Ultrasound directed self-assembly (DSA) relies on the acoustic radiation force associated with a standing ultrasound wave to organize particles dispersed in a fluid medium into specific patterns. State-of-the-art ultrasound DSA methods can only organize particles into (quasi-)periodic patterns, limited by the use of single-frequency ultrasound wave fields. Acoustic holography and acoustic waveguides provide alternatives to assembling complex patterns of particles, but generally provide low spatial accuracy and are not re-configurable because they require custom hardware for each specific pattern of particles, which is impractical. We introduce multi-frequency ultrasound wave fields to organize particles in non-periodic patterns. We theoretically derive and experimentally validate a solution methodology to determine the operating parameters (frequency, amplitude, phase) of any number and spatial arrangement of ultrasound transducers, required to assemble spherical particles dispersed in an inviscid fluid medium into any specific two-dimensional pattern. The results show that multi-frequency ultrasound DSA enables the assembly of complex, non-periodic patterns of particles with substantially fewer ultrasound transducers than single-frequency ultrasound DSA, and without incurring a penalty in terms of accuracy. The results of this work fundamentally transform the state-of-the-art knowledge of ultrasound DSA. Multi-frequency ultrasound wave fields enable a near-unlimited complexity of patterns of particles that can be assembled, increasing the relevance of the technology to practical implementation in engineering applications such as manufacturing of engineered composite materials that derive their properties from the spatial organization of the filler in the matrix material. Although this work focuses specifically on ultrasound wave fields, the theoretical model is valid for all wave phenomena. / Master of Science / Ultrasound directed self-assembly (DSA) is the process where particles dispersed in a fluid medium assemble into specific patterns due to their interactions with a sound wave and/or other particles. Current ultrasound DSA methods use a single-frequency ultrasound wave to assemble particles into specific patterns, which creates repeating patterns within the fluid medium. Other methods of assembling particles that allow for more complex, non-repeating patterns generally provide low spatial accuracy and do not allow dynamically changing the pattern as they require custom hardware for each specific pattern of particles, rendering these methods impractical. We use many ultrasound waves each with a different frequency to organize particles into complex, non-repeating patterns, which we call multi-frequency ultrasound DSA. We theoretically derive and experimentally validate a method that allows us to assemble any specific two-dimensional pattern of particles using multi-frequency ultrasound DSA. The results show that multi-frequency ultrasound DSA enables the assembly of complex, non-repeating patterns of particles with substantially resources than single-frequency ultrasound DSA, and without incurring a penalty in terms of accuracy. Multi-frequency ultrasound DSA enables a near-unlimited complexity of patterns of particles that can be assembled, increasing the relevance of the technology to practical implementation in engineering applications.

It’s becoming more and more difficult to make smaller, denser, and faster computer chips. There’s an increasing demand to design new materials to be applied in current lithographic process to get higher patterning performance. In this work, the aqueous developable single molecule resists were introduced, synthesized and patterned. A new group of epoxide other than glycidyl ether, cyclohexene oxide was introduced to functionalize a molecular core and 15 nm resolution was obtained. The directed self-assembly (DSA) of block copolymers as an alternative lithographic technique has received growing interest in the last several years for performing higher levels of pitch subdivision. A 3-step simplified process for DSA by using a photodefinable substrate was introduced by using a functionalized polyphenol with an energy switchable group and a crosslinkable group. Two high χ block copolymers PS-b-PAA and PS-b-PHEMA were successfully designed and synthesized via ATRP with controlled Mw and PDI. The size of the same PS-b-PAA polymer was tunable by varying the thermal annealing time. PS-b-PHEMA shows to be a suitable block polymer for the industry-friendly thermal annealing process. A self-complementary hydrogen-bonding urea group as a center group was used to facilitate the self-assembly of polymers. “Click” chemistry is promising for synthesis of PS-Urea-Urea-PMMA.

