Illumination Angle Research Articles

Planar chiral metasurfaces with maximal and tunable chiroptical response driven by bound states in the continuum

Optical metasurfaces with high quality factors (Q-factors) of chiral resonances can boost substantially light-matter interaction for various applications of chiral response in ultrathin, active, and nonlinear metadevices. However, current approaches lack the flexibility to enhance and tune the chirality and Q-factor simultaneously. Here, we suggest a design of chiral metasurface supporting bound state in the continuum (BIC) and demonstrate experimentally chiroptical responses with ultra-high Q-factors and near-perfect circular dichroism (CD = 0.93) at optical frequencies. We employ the symmetry-reduced meta-atoms with high birefringence supporting winding elliptical eigenstate polarizations with opposite helicity. It provides a convenient way for achieving the maximal planar chirality tuned by either breaking in-plane structure symmetry or changing illumination angle. Beyond linear CD, we also achieved strong near-field enhancement CD and near-unitary nonlinear CD in the same planar chiral metasurface design with circular eigen-polarization. Sharply resonant chirality realized in planar metasurfaces promises various practical applications including chiral lasers and chiral nonlinear filters.

Exploring seismic detection and resolution thresholds of fault zones and gas seeps in the shallow subsurface using seismic modelling

Seismic resolution and illumination issues are sources of challenges in the detailed imaging and detection of subsurface fault architecture and fluid migration. Improved constraints on resolution can provide input into monitoring requirements and detectability of CO2 leakage, and fault-sealing properties during subsurface visualization of migration pathways. This study explores detection and resolution thresholds via synthetic seismic imaging of a detailed shallow normal fault model with realistic fault architecture including sub-seismic structures of damage zones. The base fault model is built from interpretations of high-resolution P-Cable seismic data and is further developed and conditioned by outcrop-based observations and empirical laws for fracture and deformation band distribution. Damage zones of sandstone layers host deformation bands contrary to shale layers with fractures, while mixed lithologies (shaley sandstone and sandy shale) are subjected to a combination of the two deformation mechanisms. We utilize a 2D point-spread function based convolution seismic modelling to produce the synthetic seismic images. Test scenarios include one baseline fault model without a damage zone (M1), and five more advanced/detailed fault models incorporating features known from outcrops (M2-M6; damage zones, an isolated fracture corridor, and gas seeps (CO2) along damage zones of faults and in the fracture corridor). Furthermore, sensitivity analyses on two selected models test the effect of changing the illumination angle and wavelet. The results show that: (1) faults with damage zones have larger disturbances in seismic signals than faults without damage zones, (2) stronger amplitudes are distinguished for models with CO2-filled fractures, (3) a fracture corridor (5 m at it widest) is clearly visible where it crosses horizons bounding horizontal layers, (4) sensitivity tests show good imaging for illumination ≥45°, which is the average dip of the main fault segment, and (5) learnings from fault modelling offer guidance for seismic monitoring.

Iridescence untwined: honey bees can separate hue variations in space and time

Abstract Iridescence is a phenomenon whereby the hue of a surface changes with viewing or illumination angle. Many animals display iridescence but it currently remains unclear whether relevant observers process iridescent color signals as a complex collection of colors (spatial variation), or as moving patterns of colors and shapes (temporal variation). This is important as animals may use only the spatial or temporal component of the signal, although this possibility has rarely been considered or tested. Here, we investigated whether honey bees could separate the temporal and spatial components of iridescence by training them to discriminate between iridescent disks and photographic images of the iridescent patterns presented by the disks. Both stimuli therefore contained spatial color variation, but the photographic stimuli do not change in hue with varying angle (no temporal variation). We found that individual bee observers could discriminate the variable patterns of iridescent disks from static photographs during unrewarded tests. Control experiments showed that bees reliably discriminated iridescent disks from control silver disks, showing that bees were processing chromatic cues. These results suggest that honey bees could selectively choose to attend to the temporal component of iridescent signals to make accurate decisions.

