Machine Learning in Interpolation and Extrapolation for Nanophotonic Inverse Design.

The algorithmic design of nanophotonic structures promises to significantly improve the efficiency of nanophotonic components due to the strong dependence of electromagnetic function on geometry and the unintuitive connection between structure and response. Such approaches, however, can be highly computationally intensive and do not ensure a globally optimal solution. Recent theoretical results suggest that machine learning techniques could address these issues as they are capable of modeling the response of nanophotonic structures at orders of magnitude lower time per result. In this work, we explore the utilization of artificial neural network (ANN) techniques to improve the algorithmic design of simple absorbing nanophotonic structures. We show that different approaches show various aptitudes in interpolation versus extrapolation, as well as peak performances versus consistency. Combining ANNs with classical machine learning techniques can outperform some standard ANN techniques for forward design, both in terms of training speed and accuracy in interpolation, but extrapolative performance can suffer. Networks pretrained on general image classification perform well in predicting optical responses of both interpolative and extrapolative structures, with very little additional training time required. Furthermore, we show that traditional deep neural networks are able to perform significantly better in extrapolation than more complicated architectures using convolutional or autoencoder layers. Finally, we show that such networks are able to perform extrapolation tasks in structure generation to produce structures with spectral responses significantly outside those of the structures on which they are trained.

Integrating Sphere Fourier Microscopy of Highly Directional Emission.

Accurately controlling light emission using nano- and microstructured lenses and antennas is an active field of research. Dielectrics are especially attractive lens materials due to their low optical losses over a broad bandwidth. In this work we measure highly directional light emission from patterned quantum dots (QDs) aligned underneath all-dielectric nanostructured microlenses. The lenses are designed with an evolutionary algorithm and have a theoretical directivity of 160. The fabricated structures demonstrate an experimental full directivity of 61 ± 3, three times higher than what has been estimated before, with a beaming half-angle of 2.6°. This high value compared to previous works is achieved via three mechanisms. First, direct electron beam patterning of QD emitters and alignment markers allowed for more localized emission and better emitter-lens alignment. Second, the lens fabrication was refined to minimize distortions between the designed shape and the final structure. Finally, a new measurement technique was developed that combines integrating sphere microscopy with Fourier microscopy. This enables complete directivity measurements, contrary to other reported values, which are typically only partial directivities or estimates of the full directivity that rely partly on simulations. The experimentally measured values of the complete directivity were higher than predicted by combining simulations with partial directivity measurements. High directivity was obtained from three different materials (cadmium-selenide-based QDs and two lead halide perovskite materials), emitting at 520, 620, and 700 nm, by scaling the lens size according to the emission wavelength.

Nanophotonic color splitters for high-efficiency imaging.

Standard color imaging utilizes absorptive filter arrays to achieve spectral sensitivity. However, this leads to ∼2/3 of incident light being lost to filter absorption. Instead, splitting and redirecting light into spatially separated pixels avoids these absorptive losses. Herein we investigate the inverse design and performance of a new type of splitter which can be printed from a single material directly on top of a sensor surface and are compatible with 800 nm sensor pixels, thereby providing drop-in replacements for color filters. Two-dimensional structures with as few as four layers significantly improve fully color-corrected imaging performance over standard filters, with lower complexity. Being fully dielectric, these splitters additionally allow color-correction to be foregone, increasing the photon transmission efficiency to over 80%, even for sensors with fill-factors of 0.5. Performance further increases with fully 3D structures, improving light sensitivity in color-corrected imaging by a factor of 4 when compared to filters alone.

Broadband highly directive 3D nanophotonic lenses.

Controlling the directivity of emission and absorption at the nanoscale holds great promise for improving the performance of optoelectronic devices. Previously, directive structures have largely been centered in two categories-nanoscale antennas, and classical lenses. Herein, we utilize an evolutionary algorithm to design 3D dielectric nanophotonic lens structures leveraging both the interference-based control of antennas and the broadband operation of lenses. By sculpting the dielectric environment around an emitter, these nanolenses achieve directivities of 101 for point-sources, and 67 for finite-source nanowire emitters; 3× greater than that of a traditional spherical lens with nearly constant performance over a 200 nm wavelength range. The nanolenses are experimentally fabricated on GaAs nanowires, and characterized via photoluminescence Fourier microscopy, with an observed beaming half-angle of 3.5° and a measured directivity of 22. Simulations attribute the main limitation in the obtained directivity to imperfect alignment of the nanolens to the nanowire beneath.

Nanoscale Back Contact Perovskite Solar Cell Design for Improved Tandem Efficiency.

