1,809 research outputs found
Magnetism, FeS colloids, and Origins of Life
A number of features of living systems: reversible interactions and weak
bonds underlying motor-dynamics; gel-sol transitions; cellular connected
fractal organization; asymmetry in interactions and organization; quantum
coherent phenomena; to name some, can have a natural accounting via
interactions, which we therefore seek to incorporate by expanding the horizons
of `chemistry-only' approaches to the origins of life. It is suggested that the
magnetic 'face' of the minerals from the inorganic world, recognized to have
played a pivotal role in initiating Life, may throw light on some of these
issues. A magnetic environment in the form of rocks in the Hadean Ocean could
have enabled the accretion and therefore an ordered confinement of
super-paramagnetic colloids within a structured phase. A moderate H-field can
help magnetic nano-particles to not only overcome thermal fluctuations but also
harness them. Such controlled dynamics brings in the possibility of accessing
quantum effects, which together with frustrations in magnetic ordering and
hysteresis (a natural mechanism for a primitive memory) could throw light on
the birth of biological information which, as Abel argues, requires a
combination of order and complexity. This scenario gains strength from
observations of scale-free framboidal forms of the greigite mineral, with a
magnetic basis of assembly. And greigite's metabolic potential plays a key role
in the mound scenario of Russell and coworkers-an expansion of which is
suggested for including magnetism.Comment: 42 pages, 5 figures, to be published in A.R. Memorial volume, Ed
Krishnaswami Alladi, Springer 201
Stochastic Modeling and Optimal Control for Colloidal Organization, Navigation, and Machines
Colloidal suspensions consisting of particles undergoing Brownian motion are ubiquitous in scientific research and emerging technologies. Longstanding challenges in strategic control of complex colloidal systems are to investigate the principle of optimal control, overcome the curse of dimensionality, design efficient algorithms, and develop generalizable control strategies. In the first part of this dissertation, we present methods and results from three case studies to illustrate how these challenges are addressed from the perspectives of modeling and optimal control.
Single-agent optimal navigation in complex mazes. We investigate the optimal navigation principle of a self-propelled colloidal particle in complex mazes. We construct approximate Markov chain model and use the Markov decision process framework to obtain the general principle of optimal navigation.
Multiple-agent cooperation and coordination for colloidal machines. Using self-propelled Janus motors as the model system, we illustrate a new paradigm for cargo capture and transport based on multiple-agent feedback control. The control algorithm can coordinate multiple motors to cooperate on forming a reconfigurable machine for cargo capture and transport.
Low-dimensional modeling and ensemble control. Optimal control in a high dimensional self-assembly processes with limited actuations presents a challenge in both modelling and controller design. We use colloidal crystallization in an electric field as a model system to illustrate the methodologies of low-dimensional modeling and control for self-assembly processes. We use a nonlinear machine learning algorithm to characterize the dimensionality and parametrize the low-dimension manifold on which the system evolves. A low-dimensional Smoluchowski model is constructed and calibrated to illustrate the dynamic pathways of the assembly process. The resulting model is further leveraged to perform optimal control of the assembly process.