Transport of intensity diffraction tomography with non-interferometric synthetic aperture for three-dimensional label-free microscopy

We present a new label-free three-dimensional (3D) microscopy technique, termed transport of intensity diffraction tomography with non-interferometric synthetic aperture (TIDT-NSA). Without resorting to interferometric detection, TIDT-NSA retrieves the 3D refractive index (RI) distribution of biological specimens from 3D intensity-only measurements at various illumination angles, allowing incoherent-diffraction-limited quantitative 3D phase-contrast imaging. The unique combination of z-scanning the sample with illumination angle diversity in TIDT-NSA provides strong defocus phase contrast and better optical sectioning capabilities suitable for high-resolution tomography of thick biological samples. Based on an off-the-shelf bright-field microscope with a programmable light-emitting-diode (LED) illumination source, TIDT-NSA achieves an imaging resolution of 206 nm laterally and 520 nm axially with a high-NA oil immersion objective. We validate the 3D RI tomographic imaging performance on various unlabeled fixed and live samples, including human breast cancer cell lines MCF-7, human hepatocyte carcinoma cell lines HepG2, mouse macrophage cell lines RAW 264.7, Caenorhabditis elegans (C. elegans), and live Henrietta Lacks (HeLa) cells. These results establish TIDT-NSA as a new non-interferometric approach to optical diffraction tomography and 3D label-free microscopy, permitting quantitative characterization of cell morphology and time-dependent subcellular changes for widespread biological and medical applications.

Enhancing electromagnetic field gradient in tip-enhanced Raman spectroscopy with a perfect radially polarized beam.

Tip-enhanced Raman spectroscopy (TERS) is a promising label-free super-resolving imaging technique, and the electric field gradient of nanofocusing plays a role in TERS performance. In this paper, we theoretically investigated the enhancement and manipulation of the electric field gradient in a bottom-illumination TERS configuration through a tightly focused perfect radially polarized beam (PRPB). Improvement and manipulation in electric field enhancement and field gradient of the gap-plasmon mode between a plasmonic tip and a virtual surface plasmons (SPs) probe are achieved by adjusting the ring radius of the incident PRPB. Our results demonstrate that the method of optimizing the ring radius of PRPB is to make the illumination angle of incident light as close to the surface plasmon resonance (SPR) excitation angle as possible. Under the excitation of optimal parameters, more than 10 folds improvement of field enhancement and 3 times of field gradient of the gap-plasmon mode is realized compared with that of the conventional focused RPB. By this feat, our results indicate that such a method can further enhance the gradient Raman mode in TERS. We envision that the proposed method, to achieve the dynamic manipulation and enhancement of the nanofocusing field and field gradient, can be more broadly used to control light-matter interactions and extend the reach of tip-enhanced spectroscopy.

Self-sustained rolling of a liquid crystal elastomer rod under inclined light illumination

The self-sustained motion of active materials has the great application values in the fields of soft robots, medical devices, micro nano devices, etc., due to its advantage of directly harvesting energy from the environment. Recent experiment has discovered that a straight liquid crystal elastomer (LCE) rod on a horizontal surface can roll continuously under the vertical light illumination, but the start of rolling requires external disturbance. In this paper, we adopt an inclined light to manipulate the rolling of a straight LCE rod, and theoretically study its rolling behaviors to obtain the illumination angle range for triggering the self-sustained rolling. It is found that the rolling of straight LCE rod can be triggered from rest without external disturbance under the inclined light, which is different from the case of the vertical light illumination. In addition, the rolling velocity of the LCE rod can be easily controlled by the light intensity and illumination angle. These predictions are consistent with the existing experimental results. This study may guide the potential applications of the optically-responsive rod in soft robots, harvesting energy and active machinery.

Investigation of low-confinement surface phonon polariton launching on SiC and SrTiO3 using scanning near-field optical microscopy

Surface phonon polaritons (SPhPs) are important building blocks of nanophotonics, as they enable strong light–matter interaction on the nanoscale, are well-suited for applications in the mid- to far-infrared regime, and can show low losses. SrTiO3 is an interesting material for SPhPs, because it allows for reversible, nonvolatile doping with free charge carriers via oxygen vacancies and for local switching with conductive AFM tips. As a result, SrTiO3 could enable programmable nanophotonics with tunable SPhPs and direct writing of metasurfaces. Surface polariton properties can be determined by mapping their real-space propagation using scattering-type scanning near-field optical microscopy (s-SNOM), which is sensitive to the high local electric fields with nanoscale lateral resolution. Low-confinement (LC) SPhPs with wavevectors close to that of free-space radiation, such as in SrTiO3 and the model polar dielectric SiC, can be difficult to investigate in s-SNOM due to interference effects with the incident illumination and fringe spacings exceeding the scan range or the size of the focus spot. Here, we present s-SNOM measurements of LC-SPhPs on SiC and SrTiO3 launched at gold stripes, retrieve physical quantities such as launching amplitude and phase, and show that they are influenced strongly by gold stripe geometry as well as illumination angle. Using two complementary measurements, we show a convenient way to determine the out-of-plane angle of the s-SNOM setup. Finally, we predict how control over the free charge carrier concentration in SrTiO3 could enable tunable LC-SPhPs, showing the potential of SrTiO3 for programmable nanophotonics.

