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At least 37 records · Page 2

Towards predictive control of reversible nanoparticle assembly with solid-binding proteins

Although a broad range of ligand-functionalized nanoparticles and physico-chemical triggers have been exploited to create stimuli-responsive colloidal systems, little attention has been paid to the reversible assembly of unmodified nanoparticles with non-covalently bound proteins. Previously, we reported that a derivative of green fluorescent protein engineered with oppositely located silica-binding peptides mediates the repeated assembly and disassembly of 10-nm silica nanoparticles when pH is toggled between 7.5 and 8.5. We captured the subtle interplay between interparticle electrostatic repulsion and their protein-mediated short-range attraction with a multiscale model energetically benchmarked to collective system behavior captured by scattering experiments. Here, in this work, we show that both solution conditions (pH and ionic strength) and protein engineering (sequence and position of engineered silica-binding peptides) provide pathways for reversible control over growth and fragmentation, leading to clusters ranging in size from 25 nm protein-coated particles to micrometer-size aggregate. We further find that the higher electrolyte environment associated with successive cycles of base addition eventually eliminates reversibility. Our model accurately predicts these multiple length scales phenomena. The underpinning concepts provide design principles for the dynamic control of other protein- and particle-based nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ordered and disordered skyrmion states on a square substrate

We examine the ordering of skyrmions interacting with a square substrate created from a modulation of anisotropy using atomistic simulations. We consider fillings of ƒ = 1.5, 2.0, 2.5, 3.0, and 3.5 skyrmions per potential minimum as a function of magnetic field and sample size. For a filling of ƒ = 2.0, we find various dimer orderings, such as tilted dimer states, as well as antiferromagnetic ordering that is similar to the colloidal dimer ordering seen on square substrates. Furthermore, the ability of the skyrmions to change shape or annihilate produces additional states that do not occur in the colloidal systems. For certain parameters at ƒ = 2.0, half of the skyrmions can annihilate to form a square lattice, or a superlattice of trimers and monomers containing skyrmions of different sizes can form. At lower fields, ordered stretched skyrmion states can appear, and for zero field, there can be ordered stripe states. For ƒ = 3.0, we find ferromagnetic ordered trimers, tilted lattices, columnar lattices, and stretched phases. For fillings of ƒ = 1.5 and 2.5, we find bipartite lattices, different ordered and disordered states, and several extended disordered regions produced by frustration effects.

36 MATERIALS SCIENCE↗

Out-of-equilibrium interactions and collective locomotion of colloidal spheres with squirming of nematoelastic multipoles

Many living and artificial systems show similar emergent behavior and collective motions on different scales, starting from swarms of bacteria to synthetic active particles, herds of mammals, and crowds of people. What all these systems often have in common is that new collective properties like flocking emerge from interactions between individual self-propelled or driven units. Such systems are naturally out-of-equilibrium and propel at the expense of consumed energy. Mimicking nature by making self-propelled or externally driven particles and studying their individual and collective motility may allow for deeper understanding of physical underpinnings behind collective motion of large groups of interacting objects or beings. Here, in this work, using a soft matter system of colloids immersed into a liquid crystal, we show that resulting so-called nematoelastic multipoles can be set into a bidirectional locomotion by external oscillating electric fields. Out-of-equilibrium elastic interactions between such colloidal objects lead to collective flock-like behaviors emerging from time-varying elasticity-mediated interactions between externally driven propelling particles. Repulsive elastic interactions in the equilibrium state can be turned into attractive interactions in the out-of-equilibrium state under applied external electric fields. We probe this behavior at different number densities of colloidal particles and show that particles in dense dispersions collectively select the same direction of a coherent motion due to elastic interactions between near neighbors. In our experimentally implemented design, their motion is highly ordered and without clustering or jamming often present in other colloidal transport systems, which is promising for technological and fundamental-science applications, like nano-cargo transport, out-of-equilibrium assembly, and microrobotics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

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.

