Structure and Dynamics of Hybrid Colloid–Polyelectrolyte Coacervates: Insights from Molecular Simulations
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SEARCH · Engineering Papers
Results for “colloidal particles”
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Enhancing Lignin Dispersion and Bioconversion by Eliminating Thermal Sterilization
Thermal sterilization is widely applied in fermentation to ensure a pure culture. In this study, a facile and energy-efficient strategy by eliminating thermal sterilization (ETS) was unveiled for upgrading lignin bioconversion. Through alkaline solubilization and neutralization, lignin dispersion in aqueous fermentation media was significantly enhanced by ETS. Small-angle X-ray scattering and dynamic light scattering analyses indicated that the lignin colloid size was dramatically reduced. Compared to 20.5 wt % lignin precipitation during the conventional thermal sterilization, precipitated lignin was not observed within the ETS medium. 31P NMR characterization demonstrated an 11.7% increase of phenolic OH in ETS lignin. Ionization of phenolic OH presented more negatively charged groups, strengthening electrostatic repulsion, resulting in smaller colloidal particles. Interestingly, the pure culture of Rhodococcus opacus PD630 was achieved within the ETS medium due to the lack of lignin degradation ability with most natural microbes. R. opacus PD630 cell amount, lignin degradation, and lipid production by ETS increased by 330, 16.6, and 20.7%, respectively. Overall, an energy-efficient ETS strategy that promoted lignin dispersion and bioconversion significantly is reported in this study.
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Reversible Emulsions from Polyoxometalate–Polymer: A Robust Strategy to Cyclic Emulsion Catalysis and High-Internal-Phase Emulsion Materials
Reversible Pickering emulsions, achieved by switchable, interfacially active colloidal particles, that enable on-demand emulsification/demulsification or phase inversion, hold substantial promise for biphasic catalysis, emulsion polymerization, cutting fluids, and crude oil pipeline transportation. However, particles with such a responsive behavior usually require complex chemical syntheses and surface modifications, limiting their extensive use. Herein, we report a simple route to generate emulsions that can be controlled and reversibly undergo phase inversion. The emulsions are prepared and stabilized by the interfacial assembly of polyoxometalate (POM)–polymer, where their electrostatic interaction at the interface is dynamic. The wettability of the POMs that dictates the emulsion type can be readily regulated by tuning the number of polymer chains bound to POMs, which, in turn, can be controlled by varying the concentrations of both components and the water/oil ratio. In addition, the number of polymer chains anchored to the POMs can be varied by controlling the number of negative charges on the POMs through an in situ redox reaction. As such, a reversible inversion of the emulsions can be triggered by switching between exposure to ultraviolet light and the introduction of oxygen. Combining the functions of POM itself, a cyclic interfacial catalysis system was realized. Inversion of the emulsion also affords a pathway to high-internal-phase emulsions. Finally, the diversity of the POMs, the polymers, and the responsive switching groups open numerous new, simple strategies for designing a wide range of responsive soft matter for cargo loading, controlled release, and delivery in biomedical and engineering applications without time-consuming particle syntheses.
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Reconfigurable droplet networks
Droplet networks stabilized by lipid interfacial bilayers or colloidal particles have been extensively investigated in recent years and are of great interest for compartmentalized reactions and biological functions. However, current design strategies are disadvantaged by complex preparations and limited droplet size. Here, by using the assembly and jamming of cucurbit[8]uril surfactants at the oil-water interface, we show a novel means of preparing droplet networks that are multi-responsive, reconfigurable, and internally connected over macroscopic distances. Openings between the droplets enable the exchange of matter, affording a platform for chemical reactions and material synthesis. Our work requires only a manual compression to construct complex patterns of droplet networks, underscoring the simplicity of this strategy and the range of potential applications.
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Comprehensive defect suppression in perovskite nanocrystals for high-efficiency light-emitting diodes
Electroluminescence efficiencies of metal halide perovskite nanocrystals (PNCs) are limited by a lack of material strategies that can both suppress the formation of defects and enhance the charge carrier confinement. Here we report a one-dopant alloying strategy that generates smaller, monodisperse colloidal particles (confining electrons and holes, and boosting radiative recombination) with fewer surface defects (reducing non-radiative recombination). Doping of guanidinium into formamidinium lead bromide PNCs yields limited bulk solubility while creating an entropy-stabilized phase in the PNCs and leading to smaller PNCs with more carrier confinement. Further, the extra guanidinium segregates to the surface and stabilizes the undercoordinated sites. Furthermore, a surface-stabilizing 1,3,5-tris(bromomethyl)-2,4,6-triethylbenzene was applied as a bromide vacancy healing agent. The result is highly efficient PNC-based light-emitting diodes that have current efficiency of 108 cd A –1 (external quantum efficiency of 23.4%), which rises to 205 cd A –1 (external quantum efficiency of 45.5%) with a hemispherical lens.
