arXiv subjects

Delia J. Milliron

Publications and source records attributed to Delia J. Milliron.

At least 19 recordsLinked to original sources

arXiv2026

Characterizing emergent multiscale dynamics in colloidal nanoparticle gels

Colloidal gels assembled from nanoparticles (NPs) are a versatile class of soft network-based materials capable of rich dynamic, mechanical, and even optical or magnetic responses to stimuli. Understanding how their hierarchically organized processes relate to macroscopic network properties remains a broad and unresolved problem in soft matter physics. The mechanisms of gel formation can depend sensitively on the pathway and the nature of NP interactions, thus far preventing a unified theoretical bridge between nanoscopic interactions and structural evolution and network dynamics. Indirect measurement of dynamics using light-scattering techniques provides an experimental means to quantify underlying particle and network motion. X-ray photon correlation spectroscopy (XPCS) has emerged as a powerful tool for probing nanoscopic motion in nanoparticle gels, but alone cannot resolve the full spatiotemporal spectrum of dynamics that drive gelation, aging, and network mechanical properties. While in situ rheo-XPCS enables simultaneous probing of nanoscale and bulk mechanical responses, complementary light scattering, microscopy, or simulations can extend spatiotemporal characterization and, consequently, understanding of NP gel network physics. Implementing a modular model platform with tunable primary nanoparticle features allows systematic variation of nanoscopic characteristics that drive emergent gel responses and inform the development of theoretical models for a wide range of soft, dynamic, nanostructured materials. The rapid expansion of XPCS capabilities at fourth-generation light sources, combined with complementary tools and robust model systems, positions the field to move beyond descriptive fundamental studies toward the design of nanoparticle gels with adaptive and programmable behaviors.

cond-mat.soft↗

arXiv2025

SAM$^{*}$: Task-Adaptive SAM with Physics-Guided Rewards

Image segmentation is a critical task in microscopy, essential for accurately analyzing and interpreting complex visual data. This task can be performed using custom models trained on domain-specific datasets, transfer learning from pre-trained models, or foundational models that offer broad applicability. However, foundational models often present a considerable number of non-transparent tuning parameters that require extensive manual optimization, limiting their usability for real-time streaming data analysis. Here, we introduce a reward function-based optimization to fine-tune foundational models and illustrate this approach for SAM (Segment Anything Model) framework by Meta. The reward functions can be constructed to represent the physics of the imaged system, including particle size distributions, geometries, and other criteria. By integrating a reward-driven optimization framework, we enhance SAM's adaptability and performance, leading to an optimized variant, SAM$^{*}$, that better aligns with the requirements of diverse segmentation tasks and particularly allows for real-time streaming data segmentation. We demonstrate the effectiveness of this approach in microscopy imaging, where precise segmentation is crucial for analyzing cellular structures, material interfaces, and nanoscale features.

cs.CV↗

arXiv2025

Plasmon Polaritons in Disordered Nanoparticle Assemblies

Multilayer assemblies of metal nanoparticles can act as photonic structures, where collective plasmon resonances hybridize with cavity modes to create plasmon-polariton states. For sufficiently strong coupling, plasmon polaritons qualitatively alter the optical properties of light-matter systems, with applications ranging from sensing to solar energy. However, results from experimental studies have raised questions about the role of nanoparticle structural disorder in plasmon-polariton formation and light-matter coupling in plasmonic assemblies. Understanding how disorder affects optical properties has practical implications since methods for assembling low-defect nanoparticle superlattices are slow and scale poorly. Modeling realistic disorder requires large system sizes, which is challenging using conventional electromagnetic simulations. We employ Brownian dynamics simulations to construct large-scale nanoparticle multilayers with controlled structural order. We investigate their optical response using a superposition T-matrix method with 2-D periodic boundary conditions. We find that while structural disorder broadens the polaritonic stop band and the near-field hot-spot distribution, the polariton dispersion and coupling strength remain unaltered. To understand effects of nanoparticle composition, we consider assemblies with model particles mimicking gold or tin-doped indium oxide (ITO) nanocrystals. Losses due to higher damping in ITO nanocrystals prevent their assemblies from achieving the deep strong coupling of gold nanoparticle multilayers, although the former still exhibit ultrastrong coupling. We demonstrate that while computationally efficient mutual polarization method calculations employing the quasistatic approximation modestly overestimate the strength of the collective plasmon, they reproduce the polariton dispersion relations determined by electrodynamic simulations.