47 OTHER INSTRUMENTATION↗

Environmental impact of solution pH on the formation and migration of iron colloids in deep subsurface energy systems

Deep subsurface stimulation processes often promote fluid-rock interactions that can lead to the formation of small colloidal particles that are suspected to migrate through the rock matrix, partially or fully clog pores and microfractures, and promote the mobilization of contaminants. Thus, the goal of this work is to understand the geochemical changes of the host rock in response to reservoir stimulation that promote the formation and migration of colloids. Two different carbonate-rich shales were exposed to different solution pHs (pH = 2 and 7). In this study, iron and other mineral transformations at the shale-fluid interface were first characterized by synchrotron-based XRF mapping. Then, colloids that were able to migrate from the shale into the bulk fluid were characterized by synchrotron-based extended X-ray absorption structure (EXAFS), scanning electron microscopy (SEM), and single-particle inductively coupled plasma time-of-flight mass spectrometry (sp-icpTOF-MS). When exposed to the pH = 2 solution, extensive mineral dissolution and secondary precipitation was observed; iron-(oxyhydr)oxide colloids colocated with silicates were observed by SEM at the fluid-shale interfaces, and the mobilization of chromium and nickel with these iron colloids into the bulk fluid was detected by sp-icpTOF-MS. Iron EXAFS spectra of the solution at the shale-fluid interface suggests the rapid (within minutes) formation of ferrihydrite-like nanoparticles. Thus, we demonstrate that the pH neutralization promotes the mobilization of existing silicate minerals and the rapid formation of new iron colloids. These Fe colloids have the potential to migrate through the shale matrix and mobilize other heavy metals (such as Cr and Ni, in this study) and impacting groundwater quality, as well produced waters from these hydraulic fracturing operations.

54 ENVIRONMENTAL SCIENCES↗

Nematic Colloidal Micro‐Robots as Physically Intelligent Systems

Abstract Physically intelligent micro‐robotic systems exploit information embedded in micro‐robots, their colloidal cargo, and their milieu to interact, assemble, and form functional structures. Nonlinear anisotropic fluids such as nematic liquid crystals (NLCs) provide untapped opportunities to embed interactions via their topological defects, complex elastic responses, and ability to dramatically restructure in dynamic settings. Here a four‐armed ferromagnetic micro‐robot is designed and fabricated to embed and dynamically reconfigure information in the nematic director field, generating a suite of physical interactions for cargo manipulation. The micro‐robot shape and surface chemistry are designed to generate a nemato‐elastic energy landscape in the domain that defines multiple modes of emergent, bottom‐up interactions with passive colloids. Micro‐robot rotation expands the ability to sculpt interactions; the energy landscape around a rotating micro‐robot is dynamically reconfigured by complex far‐from‐equilibrium dynamics of the micro‐robot's companion topological defect. These defect dynamics allow transient information to be programmed into the domain and exploited. Robust micro‐robotic manipulation strategies are demonstrated that exploit these diverse modes of nemato‐elastic interaction to achieve cargo docking, transport, release, and assembly of complex reconfigurable structures at multi‐stable sites. Such structures are of great interest to future developments of LC‐based advanced optical device and micro‐manufacturing in anisotropic environments.

Yao, Tianyi↗

Insights into controlling bacterial cellulose nanofiber film properties through balancing thermodynamic interactions and colloidal dynamics

