Matching Items (115)
Filtering by
- Genre: Doctoral Dissertation
- Creators: Yan, Hao
- Creators: Xue, Guoliang
Description
The discovery of DNA helical structure opened the door of modern molecular biology. Ned Seeman utilized DNA as building block to construct different nanoscale materials, and introduced a new field, know as DNA nanotechnology. After several decades of development, different DNA structures had been created, with different dimension, different morphology and even with complex curvatures. In addition, after construction of enough amounts DNA structure candidates, DNA structure template, with excellent spatial addressability, had been used to direct the assembly of different nanomaterials, including nanoparticles and proteins, to produce different functional nanomaterials. However there are still many challenges to fabricate functional DNA nanostructures. The first difficulty is that the present finite sized template dimension is still very small, usually smaller than 100nm, which will limit the application for large amount of nanomaterials assembly or large sized nanomaterials assembly. Here we tried to solve this problem through developing a new method, superorigami, to construct finite sized DNA structure with much larger dimension, which can be as large as 500nm. The second problem will be explored the ability of DNA structure to assemble inorganic nanomaterials for novel photonic or electronic properties. Here we tried to utilize DNA Origami method to assemble AuNPs with controlled 3D spacial position for possible chiral photonic complex. We also tried to assemble SWNT with discrete length for possible field effect transistor device. In addition, we tried to mimic in vivo compartment with DNA structure to study internalized enzyme behavior. From our results, constructed DNA cage origami can protect encapsulated enzyme from degradation, and internalized enzyme activity can be boosted for up to 10 folds. In summary, DNA structure can serve as an ideal template for construction of functional nanomaterials with lots of possibilities to be explored.
ContributorsZhao, Zhao (Author) / Yan, Hao (Thesis advisor) / Liu, Yan (Thesis advisor) / Chen, Julian (Committee member) / Seo, Dong-Kyun (Committee member) / Arizona State University (Publisher)
Created2013
Description
Deoxyribonucleic acid (DNA), a biopolymer well known for its role in preserving genetic information in biology, is now drawing great deal of interest from material scientists. Ease of synthesis, predictable molecular recognition via Watson-Crick base pairing, vast numbers of available chemical modifications, and intrinsic nanoscale size makes DNA a suitable material for the construction of a plethora of nanostructures that can be used as scaffold to organize functional molecules with nanometer precision. This dissertation focuses on DNA-directed organization of metallic nanoparticles into well-defined, discrete structures and using them to study photonic interaction between fluorophore and metal particle. Presented here are a series of studies toward this goal. First, a novel and robust strategy of DNA functionalized silver nanoparticles (AgNPs) was developed and DNA functionalized AgNPs were employed for the organization of discrete well-defined dimeric and trimeric structures using a DNA triangular origami scaffold. Assembly of 1:1 silver nanoparticle and gold nanoparticle heterodimer has also been demonstrated using the same approach. Next, the triangular origami structures were used to co-assemble gold nanoparticles (AuNPs) and fluorophores to study the distance dependent and nanogap dependencies of the photonic interactions between them. These interactions were found to be consistent with the full electrodynamic simulations. Further, a gold nanorod (AuNR), an anisotropic nanoparticle was assembled into well-defined dimeric structures with predefined inter-rod angles. These dimeric structures exhibited unique optical properties compared to single AuNR that was consistent with the theoretical calculations. Fabrication of otherwise difficult to achieve 1:1 AuNP- AuNR hetero dimer, where the AuNP can be selectively placed at the end-on or side-on positions of anisotropic AuNR has also been shown. Finally, a click chemistry based approach was developed to organize sugar modified DNA on a particular arm of a DNA origami triangle and used them for site-selective immobilization of small AgNPs.
ContributorsPal, Suchetan (Author) / Liu, Yan (Thesis advisor) / Yan, Hao (Thesis advisor) / Lindsay, Stuart (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2012
Description
Nowadays, wireless communications and networks have been widely used in our daily lives. One of the most important topics related to networking research is using optimization tools to improve the utilization of network resources. In this dissertation, we concentrate on optimization for resource-constrained wireless networks, and study two fundamental resource-allocation problems: 1) distributed routing optimization and 2) anypath routing optimization. The study on the distributed routing optimization problem is composed of two main thrusts, targeted at understanding distributed routing and resource optimization for multihop wireless networks. The first thrust is dedicated to understanding the impact of full-duplex transmission on wireless network resource optimization. We propose two provably good distributed algorithms to optimize the resources in a full-duplex wireless network. We prove their optimality and also provide network status analysis using dual space information. The second thrust is dedicated to understanding the influence of network entity load constraints on network resource allocation and routing computation. We propose a provably good distributed algorithm to allocate wireless resources. In addition, we propose a new subgradient optimization framework, which can provide findgrained convergence, optimality, and dual space information at each iteration. This framework can provide a useful theoretical foundation for many networking optimization problems. The study on the anypath routing optimization problem is composed of two main thrusts. The first thrust is dedicated to understanding the computational complexity of multi-constrained anypath routing and designing approximate solutions. We prove that this problem is NP-hard when the number of constraints is larger than one. We present two polynomial time K-approximation algorithms. One is a centralized algorithm while the other one is a distributed algorithm. For the second thrust, we study directional anypath routing and present a cross-layer design of MAC and routing. For the MAC layer, we present a directional anycast MAC. For the routing layer, we propose two polynomial time routing algorithms to compute directional anypaths based on two antenna models, and prove their ptimality based on the packet delivery ratio metric.