physics.optics↗

arXiv2024

Plasmonic Metal Oxide Nanocrystals as Building Blocks for Infrared Metasurfaces

Based on experimental and simulation methods we helped develop, we are advancing mechanistic understanding of how self-assembled NC metamaterials can produce distinctive near- and far-field optical properties not readily achievable in lithographically patterned structures. First, the impacts of the inevitable defects and disorder associated with self-assembly can be rationalized and, in some cases, recognized as advantageous. Second, self-assembly enables intimate nanoscale intermixing of different NC and molecular components. By incorporating probe molecules within the gaps between NCs where the electric field enhancement is strongest, we show enhanced detection of molecular vibrations that can be optimized by tuning the size and resonance frequency of the NCs. We show how metasurfaces incorporating mixtures of NCs with different doping concentrations can achieve epsilon-near-zero dielectric response over a broad frequency range. Finally, considering the NC metasurface itself as a building block, we show how photonic structures incorporating these assemblies can harness and amplify their distinctive properties. Through modeling the NC monolayer as a slab with an effective permittivity response, we designed a frequency-tunable IR perfect absorber by layering the NCs on a simple open cavity structure. Since the perfect absorption architecture further enhances the IR electric field localization strength, we expect that this integration strategy can enhance molecular vibration coupling or non-linear optical response. The versatility of the NC assembly and integration approach suggests opportunities for various metal oxide NC superstructures, including mixing and stacking of NCs beyond a single monolayer, representing a vast parameter space for design of linear and nonlinear IR optical components.

physics.optics↗

arXiv2023

Morphological Control of Bundled Actin Networks Subject to Fixed-Mass Depletion

Depletion interactions are thought to significantly contribute to the organization of intracellular structures in the crowded cytosol. The strength of depletion interactions depends on physical parameters like the depletant number density and the depletant size ratio. Cells are known to dynamically regulate these two parameters by varying the copy number of proteins of a wide distribution of sizes. However, mammalian cells are also known to keep the total protein mass density remarkably constant, to within 0.5% throughout the cell cycle. We thus ask how the strength of depletion interactions varies when the total depletant mass is held fixed, a.k.a. fixed-mass depletion. We answer this question via scaling arguments, as well as by studying depletion effects on networks of reconstituted semiflexible actin $\textit{in silico}$ and $\textit{in vitro}$. We examine the maximum strength of the depletion interaction potential $U^*$ as a function of $q$, the size ratio between the depletant and the matter being depleted. We uncover a scaling relation $U^* \sim q^{-ζ}$ for two cases: fixed volume fraction $ϕ$ and fixed mass density $ρ$. For fixed volume fraction, we report $ζ< 0$. For the fixed mass density case, we report $ζ> 0$, which suggests the depletion interaction strength increases as the depletant size ratio is increased. To test this prediction, we prepared our filament networks at fixed mass concentrations with varying sizes of the depletant molecule poly(ethylene glycol) (PEG). We characterize the depletion interaction strength in our simulations via the mesh size. In experiments, we observe two distinct actin network morphologies, which we call weakly bundled and strongly bundled. We identify a mass concentration where different PEG depletant sizes leads to weakly bundled or strongly bundled morphologies...[more in main text].

cond-mat.soft↗

arXiv2022

Depletion-Driven Morphological Control of Bundled Actin Networks

The actin cytoskeleton is a semiflexible biopolymer network whose morphology is controlled by a wide range of biochemical and physical factors. Actin is known to undergo a phase transition from a single-filament state to a bundled state by the addition of polyethylene glycol (PEG) molecules in sufficient concentration. While the depletion interaction experienced by these biopolymers is well-known, the effect of changing the molecular weight of the depletant is less well understood. Here, we experimentally identify a phase transition in solutions of actin from networks of filaments to networks of bundles by varying the molecular weight of PEG polymers, while holding the concentration of these PEG polymers constant. We examine the states straddling the phase transition in terms of micro and macroscale properties. We find that the mesh size, bundle diameter, persistence length, and intra-bundle spacing between filaments across the line of criticality do not show significant differences, while the relaxation time, storage modulus, and degree of bundling change between the two states do show significant differences. Our results demonstrate the ability to tune actin network morphology and mechanics by controlling depletant size, a property which could be exploited to develop actin-based materials with switchable rigidity.