In the second part of dissertation, we report three additional relevant research projects on colloidal interaction, dynamics, and control. The first project extends ensemble control from finite-size systems to infinite-size systems using feedback control in sedimentation. The second project develops a computational method to model depletion interactions between general geometric objects The third project develops modified Stokesian dynamics methods to investigate the colloidal rod motion near a planar wall with hydrodynamic interactions
Experimental and theoretical evidence for molecular forces driving surface segregation in photonic colloidal assemblies
Surface segregation in binary colloidal mixtures offers a simple way to control both surface and bulk properties without affecting their bulk composition. Here, we combine experiments and coarse-grained molecular dynamics (CG-MD) simulations to delineate the effects of particle chemistry and size on surface segregation in photonic colloidal assemblies from binary mixtures of melanin and silica particles of size ratio (Dlarge/Dsmall) ranging from 1.0 to similar to 2.2. We find that melanin and/or smaller particles segregate at the surface of micrometer-sized colloidal assemblies (supraballs) prepared by an emulsion process. Conversely, no such surface segregation occurs in films prepared by evaporative assembly. CG-MD simulations explain the experimental observations by showing that particles with the larger contact angle (melanin) are enriched at the supraball surface regardless of the relative strength of particle-interface interactions, a result with implications for the broad understanding and design of colloidal particle assemblies
Universal reshaping of arrested colloidal gels via active doping
Colloids that interact via a short-range attraction serve as the primary
building blocks for a broad range of self-assembled materials. However, one of
the well-known drawbacks to this strategy is that these building blocks rapidly
and readily condense into a metastable colloidal gel. Using computer
simulations, we illustrate how the addition of a small fraction of purely
repulsive self-propelled colloids, a technique referred to as active doping,
can prevent the formation of this metastable gel state and drive the system
toward its thermodynamically favored crystalline target structure. The
simplicity and robust nature of this strategy offers a systematic and generic
pathway to improving the self-assembly of a large number of complex colloidal
structures. We discuss in detail the process by which this feat is accomplished
and provide quantitative metrics for exploiting it to modulate self-assembly.
We provide evidence for the generic nature of this approach by demonstrating
that it remains robust under a number of different anisotropic short-ranged
pair interactions in both two and three dimensions. In addition, we report on a
novel microphase in mixtures of passive and active colloids. For a broad range
of self-propelling velocities, it is possible to stabilize a suspension of
fairly monodisperse finite-size crystallites. Surprisingly, this microphase is
also insensitive to the underlying pair interaction between building blocks.
The active stabilization of these moderately-sized monodisperse clusters is
quite remarkable and should be of great utility in the design of hierarchical
self-assembly strategies. This work further bolsters the notion that active
forces can play a pivotal role in directing colloidal self-assembly.Comment: Supplemental Material available here:
https://aip.scitation.org/doi/suppl/10.1063/5.001651
Universal reshaping of arrested colloidal gels via active doping
Colloids that interact via a short-range attraction serve as the primary building blocks for a broad range of self-assembled materials. However, one of the well-known drawbacks to this strategy is that these building blocks rapidly and readily condense into a metastable colloidal gel. Using computer simulations, we illustrate how the addition of a small fraction of purely repulsive self-propelled colloids, a technique referred to as active doping, can prevent the formation of this metastable gel state and drive the system toward its thermodynamically favored crystalline target structure. The simplicity and robust nature of this strategy offers a systematic and generic pathway to improving the self-assembly of a large number of complex colloidal structures. We discuss in detail the process by which this feat is accomplished and provide quantitative metrics for exploiting it to modulate the self-assembly. We provide evidence for the generic nature of this approach by demonstrating that it remains robust under a number of different anisotropic short-ranged pair interactions in both two and three dimensions. In addition, we report on a novel microphase in mixtures of passive and active colloids. For a broad range of self-propelling velocities, it is possible to stabilize a suspension of fairly monodisperse finite-size crystallites. Surprisingly, this microphase is also insensitive to the underlying pair interaction between building blocks. The active stabilization of these moderately sized monodisperse clusters is quite remarkable and should be of great utility in the design of hierarchical self-assembly strategies. This work further bolsters the notion that active forces can play a pivotal role in directing colloidal self-assembly
Fabrication of high quality periodic structures through convective assembly procedures