ContributorsFang, Xi (Author) / Xue, Guoliang (Thesis advisor) / Yau, Sik-Sang (Committee member) / Ye, Jieping (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
Description
The field of cyber-defenses has played catch-up in the cat-and-mouse game of finding vulnerabilities followed by the invention of patches to defend against them. With the complexity and scale of modern-day software, it is difficult to ensure that all known vulnerabilities are patched; moreover, the attacker, with reconnaissance on their side, will eventually discover and leverage them. To take away the attacker's inherent advantage of reconnaissance, researchers have proposed the notion of proactive defenses such as Moving Target Defense (MTD) in cyber-security. In this thesis, I make three key contributions that help to improve the effectiveness of MTD.
First, I argue that naive movement strategies for MTD systems, designed based on intuition, are detrimental to both security and performance. To answer the question of how to move, I (1) model MTD as a leader-follower game and formally characterize the notion of optimal movement strategies, (2) leverage expert-curated public data and formal representation methods used in cyber-security to obtain parameters of the game, and (3) propose optimization methods to infer strategies at Strong Stackelberg Equilibrium, addressing issues pertaining to scalability and switching costs. Second, when one cannot readily obtain the parameters of the game-theoretic model but can interact with a system, I propose a novel multi-agent reinforcement learning approach that finds the optimal movement strategy. Third, I investigate the novel use of MTD in three domains-- cyber-deception, machine learning, and critical infrastructure networks. I show that the question of what to move poses non-trivial challenges in these domains. To address them, I propose methods for patch-set selection in the deployment of honey-patches, characterize the notion of differential immunity in deep neural networks, and develop optimization problems that guarantee differential immunity for dynamic sensor placement in power-networks.
First, I argue that naive movement strategies for MTD systems, designed based on intuition, are detrimental to both security and performance. To answer the question of how to move, I (1) model MTD as a leader-follower game and formally characterize the notion of optimal movement strategies, (2) leverage expert-curated public data and formal representation methods used in cyber-security to obtain parameters of the game, and (3) propose optimization methods to infer strategies at Strong Stackelberg Equilibrium, addressing issues pertaining to scalability and switching costs. Second, when one cannot readily obtain the parameters of the game-theoretic model but can interact with a system, I propose a novel multi-agent reinforcement learning approach that finds the optimal movement strategy. Third, I investigate the novel use of MTD in three domains-- cyber-deception, machine learning, and critical infrastructure networks. I show that the question of what to move poses non-trivial challenges in these domains. To address them, I propose methods for patch-set selection in the deployment of honey-patches, characterize the notion of differential immunity in deep neural networks, and develop optimization problems that guarantee differential immunity for dynamic sensor placement in power-networks.
ContributorsSengupta, Sailik (Author) / Kambhampati, Subbarao (Thesis advisor) / Bao, Tiffany (Youzhi) (Committee member) / Huang, Dijiang (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2020
Description
Originally conceived as a way to scaffold molecules of interest into three-dimensional (3D) crystalline lattices for X ray crystallography, the field of deoxyribonucleic acid (DNA) nanotechnology has dramatically evolved since its inception. The unique properties of DNA nanostructures have promoted their use not only for X ray crystallography, but for a suite of biomedical applications as well. The work presented in this dissertation focuses on both of these exciting applications in the field: 1) Nucleic acid nanostructures as multifunctional drug and vaccine delivery platforms, and 2) 3D DNA crystals for structure elucidation of scaffolded guest molecules.Chapter 1 illustrates how a wide variety of DNA nanostructures have been developed for the delivery of drugs and vaccine components. However, their applications are limited under physiological conditions due to their lack of stability in low salt environments, susceptibility to enzymatic degradation, and tendency for endosomal entrapment. To address these issues, Chapter 2 describes a PEGylated peptide coating molecule was designed to electrostatically adhere to and protect DNA origami nanostructures and to facilitate their cytosolic delivery by peptide-mediated endosomal escape. The development of this molecule will aid in the use of nucleic acid nanostructures for biomedical purposes, such as the delivery of messenger ribonucleic acid (mRNA) vaccine constructs. To this end, Chapter 3 discusses the fabrication of a structured mRNA nanoparticle for more cost-efficient mRNA vaccine manufacture and proposes a multi-epitope mRNA nanostructure vaccine design for targeting human papillomavirus (HPV) type 16-induced head and neck cancers.
DNA nanotechnology was originally envisioned to serve as three-dimensional scaffolds capable of positioning proteins in a rigid array for their structure elucidation by X ray crystallography. Accordingly, Chapter 4 explores design parameters, such as sequence and Holliday junction isomeric forms, for efficient crystallization of 3D DNA lattices. Furthermore, previously published DNA crystal motifs are used to site-specifically position and structurally evaluate minor groove binding molecules with defined occupancies. The results of this study provide significant advancement towards the ultimate goal of the field.
ContributorsHenry, Skylar J.W. (Author) / Stephanopoulos, Nicholas (Thesis advisor) / Anderson, Karen (Thesis advisor) / Blattman, Joseph (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2023