cond-mat.soft↗

arXiv2022

Dynamics of equilibrium linked colloidal gels

Colloids that attractively bond to only a few neighbors (e.g., patchy particles) can form equilibrium gels with distinctive dynamic properties that are stable in time. Here, we use a coarse-grained model to explore the dynamics of linked networks of patchy colloids whose average valence is macroscopically, rather than microscopically, constrained. Simulation results for the model show dynamic hallmarks of equilibrium gel formation and establish that the colloid-colloid bond persistence time controls the characteristic slow relaxation of the self-intermediate scattering function. The model features re-entrant network formation without phase separation as a function of linker concentration, centered at the stoichiometric ratio of linker ends to nanoparticle surface bonding sites. Departures from stoichiometry result in linker-starved or site-starved networks with reduced connectivity and shorter characteristic relaxation times with lower activation energies. Underlying the re-entrant trends, dynamic properties vary monotonically with the number of effective network bonds per colloid, a quantity that can be predicted using Wertheim's thermodynamic perturbation theory. These behaviors suggest macroscopic in situ strategies for tuning the dynamical response of colloidal networks.

cond-mat.soft↗

arXiv2022

Contact conductance governs metallicity in conducting metal oxide nanocrystal films

In bulk semiconductor materials, the insulator-metal transition (IMT) is governed by the concentration of conduction electrons. Meanwhile, even when fabricated from metallic building blocks, nanocrystal films are often insulating with inter-nanocrystal contacts acting as electron transport bottlenecks. Using a library of transparent conducting tin-doped indium oxide nanocrystal films with varied electron concentration, size, and contact area, we test candidate criteria for the IMT and establish a phase diagram for electron transport behavior. From variable temperature conductivity measurements, we learn that both the IMT and a subsequent crossover to conventional metallic behavior near room temperature are governed by the conductance of the inter-nanocrystal contacts. To cross the IMT, inter-nanocrystal coupling must be sufficient to overcome the charging energy of a nanocrystal, while conventional metallic behavior requires contact conductance to reach the conductance of a nanocrystal. This understanding can enable the design and fabrication of metallic conducting materials from nanocrystal building blocks.

cond-mat.mtrl-sci↗

arXiv2021

Assembling Inorganic Nanocrystal Gels

Inorganic nanocrystal gels retain distinct properties of individual nanocrystals while offering tunable, network structure-dependent characteristics. We review different mechanisms for assembling gels from colloidal nanocrystals including (1) controlled destabilization, (2) direct bridging, (3) depletion, as well as linking mediated by (4) coordination bonding or (5) dynamic covalent bonding, and we highlight how each impacts gel properties. These approaches use nanocrystal surface chemistry or the addition of small molecules to mediate inter-nanocrystal attractions. Each method offers advantages in terms of gel stability, reversibility, or tunability and presents new opportunities for design of reconfigurable materials and fueled assemblies.

cond-mat.mtrl-sci↗

arXiv2021

Sculpting the plasmonic responses of nanoparticles by directed electron beam irradiation

Spatial confinement of matter in functional nanostructures has propelled these systems to the forefront of nanoscience, both as a playground for exotic physics and quantum phenomena and in multiple applications including plasmonics, optoelectronics, and sensing. In parallel, the emergence of monochromated electron energy loss spectroscopy (EELS) has enabled exploration of local nanoplasmonic functionalities within single nanoparticles and the collective response of nanoparticle assemblies, providing deep insight into the associated mechanisms. However, modern synthesis processes for plasmonic nanostructures are often limited in the types of accessible geometry and materials, and even then, limited to spatial precisions on the order of tens of nm, precluding the direct exploration of critical aspects of the structure-property relationships. Here, we use the atomic-sized probe of the scanning transmission electron microscope (STEM) to perform precise sculpting and design of nanoparticle configurations. Furthermore, using low-loss (EELS), we provide dynamic analyses of evolution of the plasmonic response during the sculpting process. We show that within self-assembled systems of nanoparticles, individual nanoparticles can be selectively removed, reshaped, or arbitrarily patterned with nanometer-level resolution, effectively modifying the plasmonic response in both space and energy domains. This process significantly increases the scope for design possibilities and presents opportunities for arbitrary structure development, which are ultimately key for nanophotonic design. Nanosculpting introduces yet another capability to the electron microscope.

cond-mat.mtrl-sci↗

arXiv2020

Wertheim's thermodynamic perturbation theory with double-bond association and its application to colloid-linker mixtures