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Dependency of active pressure and equation of state on stiffness of wall
Autonomous motion and motility are hallmarks of active matter. Active agents, such as biological cells and synthetic colloidal particles, consume internal energy or extract energy from the environment to generate self-propulsion and locomotion. These systems are persistently out of equilibrium due to continuous energy consumption. It is known that pressure is not always a state function for generic active matter. Torque interaction between active constituents and confinement renders the pressure of the system a boundary-dependent property. The mechanical pressure of anisotropic active particles depends on their microscopic interactions with a solid wall. Using self-propelled dumbbells confined by solid walls as a model system, we perform numerical simulations to explore how variations in the wall stiffness influence the mechanical pressure of dry active matter. In contrast to previous findings, we find that mechanical pressure can be independent of the interaction of anisotropic active particles with walls, even in the presence of intrinsic torque interaction. Particularly, the dependency of pressure on the wall stiffness vanishes when the stiffness is above a critical level. In such a limit, the dynamics of dumbbells near the walls are randomized due to the large torque experienced by the dumbbells, leading to the recovery of pressure as a state variable of density.
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Deep learning for characterizing the self-assembly of three-dimensional colloidal systems
Creating a systematic framework to characterize the structural states of colloidal self-assembly systems is crucial for unraveling the fundamental understanding of these systems’ stochastic and non-linear behavior. The most accurate characterization methods create high-dimensional neighborhood graphs that may not provide useful information about structures unless these are well-defined reference crystalline structures. Dimensionality reduction methods are thus required to translate the neighborhood graphs into a low-dimensional space that can be easily interpreted and used to characterize non-reference structures. We investigate a framework for colloidal system state characterization that employs deep learning methods to reduce the dimensionality of neighborhood graphs. The framework next uses agglomerative hierarchical clustering techniques to partition the low-dimensional space and assign physically meaningful classifications to the resulting partitions. In this work, we first demonstrate the proposed colloidal self-assembly state characterization framework on a three-dimensional in silico system of 500 multi-flavored colloids that self-assemble under isothermal conditions. We next investigate the generalizability of the characterization framework by applying the framework to several independent self-assembly trajectories, including a three-dimensional in silico system of 2052 colloidal particles that undergo evaporation-induced self-assembly.
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Anisotropic colloidal interactions & assembly in AC electric fields
In this work, we match experimental and simulated configurations of anisotropic epoxy colloidal particles in high frequency AC electric fields by identifying analytical potentials for dipole-field and dipole-dipole interactions. We report an inverse Monte Carlo simulation algorithm to determine optimal fits of analytical potentials by matching simulated and experimental distribution functions for non-uniform liquid, liquid crystal, and crystal microstructures in varying amplitude electric fields. Two potentials that include accurate particle volume and dimensions along with a concentration dependent prefactor quantitatively capture experimental observations. At low concentrations, an effective ellipsoidal point dipole potential works well, whereas a novel stretched point dipole potential is found to be suitable at all concentrations, field amplitudes, and degrees of ordering. The simplicity, accuracy, and adjustability of the stretched point dipole potential suggest it can be applied to model field mediated microstructures and assembly of systematically varying anisotropic particle shapes.
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Customized metallodielectric colloids and their behavior in dielectrophoretic fields
A synthetic strategy for fabricating colloidal particles with spatially segregated amine-functionalized lobes enables regioselective coating with gold to afford metallodielectric particles with a variety of shapes and lobe sizes. This approach can produce either dissymmetric dumbbell-shaped two-lobed Au-TPM particles (Au-T) or dissymmetric or symmetric three-lobed particles with gold coating on one (Au-T-T and T-Au-T) or two lobes (Au-T-Au). Dielectrophoretic (DEP) forces exerted by an AC field confined between two opposing electrodes generate aggregates ranging from 1D chains to 2D close-packed lattices, depending on the particle shape and lobe arrangement. Furthermore, the aggregate structures reflect the lowest energy configurations resulting from the induced dipole moments created in particle lobes within the confined electric field.