Fast and stable Fourier ptychographic microscopy based on improved phase recovery strategy.

Fourier ptychographic microscopy (FPM) imaging is a computational imaging technology that can reconstruct wide-field high-resolution (HR) images. It uses a series of low-resolution images captured by a camera under different illumination angles. The images are stitched in the Fourier domain to expand their spectral range. Under high-angle illumination, a dark-field image is noisy with a low signal-to-noise ratio, which significantly reduces the reconstruction quality of FPM. Conventional reconstruction algorithms often have low FPM imaging performance and efficiency due to optimization strategies. In response to these problems, this paper proposes an FPM imaging method based on an improved phase recovery strategy to optimize the alternating iterative algorithm. The technique uses an improved threshold method to reduce noise in the image preprocessing stage to maximize the retention of high-frequency sample information. Moreover, an adaptive control factor is added in the subsequent iterative update process to balance the sample spectrum function. This study verifies the effectiveness of the proposed method on both simulation and experimental images. The results show that the proposed method can effectively suppress image background noise and has a faster convergence speed and higher robustness. In addition, it can be used to reconstruct HR complex amplitude images of objects under wide field-of-view conditions.

Self-regulated non-reciprocal motions in single-material microstructures.

Living cilia stir, sweep and steer via swirling strokes of complex bending and twisting, paired with distinct reverse arcs1,2. Efforts to mimic such dynamics synthetically rely on multimaterial designs but face limits to programming arbitrary motions or diverse behaviours in one structure3-8. Here we show how diverse, complex, non-reciprocal, stroke-like trajectories emerge in a single-material system through self-regulation. When a micropost composed of photoresponsive liquid crystal elastomer with mesogens aligned oblique to the structure axis is exposed to a static light source, dynamic dances evolve as light initiates a travelling order-to-disorder transition front, transiently turning the structure into a complex evolving bimorph that twists and bends via multilevel opto-chemo-mechanical feedback. As captured by our theoretical model, the travelling front continuously reorients the molecular, geometric and illumination axes relative to each other, yielding pathways composed from series of twisting, bending, photophobic and phototropic motions. Guided by the model, herewe choreograph a wide range of trajectories by tailoring parameters, including illumination angle, light intensity, molecular anisotropy, microstructure geometry, temperature and irradiation intervals and duration. We further show how this opto-chemo-mechanical self-regulation serves as a foundation for creating self-organizing deformation patterns in closely spaced microstructure arrays via light-mediated interpost communication, as well as complex motions of jointed microstructures, with broad implications for autonomous multimodal actuators in areas such as soft robotics7,9,10, biomedical devices11,12 and energy transduction materials13, and for fundamental understanding of self-regulated systems14,15.

Tomographic single pixel spatial frequency projection imaging

Conventional methods for three-dimensional (3D) imaging frequently rely on voxel-by-voxel data acquisition, which restricts the range of specimens in which they can be effectively employed. While advances in imaging technology now permit the routine acquisition of 3D images approaching video rates, there are other limitations to image formation in fluorescent microscopy that prohibit studies in large volume samples, highly scattering media, and dynamic environments. Some approaches to 3D image collection circumvent this need by the use of tomographic imaging, where sub-3D projections are collected at varying illumination angles and reconstructed through an inversion algorithm to compute an estimate of the 3D fluorophore distribution. Many such methods rely on spatially coherent light, and thus prohibit the use of fluorescent light. By employing unique spatio-temporally varying illumination patterns in conjunction with computational imaging approaches to image reconstruction, we show that some limitations of laser scanning and wide-field imaging can be overcome. We outline several approaches that utilize tomographic projections with patterned illumination to collect 3D image data. All three dimensional optical imaging exploits projection of the desired 3D information into a lower-dimensional subspace, and then a full three dimensional object is estimated from these data. We discuss a number of such single pixel strategies that project object information onto a zero-dimensional, usually a power, measurement. Further, we outline computational image reconstruction approaches that enhance the object estimates by employing a forward model for the image formation process.

