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Rational Design of Self-Assembled Na...

Indiana University., Intelligent Systems Engineering.

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Rational Design of Self-Assembled Nanoscale Materials and Devices /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Rational Design of Self-Assembled Nanoscale Materials and Devices // Camila Faccini de Lima.
Author:	Faccini de Lima, Camila,
Description:	1 electronic resource (265 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-07, Section: B.
Contained By:	Dissertations Abstracts International86-07B.
Subject:	Engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31766239
ISBN:	9798302150639

Rational Design of Self-Assembled Nanoscale Materials and Devices /
Faccini de Lima, Camila,

Rational Design of Self-Assembled Nanoscale Materials and Devices /Camila Faccini de Lima. - 1 electronic resource (265 pages)

Source: Dissertations Abstracts International, Volume: 86-07, Section: B.

From the crystal structure of a ribosome to viral capsids, self-assembly is a key principle for the creation of complex structures in nature. The self-assembly of nanomaterials has become an area of great interest for scientists and engineers, offering a bottom-up approach to the development of functional materials with optical, electromagnetic, and biological properties. Examples include nanocontainers for drug delivery, 3-dimensional electrical networks, and photonic crystals.Experiments using advanced techniques such as X-ray scattering and fluorescence and electron microscopy explore new self-assembly phenomena and expand our understanding of material behavior and properties. However, experimental work is often constrained by cost, material, time, and specialized infrastructure. Computational methods such as molecular dynamics simulations offer advantages in designing new experiments and offer insights into aspects of systems not readily available for experimental assessment. Thus, it is important to consider how to test and validate models and simulations and how experimental and computational research can work in tandem to further scientific knowledge.This dissertation focuses on two examples of experimentally-informed modeling and simulation of nanomaterial self-assembly. First, the self-assembly of photonic devices inside multi-material fiber cores is addressed. Through experimental and computational studies, we develop and validate the first analytical model capable of quantitatively predicting breakup parameters for fibers subjected to axial viscosity gradient capillary breakup. Next, a coarse-grained model is developed, informed by small-angle X-ray scattering and dynamic light scattering experiments, to capture the self-assembly of charged nanoparticles mixed with linker macromolecules over a broad range of nanoparticle charges and salt concentrations. The model is applied to elucidate the mechanisms that drive virus-like particles to spontaneously self-assemble into ordered multilayered nanostructures. Our results contribute to both the advancement of fundamental understanding of nanomaterial self-assembly and the practical capabilities to engineer nanodevices with applications in photonics, catalysis, and bio-inspired materials design.

English

ISBN: 9798302150639Subjects--Topical Terms:

586835
Engineering.
Subjects--Index Terms:

Nanomaterial

Rational Design of Self-Assembled Nanoscale Materials and Devices /
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300 $a 1 electronic resource (265 pages)
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500 $a Source: Dissertations Abstracts International, Volume: 86-07, Section: B.
500 $a Advisors: Jadhao, Vikram Committee members: Glazier, James A.; Lewis, Gregory; Setayeshgar, Sima.
502 $b Ph.D. $c Indiana University $d 2024.
520 $a From the crystal structure of a ribosome to viral capsids, self-assembly is a key principle for the creation of complex structures in nature. The self-assembly of nanomaterials has become an area of great interest for scientists and engineers, offering a bottom-up approach to the development of functional materials with optical, electromagnetic, and biological properties. Examples include nanocontainers for drug delivery, 3-dimensional electrical networks, and photonic crystals.Experiments using advanced techniques such as X-ray scattering and fluorescence and electron microscopy explore new self-assembly phenomena and expand our understanding of material behavior and properties. However, experimental work is often constrained by cost, material, time, and specialized infrastructure. Computational methods such as molecular dynamics simulations offer advantages in designing new experiments and offer insights into aspects of systems not readily available for experimental assessment. Thus, it is important to consider how to test and validate models and simulations and how experimental and computational research can work in tandem to further scientific knowledge.This dissertation focuses on two examples of experimentally-informed modeling and simulation of nanomaterial self-assembly. First, the self-assembly of photonic devices inside multi-material fiber cores is addressed. Through experimental and computational studies, we develop and validate the first analytical model capable of quantitatively predicting breakup parameters for fibers subjected to axial viscosity gradient capillary breakup. Next, a coarse-grained model is developed, informed by small-angle X-ray scattering and dynamic light scattering experiments, to capture the self-assembly of charged nanoparticles mixed with linker macromolecules over a broad range of nanoparticle charges and salt concentrations. The model is applied to elucidate the mechanisms that drive virus-like particles to spontaneously self-assemble into ordered multilayered nanostructures. Our results contribute to both the advancement of fundamental understanding of nanomaterial self-assembly and the practical capabilities to engineer nanodevices with applications in photonics, catalysis, and bio-inspired materials design.
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650 4 $a Particle physics. $3 3433269
653 $a Nanomaterial
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653 $a Self-assembly
653 $a Photonic devices
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690 $a 0798
710 2 $a Indiana University. $b Intelligent Systems Engineering. $e degree granting institution. $3 3816016
720 1 $a Jadhao, Vikram $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-07B.
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791 $a Ph.D.
792 $a 2024
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