of depression were randomly assigned to receive brief training in mindful acceptance, reappraisal, or no training prior to undergoing an autobiographical sad mood induction. Participants rated their beliefs in relation to rumination and negative experiences before and after instructions to engage in mood regulation. Results showed that relative to reappraisal or no training, training in mindful acceptance resulted in greater decreases in maladaptive beliefs about rumination. The study suggests that training in mindful acceptance promotes beneficial changes in metacognitive attitudes and beliefs relevant to depression, and contributes to a greater understanding of the mechanisms through which mindfulness-based interventions lead to positive outcomes.
Resumo:
The microphase separation of block copolymer (BCP) thin films can afford a simple and cost-effective means to studying nanopattern surfaces, and especially the fabrication of nanocircuitry. However, because of complex interface effects and other complications, their 3D morphology, which is often critical for application, can be more complex than first thought. Here, we describe how emerging microscopic methods may be used to study complex BCP patterns and reveal their rich detail. These methods include helium ion microscopy (HIM) and high resolution x-section transmission electron microscopy (XTEM), and complement conventional secondary electron and atomic force microscopies (SEM and TEM). These techniques reveal that these structures are quite different to what might be expected. We illustrate the advances in the understanding of BCP thin film morphology in several systems, which result from this characterization. The systems described include symmetric, lamellar forming polystyrene-b-polymethylmethacrylate (PS-b-PMMA), cylinder forming polystyrene-b-polydimethylsiloxane (PS-b-PDMS), as well as lamellar and cylinder forming patterns of polystyrene-b-polyethylene oxide (PS-b-PEO) and polystyrene-b-poly-4-vinylpyridine (PS-b-P4VP). Each of these systems exhibits more complex arrangements than might be first thought. Finding and developing techniques whereby complex morphologies, particularly at very small dimensions, can be determined is critical to the practical use of these materials in many applications. The importance of quantifying these complex morphologies has implications for their use in integrated circuit manufacture, where they are being explored as alternative pattern forming methods to conventional UV lithography.
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The nanometer range structure produced by thin films of diblock copolymers makes them a great of interest as templates for the microelectronics industry. We investigated the effect of annealing solvents and/or mixture of the solvents in case of symmetric Poly (styrene-block-4vinylpyridine) (PS-b-P4VP) diblock copolymer to get the desired line patterns. In this paper, we used different molecular weights PS-b-P4VP to demonstrate the scalability of such high χ BCP system which requires precise fine-tuning of interfacial energies achieved by surface treatment and that improves the wetting property, ordering, and minimizes defect densities. Bare Silicon Substrates were also modified with polystyrene brush and ethylene glycol self-assembled monolayer in a simple quick reproducible way. Also, a novel and simple in situ hard mask technique was used to generate sub-7nm Iron oxide nanowires with a high aspect ratio on Silicon substrate, which can be used to develop silicon nanowires post pattern transfer.
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This paper analyses the impact of stimulating staff creativity and idea generation on the likelihood of innovation. Using data for over 3,000 firms, obtained from the Irish Community Innovation Survey 2008-10, we examine the impact of six creativity generating stimuli on product, process, organisational, and marketing innovation. Our results indicate that the stimuli impact the four forms of innovation in different ways. For instance brainstorming and multidisciplinary teams are found to stimulate all forms of innovation, rotation of employees is found to stimulate organisational innovation, while financial and non-financial incentives are found to have no effect on any form of innovation. We also find that the co-introduction of two or more stimuli increases the likelihood of innovation more than implementing stimuli in isolation. These results have important implications for management decisions in that they suggest that firms should target their creative efforts towards specific innovation outcomes.