Deep Heating of a Snowpack by Solar Radiation

The observed gradual change in the Earth’s climate most noticeably affects the snow cover and ice sheets in the polar regions, especially during the long polar summer, when solar radiation leads to considerable increase in temperature and partial melting at some distance from the snow or ice surface. This effect, which in the polar regions is more pronounced in the snow cover, deserves serious attention as an important geophysical problem. In this article, for the first time, a theoretical analysis is made of the conditions under which the absorption of directional radiation penetrating a weakly absorbing scattering medium has a maximum at some distance from the illuminated surface. It is shown that the maximum absorption of radiation inside an optically thick medium exists only at illumination angles less than 60° from the normal. An analytical solution was obtained that gives both the magnitude of this maximum absorption and its depth below the illuminated surface. Calculations of solar radiation transfer and heat propagation in the snow layer are also performed. Various experimental data on the ice absorption index in the visible range are taken into account when determining the optical properties of snow. To calculate the transient temperature profile in the snow layer, the heat conduction equation with volumetric absorption of radiation is solved. The boundary conditions take into account the variation of solar irradiation, convective heat transfer, and radiative cooling of snow in the infrared transparency window of the cloudless atmosphere. The calculations show that the radiative cooling should be taken into account even during the polar summer.

Range-Ambiguous Clutter Suppression via FDA MIMO Planar Array Radar with Compressed Sensing

Range-ambiguous clutter is an inevitable issue for airborne forward-looking array radars, especially with the high pulse repetition frequency (PRF). In this paper, a method to suppress the range-ambiguous clutter is proposed in an FDA-MIMO radar with a forward-looking planar array. Compressed sensing FDA technology is used to suppress the range-ambiguous clutter and the forward-looking non-uniformity short-range clutter of radar. Specifically, first, the range ambiguous clutter in different regions is separated by the characteristics of the planar array radar elevation dimension and FDA radar range coupling. Meanwhile, regarding the issue of the FDA radar main lobe moving between coherent pulses, a main lobe correction (MLC) algorithm proposes a solution for the issue, where the FDA radar cannot coherently accumulate signals in the case of non-full angle illumination. Finally, compressed sensing technology and elevation dimension filtering are utilized to suppress the range ambiguous clutter at the receiver, with the approach alleviating the range dependence of clutter in the observation region. A small number of clutter snapshots can obtain an approximately ideal clutter covariance matrix through compressed sensing sparse recovery. The method not only reduces the number of training samples, but also overcomes the problem of clutter non-uniformity in the forward-looking array. Therefore, the clutter suppression problems faced by the high repetition frequency airborne radar forward-looking array structure are solved. At the analysis stage, a comparison among the conventional MIMO and FDA methods is carried on by analyzing the improvement factor (IF) curves. Numerical results verify the effectiveness of the proposed method in range-ambiguous clutter suppression.

3D time-lapse imaging of a mouse embryo using intensity diffraction tomography embedded inside a deep learning framework.

We present a compact 3D diffractive microscope that can be inserted directly in a cell incubator for long-term observation of developing organisms. Our setup is particularly simple and robust, since it does not include any moving parts and is compatible with commercial cell culture containers. It has been designed to image large specimens (>100×100×100µm3) with subcellular resolution. The sample's optical properties [refractive index (RI) and absorption] are reconstructed in 3D from intensity-only images recorded with different illumination angles produced by an LED array. The reconstruction is performed using the beam propagation method embedded inside a deep-learning network where the layers encode the optical properties of the object. This deep neural network is trained for a given multiangle intensity acquisition. After training, the weights of the neural network deliver the 3D distribution of the optical properties of the sample. The effect of spherical aberrations due to the sample holder/air interfaces are taken into account in the forward model. Using this approach, we performed time-lapse 3D imaging of preimplantation mouse embryos over six days. Images of embryos from a single cell (low-scattering regime) to the blastocyst stage (highly scattering regime) were successfully reconstructed. Due to its subcellular resolution, our system can provide quantitative information on the embryos' development and viability. Hence, this technology opens what we believe to be novel opportunities for 3D label-free live-cell imaging of whole embryos or organoids over long observation times.

