Temporal coupled-mode theory for thermal emission from multiple arbitrarily coupled resonators

Controlling the spectral response of thermal emitters has become increasingly important for a range of energy and sensing applications. Conventional approaches to achieving arbitrary spectrum selectivity in photonic systems have entailed combining multiple resonantly emissive elements together to achieve a range of spectral profiles through numerical optimization, with a universal theoretical framework lacking. Here, we develop a temporal coupled mode theory for thermal emission from multiple, arbtirarily-coupled resonators. We validate our theory against numerical simulations of complex two- and three-dimensional nanophotonic thermal emitters, highlighting the anomalous thermal emission spectra that can emerge when multiple resonators with arbitrary properties couple to each other with varying strengths

DeepAdjoint: An All-in-One Photonic Inverse Design Framework Integrating Data-Driven Machine Learning with Optimization Algorithms

In recent years, hybrid design strategies combining machine learning (ML) with electromagnetic optimization algorithms have emerged as a new paradigm for the inverse design of photonic structures and devices. While a trained, data-driven neural network can rapidly identify solutions near the global optimum with a given dataset's design space, an iterative optimization algorithm can further refine the solution and overcome dataset limitations. Furthermore, such hybrid ML-optimization methodologies can reduce computational costs and expedite the discovery of novel electromagnetic components. However, existing hybrid ML-optimization methods have yet to optimize across both materials and geometries in a single integrated and user-friendly environment. In addition, due to the challenge of acquiring large datasets for ML, as well as the exponential growth of isolated models being trained for photonics design, there is a need to standardize the ML-optimization workflow while making the pre-trained models easily accessible. Motivated by these challenges, here we introduce DeepAdjoint, a general-purpose, open-source, and multi-objective "all-in-one" global photonics inverse design application framework which integrates pre-trained deep generative networks with state-of-the-art electromagnetic optimization algorithms such as the adjoint variables method. DeepAdjoint allows a designer to specify an arbitrary optical design target, then obtain a photonic structure that is robust to fabrication tolerances and possesses the desired optical properties - all within a single user-guided application interface. Our framework thus paves a path towards the systematic unification of ML and optimization algorithms for photonic inverse design

Resonant Anti-Reflection Metasurfaces for Infrared Transmission Optics

A fundamental capability needed for any transmissive optical component is anti-reflection, yet this capability can be challenging to achieve in a cost-effective manner over longer infrared wavelengths. We demonstrate that Mie-resonant photonic structures can enable high transmission through a high-index optical component, allowing it to function effectively over long-wavelength infrared wavelengths. Using silicon as a model system, we demonstrate a resonant metasurface that enables a window optic with transmission up to 40% greater than that of unpatterned Si. Imaging comparisons with unpatterned Si and off-the-shelf germanium optics are shown as well as modulation transfer function measurements, showing excellent performance and suitability for imaging applications. Our results show how resonant photonic structures can be used to improve optical transmission through high-index optical components and highlight their possible use in infrared imaging applications

Sub-ambient radiative cooling under tropical climate using highly reflective polymeric coating

While passive radiative cooling has shown great potential in temperate regions in lowering surface temperatures, its cooling performance under tropical climate that is characterised by high solar irradiance and humidity still lacks exploration. Herein, we adopt a highly reflective polymeric coating with BaSO4 particles dispersed in P(VdF-HFP) matrix for radiative cooling in the tropics. Through the strong Mie scattering of sunlight and intrinsic bond vibration, the substrate-independent average solar reflectance and infrared emittance within the 8–13 μm atmospheric window could reach 97% and 94.2%, respectively. For the first time, surfaces could maintain sub-ambient temperatures under direct exposure to the sky and surroundings even when the solar intensity was 1000 W/m2 and downwelling atmospheric radiation was 480 W/m2, while separately achieving 2 °C below ambient during night-time with an effective cooling power of 54.4 W/m2. With a scalable fabrication-process, our cost-effective single-layer coating can be easily applied to diverse substrates, which is suitable for real-world applications in the tropics.Ministry of Education (MOE)Published versionThis study was funded by the Singapore Ministry of Education through grant no. 2018-T1-001-070