Optical Path Research Articles

Fast and low energy-consumption integrated Fourier-transform spectrometer based on thin-film lithium niobate

Abstract Integrated miniature spectrometers have impacts in industry, agriculture, and aerospace applications due to their unique advantages in portability and energy consumption. Although existing on-chip spectrometers have achieved breakthroughs in key performance metrics, such as, a high resolution and a large bandwidth, their scanning speed and energy consumption still hinder practical applications of such devices. Here, a stationary Fourier transform spectrometer is introduced based on a Mach–Zehnder interferometer structure on thin-film lithium niobate. Long and low-loss spiral waveguides with electro-optic tuning are adopted as the optical path scanning elements with a half-wave voltage of 0.14 V. A high resolution of 2.1 nm and a spectral recovery with a bandwidth of 100 nm is demonstrated under a high-speed and high-voltage scanning in the range of −100 V to +100 V at up to 100 KHz. A low energy consumption in the μJ scale per scan is also achieved.

Clinical outcomes after topography-guided FS-LASIK for myopia with nonastigmatic eyes

BackgroundTo analyze the clinical outcomes after topography-guided femtosecond laser–assisted laser in situ keratomileusis (FS-LASIK) with Phorcides Analytic Engine (PAE) algorithm or Custom-Q FS-LASIK for myopia with nonastigmatic eyes.MethodsIn this retrospective study, a total of 90 eyes with myopia without manifest astigmatism (82 patients) were included. All surgeries were performed by topography-guided FS-LASIK planned with a PAE algorithm (42 eyes) or Custom-Q system (48 eyes). Refractive, visual outcomes and corneal aberrations were compared between the two groups.ResultsAt 6 months postoperatively, the postoperative uncorrected distance visual acuity (UDVA) was 20/20 or better in 42 eyes (100%) in the PAE compared with 44 eyes (92%) in Custom-Q (P = .120). The postoperative UDVA of 20/16 or better was measured in 92% of eyes in the PAE group and 81% of eyes in the Custom Q group (P = .320). Postoperative corrected distance visual acuity, manifest refractive spherical equivalent and refractive astigmatism were similar between the two groups (P > .05). The postoperative optical path difference (OPD) and Strehl ratio (SR) were significantly better in the PAE group compared with the Custom Q group.ConclusionsTopography-guided FS-LASIK with PAE algorithm or Custom Q demonstrated similar refractive efficacy and predictability. PAE for the patients with zero manifest astigmatism demonstrated better results in correcting corneal aberrations.

Vibration-Induced Sweeping Operation in Fiber Lasers

A new vibration-based mechanism of optical frequency/wavelength sweeping in fiber lasers induced by optical path length modulation of a laser cavity section is proposed. The mechanism is implemented for an erbium-doped fiber ring laser with a saturable absorber. Without the vibrations, the laser generates a single longitudinal mode (SLM) radiation. We show experimentally for the first time that mechanical vibrations of the laser cavity section can lead to mode dynamics in both frequency and time domains. The possibility of obtaining various mode dynamics, such as vibration-induced sweeping in a wavelength range of up to 2.2 nm or SLM generation with periodic mode hopping between two fixed longitudinal modes depending on the pump wavelength, is experimentally shown. In this vibration-based approach, the interval between changes in the laser cavity modes has good stability, because it directly relates to the vibration period.

Fast and direct calibration for high numerical aperture quadriwave lateral shearing interferometry using geometry model with higher-order Taylor expansion

The current research on quadriwave lateral shearing interferometry (LSI) is primarily focused on the measurements of plane wave or quasiplane wave. When directly measuring spherical waves with high numerical apertures (NA>0.35), it will generate additional systematic errors, which affect measurement accuracy. To make the quadriwave LSI applicable to the measurements of a high-NA spherical wave, this paper proposes a fast and direct calibration method by establishing the geometry model of the quadriwave LSI with high-NA spherical wave incidence. The expression for the optical path difference represented systematic errors introduced by high-NA spherical waves in the shearing wavefronts are derived, which utilize a ninth-order Taylor expansion and Zernike polynomials fitting to achieve the high accuracy required by the high-NA spherical wave incidence. Then, the systematic errors are directly calibrated in the shearing wavefronts of four directions. This paper presents the theoretical analysis and verifies the feasibility and reliability of the proposed method through simulations and experiments, achieving a good measurement accuracy.