In recent years, nanocellulose has emerged as a sustainable and environmentally friendly alternative to traditional petroleum-derived structural polymers. Sourced either from plants, algae, or bacteria, nanocellulose can be processed into colloid, gel, film and fiber forms. However, the required fundamental understanding of process parameters that govern the morphology and structure–property relationships of nanocellulose systems, from colloidal suspensions to bulk materials, has not been developed and generalized for all forms of cellulose. This further hinders the more widespread adoption of this biopolymer in applications. Our study investigates the dispersion of cellulose nanofibers (CNFs) produced by a bacterial–yeast co-culture, in solvents, highlighting the role of thermodynamic interactions in influencing their colloidal behavior. By adjusting Hansen solubility parameters, we controlled the thermodynamic relationship between CNFs and solvents across various concentrations, studying the dilute to semi-dilute regimes. Rheological measurements revealed that the threshold at which a concentration-based regime transition occurs is distinctly solvent-dependent. Complementing rheological analysis with small angle X-ray scattering and zeta potential measurements, our findings reveal that enhancing CNF–solvent interactions increases excluded volume in the dilute regime, emphasizing the importance of the balance between fiber–fiber and fiber–solvent interactions. Moreover, we investigated the transition from colloidal to solid state by creating films from dispersions with varying interaction parameters in semi-dilute regimes. Through mechanical testing and scanning electron microscopy imaging of the fracture surfaces, we highlight the significance of electrokinetic effects in such transitions, as dispersions with higher electrokinetic stabilization gave rise to stronger and tougher films despite having less favorable thermodynamic interaction parameters. Finally, our work provides insights into the thermodynamic and electrokinetic interplay that governs bacterial CNF dispersion, offering a foundation for future application and a deeper understanding of nanocellulose's colloidal and structure-property relationships.

59 BASIC BIOLOGICAL SCIENCES↗

High energy density picoliter-scale zinc-air microbatteries for colloidal robotics

The recent interest in microscopic autonomous systems, including microrobots, colloidal state machines, and smart dust, has created a need for microscale energy storage and harvesting. However, macroscopic materials for energy storage have noted incompatibilities with microfabrication techniques, creating substantial challenges to realizing microscale energy systems. Here, we photolithographically patterned a microscale zinc/platinum/SU-8 system to generate the highest energy density microbattery at the picoliter (10 −12 liter) scale. The device scavenges ambient or solution-dissolved oxygen for a zinc oxidation reaction, achieving an energy density ranging from 760 to 1070 watt-hours per liter at scales below 100 micrometers lateral and 2 micrometers thickness in size. The parallel nature of photolithography processes allows 10,000 devices per wafer to be released into solution as colloids with energy stored on board. Within a volume of only 2 picoliters each, these primary microbatteries can deliver open circuit voltages of 1.05 ± 0.12 volts, with total energies ranging from 5.5 ± 0.3 to 7.7 ± 1.0 microjoules and a maximum power near 2.7 nanowatts. We demonstrated that such systems can reliably power a micrometer-sized memristor circuit, providing access to nonvolatile memory. We also cycled power to drive the reversible bending of microscale bimorph actuators at 0.05 hertz for mechanical functions of colloidal robots. Additional capabilities, such as powering two distinct nanosensor types and a clock circuit, were also demonstrated. The high energy density, low volume, and simple configuration promise the mass fabrication and adoption of such picoliter zinc-air batteries for micrometer-scale, colloidal robotics with autonomous functions.

Robotics↗

Activated relaxation in supercooled monodisperse atomic and polymeric WCA fluids: Simulation and ECNLE theory

Here, we combine simulation and Elastically Collective Nonlinear Langevin Equation (ECNLE) theory to study the activated relaxation in monodisperse atomic and polymeric Weeks–Chandler–Andersen (WCA) liquids over a wide range of temperatures and densities in the supercooled regime under isochoric conditions. By employing novel crystal-avoiding simulations, metastable equilibrium dynamics is probed in the absence of complications associated with size polydispersity. Based on a highly accurate structural input from integral equation theory, ECNLE theory is found to describe well the simulated density and temperature dependences of the alpha relaxation time of atomic fluids using a single system-specific parameter, a c , that reflects the nonuniversal relative importance of local cage and collective elastic barriers. For polymer fluids, the explicit dynamical effect of local chain connectivity is modeled at the fundamental dynamic free energy trajectory level based on a different parameter, N c , that quantifies the degree of intramolecular correlation of bonded segment activated barrier hopping. For the flexible chain model studied, a physically intuitive value of N c ≈ 2 results in good agreement between simulation and theory. A direct comparison between atomic and polymeric systems reveals that chain connectivity can speed up activated segmental relaxation due to weakening of equilibrium packing correlations but can slow down relaxation due to local bonding constraints. The empirical thermodynamic scaling idea for the alpha time is found to work well at high densities or temperatures but fails when both density and temperature are low. The rich and subtle behaviors revealed from simulation for atomic and polymeric WCA fluids are all well captured by ECNLE theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The mechanics of nucleation and growth and the surface tensions of active matter