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A coarse-grained simulation model for colloidal self-assembly via explicit mobile binders
Colloidal particles with mobile binding molecules constitute a powerful platform for probing the physics of self-assembly. Binding molecules are free to diffuse and rearrange on the surface, giving rise to spontaneous control over the number of droplet–droplet bonds, i.e., valence, as a function of the concentration of binders. This type of valence control has been realized experimentally by tuning the interaction strength between DNA-coated emulsion droplets. Optimizing for valence two yields droplet polymer chains, termed ‘colloidomers’, which have recently been used to probe the physics of folding. To understand the underlying self-assembly mechanisms, here we present a coarse-grained molecular dynamics (CGMD) model to study the self-assembly of this class of systems using explicit representations of mobile binding sites. Further, we explore how valence of assembled structures can be tuned through kinetic control in the strong binding limit. More specifically, we optimize experimental control parameters to obtain the highest yield of long linear colloidomer chains. Subsequently tuning the dynamics of binding and unbinding via a temperature-dependent model allows us to observe a heptamer chain collapse into all possible rigid structures, in good agreement with recent folding experiments. Our CGMD platform and dynamic bonding model (implemented as an open-source custom plugin to HOOMD-Blue) reveal the molecular features governing the binding patch size and valence control, and opens the study of pathways in colloidomer folding. This model can therefore guide programmable design in experiments.
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Advances in the photon avalanche luminescence of inorganic lanthanide-doped nanomaterials
Photon avalanche (PA)—where the absorption of a single photon initiates a ‘chain reaction’ of additional absorption and energy transfer events within a material—is a highly nonlinear optical process that results in upconverted light emission with an exceptionally steep dependence on the illumination intensity. Over 40 years following the first demonstration of photon avalanche emission in lanthanide-doped bulk crystals, PA emission has been achieved in nanometer-scale colloidal particles. The scaling of PA to nanomaterials has resulted in significant and rapid advances, such as luminescence imaging beyond the diffraction limit of light, optical thermometry and force sensing with (sub)micron spatial resolution, and all-optical data storage and processing. In this review, we discuss the fundamental principles underpinning PA and survey the studies leading to the development of nanoscale PA. Finally, we offer a perspective on how this knowledge can be used for the development of next-generation PA nanomaterials optimized for a broad range of applications, including mid-IR imaging, luminescence thermometry, (bio)sensing, optical data processing and nanophotonics.
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Unveiling Structural Heterogeneity and Imbalance of Gold Decahedral Nanoparticles using Four-dimensional Scanning Transmission Electron Microscopy
Multi-twinned structures have been observed in technologically important crystal systems, for example diamond cubic and face-centered cubic (FCC) lattices, that include materials such as diamond, silicon, a wide range of noble metals, and their nanoscale counterparts. Beyond atomic building blocks, the special arrangements also occur in the self-assembly of nanoparticles (NP) and μm-sized colloidal particles and occupy parts of their phase diagrams. Spanning a wide range of length scales, the universality of the structures arises when the systems attempt to achieve multitwinned structures by overcoming geometric misfits during minimizing surface energies with entirely {111} or close-packing facets. While it is fundamental to understand how strain is sustained upon twinned structures and symmetry breaking, the knowledge will be paramount in practical aspects such as guiding and controlling the thin film growth, anisotropic NP growth, and self-assembly of NPs. Au decahedral (Dh) NP, as the most prevalent multi-twinned model system, fits five tetrahedral motifs into a circle by sharing an axis resulting in a geometric misfit angle of 7.35°, or a disclination with power of -7.35°. Postulating how Au FCC lattice adopts the misfit, theoretical models have been developed to address the underlying lattice symmetry and inhomogeneous strain distribution separately. Yet, experimental reports regarding the former have been limited due to the relatively large X-ray beam sizes that do not fit the sizes of NPs. On the other hand, though the latter has been widely adapted in the thermodynamics of small (<10 nm) multi-twinned nanoparticles, previous literature has shown that, at edge length of 17 nm, the theory’s is invalidated by shear strain that is observed in a defect-free Au Dh NP by high-resolution transmission electron microscopy (HR-TEM) imaging. Though the advancement of aberrationcorrected scanning transmission electron microscopy (AC-STEM) imaging and ab initio calculation techniques brings new opportunities, along with challenges in complicated image analysis and limitation in particle size (usually below 10 nm), the gap between nanoscale and mesoscale has never been extended to gain insight from atomic system with straightforward interaction potentials.
4D-STEM↗
Spin echo small-angle neutron scattering using superconducting magnetic Wollaston prisms
Here, we show the implementation of superconducting magnetic Wollaston prisms for spin echo small-angle neutron scattering. Two calibration methods for the spin echo length are presented: one utilizing spin echo modulated small-angle neutron scattering and the other based on the neutron refraction by quartz wedge crystals. Our experimental results with polystyrene nano-particle colloids showcase the system’s efficacy in measuring both dilute and concentrated colloidal systems. Additionally, investigations into the pore diameter and pitch of a nano-porous alumina membrane demonstrate its capability in analyzing nano-porous materials. Furthermore, we discuss potential optimizations to further extend the accessible spin echo length.
