Matching Items (9)
Filtering by
- Genre: Doctoral Dissertation
Description
Nitrate is the most prevalent water pollutant limiting the use of groundwater as a potable water source. The overarching goal of this dissertation was to leverage advances in nanotechnology to improve nitrate photocatalysis and transition treatment to the full-scale. The research objectives were to (1) examine commercial and synthesized photocatalysts, (2) determine the effect of water quality parameters (e.g., pH), (3) conduct responsible engineering by ensuring detection methods were in place for novel materials, and (4) develop a conceptual framework for designing nitrate-specific photocatalysts. The key issues for implementing photocatalysis for nitrate drinking water treatment were efficient nitrate removal at neutral pH and by-product selectivity toward nitrogen gases, rather than by-products that pose a human health concern (e.g., nitrite). Photocatalytic nitrate reduction was found to follow a series of proton-coupled electron transfers. The nitrate reduction rate was limited by the electron-hole recombination rate, and the addition of an electron donor (e.g., formate) was necessary to reduce the recombination rate and achieve efficient nitrate removal. Nano-sized photocatalysts with high surface areas mitigated the negative effects of competing aqueous anions. The key water quality parameter impacting by-product selectivity was pH. For pH < 4, the by-product selectivity was mostly N-gas with some NH4+, but this shifted to NO2- above pH = 4, which suggests the need for proton localization to move beyond NO2-. Co-catalysts that form a Schottky barrier, allowing for localization of electrons, were best for nitrate reduction. Silver was optimal in heterogeneous systems because of its ability to improve nitrate reduction activity and N-gas by-product selectivity, and graphene was optimal in two-electrode systems because of its ability to shuttle electrons to the working electrode. "Environmentally responsible use of nanomaterials" is to ensure that detection methods are in place for the nanomaterials tested. While methods exist for the metals and metal oxides examined, there are currently none for carbon nanotubes (CNTs) and graphene. Acknowledging that risk assessment encompasses dose-response and exposure, new analytical methods were developed for extracting and detecting CNTs and graphene in complex organic environmental (e.g., urban air) and biological matrices (e.g. rat lungs).
ContributorsDoudrick, Kyle (Author) / Westerhoff, Paul (Thesis advisor) / Halden, Rolf (Committee member) / Hristovski, Kiril (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis describes several experiments based on carbon nanotube nanofludic devices and field-effect transistors. The first experiment detected ion and molecule translocation through one single-walled carbon nanotube (SWCNT) that spans a barrier between two fluid reservoirs. The electrical ionic current is measured. Translocation of small single stranded DNA oligomers is marked by large transient increases in current through the tube and confirmed by a PCR (polymerase chain reaction) analysis. Carbon nanotubes simplify the construction of nanopores, permit new types of electrical measurement, and open new avenues for control of DNA translocation. The second experiment constructed devices in which the interior of a single-walled carbon nanotube field-effect transistor (CNT-FET) acts as a nanofluidic channel that connects two fluid reservoirs, permitting measurement of the electronic properties of the SWCNT as it is wetted by an analyte. Wetting of the inside of the SWCNT by water turns the transistor on, while wetting of the outside has little effect. This finding may provide a new method to investigate water behavior at nanoscale. This also opens a new avenue for building sensors in which the SWCNT functions as an electronic detector. This thesis also presents some experiments that related to nanofabrication, such as construction of FET with tin sulfide (SnS) quantum ribbon. This work demonstrates the application of solution processed IV-VI semiconductor nanostructures in nanoscale devices.
ContributorsCao, Zhai (Author) / Lindsay, Stuart (Thesis advisor) / Vaiana, Sara (Committee member) / Ros, Robert (Committee member) / Marzke, Robert (Committee member) / Shumway, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
Nanofluidic devices in which one single-walled carbon nanotube (SWCNT) spans a barrier between two fluid reservoirs were constructed, enabling direct electrical measurement of the transport of ions and molecules. Ion current through these devices is about 2 orders of magnitude larger than that predicted from the bulk resistivity of the electrolyte. Electroosmosis drives excess current, carried by cations, and is found to be the origin of giant ionic current through SWCNT as shown by building an ionic field-effect transistor with a gate electrode embedded in the fluid barrier. Wetting of inside of the semi-conducting SWCNT by water showed the change of its electronic property, turning the electronic SWCNT field-effect transistor to "on" state. These findings provide a new method to investigate and control the ion and molecule behavior at nanoscale.