Homogeneous nucleation, a textbook transition path for phase transitions, is typically understood on thermodynamic grounds through the prism of classical nucleation theory. However, recent studies have suggested the applicability of classical nucleation theory to systems far from equilibrium. Here, in this article, we formulate a purely mechanical perspective of homogeneous nucleation and growth, elucidating the criteria for the properties of a critical nucleus without appealing to equilibrium notions. Applying this theory to active fluids undergoing motility-induced phase separation, we find that nucleation proceeds in a qualitatively similar fashion to equilibrium systems, with concepts such as the Gibbs–Thomson effect and nucleation barriers remaining valid. We further demonstrate that the recovery of such concepts allows us to extend classical theories of nucleation rates and coarsening dynamics to active systems upon using the mechanically derived definitions of the nucleation barrier and surface tensions. Three distinct surface tensions—the mechanical, capillary, and Ostwald tensions—play a central role in our theory. While these three surface tensions are identical in equilibrium, our work highlights the distinctive role of each tension in the stability of active interfaces and the nucleation and growth of motility-induced phases.

Capillary waves↗

Phonon modulation of strongly coupled gold tetrahedral plasmonic nanoparticles and a carbocyanine J-aggregate

Coupling exciton and plasmon excitations to form polaritons are of great interest for manipulating energy transfer at the nanoscale via the formation of hybrid light–matter states. In this study, we successfully couple gold tetrahedral nanoparticles with the J-aggregate forming dye 5,5′,6,6′-tetrachloro-1,1′-diethyl-3,3′-di(4-sulfobutyl)-benzimidazolocarbocyanine (TDBC) to form a strongly coupled colloidal polariton system with a Rabi splitting energy of ∼206 meV. These gold tetrahedra exhibit coherent phonon modes upon photoexcitation, which produce transient oscillations of the LSPR energy for isolated tetrahedra. Transient absorption measurements of the polariton system were performed and show how these coherent phonon modes influence the polariton states’ extinction. We found that the oscillation period increases by 0.5 ± 0.14 ps upon surface deposition of TDBC dye, demonstrating LSPR sensitivity to the refractive index environment. Shifts in the plasmon resonance due to the coherent phonon modes transiently alters LSPR alignment with the J-aggregate exciton peak, resulting in shifts of the hybrid polariton states’ oscillator strength.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Memory in aging colloidal gels with time-varying attraction

Here, we report a combined rheology, x-ray photon correlation spectroscopy, and modeling study of gel formation and aging in suspensions of nanocolloidal spheres with volume fractions of 0.20 and 0.43 and with a short-range attraction whose strength is tuned by changing temperature. Following a quench from high temperature, where the colloids are essentially hard spheres, to a temperature below the gel point, the suspensions form gels that undergo aging characterized by a steadily increasing elastic shear modulus and slowing, increasingly constrained microscopic dynamics. The aging proceeds at a faster rate for stronger attraction strength. When the attraction strength is suddenly lowered during aging, the gel properties evolve non-monotonically in a manner resembling the Kovacs effect in glasses, in which the modulus decreases and the microscopic dynamics become less constrained for a period before more conventional aging resumes. Eventually, the properties of the gel following the decrease in attraction strength converge to those of a gel that has undergone aging at the lower attraction strength throughout. The time scale of this convergence increases as a power law with the age at which the attraction strength is decreased and decreases exponentially with the magnitude of the change in attraction. A model for gel aging in which particles attach and detach from the gel at rates that depend on their contact number reproduces these trends and reveals that the non-monotonic behavior results from the dispersion in the rates that the populations of particles with different contact number adjust to the new attraction strength.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving nanoparticle superlattice stability with deformable polymer gels