We extend Wertheim's thermodynamic perturbation theory to derive the association free energy of a multicomponent mixture for which double bonds can form between any two pairs of the molecules' arbitrary number of bonding sites. This generalization reduces in limiting cases to prior theories that restrict double bonding to at most one pair of sites per molecule. We apply the new theory to an associating mixture of colloidal particles ("colloids") and flexible chain molecules ("linkers"). The linkers have two functional end groups, each of which may bond to one of several sites on the colloids. Due to their flexibility, a significant fraction of linkers can "loop" with both ends bonding to sites on the same colloid instead of bridging sites on different colloids. We use the theory to show that the fraction of linkers in loops depends sensitively on the linker end-to-end distance relative to the colloid bonding-site distance, which suggests strategies for mitigating the loop formation that may otherwise hinder linker-mediated colloidal assembly.

cond-mat.soft↗

arXiv2020

Effects of linker flexibility on phase behavior and structure of linked colloidal gels

Colloidal nanocrystal gels can be assembled using a difunctional "linker" molecule to mediate bonding between nanocrystals. The conditions for gelation and the structure of the gel are controlled macroscopically by the linker concentration and microscopically by the linker's molecular characteristics. Here, we demonstrate using a toy model for a colloid-linker mixture that linker flexibility plays a key role in determining both phase behavior and structure of the mixture. We fix the linker length and systematically vary its bending stiffness to span the flexible, semiflexible, and rigid regimes. At fixed linker concentration, flexible-linker and rigid-linker mixtures phase separate at low colloid volume fractions in agreement with predictions of first-order thermodynamic perturbation theory, but the semiflexible-linker mixtures do not. We correlate and attribute this qualitatively different behavior to undesirable "loop" linking motifs that are predicted to be more prevalent for linkers with end-to-end distances commensurate with the locations of chemical bonding sites on the colloids. Linker flexibility also influences the spacing between linked colloids, suggesting strategies to design gels with desired phase behavior, structure, and by extension, structure-dependent properties.

cond-mat.soft↗

arXiv2020

Intrinsic Optical and Electronic Properties from Quantitative Analysis of Plasmonic Semiconductor Nanocrystal Ensemble Optical Extinction

The optical extinction spectra arising from localized surface plasmon resonance in doped semiconductor nanocrystals (NCs) have intensities and lineshapes determined by free charge carrier concentrations and the various mechanisms for damping the oscillation of those free carriers. However, these intrinsic properties are convoluted by heterogeneous broadening when measuring spectra of ensembles. We reveal that the traditional Drude approximation is not equipped to fit spectra from a heterogeneous ensemble of doped semiconductor NCs and produces fit results that violate Mie scattering theory. The heterogeneous ensemble Drude approximation (HEDA) model rectifies this issue by accounting for ensemble heterogeneity and near-surface depletion. The HEDA model is applied to tin-doped indium oxide NCs for a range of sizes and doping levels but we expect it can be employed for any isotropic plasmonic particles in the quasistatic regime. It captures individual NC optical properties and their contributions to the ensemble spectra thereby enabling the analysis of intrinsic NC properties from an ensemble measurement. Quality factors for the average NC in each ensemble are quantified and found to be notably higher than those of the ensemble. Carrier mobility and conductivity derived from HEDA fits matches that measured in the bulk thin film literature.

physics.optics↗

arXiv2020

Separating physically distinct mechanisms in complex infrared plasmonic nanostructures via machine learning enhanced electron energy loss spectroscopy

Low-loss electron energy loss spectroscopy (EELS) has emerged as a technique of choice for exploring the localization of plasmonic phenomena at the nanometer level, necessitating analysis of physical behaviors from 3D spectral data sets. For systems with high localization, linear unmixing methods provide an excellent basis for exploratory analysis, while in more complex systems large numbers of components are needed to accurately capture the true plasmonic response and the physical interpretability of the components becomes uncertain. Here, we explore machine learning based analysis of low-loss EELS data on heterogeneous self-assembled monolayer films of doped-semiconductor nanoparticles, which support infrared resonances. We propose a pathway for supervised analysis of EELS datasets that separate and classify regions of the films with physically distinct spectral responses. The classifications are shown to be robust, to accurately capture the common spatiospectral tropes of the complex nanostructures, and to be transferable between different datasets to allow high-throughput analysis of large areas of the sample. As such, it can be used as a basis for automated experiment workflows based on Bayesian optimization, as demonstrated on the ex situ data. We further demonstrate the use of non-linear autoencoders (AE) combined with clustering in the latent space of the AE yields highly reduced representations of the system response that yield insight into the relevant physics that do not depend on operator input and bias. The combination of these supervised and unsupervised tools provides complementary insight into the nanoscale plasmonic phenomena.

