Electro-optic (EO) modulators are crucial components to generate high-speed photonic signals in the modern photonic communication system. Here we study the performance of a hybrid EO modulator employing a Si slot waveguide and a BaTiO3 layer, where the EO effect of BaTiO3 is stronger than that of widely used LiNbO _3 . We demonstrate that an appropriate design for the slot waveguide, the BaTiO _3 layer, and doped Si connectors to metal contacts can achieve a low voltage-length product V_π L of 0.16 V cm, a wide modulation bandwidth of 50 GHz, and a small propagation loss of <1 dB/cm simultaneously. These values indicate efficient use of the proposed modulator in the photonic communication system.

In the study of reading, eye-tracking technology offers unique insights into the time-course of how individuals extract information from text. A significant hurdle in using multi-line paragraph stimuli is the need to align eye gaze position with the correct line. This is made more difficult by positional noise in the eye-tracking data, primarily due to vertical drift, and often necessitates manual intervention. Such manual correction is labor-intensive, subjective, and limits the scalability of research efforts. As a result, automated solutions are desirable, especially those that do not require extensive technical skills and still allow close control over the outcome. To address this, we introduce GazeGenie: a comprehensive software solution designed specifically for researchers in eye-tracking studies on multi-line reading. Accessible via an intuitive web browser-based user interface and easily installed using Docker, GazeGenie streamlines the entire data processing pipeline from parsing fixations from raw data to calculation of word and sentence-based measures based on cleaned and drift-corrected fixations. The software's core features include the recently introduced Dual Input Stream Transformer (DIST) model and various classical algorithms all of which can be combined within a Wisdom of the Crowds (WOC) approach to enhance accuracy in fixation line-assignment. By providing an all-in-one solution for researchers, we hope to make automated fixation alignment more accessible, reducing researchers' reliance on manual intervention in vertical fixation alignment. This should lead to more accurate, efficient, and reproducible analyses of multi-line eye-movement data and pave the way to enabling larger scale studies to be carried out.

Solar Irradiance measurements are critical for a broad range of energy systems, including evaluating performance ratios of photovoltaic systems, as well as forecasting power generation. Using sky images to evaluate solar irradiance, allows for a low-cost, low-maintenance, and easy integration into Internet-of-things network, with minimal data loss. This work demonstrates that a vision transformer-based machine learning model can produce accurate irradiance estimates based on sky-images without any auxiliary data being used. The training data utilizes 17 years of global horizontal, diffuse and direct data, based on a high precision pyranometer and pyrheliometer sun-tracked system; in-conjunction with sky images from a standard lens and a fish-eye camera. The vision transformer-based model learns to attend to relevant features of the sky-images and to produce highly accurate estimates for both global horizontal irradiance (RMSE =52 W/m2) and diffuse irradiance (RMSE = 31 W/m2). This work compares the model’s performance on wide field of view all-sky images as well as images from a standard camera and shows that the vision transformer model works best for all-sky images. For images from a normal camera both vision transformer and convolutional architectures perform similarly with the convolution-based architecture showing an advantage for direct irradiance with an RMSE of 155 W/m2.

We introduce a novel Dual Input Stream Transformer (DIST) for the challenging problem of assigning fixation points from eye-tracking data collected during passage reading to the line of text that the reader was actually focused on. This post-processing step is crucial for analysis of the reading data due to the presence of noise in the form of vertical drift. We evaluate DIST against eleven classical approaches on a comprehensive suite of nine diverse datasets. We demonstrate that combining multiple instances of the DIST model in an ensemble achieves high accuracy across all datasets. Further combining the DIST ensemble with the best classical approach yields an average accuracy of 98.17 %. Our approach presents a significant step towards addressing the bottleneck of manual line assignment in reading research. Through extensive analysis and ablation studies, we identify key factors that contribute to DIST's success, including the incorporation of line overlap features and the use of a second input stream. Via rigorous evaluation, we demonstrate that DIST is robust to various experimental setups, making it a safe first choice for practitioners in the field.

This paper proposes an anticipative transformer-based model for short-term solar irradiance forecasting. Given a sequence of sky images, our proposed vision transformer encodes features of consecutive images, feeding into a transformer decoder to predict irradiance values associated with future unseen sky images. We show that our model effectively learns to attend only to relevant features in images in order to forecast irradiance. Moreover, the proposed anticipative transformer captures long-range dependencies between sky images to achieve a forecasting skill of 21.45 % on a 15 minute ahead prediction for a newly introduced dataset of all-sky images when compared to a smart persistence model.

