Autoperforation of two-dimensional materials to generate colloidal state machines capable of locomotion

Liu, Albert Tianxiang Tianxiang; Yang, Jing; LeMar, Lexy; Zhang, Ge; Pervan, Ana; Murphey, Todd D.

doi:10.1039/d0fd00030b

Cited by 11 publications

(14 citation statements)

References 28 publications

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“…Research in nanofabrication and synthesis methods have yielded sophisticated synthetic devices, including particles that serve a particular function (e.g., light control for nanoactuation [11], performing clocked, multistage logic [12], actuation using external magnetic fields [13], [14]), but not particles possessing autonomous circuitry, logic manipulation, and information storage [1]. Besides the work published in [1], [9], existing micro-or nanoparticles do not autonomously process information when decoupled from their environment [15], [16]. The particles created in Koman and Liu et al [1], [9] are the basis for the synthetic cells proposed in this paper, and we will make the following assumptions based on this work:…”

Section: Related Workmentioning

confidence: 99%

“…Besides the work published in [1], [9], existing micro-or nanoparticles do not autonomously process information when decoupled from their environment [15], [16]. The particles created in Koman and Liu et al [1], [9] are the basis for the synthetic cells proposed in this paper, and we will make the following assumptions based on this work:…”

Section: Related Workmentioning

confidence: 99%

“…Decaying memory enables synthetic cells' success bits to turn off (back to 0) after some amount of time has passed since they last detected a target. We know from [1], [9] that this is physically feasible, given variable chemical decay rates and reactions that act similarly to capacitors with a decaying charge.…”

Section: Multiple and Moving Targetsmentioning

confidence: 99%

“…These devices are around 100µm in size, rendering classical computation using a CPU impossible. But simple movement, sensory, and memory elements can potentially be combined with a series of physically realizable logical operators to enable a specific task [8], [9] (e.g., a simple reinforcement 1 Department of Mechanical Engineering, Northwestern University, Evanston, Illinois, USA anapervan@u.northwestern.edu t-murphey@northwestern.edu Fig. 1: A cyclic maze that mimics aspects of the circulatory system.…”

Section: Introductionmentioning

confidence: 99%

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Bayesian Particles on Cyclic Graphs

Pervan¹,

Murphey²

2020

Preprint

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We consider the problem of designing synthetic cells to achieve a complex goal (e.g., mimicking the immune system by seeking invaders) in a complex environment (e.g., the circulatory system), where they might have to change their control policy, communicate with each other, and deal with stochasticity including false positives and negatives-all with minimal capabilities and only a few bits of memory.We simulate the immune response using cyclic, maze-like environments and use targets at unknown locations to represent invading cells. Using only a few bits of memory, the synthetic cells are programmed to perform a reinforcement learning-type algorithm with which they update their control policy based on randomized encounters with other cells. As the synthetic cells work together to find the target, their interactions as an ensemble function as a physical implementation of a Bayesian update. That is, the particles act as a particle filter.This result provides formal properties about the behavior of the synthetic cell ensemble that can be used to ensure robustness and safety. This method of simplified reinforcement learning is evaluated in simulations, and applied to an actual model of the human circulatory system.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Multiple and Moving Targetsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bayesian Particles on Cyclic Graphs

Pervan¹,

Murphey²

2020

Preprint

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“…Towards a formal characterization of the minimum capabilities required by individual modules of programmable matter to achieve a given system behavior, many abstract models have been proposed over the last several decades [3,11,12,13,31,37,38,39,41]. We focus on the amoebot model [19,21] which is motivated by micro-and nano-scale robotic systems with strictly limited computational and locomotive capabilities [34,35,36,42,43]. The amoebot model abstracts active programmable matter as a collection of simple computational elements called amoebots that utilize local interactions to collectively achieve tasks involving coordination, movement, and reconfiguration.…”

Section: Introductionmentioning

confidence: 99%

The Canonical Amoebot Model: Algorithms and Concurrency Control

Daymude¹,

Richa²,

Scheideler³

2021

Preprint

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The amoebot model abstracts active programmable matter as a collection of simple computational elements called amoebots that interact locally to collectively achieve tasks of coordination and movement. Since its introduction (SPAA 2014), a growing body of literature has adapted its assumptions for a variety of problems; however, without a standardized hierarchy of assumptions, precise systematic comparison of results under the amoebot model is difficult. We propose the canonical amoebot model, an updated formalization that distinguishes between core model features and families of assumption variants. A key improvement addressed by the canonical amoebot model is concurrency. Much of the existing literature implicitly assumes amoebot actions are isolated and reliable, reducing analysis to the sequential setting where at most one amoebot is active at a time. However, real programmable matter systems are concurrent. The canonical amoebot model formalizes all amoebot communication as message passing, leveraging adversarial activation models of concurrent executions. Under this granular treatment of time, we take two complementary approaches to concurrent algorithm design. In the first -using hexagon formation as a case study -we establish a set of sufficient conditions that guarantee an algorithm's correctness under any concurrent execution, embedding concurrency control directly in algorithm design. In the second, we present a concurrency control protocol that uses locks to convert amoebot algorithms that terminate in the sequential setting and satisfy certain conventions into algorithms that exhibit equivalent behavior in the concurrent setting. These complementary approaches to concurrent algorithm design under the canonical amoebot model open new directions for distributed computing research on programmable matter and form a rigorous foundation for connections to related literature.

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Memristor Circuits for Colloidal Robotics: Temporal Access to Memory, Sensing, and Actuation

Yang

Liu

Berrueta

et al. 2021

Advanced Intelligent Systems

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Micrometer‐scale robots capable of navigating enclosed spaces and remote locations are approaching reality. However, true autonomy remains an open challenge despite substantial progress made with externally supervised and manipulated systems. To accelerate the development of autonomous microrobots, alternatives to conventional top‐down lithography are sought. Such additive technologies like printing, coating, and colloidal self‐assembly allow for rapid prototyping and access to novel materials, such as polymers, bio‐ and nanomaterials. On the basis of recent experimental findings that memristive networks can be rapidly printed and lifted off as electronic microparticles, an alternative design paradigm is introduced based on arrays of two‐terminal memristive elements, which enables real‐time use of memory, sensing, and actuation in microrobots. Several memristor‐based designs are validated, each representing a key building block toward robotic autonomy: tracking elapsed time, timestamping a rare event, continuously cataloguing time‐indexed data, and accessing the collected information for a feedback‐controlled response as in a robotic glucose‐responsive insulin. The computational results establish an actionable framework for microrobotic design—tasks normally requiring complex circuits can now be achieved with self‐assembled and printed memristor arrays within microparticles.

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Autoperforation of two-dimensional materials to generate colloidal state machines capable of locomotion

Abstract: A central ambition of the robotics field has been to increasingly miniaturize such systems, with perhaps the ultimate achievement being the synthetic microbe or cell sized machine. To this end,...

Cited by 11 publications

References 28 publications

Bayesian Particles on Cyclic Graphs

Bayesian Particles on Cyclic Graphs

The Canonical Amoebot Model: Algorithms and Concurrency Control

Memristor Circuits for Colloidal Robotics: Temporal Access to Memory, Sensing, and Actuation

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