Deep learning has become the dominant approach in artificial intelligence to solve complex data-driven problems. Originally applied almost exclusively in computer-science areas such as image analysis ...and nature language processing, deep learning has rapidly entered a wide variety of scientific fields including physics, chemistry and material science. Very recently, deep neural networks have been introduced in the field of nanophotonics as a powerful way of obtaining the nonlinear mapping between the topology and composition of arbitrary nanophotonic structures and their associated functional properties. In this paper, we have discussed the recent progress in the application of deep learning to the inverse design of nanophotonic devices, mainly focusing on the three existing learning paradigms of supervised-, unsupervised-, and reinforcement learning. Deep learning forward modelling i.e. how artificial intelligence learns how to solve Maxwell’s equations, is also discussed, along with an outlook of this rapidly evolving research area.
Abstract
Intensive development of nanofabrication processes has opened a new window to control electromagnetic waves using subwavelength nanostructures array, named metasurfaces. Although the ...metasurfaces have succeeded in achieving unprecedented functionality by arranging various shapes of nanostructures to modulate the properties of the incident light, inherent passive characteristics make it impossible to alter the engraved functions after it is fabricated. To give tunability to metasurfaces, various methods have been proposed by using a thermal, chemical, optical and physical stimulus. In particular, electrically tunable metasurfaces are attractive in that they are easy to control precisely and could be integrated into electronic devices. In this review, we categorize the representative electrical tuning mechanisms and research into three; voltage-operated modulation, electrochemical-driven modulation, and externally mediated modulation. Voltage-operated modulation uses materials that could be directly reorganized by an electric field, including liquid crystals and Drude materials. Electrochemical-driven modulation adjusts the optical properties of metasurfaces through electrochemical responses such as electrochromism and electrodeposition. Lastly, externally mediated modulation causes a change in the geometric parameters of metasurfaces or in the phase of the constituent materials by converting electrical energy into thermal or mechanical stimulation. This paper concludes after explaining the pros and cons of each mechanism and the new possibilities which electrically-responsive metasurfaces could bring about.
Radiative cooling, a technology that lowers the temperature of terrestrial objects by dissipating heat into outer space, presents a promising ecologically‐benign solution for sustainable cooling. ...Recent years witness substantial progress in radiative cooling technologies, bringing them closer to commercialization. This comprehensive review provides a structured overview of radiative cooling technologies, encompassing essential principles, fabrication techniques, and practical applications, with the goal of guiding researchers toward successful commercialization. The review begins by introducing the fundamentals of radiative cooling and the associated design strategies to achieve it. Then, various fabrication methods utilized for the realization of radiative cooling devices are thoroughly discussed. This discussion includes detailed assessments of scalability, fabrication costs, and performance considerations, encompassing both structural designs and fabrication techniques. Building upon these insights, potential fabrication approaches suitable for practical applications and commercialization are proposed. Further, the recent efforts made toward the practical applications of radiative cooling technology, including its visual appearance, switching capability, and compatibility are examined. By encompassing a broad range of topics, from fundamental principles to fabrication and applications, this review aims to bridge the gap between theoretical research and real‐world implementation, fostering the advancement and widespread adoption of radiative cooling technology.
Radiative cooling technologies garner significant interest as ecologically‐benign solutions for future energy sustainability. This comprehensive review offers a well‐organized exploration of radiative cooling, encompassing its foundational design principles, fabrication techniques, potential methods for practical implementation, and real‐world applications. Its overarching aim is to guide researchers seeking successful commercialization within this field.
The instrumented indentation technique has been investigated to efficiently evaluate the mechanical responses of materials with few limitations on the shape and size of the specimen. There have been ...attempts to discover a direct correlation between the stress-strain curve and the indenting load-displacement curve by introducing the concept of representative strain and stress. However, it is still difficult to find relible parameters and to distinguish similar load-displacement curves that correspond to different stress-strain curves with a limited number of experimental datasets. The present study introduces a finite element method (FEM)-based simulation that can output various load-displacement datasets corresponding to intrinsic properties of materials, including strain rate; these datasets are validated using experimental indentation results for diverse metallic materials at different indenting speeds (0.6, 0.9, 1.2 mm/min). In addition, an autoencoder (AE)-shaped artificial neural network (ANN) model is designed to efficiently characterize those datasets. Then, the indenting load-displacement datasets are extracted into effective physically meaningful datasets by introducing a data post-processing procedure. The proposed indentation FEM-AE-shaped ANN model demonstrates that a long-range true stress-strain curve can be attained even from a noisy experimental load-displacement dataset.
Abstract
Sub-wavelength diffractive optics, commonly known as meta-optics, present a complex numerical simulation challenge, due to their multi-scale nature. The behavior of constituent ...sub-wavelength scatterers, or meta-atoms, needs to be modeled by full-wave electromagnetic simulations, whereas the whole meta-optical system can be modeled using ray/ Fourier optics. Most simulation techniques for large-scale meta-optics rely on the local phase approximation (LPA), where the coupling between dissimilar meta-atoms is neglected. Here we introduce a physics-informed neural network, coupled with the overlapping boundary method, which can efficiently model the meta-optics while still incorporating all of the coupling between meta-atoms. We demonstrate the efficacy of our technique by designing 1mm aperture cylindrical meta-lenses exhibiting higher efficiency than the ones designed under LPA. We experimentally validated the maximum intensity improvement (up to 53%) of the inverse-designed meta-lens. Our reported method can design large aperture ( ~ 10
4
− 10
5
λ
) meta-optics in a reasonable time (approximately 15 minutes on a graphics processing unit) without relying on the LPA.