Quasiperiodicity is a form of spatial order that has been observed in quasicrystalline matter but not light. We construct a quasicrystalline surface out of a light emitting diode. Using a nanoscale waveguide as a microscope (NSOM), we directly image the light field at the surface of the diode. Here we show, using reciprocal space representations of the images, that the light field is quasiperiodic. We explain the structure of the light field with wave superposition. Periodic ordering is limited to at most six-fold symmetry. The light field exhibits 12-fold quasisymmetry, showing order while disproving periodicity. This demonstrates that a new class, consisting of projections from hyperspace, exists in the taxonomy of light ordering.

Solar cells based on GaAs often include a wide-bandgap semiconductor as a window layer to improve surface passivation. Such devices often have poor photon-to-electron conversion efficiency at higher photon energies due to parasitic absorption. In this article, we deposit FAPbBr3 perovskite quantum dots on the AlInP window layer of a GaAs thin-film solar cell to improve the external quantum efficiency (EQE) across its entire absorption range, resulting in an 18% relative enhancement of the short-circuit current density. Luminescent downshifting from the quantum dots to the GaAs device contributes to a large effective enhancement of the internal quantum efficiency (IQE) at shorter wavelengths. Additionally, improved surface passivation of the window layer results in a 14–16% broadband increase of the IQE. These mechanisms combined with increased overall photon collection (antireflective effects) results in a doubling of the EQE in the ultraviolet region of the solar spectrum. Our results show a promising application of perovskite nanocrystals to improve the performance of well-established thin-film solar cell technologies.

Reduction of surface reflection loss is crucial for high efficiency next generation Si solar cells. Surface texturing provides a viable method to reduce loss over the full solar bandwidth. Previous studies have concentrated on simple moth-eye silicon pillar arrays protruding from the surface. Using FDTD simulation methods, we undertake a systematic investigation into performance benefits provided by complex semi-random photonic quasi-crystal surface patterning methodologies whereby arrays of air holes are etched deep into the solar cell surface. In contrast to other studies we carefully investigate the effect of lattice symmetry, systematically comparing performance of simple 6-fold symmetric triangular photonic crystal patterning to 12 fold symmetry photonic quasicrystal patterning and infinitely symmetric 2D Fibonacci patterning. We optimize key geometric parameters such as lattice pitch, hole size and etch depth to maximize optical performance for each lattice type. 12 fold photonic quasi crystal lattice is found to provide best overall anti-reflectance performance providing a solarcorrected average reflectance of 8.3% for a hole depth of 1.5 mu m and 300 nm diameter, in comparison to 36.4% for a bare silicon solar cell surface. Practical feasibility of the optimal designs is demonstrated by fabrication of physical prototypes consisting of arrays of nm scale air-holes etched into the surface of a silicon slab fabricated Using e-beam lithography and ICP/RIE etching. FDTD Simulation methodology is validated by convergence studies as well as comparison to optical measurements on these fabricated devices. Furthermore, in contrast to previous studies we provide an in depth analysis of the physical mechanisms responsible for reduction in surface reflection, determining the parameter space where conventional Gaussian optical processes such as effective refractive index, refraction and Fresnel reflection dominate, vs parameter space where sub wavelength photonic crystal scattering effects play the main role. We finish up with an analysis of electrical performance for the optimal designs to further validate real world performance. Taking electrical performance into account we determine that infinite-symmetry 2D Fibonacci patterning far outperforms lower symmetry 12 fold and triangular arrangement. We believe that this is the first in depth investigation into 2D Fibonacci patterning in silicon solar cells.

We investigate the performances of two slot-waveguide modulator designs using optical and electrical simulations. The proposed designs utilize high confinement Si slot waveguides in combination with LiNbO3 (LN). This allows for efficient modulation due to the strong Pockels effect of the LN and the strong electric field of the slot-waveguide.

In this work, we probe the photodegradative behaviour of CsPbBr3 perovskite nanocrystals under illumination intensities in excess of 1 W/cm(2). In doing so, we uncover optical behaviours unique to this extreme form of degradation - namely a pronounced period of increasing photoluminescent intensity at the outset of degradation along with a red-shifted emission lobe. We also compare the photochemical lifetimes of CsPbBr3 to the relating organic-inorganic hybrid of FAPbBr(3) and show that FAPbBr(3) can withstand such high intensities for approximately ten times longer than CsPbBr3. This marks out FAPbBr(3) as a potential successor to CsPbBr3 in optoelectronic applications.

Perovskite nanocrystals of the form FAPbBr 3 display significant promise in the field of optoelectronics. In particular, these nanocrystals could bridge the `green gap' of LED technology, and also serve to down-convert ultraviolet light for harvesting using silicon-based photovoltaic cells. To remain competitive with traditional devices, optimising the energy transfer between the nanocrystal and the device is crucial, however very little investigation has been performed into this subject. Here, we characterise the energy transfer dynamics of FAPbBr 3 nanocrystals on a silicon substrate using time-resolved photoluminescence. We also use deposited 'spacer layers' to vary the displacement of the nanocrystals from the silicon in order to observe the effect on the energy-transfer dynamics. We find that the overall photoluminescent lifetime increases when reducing the distance between between the nanocrystals and the silicon layer, which runs counter to the expected behaviour. This suggests that the presence of an optically-active substrate suppresses photoluminescent lifetime and, further, suggests that nanocrystal-to-nanocrystal transfer is highly efficient.