A self-powered photoelectrochemical and non-enzymatic glucose sensor based on ERGO/ZnONWs/CdS photoanode

We have developed an efficient, self-powered, non-enzymatic photoelectrochemical (PEC) glucose sensor operating in the visible spectrum. The sensor is based on electrochemically reduced graphene oxide (ERGO) and zinc oxide (ZnO) nanowalls (NWs) decorated with cadmium sulfide (CdS) quantum dots (QDs). We used a one-pot electrochemical process to grow vertically aligned ZnONWs on ERGO, followed by using the sequential ionic layer adsorption and reaction (SILAR) technique to decorate the ZnONWs with CdS QDs. The resulting ERGO/ZnONWs/CdS photoelectrode exhibits a three-dimensional hierarchical morphology, providing a large surface area for enhanced surface-substrate interactions and increased optical path length, leading to high absorptivity at visible light. Under one solar light illumination without a bias voltage, the electrode generated a significantly higher photocurrent density (1150 µAcm-2) in the presence of glucose (15.00 mM) than in the absence of glucose (150 µAcm-2). As a PEC glucose sensor, the ERGO/ZnONWs/CdS photoelectrode demonstrated two linear correlations in the glucose concentration range of 0.01–1.00 mM and 1.00–15.00 mM. The sensor has 430.06 and 25.75 µA cm-2mM-1 sensitivities and a low detection limit (1.1 µM). This novel visible light-mediated self-powered electrochemical sensing platform is cost-effective, reproducible, and stable for non-enzymatic glucose detection.

Optical path length difference of ray paths inside a reference sphere: a new approach for determining wavefront aberrations in axially symmetrical systems with an object at infinity

A new, to the best of our knowledge, method is proposed to analyze the wavefront aberrations in an axially symmetrical system with an object at infinity. The study commences by determining the optical path length (OPL) difference between two ray paths from the object to the reference sphere. The proposed method is then used to explore the claim in J. Opt. Soc. Am. A 19, 1187 (2002)JOAOD60740-323210.1364/JOSAA.19.001187 that wavefront aberrations do not depend on the radius of the reference sphere. It is found that this claim does not hold when the image plane is non-Gaussian. The proposed approach is applied to determine the primary wavefront aberrations of an axially symmetrical system with an object at infinity. The numerical values of the primary aberrations (spherical, coma, astigmatism, and field curvature) are in excellent agreement with those determined by Zemax simulations. The superiority of the proposed method over Zemax in determining the distortion aberration is confirmed through raytracing. Overall, the proposed method provides a useful contribution to the development of optical systems for applications requiring high-resolution imaging.

Secure Patient Data Monitoring and Efficient Routing Optimization using a Hyperelliptic Curve Cryptography with Fuzzy-based Priority in WBSN

Aims and Background: Wireless Body Sensor Network (WBSN) technology is one of the major research areas in the medical and entertainment industries. A wireless sensor network (WSN) is a dense sensor network that senses environmental conditions, processes, and outgoing data at the sink node. A WBSN develops patient monitoring systems that provide the flexibility and mobility needed to monitor patient health. In data communications, it is difficult to find flexible optical routing paths, switching capabilities, and packet processing in the composition of optical networks. Information-centric networks (ICNs) are a new network model and are different from information- centric models. The priority of the information-centric model is the communication network. Objectives: In the existing literature, such methods are typically developed using computationally expensive procedures, such as bilinear pairing, elliptic curve operations, etc., which are unsuitable for biomedical devices with limited resources. Using the concept of hyperelliptic curve cryptography (HECC), we propose a new solution: a smart card-based two-factor mutual authentication scheme. In this new scheme, HECC’s finest properties, such as compact parameters and key sizes, are utilized to enhance the real-time performance of an IoT-based TMIS system. Methodology: A fuzzy–based Priority Aware Data Sharing (FPADS) method is introduced to schedule the priority data and monitor the transmission length. The child node adjusts the transmission speed of the cluster head with the help of a fuzzy logic controller (FLC). Results: The proposed model estimated the traffic load of the child node and the priority of the different amounts of data to be transmitted. The principle of scheduling data packets to be developed is based on the precedence of the data with the lowest transmit length in the network. Conclusion: The proposed FPADS performance increases in terms of scheduling time utilisation, traffic distribution, and mean delay. Simulations have been done using NS2, and the outcomes have shown that the proposed methodology is efficient and improves the overall QoS of the system.