ContributorsPang, Pei (Author) / Lindsay, Stuart (Thesis advisor) / Ros, Robert (Committee member) / Shumway, John (Committee member) / Tao, Nongjian (Committee member) / Menéndez, Jose (Committee member) / Arizona State University (Publisher)
Created2011
Description
With the maturity of advanced composites as feasible structural materials for various applications there is a critical need to solve the challenge of designing these material systems for optimal performance. However, determining superior design methods requires a deep understanding of the material-structure properties at various length scales. Due to the length-scale dependent behavior of advanced composites, multiscale modeling techniques may be used to describe the dominant mechanisms of damage and failure in these material systems. With polymer matrix fiber composites and nanocomposites it becomes essential to include even the atomic length scale, where the resin-hardener-nanofiller molecules interact, in the multiscale modeling framework. Additionally, sources of variability are also critical to be included in these models due to the important role of uncertainty in advance composite behavior. Such a methodology should be able to describe length scale dependent mechanisms in a computationally efficient manner for the analysis of practical composite structures.
In the research presented in this dissertation, a comprehensive nano to macro multiscale framework is developed for the mechanical and multifunctional analysis of advanced composite materials and structures. An atomistically informed statistical multiscale model is developed for linear problems, to estimate and scale elastic properties of carbon fiber reinforced polymer composites (CFRPs) and carbon nanotube (CNT) enhanced CFRPs using information from molecular dynamics simulation of the resin-hardener-nanofiller nanoscale system. For modeling inelastic processes, an atomistically informed coupled damage-plasticity model is developed using the framework of continuum damage mechanics, where fundamental nanoscale covalent bond disassociation information is scaled up as a continuum scale damage identifying parameter. This damage model is coupled with a nanocomposite microstructure generation algorithm to study the sub-microscale damage mechanisms in CNT/CFRP microstructures. It is further integrated in a generalized method of cells (GMC) micromechanics model to create a low-fidelity computationally efficient nonlinear multiscale method with imperfect interfaces between the fiber and matrix, where the interface behavior is adopted from nanoscale MD simulations. This algorithm is used to understand damage mechanisms in adhesively bonded composite joints as a case study for the comprehensive nano to macroscale structural analysis of practical composites structures. At each length scale sources of variability are identified, characterized, and included in the multiscale modeling framework.
In the research presented in this dissertation, a comprehensive nano to macro multiscale framework is developed for the mechanical and multifunctional analysis of advanced composite materials and structures. An atomistically informed statistical multiscale model is developed for linear problems, to estimate and scale elastic properties of carbon fiber reinforced polymer composites (CFRPs) and carbon nanotube (CNT) enhanced CFRPs using information from molecular dynamics simulation of the resin-hardener-nanofiller nanoscale system. For modeling inelastic processes, an atomistically informed coupled damage-plasticity model is developed using the framework of continuum damage mechanics, where fundamental nanoscale covalent bond disassociation information is scaled up as a continuum scale damage identifying parameter. This damage model is coupled with a nanocomposite microstructure generation algorithm to study the sub-microscale damage mechanisms in CNT/CFRP microstructures. It is further integrated in a generalized method of cells (GMC) micromechanics model to create a low-fidelity computationally efficient nonlinear multiscale method with imperfect interfaces between the fiber and matrix, where the interface behavior is adopted from nanoscale MD simulations. This algorithm is used to understand damage mechanisms in adhesively bonded composite joints as a case study for the comprehensive nano to macroscale structural analysis of practical composites structures. At each length scale sources of variability are identified, characterized, and included in the multiscale modeling framework.
ContributorsRai, Ashwin (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Rajadas, John (Committee member) / Fard, Masoud Yekani (Committee member) / Arizona State University (Publisher)
Created2018
Description
Flame retardants (FRs) are applied to variety of consumer products such as textiles and polymers for fire prevention and fire safety. Substantial research is ongoing to replace traditional FRs with alternative materials that are less toxic, present higher flame retardancy and result in lower overall exposure as there are potential health concerns in case of exposure to popular FRs. Carbonaceous nanomaterials (CNMs) such as carbon nanotubes (CNTs) and graphene oxide (GO) have been studied and applied to polymer composites and electronics extensively due to their remarkable properties. Hence CNMs are considered as potential alternative materials that present high flame retardancy. In this research, different kinds of CNMs coatings on polyester fabric are produced and evaluated for their use as flame retardants. To monitor the mass loading of CNMs coated on the fabric, a two-step analytical method for quantifying CNMs embedded in polymer composites was developed. This method consisted of polymer dissolution process using organic solvents followed by subsequent programmed thermal analysis (PTA). This quantification technique was applicable to CNTs with and without high metal impurities in a broad range of polymers. Various types of CNMs were coated on polyester fabric and the efficacy of coatings as flame retardant was evaluated. The oxygen content of CNMs emerged as a critical parameter impacting flame retardancy with higher oxygen content resulting in less FR efficacy. The most performant nanomaterials, multi-walled carbon nanotubes (MWCNTs) and amine functionalized multi-walled carbon nantoubes (NH2-MWCNT) showed similar FR properties to current flame retardants with low mass loading (0.18 g/m2) and hence are promising alternatives that warrant further investigation. Chemical/physical modification of MWCNTs was conducted to produce well-dispersed MWCNT solutions without involving oxygen for uniform FR coating. The MWCNTs coating was studied to evaluate the durability of the coating and the impact on the efficacy during use phase by conducting mechanical abrasion and washing test. Approximately 50% and 40% of MWCNTs were released from 1 set of mechanical abrasion and washing test respectively. The losses during simulated usage impacted the flame retardancy negatively.