Nanostructuring for the purpose of reflectance reduction has been widely investigated for Silicon based solar applications. Bare Silicon surfaces reflect between 50 and 60 % of the incident light and are thus unsuitable for absorbing significant amounts of sunlight. A typical approach to addressing this is to use an anti-reflective coating on top of the Silicon which reduces reflectance via destructive interference. Since this interference is mainly dependent on the thickness of film this type of anti-reflection layer can only be optimized for a certain wavelength and thus is inherently limited. To reduce the reflectance over a broad range of wavelengths a structuring based approach is necessary. A common approach to implementing this is by wet etching the top surface of a crystalline solar cell to create pyramid structures based on the crystalline dependence of the etching process. Since this approach exploits the crystalline structure it is most suited for crystalline Si. Dry etching based nanostructuring can offer a high level of control over the resulting structure with the crystalline dependence being less concern. One approach is to etch cylindrical holes arranged in a periodic fashion into the top surface of the device to create a photonic crystal lattice. Here we present a systematic analysis of a photonic crystal slabs in Silicon and how the geometry affect the reflectance of the device. Lumerical’s FDTD solution is used to vary the pitch, diameter and depth of the cylindrical holes making up the Photonic Crystal structure. The analysis reveals that air fill fraction and hole depth are the most significant determinants of the overall reflectance.

LED surface structuring has been widely used to increase light extraction[1]. Due to the high refractive index of the thick GaN epitaxy layers, most emitted light becomes trapped and reabsorbed by the epitaxial layers. While random structuring can effectively scatter trapped light out of the LED, it gives little control over the resulting beam-shapef[2]. Photonic crystals however provide a means to simultaneously improve light extraction efficiency and control beam directionality. Furthermore, P-side up LEDs normally utilize a transparent top contact layer in order to allow top light emission whilst maintaining good electrical properties. In this paper we investigate a novel photonic crystal LED configuration with a non-transparent metal top contact layer, and cylindrical holes etched through the top contact layer and deep into the underlying epitaxy. In this novel configuration light emission is only possible from the etched holes giving rise to extreme beam steering effects. We utilize broadband spectroscopic reflectometry to experimentally investigate beam shape and optical properties from fabricated devices. We observe a range of achievable beam patterns with extreme deviations from the normal Lambertian. We investigate the effect of square and triangular photonic crystal lattices on beam directionality.

In this paper, we propose a hybrid quantum dot (QD)/solar cell configuration to improve performance of interdigitated back contact (IBC) silicon solar cells, resulting in 39.5% relative boost in the short-circuit current (JSC) through efficient utilisation of resonant energy transfer (RET) and luminescent downshifting (LDS). A uniform layer of CdSe1-xSx/ZnS quantum dots is deposited onto the AlOx surface passivation layer of the IBC solar cell. QD hybridization is found to cause a broadband improvement in the solar cell external quantum efficiency. Enhancement over the QD absorption wavelength range is shown to result from LDS. This is confirmed by significant boosts in the solar cell internal quantum efficiency (IQE) due to the presence of QDs. Enhancement over the red and near-infrared spectral range is shown to result from the anti-reflection properties of the QD layer coating. A study on the effect of QD layer thickness on solar cell performance was performed and an optimised QD layer thickness was determined. Time-resolved photoluminescence (TRPL) spectroscopy was used to investigate the photoluminescence dynamics of the QD layer as a function of AlOx spacer layer thickness. RET can be evoked between the QD and Si layers for very thin AlOx spacer layers, with RET efficiencies of up to 15%. In the conventional LDS architecture, down-converters are deposited on the surface of an optimised anti-reflection layer, providing relatively narrowband enhancement, whereas the QDs in our hybrid architecture provide optical enhancement over the broadband wavelength range, by simultaneously utilising LDS, RET-mediated carrier injection, and antireflection effects, resulting in up to 40% improvement in the power conversion efficiency (PCE). Low-cost synthesis of QDs and simple device integration provide a cost-effective solution for boosting solar cell performance.

CdSxSe1-x/ZnS (core/shell) quantum dots were used in combination with band-pass filters to convert blue light emitted from InGaN/GaN LEDs to different wavelengths. We present results to show this approach is a promising way of achieving tunable color conversion.

We demonstrate spectrally tunable hybrid photonic crystal Quantum Dots (QDs) LEDs. QDs are embedded into photonic crystals of GaN/InGaN LED for efficient color conversion. Color tunable LED has individually addressable LED module.