A temperature-compensated CO2 detection system based on non-dispersive infrared spectral technology.

The concentration of carbon dioxide (CO2) is an important indicator for coal mine safety. Real-time monitoring of CO2 concentration is of great importance for taking actions in advance to avoid the occurrence of potential accidents. To address the issues of poor portability and high cost associated with existing coal mine CO2 detection equipment, this paper develops a miniaturized CO2 detection system based on non-dispersive infrared (NDIR) technology. This sensor integrates an infrared light source and a dual-channel pyroelectric detector into a reflective gas chamber, thereby achieving an extended optical path and higher system sensitivity within limited space. Meanwhile, the noise interference was greatly mitigated by using hardware and software filtering techniques. Based on principle analysis, the Lambert-Beer law was parametrically corrected, and then, a model relationship between the dual-channel voltage ratio and concentration was established. In addition, temperature compensation for zero and span values was introduced to improve the adaptability of the detection results to temperature changes. Testing results indicate that the developed detection system can realize CO2 measurement in the concentration range of 0 to 50 000 ppm within a temperature range of 0-40 °C, with a maximum detection error of less than 0.12% and a repeatability deviation of less than 1.04%. During a stability test for 12h, the maximum concentration drift is 0.07%, indicating that the developed system meets the requirements for monitoring CO2 safety in coal mines.

Correcting Optical Aberration via Depth-Aware Point Spread Functions.

Optical aberration is a ubiquitous degeneration in realistic lens-based imaging systems. Optical aberrations are caused by the differences in the optical path length when light travels through different regions of the camera lens with different incident angles. The blur and chromatic aberrations manifest significant discrepancies when the optical system changes. This work designs a transferable and effective image simulation system of simple lenses via multi-wavelength, depth-aware, spatially-variant four-dimensional point spread functions (4D-PSFs) estimation by changing a small amount of lens-dependent parameters. The image simulation system can alleviate the overhead of dataset collecting and exploiting the principle of computational imaging for effective optical aberration correction. With the guidance of domain knowledge about the image formation model provided by the 4D-PSFs, we establish a multi-scale optical aberration correction network for degraded image reconstruction, which consists of a scene depth estimation branch and an image restoration branch. Specifically, we propose to predict adaptive filters with the depth-aware PSFs and carry out dynamic convolutions, which facilitate the model's generalization in various scenes. We also employ convolution and self-attention mechanisms for global and local feature extraction and realize a spatially-variant restoration. The multi-scale feature extraction complements the features across different scales and provides fine details and contextual features. Extensive experiments demonstrate that our proposed algorithm performs favorably against state-of-the-art restoration methods.

Biologically inspired shell-hollow particles for designing efficient passive all-sky radiative cooling

Passive radiation cooling (PRC), as the most promising technology to meet future cooling needs, has attracted great interest. However, there are still huge challenges in manufacturing high-efficiency and low-cost radiant coolers suitable for all-day use. Here, we report a secondary micro-nano shell-hollow structure based on blending method, inspired by the African white beetle Goliathus goliatus. Due to the difference in reflectance between the shell and the internal air, compared with the homogeneous particles, the scattered light has a changed optical path at the interface of the core (air) and the shell (SiO2), and most of the light escapes from the particles, showing strong total internal reflection. The design ingeniously deposits the nano-sized shell-hollow structure on the surface of the micron-sized shell-hollow structure, achieving high solar reflectance (95 ​%)and excellent long-wave infrared emissivity (94 ​%). Sub-ambient cooling of 7.8 and 4.7 ​°C can be achieved at night and daytime, respectively. Silica microspheres with shell and hollow structure can be prepared by soft template method, which is mature, reliable, simple and cheap.Our work provides new ideas for the design and manufacture of high-performance Passive all-day radiative cooling (PARC).

Design and optimization of handheld alloy analysis instrument based on microjoule high pulse repetition frequency LIBS.

