Pattern recognition with “materials that compute”

Fang, Yan; Yashin, Victor V.; Levitan, Steven P.; Balazs, Anna C.

doi:10.1126/sciadv.1601114

Cited by 52 publications

(40 citation statements)

References 29 publications

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“…To conclude, recent technological advances in the fabrication of soft [50,51] and fluid-based [20,22,26,52] active materials demand novel theoretical and algorithmic ideas to guide the functional design of autonomous logical units [13][14][15], pattern recognition systems [53] and information transport devices operating far from thermal equilibrium. Vertex models that account for the relevant physical conservation laws and locally driven matter fluxes offer a flexible testbed for exploring generic properties and limitations of signal transduction in active systems.…”

Section: Resultsmentioning

confidence: 99%

Information transmission and signal permutation in active flow networks

2018

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Recent experiments show that both natural and artificial microswimmers in narrow channel-like geometries will self-organise to form steady, directed flows. This suggests that networks of flowing active matter could function as novel autonomous microfluidic devices. However, little is known about how information propagates through these far-from-equilibrium systems. Through a mathematical analogy with spin-ice vertex models, we investigate here the input-output characteristics of generic incompressible active flow networks (AFNs). Our analysis shows that information transport through an AFN is inherently different from conventional pressure or voltage driven networks. Active flows on hexagonal arrays preserve input information over longer distances than their passive counterparts and are highly sensitive to bulk topological defects, whose presence can be inferred from marginal input-output distributions alone. This sensitivity further allows controlled permutations on parallel inputs, revealing an unexpected link between active matter and group theory that can guide new microfluidic mixing strategies facilitated by active matter and aid the design of generic autonomous information transport networks.

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Section: Resultsmentioning

confidence: 99%

Information transmission and signal permutation in active flow networks

2018

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“…Such devices will do computation by changing properties of their material substrates. First steps in this direction have been in designing Belousov-Zhabotinsky medium based computing devices for pattern recognition [41] and configurable logical gates [42], learning slime mould chip [7], electric current based computing [43], programmable excitation wave propagation in living bioengineered tissues [44], heterotic computing [45], memory devices in digital collides [46].…”

Section: Discussionmentioning

confidence: 99%

Computing via material topology optimisation

Safonov

Adamatzky

2018

Applied Mathematics and Computation

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We construct logical gates via topology optimisation (aimed to solve a station problem of heat conduction) of a conductive material layout. Values of logical variables are represented high and low values of a temperature at given sites. Logical functions are implemented via the formation of an optimum layout of conductive material between the sites with loading conditions. We implement and and xor gates and a one-bit binary half-adder.

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“…Future focal points of prototyping computing, sensing and actuating devices using interacting excitation wave-fronts are soft robotics with gels impregnated with excitable chemical systems [101–104], self-propulsive BZ droplets and chemical robots [105, 106], BZ medium encapsulated in arrays of micro-droplets [107, 108], controlling micro-fluidic systems with excitable media [109], nano-scale realisations of reaction-diffusion computers [110], and implementation of computing circuits with wave-fronts of electrical potential travelling in bioengineered living tissue [111]. …”

Section: Discussionmentioning

confidence: 99%

On Emulation of Flueric Devices in Excitable Chemical Medium

Adamatzky

2016

PLoS ONE

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Flueric devices are fluidic devices without moving parts. Fluidic devices use fluid as a medium for information transfer and computation. A Belousov-Zhabotinsky (BZ) medium is a thin-layer spatially extended excitable chemical medium which exhibits travelling excitation wave-fronts. The excitation wave-fronts transfer information. Flueric devices compute via jets interaction. BZ devices compute via excitation wave-fronts interaction. In numerical model of BZ medium we show that functions of key flueric devices are implemented in the excitable chemical system: signal generator, and, xor, not and nor Boolean gates, delay elements, diodes and sensors. Flueric devices have been widely used in industry since late 1960s and are still employed in automotive and aircraft technologies. Implementation of analog of the flueric devices in the excitable chemical systems opens doors to further applications of excitation wave-based unconventional computing in soft robotics, embedded organic electronics and living technologies.

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Pattern recognition with “materials that compute”

Abstract: We design a self-powered materials system that transduces chemical, mechanical, and electrical energy to perform computation.

Cited by 52 publications

References 29 publications

Information transmission and signal permutation in active flow networks

Information transmission and signal permutation in active flow networks

Computing via material topology optimisation

On Emulation of Flueric Devices in Excitable Chemical Medium

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