A molecular dynamics coarse-grained block copolymer (BCP) model was developed and used to studied directed self-assembly (DSA), especially in regards to applications for semiconductor manufacturing. Most of the thesis is spent investigating the effect that guiding layer properties and block copolymer properties have on line roughness and defect density in a BCP-DSA process. These two effects are perhaps the most critical in making BCP-DSA a cost efficient industrial process. It is found that guiding patterns have little effect on line roughness and in fact that the BCP heals the majority of roughness in the underlying pattern. BCP properties have a larger effect on line roughness. Segregation strength (as measured by χN, where χ is the Flory- Huggins interaction parameter and N is the degree of polymerization) resulted in a larger than expected increase in line roughness when χN was low. Polydispersity resulted in a moderate increase in line roughness. In regards to equilibrium defect density, free energy calculations showed that χ was the primary determining factor, not χN as many expected. Equilibrium defect density was found to decrease exponentially with increasing χ. Defect density is also found to scale exponentially with polydispersity. Concerning defect heal rate, which can increase the real defect rate of a process if said rate is too low, it is found that increasing χN linearly increased the barrier to defect healing, which means that the defect heal rate decreases exponentially. However, for thin films this is only true for χN > ~ 50. Below χN ~ 50, the barrier is approximately constant. These results give excellent guidance to the type of materials and processes necessary to optimize a BCP-DSA process. A simulation technique designed to more efficiently sample over energy barriers called protracted noise dynamics for polymer systems was developed and studied. It was found that a decrease in simulation time of up to 4 orders of magnitude was achieved. The effect of box size on allowable pitches for a lamellar forming BCP was derived and demonstrated. It was found that more elongated boxes yielded more possible pitches and more accurate results. A short study on the effect of multiblock copolymers on the location of the order-disorder transition was also carried out and it was found that multiblock copolymers had small effect on the ODT. The distribution of chain conformations was also calculated.

Block copolymers demonstrate potential in next-generation lithography as a solution for overcoming the limitations of conventional lithographic techniques. Ideal block copolymer materials for this application can be synthesized on a commercial scale, have high [chi]-parameters promoting self-assembly into sub-20 nm pitch domains, have controllable alignment and orientation, and have high etch contrast between the domains for facilitating pattern transfer into the underlying substrate. Block copolymers that contain silicon in one domain are attractive for nanopatterning since they often fulfill at least three of these requirements. However, silicon-containing materials are notoriously difficult to orient in thin films due to the low surface energy of the silicon-containing block, which typically wets the free surface interface. In this work, the methodology behind material choice and the synthesis of new silicon-containing block copolymers by a variety of polymerization techniques will be described. Thin film self-assembly of the block copolymers with domains oriented perpendicular to the plane of the substrate is achieved using different solvent annealing and neutral surface treatments with thermal annealing conditions. Block copolymer patterns are transferred to the underlying substrate by reactive ion etching and directed self-assembly of the polymers is demonstrated using chemical contrast patterns. Interesting thermodynamics governing the self-assembly of block copolymers with solvent annealing will also be discussed. Finally, new amphiphilic block copolymers will be described that were created with lithographic applications in mind but that are most useful for biological applications in drug delivery. / text