We briefly describe the design of a handheld metal detection instrument based on microjoule high repetition frequency laser-induced breakdown spectroscopy. The instrument uses a Raspberry Pi as the control core and a laser with a frequency of 10kHz and a single pulse energy of 100 µJ as the excitation source. In addition, a mini-putter is built into the instrument to move the laser, allowing the ablation of the sample surface line area without external auxiliary equipment. The excitation-generated plasma radiation is collected by a simple optical path and transmitted directly to the spectrometer. We also constructed and trained a Backpropagation Artificial Neural Network (BP-ANN) model based on 12 different grades of alloys and transplanted the feedback process of the BP-ANN to the Raspberry Pi, which realized the rapid classification of the 12 alloys with >95% classification accuracy on the handheld instrument.

Image reconstruction from speckle patterns on double diffusers condition by deep learning

Reconstructing images from speckle patterns using deep learning methods is emerging as an effective alternative to traditional approaches. To overcome the potential multiple diffuser distortions occurring between the emission and the detection of the optical path, we establish a 4-f imaging system incorporating dual diffusers, one positioned in front of the image plane and the other after the object plane, to capture plenty of scattered object images. To effectively reconstruct from the experimentally acquired speckle patterns, we add the Triple Attention Module into the UNeXt convolutional network (TAM-UNeXt) and concurrently preprocess the autocorrelation spectrum of the patterns inspired by the angular memory effect theory. We compare the recovery results of the TAM-UNeXt under various conditions, including different grit sizes, numbers, and positions of the diffusers, as well as several optical lens setups, to verify its adaptability under diverse double diffuser conditions.

Multiphysics Coupling Simulation of Off-Axis Integrated Cavity Optical Sensing System

The optical properties of an off-axis integrated cavity system are influenced by both structural deformation and thermal deformation. In this paper, the finite element simulation and analysis software COMSOL multiphysics was used to numerically simulate the optical system. By coupling geometric optics, solid mechanics, and solid heat transfer and conducting parametric temperature scanning, a multiphysics simulation of the off-axis integrated cavity optical sensing system was achieved. The effects of different temperature conditions on the stress field, displacement field, and optical mirrors were analyzed, and changes in optical properties were assessed using ray trajectories and point diagrams. Additionally, optical simulation software was used to simulate and optimize the experimental optical path, obtaining the distribution of light spots on the detector surface. This provides a theoretical basis for the subsequent optimization of the off-axis integrated cavity optical system.

Deep-learning-assisted sidewall profiling white light interferometry system for accurately measuring 3D profiles and surface roughness on the groove sidewalls of precision components.

The accurate measurement of surface three-dimensional (3D) profile and roughness on the groove sidewalls of components is of great significance to diverse fields such as precision manufacturing, machining processes, energy transportation, medical equipment, and semiconductor industry. However, conventional optical measurement methods struggle to measure surface profiles on the sidewall of a small groove. Here, we present a deep-learning-assisted sidewall profiling white light interferometry system, which consists of a microprism-based interferometer, an optical path compensation device, and a convolutional neural network (CNN), for the accurate measurement of surface 3D profile and roughness on the sidewall of a small groove. We have demonstrated that the sidewall profiling white light interferometry system can achieve a measurement accuracy of 2.64 nm for the 3D profile on a groove sidewall. Moreover, we have demonstrated that the CNN-based single-image super-resolution (SISR) technique could improve the measurement accuracy of surface roughness by over 30%. Our system can be utilized in cases where the width of the groove is only 1 mm and beyond, limited only by the size of the microprism and the working distance of the objective used in our system.

Optofluidic phase modulator based on electrowetting liquid lens

In this paper, a liquid optical phase modulator modified from a cylindrical two-liquid electrowetting liquid lens is presented. A movable optical plane is constructed by fixing a transparent sheet between two immiscible liquids. By using the electrowetting effect to flatten the optical plane along the through-light direction, the length ratio of the two liquids in the through-light direction can be fine-tuned to modify the optical path to realize phase modulation. To validate this concept, we experimentally fabricated a prototype phase modulator and tested its phase modulation capability. Experiments show that the phase shift range can be up to 5.82 π and the phase shift accuracy can be up to λ/60, a drive time of 72 ms and a relaxation time of 34 ms within the range of applied voltage 40–80 V DC voltage.