The Influence of Intelligent Visual Sensing Technology on Online English Teaching in Wireless Network Environment

The study is aimed at improving the quality of online English teaching and enhancing students’ English learning ability and effect. First, the current situation of online English teaching is analyzed. Second, the image recognition algorithm in artificial intelligence (AI) visual sensing technology is used to process the image, and the effects of illumination and image acquisition angle are analyzed. Finally, AI image recognition technology is applied to online English teaching, and its impact on online English teaching is analyzed. The results show that AI visual sensing technology can accurately recognize students’ facial information. Therefore, it can confirm the identity of students, help to count the number of students in online English teaching, and improve students’ autonomous learning ability. In addition, it can also record students’ facial information in real time and analyze students’ emotional changes in the learning process to adjust the teaching process and improve the teaching quality in an all-round way. The results provide technical support for improving online English teaching and contribute to English teaching reform.

Correlation Study of 3D Surface Roughness of Milled Surfaces with Laser Speckle Pattern.

Current studies are focused on the correlation between characteristic features extracted from the laser speckle pattern of machined surfaces and 2D surface roughness parameters. Since milled surfaces are 3D in nature, 3D surface roughness parameters will provide a more accurate representation of the surface. Novelties of this work are: (1) an inexpensive laser pointer, which was used for presentation and was used without any spatial filtering setup for producing the laser speckle pattern; (2) a correlation study, which was conducted between characteristic features extracted from the speckle pattern and 3D surface roughness; and (3) the influence of angle of illumination, lens aperture size (f-number) and shutter speed on the correlation. A highest coefficient of determination of 0.8955 was obtained for the correlation between the gray level co-occurrence matrix descriptor, namely energy, and 3D surface roughness parameter, namely ten-point height S10z, at an illumination angle of 45°, f-number of 16 and shutter speed of 1/100 s.

Randomized multi-angle illumination for improved linear array photoacoustic computed tomography in brain.

One of the key challenges in linear array transducer-based photoacoustic computed tomography is to image structures embedded deep within the biological tissue with limited optical energy. Here, we utilized a manually controlled multi-angle illumination technique to allow the incident photons to interact with the imaging targets for longer periods of time and diffuse further in all directions. We have developed and optimized a compact probe that enables manual changes to the angle of illumination while acquiring photoacoustic signals. The performance has been demonstrated and evaluated by imaging complex blood vessel mimicking phantoms in-vitro and sheep brain samples ex-vivo. For effective image reconstruction from the data acquired by multi-angle illumination method, we have utilized a method based on the extraction of maximum intensity. In both cases, multi-angle illumination has out-performed the conventional fixed angle illumination technique to improve the overall image quality. Specifically, extraction of the imaging targets located at greater axial depths was possible using this multi-angle illumination technique.

Angular‐Encrypted Quad‐Fold Display of Nanoprinting and Meta‐Holography for Optical Information Storage

AbstractThe compactness and programmable versatility make metasurface a promising candidate for optical information encryption and storage. The typical strategy for storage capacity enhancement is essential to expand the metasurface multiplexing channels. Various controllable optical parameters are progressively realized for optical encryption and multiplexing, including wavelength, polarization, orbital angular momentum (OAM), forward/backward illumination, etc. However, as one of the most critical parameters, the incident wavevector (k) direction, namely, the illumination angle, has not been fully explored due to the lack of angular‐encoding capability. Herein, the angular‐encrypted freedom for both amplitude and phase manipulation is theoretically and experimentally achieved by strategically screening the architectural blocks to fulfill the complex‐amplitude requirement. Utilizing the angular‐induced alteration from surface plasmonic resonances (SPRs) and Fabry–Perot (FP) nanocavity resonances, a single angular‐encrypted metasurface has been successfully realized to simultaneously enable quad‐fold independent‐encoding channels, including dual‐holography and dual‐nanoprinting images. Compared to the spatial multiplexing scheme in many previous works, the angular‐encrypted strategy drastically boosts the information storage density and capacity. It is believed that the proposed angular‐encryption finds a new path to achieve multiplexing meta‐devices with fully controlled angular‐resolution and promisingly expands the information capacity for optical encryption with a brand‐new degree of freedom.