Tandem photovoltaics, combining absorber layers with two distinct band gap energies into a single device, provide a practical solution to reduce thermalization losses in solar energy conversion. Traditionally, tandem devices have been assembled using two-terminal (2-T) or four-terminal (4-T) configurations; the 2-T limits the tandem performance due to the series connection requiring current matching, while the standard 4-T configuration requires at least three transparent electrical contacts, which reduce the total collected power due to unavoidable parasitic absorption. Here, we introduce a novel architecture based on a nanoscale back-contact for a thin-film top cell in a three terminal (3-T) configuration. Using coupled optical-electrical modeling, we optimize this architecture for a planar perovskite-silicon tandem, highlighting the roles of nanoscale contacts to reduce the required perovskite electronic quality. For example, with an 18% planar silicon base cell, the 3-T back contact design can reach a 32.9% tandem efficiency with a 10 µm diffusion length perovskite material. Using the same perovskite quality, the 4-T and 2-T configurations only reach 30.2% and 24.8%, respectively. We also confirm that the same 3-T efficiency advantage applies when using 25% efficient textured silicon base cells, where the tandems reach 35.2% and 32.8% efficiency for the 3-T, and 4-T configurations, respectively. Furthermore, because our design is based on the individual subcells being back-contacted, further improvements can be readily made by optimizing the front surface, which is left free for additional antireflective coating, light trapping, surface passivation, and photoluminescence outcoupling enhancements.

3D multi-energy deconvolution electron microscopy.

Three-dimensional (3D) characterization of nanomaterials is traditionally performed by either cross-sectional milling with a focused ion beam (FIB), or transmission electron microscope tomography. While these techniques can produce high quality reconstructions, they are destructive, or require thin samples, often suspended on support membranes. Here, we demonstrate a complementary technique allowing non-destructive investigation of the 3D structure of samples on bulk substrates. This is performed by imaging backscattered electron (BSE) emission at multiple primary beam energies - as the penetration depth of primary electrons is proportional to the beam energy, depth information can be obtained through variations in the beam acceleration. The detected signal however consists of a mixture of the penetrated layers, meaning the structure's three-dimensional geometry can only be retrieved after deconvolving the BSE emission profile from the observed BSE images. This work demonstrates this novel approach by applying a blind source separation deconvolution algorithm to multi-energy acquired BSE images. The deconvolution can thereby allow a 3D reconstruction to be produced from the acquired images of an arbitrary sample, showing qualitative agreement with the true depth structure, as verified through FIB cross-sectional imaging.

Super-resolution imaging of light-matter interactions near single semiconductor nanowires.

Nanophotonics is becoming invaluable for an expanding range of applications, from controlling the spontaneous emission rate and the directionality of quantum emitters, to reducing material requirements of solar cells by an order of magnitude. These effects are highly dependent on the near field of the nanostructure, which constitutes the evanescent fields from propagating and resonant localized modes. Although the interactions between quantum emitters and nanophotonic structures are increasingly well understood theoretically, directly imaging these interactions experimentally remains challenging. Here we demonstrate a photoactivated localization microscopy-based technique to image emitter-nanostructure interactions. For a 75 nm diameter silicon nanowire, we directly observe a confluence of emission rate enhancement, directivity modification and guided mode excitation, with strong interaction at scales up to 13 times the nanowire diameter. Furthermore, through analytical modelling we distinguish the relative contribution of these effects, as well as their dependence on emitter orientation.

Nanohole Structuring for Improved Performance of Hydrogenated Amorphous Silicon Photovoltaics.

While low hole mobilities limit the current collection and efficiency of hydrogenated amorphous silicon (a-Si:H) photovoltaic devices, attempts to improve mobility of the material directly have stagnated. Herein, we explore a method of utilizing nanostructuring of a-Si:H devices to allow for improved hole collection in thick absorber layers. This is achieved by etching an array of 150 nm diameter holes into intrinsic a-Si:H and then coating the structured material with p-type a-Si:H and a conformal zinc oxide transparent conducting layer. The inclusion of these nanoholes yields relative power conversion efficiency (PCE) increases of ∼45%, from 7.2 to 10.4% PCE for small area devices. Comparisons of optical properties, time-of-flight mobility measurements, and internal quantum efficiency spectra indicate this efficiency is indeed likely occurring from an improved collection pathway provided by the nanostructuring of the devices. Finally, we estimate that through modest optimizations of the design and fabrication, PCEs of beyond 13% should be obtainable for similar devices.

Grain boundary engineering for improved thin silicon photovoltaics.

In photovoltaic devices, the bulk disorder introduced by grain boundaries (GBs) in polycrystalline silicon is generally considered to be detrimental to the physical stability and electronic transport of the bulk material. However, at the extremum of disorder, amorphous silicon is known to have a beneficially increased band gap and enhanced optical absorption. This study is focused on understanding and utilizing the nature of the most commonly encountered Σ3 GBs, in an attempt to balance incorporation of the advantageous properties of amorphous silicon while avoiding the degraded electronic transport of a fully amorphous system. A combination of theoretical methods is employed to understand the impact of ordered Σ3 GBs on the material properties and full-device photovoltaic performance.

Origins of structural hole traps in hydrogenated amorphous silicon.

The inherently disordered nature of hydrogenated amorphous silicon (a-Si:H) obscures the influence of atomic features on the trapping of holes. To address this, we have created a set of over two thousand ab initio structures of a-Si:H and explored the influence of geometric factors on the occurrence of deep hole traps using density-functional theory. Statistical analysis of the relative contribution of various structures to the trap distribution shows that floating bonds and ionization-induced displacements correlate most strongly with hole traps in our ensemble.