cond-mat.mtrl-sci↗

arXiv2020

Universal Gelation of Metal Oxide Nanocrystals via Depletion Attractions

Nanocrystal gelation provides a powerful framework to translate nanoscale properties into bulk materials and to engineer emergent properties through the assembled microstructure. However, many established gelation strategies rely on chemical reactions and specific interactions, e.g., stabilizing ligands or ions on the surface of the nanocrystals, and are therefore not easily transferrable. Here, we report a general gelation strategy via non-specific and purely entropic depletion attractions applied to three types of metal oxide nanocrystals. The gelation thresholds of two compositionally distinct spherical nanocrystals agree quantitatively, demonstrating the adaptability of the approach for different chemistries. Consistent with theoretical phase behavior predictions, nanocrystal cubes form gels at a lower polymer concentration than nanocrystal spheres, allowing shape to serve as a handle to control gelation. These results suggest that the fundamental underpinnings of depletion-driven assembly, traditionally associated with larger colloidal particles, are also applicable at the nanoscale.

cond-mat.soft↗

arXiv2019

Structure and phase behavior of polymer-linked colloidal gels

Low-density "equilibrium" gels that consist of a percolated, kinetically arrested network of colloidal particles and are resilient to aging can be fabricated by restricting the number of effective bonds that form between the colloids. Valence-restricted patchy particles have long served as one archetypal example of such materials, but equilibrium gels can also be realized through a synthetically simpler and scalable strategy that introduces a secondary linker, such as a small ditopic molecule, to mediate the bonds between the colloids. Here, we consider the case where the ditopic linker molecules are low-molecular-weight polymers and demonstrate using a model colloid-polymer mixture how macroscopic properties such as the phase behavior as well as the microstructure of the gel can be designed through the polymer molecular weight and concentration. The low-density window for equilibrium gel formation is favorably expanded using longer linkers, while necessarily increasing the spacing between all colloids. However, we show that blends of linkers with different sizes enable wider variation in microstructure for a given target phase behavior. Our computational study suggests a robust and tunable strategy for the experimental realization of equilibrium colloidal gels.

cond-mat.soft↗

arXiv2018

Gelation of Plasmonic Metal Oxide Nanocrystals by Polymer-Induced Depletion-Attractions

Gelation of colloidal nanocrystals (NCs) emerged as a strategy to preserve inherent nanoscale properties in multiscale architectures. Yet available gelation methods still struggle to reliably control nanoscale optical phenomena such as photoluminescence and localized surface plasmon resonance (LSPR) across NC systems due to processing variability. Here, we report on an alternative gelation method based on physical inter-NC interactions: short-range depletion-attractions balanced by long-range electrostatic repulsions. The latter are established by removing the native organic ligands that passivate tin-doped indium oxide (ITO) NCs while the former are introduced by mixing with small polyethylene glycol (PEG) chains. As we incorporate increasing concentrations of PEG, we observe a reentrant phase behavior featuring two favorable gelation windows; the first arises from bridging effects while the second is attributed to depletion-attractions according to phase behavior predicted by our unified theoretical model. The NCs remain discrete within the gel network, based on X-ray scattering and high-resolution transmission electron microscopy. The infrared optical response of the gel is reflective of both the NC building blocks and the network architecture, being characteristic of ITO NC LSPR with coupling interactions between neighboring NCs.

cond-mat.mes-hall↗

arXiv2018

Tuning Nanocrystal Surface Depletion by Controlling Dopant Distribution as a Route Toward Enhanced Film Conductivity

Electron conduction through bare metal oxide nanocrystal (NC) films is hindered by surface depletion regions resulting from the presence of surface states. We control the radial dopant distribution in tin-doped indium oxide (ITO) NCs as a means to manipulate the NC depletion width. We find in films of ITO NCs of equal overall dopant concentration that those with dopant-enriched surfaces show decreased depletion width and increased conductivity. Variable temperature conductivity data shows electron localization length increases and associated depletion width decreases monotonically with increased density of dopants near the NC surface. We calculate band profiles for NCs of differing radial dopant distributions and, in agreement with variable temperature conductivity fits, find NCs with dopant-enriched surfaces have narrower depletion widths and longer localization lengths than those with dopant-enriched cores. Following amelioration of NC surface depletion by atomic layer deposition of alumina, all films of equal overall dopant concentration have similar conductivity. Variable temperature conductivity measurements on alumina-capped films indicate all films behave as granular metals. Herein, we conclude that dopant-enriched surfaces decrease the near-surface depletion region, which directly increases the electron localization length and conductivity of NC films.

cond-mat.mes-hall↗