ContributorsNosaka, Takayuki (Author) / Herckes, Pierre (Thesis advisor) / Westerhoff, Paul (Committee member) / Wang, Qing Hua (Committee member) / Arizona State University (Publisher)
Created2018
Description
Progressive miniaturization in electronics demands advanced materials with excellent energy conversion and transport properties. Opportunities exist in novel material morphologies such as hierarchical structures, multi-functional composites and nanoscale architectures which may offer mechanical, thermal and electronic properties tailored to a wide range of applications (e.g., aerospace, robotics, biomedical etc.). However, the manufacturing capabilities have always posed a grand challenge in realizing the advanced material morphologies. Furthermore, the multi-scale modeling of complex material architectures has been extremely challenging owing to the limitations in computation methodologies and lack of understanding in nano-/micro-meter scale physics. To address these challenges, this work considers the morphology effect on carbon nanotube (CNT)-based composites, CNT fibers and thermoelectric (TE) materials. First, this work reports additively manufacturable TE morphologies and analyzes the thermo-electric transport behavior. This research introduces innovative honeycomb TE architectures that showed ~26% efficiency increase and ~25% density reduction compared to conventional rectangular TE architectures. Moreover, this work presents 3D printable compositionally segmented TE architecture which provides record-high efficiencies (up to 8.7%) over wide temperature ranges if the composition and aspect ratio of multiple TE materials are optimized within a single TE device. Next, this research proposes computationally efficient two-dimensional (2D) finite element model (FEM) to study the electrical and thermal properties in CNT based composites by simultaneously considering the stochastic CNT distributions, CNT fractions (upto 80%) and interfacial resistances. The FEM allows to estimate the theoretical maximum possible conductivities with corresponding interfacial resistances if the CNT morphologies are carefully controlled, along with appreciable insight into the energy transport physics. Then, this work proposes a data-driven surrogate model based on convolutional neural networks to rapidly approximate the composite conductivities in a second with accuracy > 98%, compared to FEM taking >100 minutes per simulation. Finally, this research presents a pseudo 2D FEM to approximate the electrical and thermal properties in CNT fibers at various CNT aspect ratios (up to 10,000) by simultaneously considering CNT-CNT interfacial effects along with the stochastic distribution of inter-bundle voids.
ContributorsEjaz, Faizan (Author) / Kwon, Beomjin (Thesis advisor) / Zhuang, Houlong (Committee member) / Song, Kenan (Committee member) / Wang, Robert (Committee member) / Kang, Wonmo (Committee member) / Arizona State University (Publisher)
Created2023
Description
Microfluidics has enabled many biological and biochemical applications such as high-throughput drug testing or point-of-care diagnostics. Dielectrophoresis (DEP) has recently achieved prominence as a powerful microfluidic technique for nanoparticle separation. Novel electric field-assisted insulator-based dielectrophoresis (iDEP) microfluidic devices have been employed to fractionate rod-shaped nanoparticles like Single-walled carbon nanotubes (SWNTs) and manipulate biomolecules like Deoxyribonucleic acid (DNA) and proteins. This dissertation involves the development of traditional as well as 3D-printed iDEP devices for the manipulation of nm-to-µm scale analytes. First, novel iDEP microfluidic constriction-based sorting devices were developed to introduce inhomogeneous electric field gradients to fractionate SWNTs by length. SWNTs possess length-specific optical and electrical properties, expanding their potential applications for future nanoscale devices. Standard synthesis procedures yield SWNTs in large-length polydispersity and chirality. Thus, an iDEP-based fractionation tool for desired lengths of SWNTs may be beneficial. This dissertation presents the first study of DEP characterization and fractionation of SWNTs using an iDEP microfluidic device. Using this iDEP constriction sorter device, two different length distributions of SWNTs were sorted with a sorting efficiency of >90%. This study provides the fundamentals of fractionating SWNTs by length, which can help separate and purify SWNTs for future nanoscale-based applications. Manipulation of nm-scale analytes requires achieving high electric field gradients in an iDEP microfluidic device, posing one of the significant challenges for DEP applications. Introducing nm-sized constrictions in an iDEP device can help generate a higher electric field gradient. However, this requires cumbersome and expensive fabrication methods. In recent years, 3D printing has drawn tremendous attention in microfluidics, alleviating complications associated with complex fabrication methods. A high-resolution 3D-printed iDEP device was developed and fabricated for iDEP-based manipulation of analytes. A completely 3D-printed device with 2 µm post-gaps was realized, and fluorescent polystyrene (PS) beads, λ-DNA, and phycocyanin protein trapping were demonstrated. Furthermore, a nm-resolution 3D-printed iDEP device was successfully printed. In the future, these high-resolution 3D-printed devices may lead to exploring DEP characteristics of nanoscale analytes like single protein molecules and viruses. The electric field-assisted unique fractionation phenomena in microfluidic platforms will become a critical solution for nanoparticle separation and manipulating biomolecules.