Polymer nanoparticles (PNPs) that exhibit selective stimuli-responsive degradation and drug release at tumor sites are promising candidates in the development of smart nanomedicines. In this thesis, we demonstrate a microfluidic approach to manufacturing biological stimuli-responsive PNPs with flow-tunable physicochemical and pharmacological properties. The investigated PNPs contain cleavable disulfide linkages in two different locations (core and interface, DualM PNPs) exhibiting responsivity to elevated levels of glutathione (GSH), such as those found within cancerous cells. First, we conduct a mechanistic study on the microfluidic formation of DualM PNPs without encapsulated drug. We show that physicochemical properties, including size, morphology, and internal structure, of DualM PNPs are tunable with manufacturing flow rate. Microfluidic formation of DualM PNPs is explained by the interplay of shear-induced coalescence, shear-induced breakup, and intraparticle chain rearrangements. In addition, we demonstrate that rates of GSH-triggered changes in size and internal structure are linearly correlated with initial PNP sizes and internal structures, respectively. Next, we expand our study to focus on microfluidic control of pharmacological properties of DualM PNPs containing either an anticancer drug (paclitaxel, PAX-PNPs) or a fluorescent drug surrogate (DiI-PNPs). Microfluidic PAX-PNPs and DiI-PNPs show similar sizes and morphologies with their non-drug-loaded counterparts under the same flow conditions. We then show that pharmacological properties of DualM PNPs, including encapsulation efficiency, GSH-triggered release rate, cell uptake, cytotoxicity against MCF-7 (cancerous) and HaCaT (healthy), and relative difference in MCF-7 and HaCaT cytotoxicity, all increase linearly as flow-directed PNP size decreases, providing remarkably simple process-structure-property relationships. In addition, we show that microfluidic manufacturing improves encapsulation homogeneities within PNPs relative to bulk nanoprecipitation. These results highlight the potential of flow-directed shear processing in microfluidics for providing controlled manufacturing routes to biological stimuli-responsive nanomedicines optimized for specific therapeutic applications. Finally, we summarize various design strategies of biological stimuli-responsive PNPs. We show that the location and density of disulfide linkages within PNPs determines stimulus-triggered degradation mechanism and kinetics. In addition, we show various bottom-up approaches to tune PNP responsivities that involves chemical processing, including formulation chemistry and intramolecular forces. Along with the top-down microfluidic approach that we demonstrate experimentally, this chapter provides a more comprehensive understanding of process-structure-property relations opening up vast possibilities for manufacturing smarter nanomedicines. / Graduate

Nanoscale structures play a fundamental role in diverse scientific areas, including biology and information technology. It is necessary to develop methods that can observe nanoscale structures and dynamic processes that involve them. Colloidal plasmonic nanoparticles (plasmonic “atoms”) and their clusters (plasmonic “molecules”) are nanoscale objects with remarkable optical properties that provide new opportunities for sensing and imaging on the relevant length and time scales. Many biology questions require optically monitoring of the dynamic behavior of biological systems on single molecule level. In contrast to the commonly used fluorescent probes which have the problem of bleaching, blinking and relatively weak signals, plasmonic probes display superb brightness, persistency and photostability, thus enable long observation time and high temporal and spacial resolutions. When plasmonic atoms are clustered together, their resonances redshift while the intensities increase as a result of plasmon coupling. These optical responses are dependent on the interparticle gaps and the overall geometry, which makes plasmonic molecules capable of detecting biomolecule clustering and measuring nanometer scale distance fluctuations. In this dissertation, individual plasmonic atoms are firstly evaluated as imaging probe and their interactions with lipid membrane are tested on a newly developed on-chip black lipid membrane system. Subsequently, plasmonic dimers (plasmon rulers) prepared through DNA-programmed self-assembly are monitored to detect the mechanical properties of single biopolymers. Measurement of the spring constant of short (tens of nucleotides or base pairs) DNAs is demonstrated through plasmon coupling microscopy. Colloidal plasmonic atoms of various materials, sizes and shapes scatter vivid colors in the full-visible range. Assembling them into plasmonic molecules provides additional degrees of freedom for color manipulation. More importantly, the electric field in the gaps of plasmonic molecules can be enhanced by several orders of magnitude, which is highly desirable in single molecule sensing applications. In this dissertation, the fundamentals of plasmonic coupling are investigated through one-dimensional gold nanosphere chains. Using the directed self-assembly approach, multichromatic color-switchable plasmonic nanopixels composed of plasmonic atoms and molecules of various materials, sizes, shapes and geometries are integrated in one image with nanometer precision, which facilitates the encoding of complex spectral features with high relevance in security tagging and high density optical data storage. / 2017-01-01T00:00:00Z

