Diffusion metamaterials

Zhang, Zeren; Xu, Liujun; Qu, Teng; Lei, Min; Lin, Zhi‐Kang; Ouyang, Xiaoping; Jiang, Jianhua; Huang, Jiping

doi:10.1038/s42254-023-00565-4

Cited by 88 publications

(14 citation statements)

References 236 publications

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“…To tackle this issue, tunable metamaterials with dynamic features have emerged, covering optics, [25] acoustics, [26] mechanics, [27,28] and thermotics. [29][30][31][32][33][34][35] For example, advanced thermal functions have been realized, such as macroscopic thermal diodes, [29] tunable analog thermal materials, [36] path-dependent thermal devices, [37] and liquidsolid hybrid metamaterials. [38] Additionally, adaptive thermal devices are presented to maintain functionality or stability depending on application scenes.…”

Section: Doi: 101002/adma202305791mentioning

confidence: 99%

Deep Learning‐Assisted Active Metamaterials with Heat‐Enhanced Thermal Transport

Jin,

Xu,

et al. 2023

Advanced Materials

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Heat management is crucial for state‐of‐the‐art applications such as passive radiative cooling, thermally adjustable wearables, and camouflage systems. Their adaptive versions, to cater to varied requirements, lean on the potential of adaptive metamaterials. Existing efforts, however, feature with highly anisotropic parameters, narrow working‐temperature ranges, and the need for manual intervention, which remain long‐term and tricky obstacles for the most advanced self‐adaptive metamaterials. To surmount these barriers, we introduce heat‐enhanced thermal diffusion metamaterials powered by deep learning. Such active metamaterials can automatically sense ambient temperatures and swiftly, as well as continuously, adjust their thermal functions with a high degree of tunability. They maintain robust thermal performance even when external thermal fields change direction, and both simulations and experiments demonstrate exceptional results. Furthermore, we design two metadevices with on‐demand adaptability, performing distinctive features with isotropic materials, wide working temperatures, and spontaneous response. This work offers a framework for the design of intelligent thermal diffusion metamaterials and can be expanded to other diffusion fields, adapting to increasingly complex and dynamic environments.This article is protected by copyright. All rights reserved

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Section: Doi: 101002/adma202305791mentioning

confidence: 99%

Deep Learning‐Assisted Active Metamaterials with Heat‐Enhanced Thermal Transport

Jin,

Xu,

et al. 2023

Advanced Materials

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“…[23] Given the pressing need for further breakthroughs in these areas, substantial efforts have been devoted to achieving nonreciprocal heat transfer over the past decade. [24,25] However, most existing approaches to macroscopic thermal nonreciprocity rely on nonlinear or spatiotemporal-modulation effects, [26,27] which come with apparent drawbacks, such as limited operating temperature ranges and complex experimental setups. [28][29][30] Meanwhile, constrained by their inherent mechanisms, these methods can hardly be effective under both dynamic and static excitations.…”

Section: Introductionmentioning

confidence: 99%

Nonreciprocal Heat Circulation Metadevices

Ju,

Cao,

Wang

et al. 2023

Advanced Materials

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Thermal nonreciprocity typically stems from nonlinearity or spatiotemporal variation of parameters. However, constrained by the inherent temperature‐dependent properties and the law of mass conservation, previous works have been compelled to treat dynamic and steady‐state cases separately. Here, by establishing a unified thermal scattering theory, the creation of a convection‐based thermal metadevice which supports both dynamic and steady‐state nonreciprocal heat circulation is reported. The nontrivial dependence between the nonreciprocal resonance peaks and the dynamic parameters is observed and the unique nonreciprocal mechanism of multiple scattering is revealed at steady state. This mechanism enables thermal nonreciprocity in the initially quasi‐symmetric scattering matrix of the three‐port metadevice and has been experimentally validated with a significant isolation ratio of heat fluxes. The findings establish a framework for thermal nonreciprocity that can be smoothly modulated for dynamic and steady‐state heat signals, it may also offer insight into other heat‐transfer‐related problems or even other fields such as acoustics and mechanics.

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“…In most cases, 𝜅o differs from 𝜅 b , and different thermal conductivities lead to variation in the temperature gradient around the object; such variation is the reason why most objects are not thermally stealthy in the background environment. [39][40][41] The above-mentioned studies demonstrated the ability of thermal cloaks to manipulate the thermal field in space. In the present work, the effect of thermal cloak geometrical parameters is studied to achieve enhanced performance in a limited space.…”

mentioning

confidence: 97%

Autonomously Tuning Multilayer Thermal Cloak with Variable Thermal Conductivity Based on Thermal Triggered Dual Phase-Transition Metamaterial

Lou 娄,

Xia 夏

2023

Chinese Phys. Lett.

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Thermal cloaks offer the potential to conceal internal objects from detection or prevent thermal shock by controlling external heat flow. However, most conventional natural materials lack the desired flexibility and versatility required for on-demand thermal manipulation. In this study, we propose a solution in the form of homogeneous multilayer thermodynamic cloaks. Through an ingenious design, these cloaks achieve exceptional and extreme parameters, enabling the distribution of multiple materials in space. We first investigated the effects of important design parameters on the thermal shielding effectiveness of conventional thermal cloaks. Subsequently, we introduce an autonomous tuning function for the thermodynamic cloak, accomplished by leveraging two phase transition materials as thermal conductive layers. Remarkably, this tuning function does not require any energy input. Finite element analysis results demonstrate a significant reduction in the temperature gradient inside the thermal cloak compared to the surrounding background. This reduction indicates the cloak's remarkable ability to manipulate the spatial thermal field. Furthermore, the utilization of materials undergoing phase transition leads to an increase in thermal conductivity, enabling the cloak to achieve the opposite variation of the temperature field between the object region and the background. This means that while the temperature gradient within the cloak decreases, the temperature gradient in the background increases. This work addresses a compelling and crucial challenge in the realm of thermal metamaterials—the autonomous tuning of the thermal field without energy input. Such an achievement is currently unattainable with existing natural materials. This study establishes the groundwork for the application of thermal metamaterials in thermodynamic cloaks, with potential extensions into thermal energy harvesting, thermal camouflage, and thermoelectric conversion devices. By harnessing phonons, our findings provide an unprecedented and practical approach to flexibly implementing thermal cloaks and manipulating heat flow.

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Diffusion metamaterials

Cited by 88 publications

References 236 publications

Deep Learning‐Assisted Active Metamaterials with Heat‐Enhanced Thermal Transport

Deep Learning‐Assisted Active Metamaterials with Heat‐Enhanced Thermal Transport

Nonreciprocal Heat Circulation Metadevices

Autonomously Tuning Multilayer Thermal Cloak with Variable Thermal Conductivity Based on Thermal Triggered Dual Phase-Transition Metamaterial

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