An official website of the United States government
We present compact integrated speckle spectrometers based on monofractal and multifractal scattering media in a silicon-on-insulator platform. Through both numerical and experimental studies we demonstrate enhanced optical throughput, and hence signal-to-noise ratio, for a number of random structures with tailored multifractal geometries without affecting the spectral decay of the speckle correlation functions. Moreover, we show that the developed multifractal media outperform traditional scattering spectrometers based on uniform random distributions of scattering centers. Our findings establish the potential of low-density random media with multifractal correlations for integrated on-chip applications beyond what is possible with uncorrelated random disorder.
more »
« less
Localization landscape of optical waves in multifractal photonic membranes
In this paper, we investigate the localization properties of optical waves in disordered systems with multifractal scattering potentials. In particular, we apply the localization landscape theory to the classical Helmholtz operator and, without solving the associated eigenproblem, show accurate predictions of localized eigenmodes for one- and two-dimensional multifractal structures. Finally, we design and fabricate nanoperforated photonic membranes in silicon nitride (SiN) and image directly their multifractal modes using leaky-mode spectroscopy in the visible spectral range. The measured data demonstrate optical resonances with multiscale intensity fluctuations in good qualitative agreement with numerical simulations. The proposed approach provides a convenient strategy to design multifractal photonic membranes, enabling rapid exploration of extended scattering structures with tailored disorder for enhanced light-matter interactions.
more »
« less
- Award ID(s):
- 2110215
- PAR ID:
- 10502517
- Publisher / Repository:
- Optical Materials Express
- Date Published:
- Journal Name:
- Optical Materials Express
- Volume:
- 14
- Issue:
- 4
- ISSN:
- 2159-3930
- Page Range / eLocation ID:
- 1008
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Biological photonic structures can precisely control light propagation, scattering, and emission via hierarchical structures and diverse chemistry, enabling biophotonic applications for transparency, camouflaging, protection, mimicking and signaling. Corresponding natural polymers are promising building blocks for constructing synthetic multifunctional photonic structures owing to their renewability, biocompatibility, mechanical robustness, ambient processing conditions, and diverse surface chemistry. In this review, we provide a summary of the light phenomena in biophotonic structures found in nature, the selection of corresponding biopolymers for synthetic photonic structures, the fabrication strategies for flexible photonics, and corresponding emerging photonic-related applications. We introduce various photonic structures, including multi-layered, opal, and chiral structures, as well as photonic networks in contrast to traditionally considered light absorption and structural photonics. Next, we summarize the bottom-up and top-down fabrication approaches and physical properties of organized biopolymers and highlight the advantages of biopolymers as building blocks for realizing unique bioenabled photonic structures. Furthermore, we consider the integration of synthetic optically active nanocomponents into organized hierarchical biopolymer frameworks for added optical functionalities, such as enhanced iridescence and chiral photoluminescence. Finally, we present an outlook on current trends in biophotonic materials design and fabrication, including current issues, critical needs, as well as promising emerging photonic applications.more » « less
-
Abstract Bio‐enabled and bio‐mimetic nanomaterials represent functional materials, which use bio‐derived materials and synthetic components to bring the better of two, natural and synthetic, worlds. Prospective broad applications are flexibility and mechanical strength of lightweight structures, adaptive photonic functions and chiroptical activity, ambient processing and sustainability, and potential scalability along with broad sensing/communication abilities. Here, we summarize recent results on relevant functional photonic materials with responsive behavior under mechanical stresses, magnetic field, and changing chemical environment. We focus on recent achievements and trends in tuning optical materials' properties such as light scattering, absorption and reflection, light emission, structural colors, optical birefringence, linear and circular polarization for prospective applications in biosensing, optical communication, optical encoding, fast actuation, biomedical fields, and tunable optical appearance.more » « less
-
We propose a rigorous approach for the inverse design of functional photonic structures by coupling the adjoint optimization method and the 2D generalized Mie theory (2D-GMT) for the multiple scattering problem of finite-sized arrays of dielectric nanocylinders optimized to display desired functions. We refer to these functional scattering structures as “photonic patches.” We briefly introduce the formalism of 2D-GMT and the critical steps necessary to implement the adjoint optimization algorithm to photonic patches with designed radiation properties. In particular, we showcase several examples of periodic and aperiodic photonic patches with optimal nanocylinder radii and arrangements for radiation shaping, wavefront focusing in the Fresnel zone, and for the enhancement of the local density of states (LDOS) at multiple wavelengths over micron-sized areas. Moreover, we systematically compare the performances of periodic and aperiodic patches with different sizes and find that optimized aperiodic Vogel spiral geometries feature significant advantages in achromatic focusing compared to their periodic counterparts. Our results show that adjoint optimization coupled to 2D-GMT is a robust methodology for the inverse design of compact photonic devices that operate in the multiple scattering regime with optimal desired functionalities. Without the need for spatial meshing, our approach provides efficient solutions at a strongly reduced computational burden compared to standard numerical optimization techniques and suggests compact device geometries for on-chip photonics and metamaterials technologies.more » « less
-
Abstract Machine learning provides a promising platform for both forward modeling and the inverse design of photonic structures. Relying on a data-driven approach, machine learning is especially appealing for situations when it is not feasible to derive an analytical solution for a complex problem. There has been a great amount of recent interest in constructing machine learning models suitable for different electromagnetic problems. In this work, we adapt a region-specified design approach for the inverse design of multilayered nanoparticles. Given the high computational cost of dataset generation for electromagnetic problems, we specifically investigate the case of a small training dataset, enhanced via random region specification in an inverse convolutional neural network. The trained model is used to design nanoparticles with high absorption levels and different ratios of absorption over scattering. The central design wavelength is shifted across 350–700 nm without re-training. We discuss the implications of wavelength, particle size, and the training dataset size on the performance of the model. Our approach may find interesting applications in the design of multilayer nanoparticles for biological, chemical, and optical applications as well as the design of low-scattering absorbers and antennas.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript
- Journal Article:
- https://doi.org/10.1364/OME.520201