Maitriser les coûts de fabrication des circuits intégrés tout en augmentant leur densité est d'une importance primordiale pour maintenir une certaine rentabilité dans l’industrie du semi-conducteur. Parmi les différents composants d’un circuit, nous nous intéressons aux connections verticales et métalliques, connues sous le nom de « vias ». Durant la fabrication, un processus de lithographie complexe est utilisé pour former une disposition de vias est formée sur une plaque de silicium, à l’aide d’un un masque optique. Pour des raisons de fabrication, une distance minimum entre les vias doit être respectée. Lorsque cette distance n’est pas respectée, nous parlons de « conflit ». Afin de supprimer ces conflits, l’industrie utilise une technique qui permet de décomposer une disposition de vias cible en plusieurs sous-ensembles, où les contraintes de distance minimum sont respectées : la formation des sous-ensembles individuels se fait en séquence sur la plaque de silicium en utilisant un masque optique par sous-ensemble. Cette technique est appelée Multiple Patterning (MP). Il y a de nombreuses façons de décomposer une disposition de vias et le but est d’assigner les vias à un nombre minimum de masques, car les masques sont coûteux. Minimiser le nombre de masques est équivalent à minimiser le nombre de couleurs dans un graphe disque unitaire. Ce problème est NP-difficile, mais un certain nombre de « bonnes » heuristiques existent. Une technique récente et prometteuse basée sur l’auto-assemblage et direction des molécules, aussi connue sous le nom Directed Self Assembly (DSA), permet de grouper les vias en conflits à condition de respecter certaines contraintes. L’objectif est de trouver la meilleure façon de grouper les vias afin de minimiser le nombre de masques tout en respectant les contraintes liées à DSA. Ce problème est un problème de coloration de graphes où les sommets de chaque couleurs définissent un ensemble de chemins « indépendants » de longueurs au plus k que nous appelons aussi le problème de coloration par k-chemins. Durant la modélisation, nous avons distingué deux problèmes de coloration par k-chemins pertinents: le problème général et le problème induit. Les deux problèmes sont connus pour être NP-difficile, ce qui explique l’utilisation d’heuristiques dans l’industrie pour trouver une décomposition valide en sous-ensembles. Dans cette étude, nous nous intéressons à des méthodes exactes afin de concevoir des solutions optimales et d’évaluer la qualité de l’heuristique développée en industrie (chez Mentor Graphics). Nous présentons différentes méthodes: une approche par programmation linéaire en nombre entier (ILP) où nous étudions plusieurs formulations, une approche par programmation dynamique pour résoudre le cas induit quand k=1 ou k=2 et lorsque les graphes ont une petite longueur arborescente ; enfin, nous étudions le cas particulier des graphes lignes. Les résultats des différentes études numériques montrent que les formulations ILP « naïves » sont les meilleures. Elles listent tous les chemins possibles de longueur au plus k. Les tests sur des données industrielles ayant au plus 2000 sommets (plus grande composante connexe parmi celles qui constituent une instance) ont montré que les deux problèmes, général et induit, sont résolus en moins de 6 secondes, pour k=1 et k=2. La programmation dynamique, appliquée au problème induit de coloration par k-chemins quand k=1 et k=2, montre des résultats équivalents à ceux de la formulation ILP naïve. Cependant, nous nous attendons à de meilleurs résultats par programmation dynamique quand la valeur de k augmente. Enfin, nous montrons qu’un cas particuliers des graphes lignes peut être résolu en temps polynomial en exploitant les propriétés de l’algorithme d'Edmonds et des couplages dans les graphes bipartis. / Controlling the manufacturing costs of integrated circuits while increasing their density is of a paramount importance to maintain a certain degree of profitability in the semi-conductor industry. Among various components of a circuit, we are interested in vertical metallic connections known as “vias”. During manufacturing, a complex lithography process is used to form an arrangement of vias on a silicon wafer support, using an optical mask. For manufacturing reasons, a minimum distance between the vias must be respected. Whenever this is not the case, we are talking about a “conflict”. In order to eliminate these conflicts, the industry uses a technique that decomposes an arrangement of vias in several subsets, where minimum distance constraints are respected: the formation of the individual subsets is done, in sequence, on a silicon wafer using one optical mask per subset. This technique is called Multiple Patterning (MP). There are several ways to decompose an arrangement of vias, the goal being to assign the vias to a minimum number of masks, since the masks are expensive. Minimizing the number of masks is equivalent to minimizing the number of colors in a unit disk graph. This is a NP-hard problem however, a number of “good” heuristics exist. A recent and promising technique is based on the direction and self-assembly of the molecules called Directed Self Assembly (DSA), allows to group vias in conflict according to certain conditions. The main challenge is to find the best way of grouping vias to minimize the number of masks while respecting the constraints related to DSA. This problem is a graph coloring problem where the vertices within each color define a set of independent paths of length at most k also called a k-path coloring problem. During the graph modeling, we distinguished two k-path coloring problems: a general problem and an induced problem. Both problems are known to be NP-hard, which explains the use of heuristics in the industry to find a valid decomposition into subsets. In this study, we are interested in exact methods to design optimal solutions and evaluate the quality of heuristics developed in the industry (at Mentor Graphics). We present different methods: an integer linear programming (ILP) approach where we study several formulations, a dynamic programming approach to solve the induced case when k=1 or k=2 and when the graphs have small tree-width; finally, we study a particular case of line graphs. The results of the various numerical studies show that the naïve ILP formulations are the best, they list all possible paths of length at most k. Tests on a snippet of industrial instances of at most 2000 vertices (a largest connected component among those constituting an instance) have shown that the two problems, general and induced, are solved in less than 6 seconds, for k=1 and k=2. Dynamic programming, applied to the induced k-path coloring when k=1 and k=2, shows results equivalent to those of the naïve ILP formulation, but we expect better results by dynamic programming when the value of k increases. Finally, we show that the particular case of line graphs can be solved in polynomial time by exploiting the properties of Edmonds’ algorithm and bipartite matching.

