Center for Dynamics and Control of Materials Publications

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The Center for Dynamics and Control of Materials: an NSF MRSEC brings together researchers from across science and engineering to create materials with new atomic-scale structures and functionalities, and to develop approaches for actively controlling and reconfiguring materials in real time. These materials will enable the development of new and improved technologies in areas such as sustainable energy, quantum information processing, bioinspired systems, and semiconductors for telecommunications, computing, and sensing.

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Now showing 1 - 10 of 188
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    Plasmonic response of complex nanoparticle assemblies
    (2022-09-15) Sherman, Zachary M.; Kim, Kihoon; Kang, Jiho; Roman, Benjamin J.; Crory, Hannah S. N.; Conrad, Diana L.; Valenzuela, Stephanie A.; Lin, Emily Y.; Dominguez, Manuel N.; Gibbs, Stephen L.; Anslyn, Eric V.; Milliron, Delia J.; Truskett, Thomas M.
    Optical properties of nanoparticle assemblies reflect distinctive characteristics of their building blocks and spatial organization, giving rise to emergent phenomena. Integrated experimental and computational studies have established design principles connecting the structure to properties for assembled clusters and superlattices. However, conventional electromagnetic simulations are too computationally expensive to treat more complex assemblies. Here we establish a fast, materials agnostic method to simulate the optical response of large nanoparticle assemblies incorporating both structural and compositional complexity. This many-bodied, mutual polarization method resolves limitations of established approaches, achieving rapid, accurate convergence for configurations including thousands of nanoparticles, with some overlapping. We demonstrate these capabilities by reproducing experimental trends and uncovering far- and near-field mechanisms governing the optical response of plasmonic semiconductor nanocrystal assemblies including structurally complex gel networks and compositionally complex mixed binary superlattices. This broadly applicable framework will facilitate the design of complex, hierarchically structured, and dynamic assemblies for desired optical characteristics.
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    Modular mixing in plasmonic metal oxide nanocrystal gels with thermoreversible links
    (AIP Publishing, 2023-01-10) Kang, Jiho; Sherman, Zachary M.; Crory, Hannah S. N.; Conrad, Diana L.; Berry, Marina W.; Roman, Benjamin J.; Anslyn, Eric V.; Truskett, Thomas M.; Milliron, Delia J.
    Gelation offers a powerful strategy to assemble plasmonic nanocrystal networks incorporating both the distinctive optical properties of con- stituent building blocks and customizable collective properties. Beyond what a single-component assembly can offer, the characteristics of nanocrystal networks can be tuned in a broader range when two or more components are intimately combined. Here, we demonstrate mixed nanocrystal gel networks using thermoresponsive metal–terpyridine links that enable rapid gel assembly and disassembly with ther- mal cycling. Plasmonic indium oxide nanocrystals with different sizes, doping concentrations, and shapes are reliably intermixed in linked gel assemblies, exhibiting collective infrared absorption that reflects the contributions of each component while also deviating systematically from a linear combination of the spectra for single-component gels. We extend a many-bodied, mutual polarization method to simulate the optical response of mixed nanocrystal gels, reproducing the experimental trends with no free parameters and revealing that spectral devia- tions originate from cross-coupling between nanocrystals with distinct plasmonic properties. Our thermoreversible linking strategy directs the assembly of mixed nanocrystal gels with continuously tunable far- and near-field optical properties that are distinct from those of the building blocks or mixed close-packed structures.
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    Dynamics of equilibrium-linked colloidal networks
    (AIP Publishing, 2022-11-08) Kwon, Taejin; Wilcoxson, Tanner A.; Milliron, Delia J,; Truskett, Thomas M.
    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 linker-saturated 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 dynamic response of colloidal networks.
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    Depletion-driven assembly of polymer-coated nanocrystals
    (2022-09-05) Green, Allison M.; Kadulkar, Sanket; Sherman, Zachary M.; FitzSimons, Thomas M.; Ofosu, Charles K.; Yan, Jiajun; Zhao, David; Ilavsky, Jan; Rosales, Adrienne M.; Helms, Brett A.; Ganesan, Venkat; Truskett, Thomas M.; Milliron, Delia J.