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Ion transport through reconfigurable nanoparticle-surfactant stabilized droplet interface bilayers
Despite their adaptability and mechanical stability, Pickering emulsions based on the interfacial assembly of colloidal particles have not found use in iontronics, since the dense interfacial packing of micron-sized particles precludes functional connectivity between two droplets. In this work, we introduce a chemically reconfigurable droplet interface bilayer (DIB) platform based on the interfacial assembly of nanoparticle-surfactants (NPSs) that enables spontaneous or field-induced formation of ion-conducting nanochannels, eliminating the need of ionophores or nanochannel-forming proteins. These nanoscopic channels emerge from packing defects in the jammed interfacial assemblies of the charged NPSs and support size and charge selective, hysteretic ion transport governed by interfacial electrostatics and dimensional constraints. The NPS-DIBs show short-term and long-term plasticity, hallmarks of neuromorphic behavior, that are mediated by the structural and chemical design of the bilayer. These assemblies establish a versatile, chemically tunable platform that couples soft-matter mechanics with interfacial ionic functionality, offering a robust foundation for soft iontronic systems.
36 MATERIALS SCIENCE↗
Spontaneous skyrmion conformal lattice and transverse motion during dc and ac compression
Abstract We use atomistic-based simulations to investigate the behavior of ferromagnetic skyrmions being continuously compressed against a rigid wall under dc and ac drives. The compressed skyrmions can be annihilated close to the wall and form a conformal crystal with both a size and a density gradient, making it distinct from conformal crystals observed previously for superconducting vortices and colloidal particles. For both dc and ac driving, the skyrmions can move transverse to the compression direction due to a combination of density and size gradients. Forces in the compression direction are converted by the Magnus force into transverse motion. Under ac driving, the amount of skyrmion annihilation is reduced and we find a skyrmion Magnus ratchet pump. We also observe shear banding in which skyrmions near the wall move up to twice as fast as skyrmions further from the wall. When we vary the magnitude of the applied drive, we find a critical current above which the skyrmions are completely annihilated during a time scale that depends on the magnitude of the drive. By varying the magnetic parameters, we find that the transverse motion is strongly dependent on the skyrmion size. Smaller skyrmions are more rigid, which interferes with the size gradient and destroys the transverse motion. We also confirm the role of the size gradient by comparing our atomistic simulations with a particle-based model, where we find that the transverse motion is only transient. Our results are relevant for applications where skyrmions encounter repulsive magnetic walls, domain walls, or interfaces.
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Statics and dynamics of skyrmions interacting with disorder and nanostructures
Magnetic skyrmions are topologically stable nanoscale particlelike objects that were discovered in 2009. Since that time, intense research interest in the field has led to the identification of numerous compounds that support skyrmions over a range of conditions spanning from cryogenic to room temperatures. Skyrmions can be set into motion under various types of driving, and the combination of their size, stability, and dynamics makes them ideal candidates for numerous applications. At the same time, skyrmions represent a new class of system in which the energy scales of the skyrmion-skyrmion interactions, sample disorder, temperature, and drive can compete. A growing body of work indicates that the static and dynamic states of skyrmions can be influenced strongly by pinning or disorder in the sample; thus, an understanding of such effects is essential for the eventual use of skyrmions in applications. The current state of knowledge regarding individual skyrmions and skyrmion assemblies interacting with quenched disorder or pinning is reviewed. Additionally, the microscopic mechanisms for skyrmion pinning, including the repulsive and attractive interactions that can arise from impurities, grain boundaries, or nanostructures, are outlined. This is followed by descriptions of depinning phenomena, sliding states over disorder, the effect of pinning on the skyrmion Hall angle, the competition between thermal and pinning effects, the control of skyrmion motion using ordered potential landscapes such as one- or two-dimensional periodic asymmetric substrates, the creation of skyrmion diodes, and skyrmion ratchet effects. Highlighted are the distinctions arising from internal modes and the strong gyrotropic or Magnus forces that cause the dynamical states of skyrmions to differ from those of other systems with pinning, such as vortices in type-II superconductors, charge density waves, or colloidal particles. Throughout this review future directions and open questions related to the pinning and dynamics in skyrmion systems are also discussed.
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Controlling colloidal crystals via morphing energy landscapes and reinforcement learning
We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning–based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 10 3 particles with mean process times scaling as N 0.5 . Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.
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