A crucial aspect in shielding a variety of advanced electronic devices from electromagnetic detection involves controlling the flow of electromagnetic waves, akin to invisibility cloaks. Decades ago, ...the exploration of transformation optics heralded the dawn of modern invisibility cloaks, which has stimulated immense interest across various physical scenarios. However, most prior research is simplified to low‐dimensional and stationary hidden objects, limiting their practical applicability in a dynamically changing world. This study develops a 3D large‐scale intelligent cloak capable of remaining undetectable even in non‐stationary conditions. By employing thousand‐level reconfigurable full‐polarization metasurfaces, this work has achieved an exceptionally high degree of freedom in sculpting the scattering waves as desired. Serving as the core computational unit, a hybrid inverse design enables the cloaked vehicle to respond in real‐time, with a rapid reaction time of just 70 ms. These experiments integrate the cloaked vehicle with a perception‐decision‐control‐execution system and evaluate its performance under random static positions and dynamic travelling trajectories, achieving a background scattering matching degree of up to 93.3%. These findings establish a general paradigm for the next generation of intelligent meta‐devices in real‐world settings, potentially paving the way for an era of “Electromagnetic Internet of Things.”
The 3D full‐polarization cloaking system is proposed and the in situ dynamic invisibility is realized using a travelling vehicle. The cloaking system integrates with a perception‐decision‐control‐execution operation loop, which mainly contains external sensors, high‐performance metasurfaces, and hybrid inverse optimization strategy. Experiment results verifies its performance which yields a background scattering matching degree of up to 93.3%.
Passive daytime radiative cooling (PDRC) devices have enabled subambient cooling of terrestrial objects without any energy input, offering great potential to future clean energy technology. Among ...various PDRC structures, random dielectric particles in a polymer matrix or paint-like coatings have displayed powerful radiative cooling performances with excellent scalability and easy fabrication. While modeling and analyzing such a system is nontrivial to enhance the cooling effect and engineer the structures to be utilized in various applications, it is essential to understand its complex physical relations and determine the optimal design conditions. In this work, we have thoroughly analyzed the optical properties and radiative cooling performances of PDRC paints composed of two-material particles (SiO2 and Al2O3) using 2D FDTD simulation and investigated the optimal design conditions. Specifically, we have studied the effects of design parameters, such as particle size, size distribution, binder volume ratio, and coating thickness. Subsequently, we have conducted an outdoor cooling measurement of the fabricated PDRC paints to demonstrate their radiative cooling potential and to analyze and understand their performance based on our numerical investigations. The fabricated PDRC paints exhibited high solar reflectance (0.958) and strong long-wave infrared emission (0.937) in the atmospheric transparency window, achieving a maximum temperature drop of 9.1 °C. This comprehensive study provides a detailed characterization of the structure and material parameters of the multimaterial PDRC paint system.
Quantum dots (QDs) are semiconducting nanoparticles that exhibit unique fluorescent characteristics when excited by an ultraviolet light source. Owing to their highly saturated emissions, display ...panels using QDs as pixels have been presented. However, the complications of the nanofabrication procedure limit the industrial application of QDs. This study suggests a method to arrange high-aspect-ratio QD pixels by inducing both Laplace-pressure-driven capillary flow and thermally driven Marangoni flow. The evaporation of colloidal QDs induces a capillary flow that drives the QDs toward the inner tips of V-shaped structures. Additionally, the Marangoni flow arranges the gathered QDs at the tip; thus, they could form a high dune, overcoming the limitations of the existing capillary assembly method using evaporation. Using these phenomena, clover-shaped (assembly of V-shaped edges) templates were made to gather numerous QDs, and the clover with a 30° angle afforded the highest brightness among all the angle structures. Finally, by demonstrating a 100-cm2-sized QD microarray with high uniformity (98.6%), our method shows the feasibility of large-area fabrication, which has extensive application in manufacturing QD displays, anti-counterfeiting labels, and other QD-based optical devices.
Physically Transient Electronic Devices (PiTEDs) are building blocks of biodissolvable diagnostics and therapeutics. We fabricate a PiTED integrated with data storage and brain-inspired computing ...capable of data collection and decision-making in case of an emergency. It is also compatible with the physiological environment of the human body and biologically soluble and degradable after performing the required task. A flexible and transparent biomemristor with Mg/collagen/ITO structure is fabricated using a facile solution-assisted process. The flexible collagen-based biomemristor shows vital characterizations for a reproducible memristor, including extensive data retention and endurance cycles. The fish collagen-based device benefits from its biodegradability due to using dissolvable Mg electrodes and collagen from the fish scale as a naturally abundant protein. The Mg electrodes dissolved with water via hydrolysis after dropping water on the device. The electrolyte thin film is also easily water-soluble. The biomemristor shows a conductance modulation behavior of a biological synapse, including potentiation and depression. We constructed a memristive neuromorphic network to realize pattern recognition with a 92.2% accuracy. This device has potential applications in storing and analyzing top-secret information in defense services and implantable dissolvable medical systems.
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