Techniques aimed at scalable realization of periodic structures from self-assembly of constituent building blocks, an approach that could supplant microfabrication procedures, are often constrained by the lack of diversity in packing arrangements achievable with assembly of simple constituents (e.g., spherical particles). In this work, we present a strategy to effectively pattern colloidal crystalline assemblies at two characteristic scales; achieving extensive non-classical particle packing amidst fully periodic, banded structural defects. We first introduce a scalable and robust approach to fabricate non-hexagonal crystals comprised of mono-sized spherical particles through introduction of periodically oscillating flow-fields during convective particle deposition. Through this technique, we report the discovery of extensive and tunable square-packed arrangements of monosized particles i.e., (100) fcc facets oriented parallel to the underlying substrate in self-assembled colloidal structures. Besides forming large (100) fcc crystalline domains with relatively few defects, the process also results in colloidal crystals having negligible variation in thickness while simultaneously yielding controlled proportions of both hexagonal and square-packed arrangements. The formation of domains of (100) fcc symmetry structures as a result of added vibration is robust across a range of micron-scale monosized spherical colloidal suspensions (e.g., polystyrene, silica) as well as substrate surface chemistries (e.g., hydrophobic, hydrophilic). In-situ visualization during self-assembly process as well as colloidal-crystal fabrication realized at varying frequency and amplitudes of vibration gives clues toward the mechanism of this flow-driven self-assembly method.In the second part of the work, we explore the introduction of volume defects in the uniformly-packed particle assemblies. Here, unlike randomly generated defects in packing structures, we demonstrate the formation of continuous, periodic banded defects comprised of particles with an fcc (110) packing configuration, and with tunable band periodicity. Studies aimed at discerning the specific effects of vibration conditions and meniscus properties help establish a mechanistic picture of the formation of fcc (110) banded structures based on stress relaxation in crystals through generation and movement of dislocations. The final chapters of the dissertation discuss how the convective assembly techniques could be efficiently used towards fabricating various devices for energy conversion and storage
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Thermodynamic and Dynamic Models for Directed Assembly of Small Ensembles of Colloidal Particles
Self and directed assembly of finite clusters (10 to 1000) of colloidal particles into crystalline objects is an emerging area of scientific interest that finds applica- tions in manufacturing of photonic crystals and other meta-materials. Such assembly problems are also of fundamental scientific interest because they involve thermodynamically small systems, with a number of particles that is far below the bulk limit. Robust methods for assembling defect-free target structures will ultimately require reduced-dimension process models that link the particle-level dynamics of the colloids to the actuator states. We have developed a three-part strategy for developing such process models.
First, we employ diffusion mapping (DMaps), a machine learning technique, on raw trajectory data to identify slow, low-dimensional manifolds in the system dy- namics. Second, we identify convenient observables, or order parameters (OPs), that strongly correlate with low-dimensional DMap coordinates; this step may involve a feedback loop with the DMap process itself. Third, we use a Fokker-Planck or Smoluchowski formalism to build free energy and diffusivity landscapes in the OPs, which serve as our reduced-dimension process models. We have applied this technique to two model systems in this work. The first system comprises 32 silica particles, which interact via a temperature-tunable depletion interaction potential. This system shows transitions between an expanded and condensed phase when the pair interaction strength is changed by a few kBT . The second system comprises 210 quasi-2D silica particles confined within quadrupole electrodes and the interaction strength, which is of the order of few kBT , is tuned by an externally applied electric field. This system shows interesting features like the formation and annealing of polycrystalline microstructures as the magnitude of the applied field is changed. We systematically compare and contrast the DMap analysis on both these model systems. We construct an optimal control policy map in the low-dimensional DMap coordinates using dynamic programming. The free energy and diffusivity landscapes along with the control policy map is used to robustly assemble perfect colloidal crystals.
We have also examined the phase behavior of the depletion potential system via a histogram-based simulation approach. We conducted replica exchange Monte Carlo simulations of these small colloidal clusters and generated potential energy histograms for various levels of the osmotic pressure that controls the interaction strength. By carefully tuning the osmotic pressure, we observed bimodal distributions in the potential energy space, which is indicative of coexistence between fluid-like and solid-like configurations. Quantitative analysis of these histograms yield phase coexistence curves for these small clusters and we report comparisons with bulk colloidal phase diagrams
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