    Depletion-driven assembly has been widely studied for micron-sized colloids, but questions remain at the nanoscale where the governing physics are impacted by the stabilizing surface ligands or wrapping polymers, whose length scales are on the same order as those of the colloidal core and the depletant. Here, we probe how wrapping colloidal tin-doped indium oxide nanocrystals with polymers affects their depletion- induced interactions and assembly in solutions of polyethylene glycol. Copolymers of polyacrylic acid grafted with polyethylene oxide provide nanocrystal wrappings with different effective polymer graft densities and molecular weights. (Ultra) small angle X-ray scattering, coarse-grained molecular dynamics simulation, and molecular thermo- dynamic theory were combined to analyze how depletant size and polymer wrapping characteristics affect depletion interactions, structure, and phase behavior. The re- sults show how depletant molecular weight, as well as surface density and molecular weight of polymer grafts, set thresholds for assembly. These signatures are unique to depletion-driven assembly of nanoscale colloids and mirror phase behaviors of grafted nanoparticle–polymer composites. Optical and rheological responses of depletion-driven assemblies of nanocrystals with different polymer shell architectures were probed to learn how their structural differences impact properties. We discuss how these han- dles for depletion-driven assembly at the nanoscale may provide fresh opportunities for designing responsive depletion interactions and dynamically reconfigurable materials.
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    Machine learning-assisted design of material properties
    (2022-01-26) Kadulkar, Sanket; Sherman, Zachary M.; Ganesan, Venkat; Truskett, Thomas M.
    Designing functional materials requires a deep search through multidimensional spaces for system parameters that yield desirable material properties. For cases where conventional parameter sweeps or trial-and-error sampling are impractical, inverse methods that frame design as a constrained optimization problem present an attractive alternative. However, even efficient algorithms require time- and resource-intensive characterization of material properties many times during optimization, imposing a design bottleneck. Approaches that incorporate machine learning can help address this limitation and accelerate the discovery of materials with targeted properties. In this article, we review how to leverage machine learning to reduce dimensionality in order to effectively explore design space, accelerate property evaluation, and generate unconventional material structures with optimal properties. We also discuss promising future directions, including integration of machine learning into multiple stages of a design algorithm and interpretation of machine learning models to understand how design parameters relate to material properties.
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    Facet-Enhanced Dielectric Sensitivity in Plasmonic Metal Oxide Nanocubes
    (2022) Roman, Benjamin J.; Shubert-Zuleta, Sofia A.; Shim, Grant; Kyveryga, Victoria; Faris, Mohamed; Milliron, Delia J.
    The resonant frequency of plasmonic nanoparticles depends on the refractive index of the local environment, a property which is directly useful for sensing applications and is indicative of potential utility for other applications based on near-field enhancement of light intensity. While the morphology dependence of dielectric sensitivity has been well studied in noble metal nanoparticles, less investigated is the sensitivity of degenerately doped metal oxide nanocrystals, whose plasmon resonances lie in the near- to mid- infrared. Here, we report the dielectric sensitivity of fluorine and tin co-doped indium oxide nanocubes, its dependence on their sharp faceting that gives rise to multiple plasmonic modes, and on their tin-dopant concentration. We find that the plasmon mode associated with the nanocube corners is the most sensitive and that raising dopant concentration increases dielectric sensitivity. Comparing to finite element simulations that assume a spatially uniform free electron distribution in the nanocubes, we show that the plasmon modes associated with the edges and the faces of the nanocubes are less sensitive than expected, and that their reduced dielectric sensitivity can be rationalized by the presence of band bending and a resulting surface depletion layer. Interestingly, simulations suggest that Fermi level pinning occurs predominantly on the cube faces, reshaping the free electron volume so that the depletion layer effectively insulates the faces and edges from the surrounding environment, while the corner mode remains sensitive.
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    Multiscale modeling of solute diffusion in triblock copolymer membranes
    (AIP Publishing, 2023-01-11) Cooper, Anthony J.; Howard, Michael P.; Kadulkar, Sanket; Zhao, David; Delaney, Kris T.; Ganesan, Venkat; Truskett, Thomas M.; Fredrickson, Glenn H.
    We develop a multiscale simulation model for diffusion of solutes through porous triblock copolymer membranes. The approach combines two techniques: self-consistent field theory (SCFT) to predict the structure of the self-assembled, solvated membrane and on-lattice kinetic Monte Carlo (kMC) simulations to model diffusion of solutes. Solvation is simulated in SCFT by constraining the glassy membrane matrix while relaxing the brush-like membrane pore coating against the solvent. The kMC simulations capture the resulting solute spatial distribution and concentration-dependent local diffusivity in the polymer-coated pores; we parameterize the latter using particle-based simulations. We apply our approach to simulate solute diffusion through nonequilibrium morphologies of a model triblock copolymer, and we correlate diffusivity with structural descriptors of the morphologies. We also compare the model’s predictions to alternative approaches based on simple lattice random walks and find our multiscale model to be more robust and systematic to parameterize. Our multiscale modeling approach is general and can be readily extended in the future to other chemistries, morphologies, and models for the local solute diffusivity and interactions with the membrane.