The self-assembly of colloidal nanoparticles into ordered superlattices typically uses dynamic interactions to govern particle crystallization, as these non-permanent bonds prevent the formation of kinetically trapped, disordered aggregates. However, while the use of reversible bonding is critical in the formation of highly ordered particle arrangements, dynamic interactions also inherently make the structures more prone to disassembly or disruption when subjected to different environmental stimuli. Thus, there is typically a trade-off between the ability to initially form an ordered colloidal material and the ability of that material to retain its order under different conditions. Here, we present a method for embedding colloidal nanoparticle superlattices into a polymer gel matrix. This encapsulation strategy physically prevents the nanoparticles from dissociating upon heating, drying, or the introduction of chemicals that would normally disrupt the lattice. However, the use of a gel as the embedding medium still permits further modification of the colloidal nanoparticle lattice by introducing stimuli that deform the gel network (as this deformation in turn alters the nanoparticle lattice structure in a predictable manner). Moreover, encapsulation of the lattice within a gel permits further stabilization into fully solid materials by removing the solvent from the gel or by replacing the solvent with a liquid monomer that can be photopolymerized. This embedding method therefore makes it possible to incorporate ordered colloidal arrays into a polymer matrix as either dynamic or static structures, expanding their potential for use in responsive materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physics-tailored machine learning reveals unexpected physics in dusty plasmas

Dusty plasma is a mixture of ions, electrons, and macroscopic charged particles that is commonly found in space and planetary environments. The particles interact through Coulomb forces mediated by the surrounding plasma, and as a result, the effective forces between particles can be nonconservative and nonreciprocal. Machine learning (ML) models are a promising route to learn these complex forces, yet their structure should match the underlying physical constraints to provide useful insight. Here, we demonstrate and experimentally validate an ML approach that incorporates physical intuition to infer force laws in a laboratory dusty plasma. Trained on 3D particle trajectories, the model accounts for inherent symmetries, nonidentical particles, and learns the effective nonreciprocal forces between particles with exquisite accuracy (R 2 > 0.99). We validate the model by inferring particle masses in two independent yet consistent ways. The model’s accuracy enables precise measurements of particle charge and screening length, identifying large deviations from common theoretical assumptions. Our ability to identify unknown physics from experimental data demonstrates how ML-powered approaches can guide new routes of scientific discovery in many-body systems. Furthermore, we anticipate our ML approach to be a starting point for inferring laws from dynamics in a wide range of many-body systems, from colloids to living organisms.

Science & Technology - Other Topics↗

Geometrical control of topological charge transfer in Shakti-Cairo colloidal ice

Lattice transformations that preserve the system topology, but not its geometry, are common in condensed matter systems. However, how geometric constrains influence the topological properties of the lattices is still unclear. Here we show that a geometric transformation between two mixed coordination lattices, from Shakti to Cairo in an artificial colloidal ice, leads to a breakdown of the ice rule in all but one specific geometry. We observe a transfer of topological charge among sublattices which can be controlled in sign and intensity, vanishing at the ice-rule point. These unusual topological effects are absent in magnetic spin ices and they are due to collective, non-local geometric frustration in the particle ice. By merging numerical simulations, theory and experiments, we demonstrate how the charge transfer occurs in the Cairo geometry. The broader implication of our results is that we demonstrate how geometric constraints can control the topological properties of a mesoscopic colloidal system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Skyrmion-skyrmionium phase separation and laning transitions via spin-orbit torque currents