Robust multi-angle structured illumination lensless microscopy via illumination angle calibration.

Multi-angle structured illumination lensless (MASIL) microscopy enables high-resolution image recovery over a large field of view. Successful image recovery of MASIL microscopy, however, relies on an accurate knowledge of the multi-angle illumination. System misalignments and slight deviations from the true illumination angle may result in image artifacts in reconstruction. Here we report a MASIL microscopy system that is robust against illumination misalignment. To calibrate the illumination angles, we design and use a double-sided mask, which is a glass wafer fabricated with a ring-array pattern on the upper surface and a disk-array pattern on the lower surface. As such, the illumination angles can be decoded from the captured images by estimating the relative displacement of the two patterns. We experimentally demonstrate that this system can achieve successful image recovery without any prior knowledge of the illumination angles. The reported approach provides a simple yet robust resolution for wide-field lensless microscopy. It can solve the LED array misalignment problem and calibrate angle-varied illumination for a variety of applications.

Precision Detection of Dense Plums in Orchards Using the Improved YOLOv4 Model.

The precision detection of dense small targets in orchards is critical for the visual perception of agricultural picking robots. At present, the visual detection algorithms for plums still have a poor recognition effect due to the characteristics of small plum shapes and dense growth. Thus, this paper proposed a lightweight model based on the improved You Only Look Once version 4 (YOLOv4) to detect dense plums in orchards. First, we employed a data augmentation method based on category balance to alleviate the imbalance in the number of plums of different maturity levels and insufficient data quantity. Second, we abandoned Center and Scale Prediction Darknet53 (CSPDarknet53) and chose a lighter MobilenetV3 on selecting backbone feature extraction networks. In the feature fusion stage, we used depthwise separable convolution (DSC) instead of standard convolution to achieve the purpose of reducing model parameters. To solve the insufficient feature extraction problem of dense targets, this model achieved fine-grained detection by introducing a 152 × 152 feature layer. The Focal loss and complete intersection over union (CIOU) loss were joined to balance the contribution of hard-to-classify and easy-to-classify samples to the total loss. Then, the improved model was trained through transfer learning at different stages. Finally, several groups of detection experiments were designed to evaluate the performance of the improved model. The results showed that the improved YOLOv4 model had the best mean average precision (mAP) performance than YOLOv4, YOLOv4-tiny, and MobileNet-Single Shot Multibox Detector (MobileNet-SSD). Compared with some results from the YOLOv4 model, the model size of the improved model is compressed by 77.85%, the parameters are only 17.92% of the original model parameters, and the detection speed is accelerated by 112%. In addition, the influence of the automatic data balance algorithm on the accuracy of the model and the detection effect of the improved model under different illumination angles, different intensity levels, and different types of occlusions were discussed in this paper. It is indicated that the improved detection model has strong robustness and high accuracy under the real natural environment, which can provide data reference for the subsequent orchard yield estimation and engineering applications of robot picking work.

The global thermophysical properties of (433) Eros

We present results from a shape-based, rotationally-resolved thermophysical model of near-Earth asteroid (433) Eros, using reflected and near-IR spectra collected at the NASA Infrared Telescope Facility (IRTF) over 18 nights (25 disk-integrated spectra in total) from 2009 to 2019. The data sample a variety of viewing geometries, illumination angles, and rotational phases and therefore allow us to characterize Eros's surface physical properties in detail, particularly at wavelengths in the thermal near-IR regime (λ > 3.5 μm) that were not measured by the NEAR Shoemaker mission. Eros's shape, spin state, density, albedo, and other physical properties measured by NEAR were incorporated into our model, leaving thermal inertia and surface roughness as free parameters. We find that a thermal inertia range of 100–150 J m−2 K−1 s-1/2 and a roughness crater fraction of 0.3–0.4 with crater opening angle 130° (equivalent adirectional rms slope angle of 32° +/− 4°) fit data from 18 spectra at the 1σ level, but do not fit the remaining 7 spectra. This suggests that Eros's thermal properties vary over its surface, which has important implications for linking remote sensing data to spacecraft measurements of the physical properties of near-Earth asteroids.