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    Symmetry-breaking in patch formation on triangular gold nanoparticles by asymmetric polymer grafting
    (Springer Nature Limited, 2022-11-09) Kim, Ahyoung; Vo, Thi; An, Hyosung; Banerjee, Progna; Yao, Lehan; Zhou, Shan; Kim, Chansong; Milliron, Delia J.; Glotzer, Sharon C.; Chen, Qian
    Synthesizing patchy particles with predictive control over patch size, shape, placement and number has been highly sought-after for nanoparticle assembly research, but is fraught with challenges. Here we show that polymers can be designed to selectively adsorb onto nanoparticle surfaces already partially coated by other chains to drive the formation of patchy nanoparticles with broken symmetry. In our model system of triangular gold nanoparticles and polystyrene-b-polyacrylic acid patch, single- and double-patch nanoparticles are produced at high yield. These asymmetric single-patch nanoparticles are shown to assemble into self-limited patch‒patch connected bowties exhibiting intriguing plasmonic properties. To unveil the mechanism of symmetry- breaking patch formation, we develop a theory that accurately predicts our experimental observations at all scales—from patch patterning on nano- particles, to the size/shape of the patches, to the particle assemblies driven by patch‒patch interactions. Both the experimental strategy and theoretical prediction extend to nanoparticles of other shapes such as octahedra and bipyramids. Our work provides an approach to leverage polymer interactions with nanoscale curved surfaces for asymmetric grafting in nanomaterials engineering.
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    Effect of pH on the Properties of Hydrogels Cross-Linked via Dynamic Thia-Michael Addition Bonds
    (ACS Publications, 2021-12-28) FitzSimons, Thomas M.; Anslyn, Eric V.; Rosales, Adrienne M.
    Hydrogels cross-linked with dynamic covalent bonds exhibit time-dependent properties, making them an advantageous platform for applications ranging from biomaterials to self-healing networks. However, the relationship between the cross-link exchange kinetics, material properties, and stability of these platforms is not fully understood, especially upon addition of external stimuli. In this work, pH was used as a handle to manipulate cross-link exchange kinetics and control the resulting hydrogel mechanics and stability in a physiologically relevant window. Poly(ethylene glycol)-based hydrogels were cross-linked with a reversible thia-Michael addition reaction in aqueous buffer between pH 3 and pH 7. The rate constants of bond exchange and equilibrium constants were determined for each pH value, and these data were correlated with the resulting mechanical profiles of the bulk hydrogels. With increasing pH, both the forward and the reverse rate constants increased, while the equilibrium constant decreased. These changes led to faster stress relaxation and less stiff hydrogels at more basic pH values. The elevated pH values also led to an increased mass loss and a faster rate of release of an encapsulated model bovine serum albumin fluorescent protein. The connection between the kinetics, mechanics, and molecular release profiles provides important insight into the structure−property relationships of dynamic covalent hydrogels, and this system offers a promising platform for controlled release between physiologically relevant pH values.
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    Contact conductance governs metallicity in conducting metal oxide nanocrystal films
    (2022) Staller, Corey M.; Gibbs, Stephen L.; Gan, Xing Yee; Bender, Jay T.; Jarvis, Karalee; Ong, Gary K.; Milliron, Delia J.
    Although colloidal nanoparticles hold promise for fabricating electronic components, the properties of nanoparticle-derived materials can be unpredictable. Materials made from metallic nanocrystals exhibit a variety of transport behavior ranging from insulators, with inter- nanocrystal contacts acting as electron transport bottlenecks, to conventional metals, where phonon scattering limits electron mobility. The insulator-metal transition (IMT) in nanocrystal films is thought to be determined by contact conductance. Meanwhile, criteria are lacking to predict the characteristic transport behavior of metallic nanocrystal films beyond this threshold. Using a library of transparent conducting tin-doped indium oxide nanocrystal films with varied electron concentration, size, and contact area, we assess the IMT as it depends on contact conductance and show how contact conductance is also key to predicting the temperature- dependence of conductivity in metallic films. The results establish a phase diagram for electron transport behavior that can guide the creation of metallic conducting materials from nanocrystal building blocks.