Aujourd'hui, les outils de lithographie utilisés dans l'industrie arrivent à leur limite de résolution en simple exposition. Pour continuer à diminuer les dimensions, il faut utiliser des techniques de double exposition, mais cela entraîne une explosion des coûts de fabrication. Cette thèse se focalise sur les aspects de modélisation de deux techniques, Sidewall Image Transfer et Directed Self-Assembly, qui sont pressenties pour permettre à l'industrie de continuer la réduction des dimensions des transistors, tout en minimisant les coûts. / Today, the lithographic tools used in industry came to their resolution limit in single patterning. In order to continue the reduction of dimensions, it is necessary to use double patterning, but this increase drastically the cost of manufacturing. This thesis focus on the modelisation aspects of two techniques, Sidewal Image Transfer and Directed Self-Assembly, that can help the industry continuing making transistors even smaller, while keeping the costs manageable.

No description available.

Block copolymer self-assembly has demonstrated sub-optical lithographic resolution . High values of chi, the block copolymer interaction parameter, are required to achieve next-generation lithographic resolution . Unfortunately, high values of chi can lead to thin film orientation control difficulties , which are believed to be caused by large differences in the surface energy of each block relative to the substrate and the free surface. The substrate-block interface can be modified to achieve a surface energy intermediate to that of each individual block ; the air-polymer interface, however, presents additional complications. This thesis describes the synthesis of polymers for top coat surface treatments, which are designed to modify the surface energy of the air-block copolymer interface and enable block copolymer orientation control upon thermal annealing. Polymers with β-keto acid functionality were synthesized to allow polarity switching upon decarboxylation. Syntheses of anhydride containing polymers were established that provide another class of polarity switching materials. / text