ContributorsRabbani, Mohammad Towshif (Author) / Ros, Alexandra (Thesis advisor) / Stephanopoulos, Nicholas (Committee member) / Buttry, Daniel (Committee member) / Arizona State University (Publisher)
Created2022
Description
Damage and failure of advanced composite materials and structures are often manifestations of nonlinear deformation that involve multiple mechanisms and their interactions at the constituent length scale. The presence and interactions of inelastic microscale constituents strongly influence the macroscopic damage anisotropy and useful residual life. The mechano-chemical interactions between constituents at the atomistic length scale play a more critical role with nanoengineered composites. Therefore, it is desirable to link composite behavior to specific microscopic constituent properties explicitly and lower length scale features using high-fidelity multiscale modeling techniques.In the research presented in this dissertation, an atomistically-informed multiscale modeling framework is developed to investigate damage evolution and failure in composites with radially-grown carbon nanotube (CNT) architecture. A continuum damage mechanics (CDM) model for the radially-grown CNT interphase region is developed with evolution equations derived using atomistic simulations. The developed model is integrated within a high-fidelity generalized method of cells (HFGMC) micromechanics theory and is used to parametrically investigate the influence of various input micro and nanoscale parameters on the mechanical properties, such as elastic stiffness, strength, and toughness. In addition, the inter-fiber stresses and the onset of damage in the presence of the interphase region are investigated to better understand the energy dissipation mechanisms that attribute to the enhancement in the macroscopic out-of-plane strength and toughness. Note that the HFGMC theory relies heavily on the description of microscale features and requires many internal variables, leading to high computational costs. Therefore, a novel reduced-order model (ROM) is also developed to surrogate full-field nonlinear HFGMC simulations and decrease the computational time and memory requirements of concurrent multiscale simulations significantly.
The accurate prediction of composite sandwich materials' thermal stability and durability remains a challenge due to the variability of thermal-related material coefficients at different temperatures and the extensive use of bonded fittings. Consequently, the dissertation also investigates the thermomechanical performance of a complex composite sandwich space structure subject to thermal cycling. Computational finite element (FE) simulations are used to investigate the intrinsic failure mechanisms and damage precursors in honeycomb core composite sandwich structures with adhesively bonded fittings.
ContributorsVenkatesan, Karthik Rajan (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Yekani Fard, Masoud (Committee member) / Stoumbos, Tom (Committee member) / Arizona State University (Publisher)
Created2021
Description
Driven by the curiosity for the secret of life, the effort on sequencing of DNAs and other large biopolymers has never been respited. Advanced from recent sequencing techniques, nanotube and nanopore based sequencing has been attracting much attention. This thesis focuses on the study of first and crucial compartment of the third generation sequencing technique, the capture and translocation of biopolymers, and discuss the advantages and obstacles of two different nanofluidic pathways, nanotubes and nanopores for single molecule capturing and translocation. Carbon nanotubes with its constrained structure, the frictionless inner wall and strong electroosmotic flow, are promising materials for linearly threading DNA and other biopolymers for sequencing. Solid state nanopore on the other hand, is a robust chemical, thermal and mechanical stable nanofluidic device, which has a high capturing rate and, to some extent, good controllable threading ability for DNA and other biomolecules. These two different but similar nanofluidic pathways both provide a good preparation of analyte molecules for the sequencing purpose. In addition, more and more research interests have move onto peptide chains and protein sensing. For proteome is better and more direct indicators for human health, peptide chains and protein sensing have a much wider range of applications on bio-medicine, disease early diagnoses, and etc. A universal peptide chain nanopore sensing technique with universal chemical modification of peptides is discussed in this thesis as well, which unifies the nanopore capturing process for vast varieties of peptides. Obstacles of these nanofluidic pathways are also discussed. In the end of this thesis, a proposal of integration of solid state nanopore and fixed-gap recognition tunneling sequencing technique for a more accurate DNA and peptide readout is discussed, together with some early study work, which gives a new direction for nanopore based sequencing.
ContributorsSong, Weisi (Author) / Lindsay, Stuart (Thesis advisor) / Ros, Robert (Committee member) / Qing, Quan (Committee member) / Zhang, Peiming (Committee member) / Arizona State University (Publisher)
Created2015