Many driven binary systems can exhibit laning transitions when the two species have different mobilities, such as colloidal particles with opposite charges in electric fields. Another example is pedestrian or active-matter systems, where particles moving in opposite directions form a phase-separated state that enhances the overall mobility. In this work, we use atomistic simulations to demonstrate that mixtures of skyrmions and skyrmioniums also exhibit pattern formation and laning transitions. Skyrmions move more slowly and at a finite skyrmion Hall angle compared to skyrmioniums, which move faster and without a skyrmion Hall effect. At low drives, the system forms a partially jammed phase where the skyrmioniums are dragged by the surrounding skyrmions, resulting in a finite angle of motion for the skyrmioniums. At higher drives, the system transitions into a laned state, but unlike colloidal systems, the lanes in the skyrmion-skyrmionium mixture are tilted relative to the driving direction due to the intrinsic skyrmion Hall angle. In the laned state, the skyrmionium angle of motion is reversed when it aligns with the tilted lane structure. At even higher drives, the skyrmioniums collapse into skyrmions. Below a critical skyrmion density, both textures can move independently with few collisions, but above this density, the laning state disappears entirely, and the system transitions to a skyrmion-only state. We map out the velocity and Hall responses of the different textures and identify three distinct phases: partially jammed, laned, and skyrmion-only moving crystal states. In conclusion, we compare our results to recent observations of tilted laning phases in pedestrian flows, where chiral symmetry breaking in the particle interactions leads to similar behavior.

36 MATERIALS SCIENCE↗

Unlocking hidden information in sparse small-angle neutron scattering measurements

Hypothesis Small-Angle Neutron Scattering (SANS) is a powerful technique for studying soft matter systems such as colloids, polymers, and lyotropic phases, providing nanoscale structural insights. However, its effectiveness is limited by low neutron flux, leading to long acquisition times and noisy data. Here, we hypothesize that Bayesian statistical inference using Gaussian Process Regression (GPR) can reconstruct high-fidelity scattering data from sparse measurements by leveraging intensity smoothness and continuity. Experiments and Simulations The method was benchmarked computationally and validated through SANS experiments on various soft matter systems, including wormlike micelles, colloidal suspensions, polymeric structures, and lyotropic phases. GPR-based inference was applied to both experimental and synthetic data to evaluate its effectiveness in noise reduction and intensity reconstruction. Findings GPR significantly enhances SANS data quality and therefore reducing measurement times by up to two orders of magnitude. This cost-effective approach maximizes experimental efficiency, enabling high-throughput studies and real-time monitoring of dynamic systems. It is particularly beneficial for weakly scattering and time-sensitive studies. Beyond SANS, this framework applies to other low-SNR techniques, including laboratory-based small-angle X-ray scattering and various dynamical scattering methods. Furthermore, it offers transformative potential for compact neutron sources, enhancing their viability for structural analysis in resource-limited settings.

Small angle neutron scattering↗

Reversible to irreversible transitions for cyclically driven particles on periodic obstacle arrays

Here, we examine the collective dynamics of disks moving through a square array of obstacles under cyclic square wave driving. Below a critical density, we find that the system organizes into a reversible state in which the disks return to the same positions at the end of every drive cycle. Above this density, the dynamics are irreversible and the disks do not return to the same positions after each cycle. The critical density depends strongly on the angle θ between the driving direction and a symmetry axis of the obstacle array, with the highest critical densities appearing at commensurate angles such as θ = 0° and θ = 45° and the lowest critical densities falling at θ = arctan (0.618), the inverse of the golden ratio, where the flow is the most degenerate. As the density increases, the number of cycles required to reach a reversible state grows as a power law with an exponent near ν = 1.36, similar to what is found in periodically driven colloidal and superconducting vortex systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