Speckle noise suppression of a reconstructed image in digital holography based on the BM3D improved convolutional neural network

In digital holographic measurement, when light waves pass through inhomogeneous media or surfaces, speckle noise is generated, resulting in random, granular light and dark spots in the hologram, which greatly reduces the image quality. Therefore, in order to improve the image quality of holographic reconstruction, a noise reduction method based on the BM3D improved convolutional neural network (CNN) is proposed in this paper. Firstly, the similarity and important statistical information between blocks can be obtained by using BM3D. Then, the denoising convolutional neural network (DnCNN) is used to learn the relationship between the noise of a large number of samples and the noise image, and further purify the image to retain the details for a better denoising effect. Finally, a reflective off-axis digital holographic optical path system is constructed to collect the holograms of the test samples, and the reconstructed images are obtained by the Fresnel diffraction method to constitute a dataset with the simulated holographic reconstructed images to validate the proposed method in this paper, compared to the other methods, such as DnCNN, convolutional blind denoising network (CBDNet), BM3D, and Wiener filtering. The experimental results of qualitative and quantitative analyses show that the proposed method combines the advantages of traditional algorithms and deep learning, significantly enhances the robustness of the system, optimizes the denoising performance, and preserves the details of the reconstructed image to the greatest extent.

A hybrid learning approach to better classify exhaled breath's infrared spectra: A noninvasive optical diagnosis for socially significant diseases.

Early diagnosis is crucial for effective treatment of socially significant diseases, such as type 1 diabetes mellitus (T1DM), pneumonia, and asthma. This study employs a diagnostic method based on infrared laser spectroscopy of human exhaled breath. The experimental setup comprises a quantum cascade laser, which emits in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3-12.8 μm (780-1890 cm-1), and a Herriott multipass gas cell with a specific optical path length of 76 m. Using this setup, spectra of exhaled breath in the mid-infrared range were obtained from 165 volunteers, including healthy individuals, patients with T1DM, asthma, and pneumonia. The study proposes a hybrid approach for classifying these spectra, utilizing a variational autoencoder for dimensionality reduction and a support vector machine method for classification. The results demonstrate that the proposed hybrid approach outperforms other machine learning method combinations.

Whole-field principal angle and optical path retardation measurements using white light OPD scanning polariscope with first moment algorithm

White-light Optical Path Difference (OPD) scanning polariscope is currently an accepted technique for analyzing photoelastic specimens. While it has proven effective in overcoming limitations associated with phase-stepping and fringe scanning techniques, it is constrained when evaluating optical path retardation smaller than the light source coherence length. To address this limitation, a white-light OPD scanning polariscope, equipped with a first moment algorithm, has been introduced for the comprehensive examination of whole-field principal angle and optical path retardation. This article demonstrates the design and operational principles of the proposed polariscope, details an experimental setup for its deployment, and presents findings from practical applications of this setup. The results confirm the effectiveness and practicality of the proposed polariscope. Furthermore, these results highlight its precision, with standard deviations of 0.176° for principal angle and 6.4 nm for optical path retardation measurements.

Achievement splitting for topological states with pseudospin in phase modulation by using gyromagnetic photonic crystals

As we know, valley-Hall kink states or pseudospin helical edge states are excited by polarized-momentum-locking [left-handed circular polarization (LCP) and right-handed circular polarization (RCP)] because the valley-Hall kink modes or pseudospin polarized modes have intrinsic and local chirality, which is difficult for these states to achieve phase modulation. Here we theoretically design and study a compatible topological photonic system with coexistence of photonic quantum Hall phase and pseudospin Hall phase, which is composed of gyromagnetic photonic crystals with a deformed honeycomb lattice containing six cylinders. A typical kind of hybrid topological waveguide states with pseudospin-characteristic, magnetic field-dependent, and strong robustness against backscattering and perfect electric conductor (PEC) is realized in the present system. Furthermore, we re-design a structure with intersection-liked, achieve splitting for one-way pseudospin quantum Hall edge states by using phase modulation. Robustness of the one-way pseudospin-quantum Hall edge states in splitting has been demonstrated as well. Additionally, PEC inserted in transport channel brings optical path difference in waveguide transmission, which would influence splitting for hybrid topological waveguide states in phase difference modulation. This work not only provides a new way for manipulation (i.e., phase modulation) of hybrid topological waveguide states in compatible topological photonic system from distinct topological classes but also has potential in various applications, such as sensing, signal processing, and on-chip communications.

Preliminary Assessment of On-Orbit Radiometric Calibration Challenges in NOAA-21 VIIRS Reflective Solar Bands (RSBs)

The National Oceanic and Atmospheric Administration (NOAA) 21 Visible Infrared Imaging Radiometer Suite (VIIRS) was successfully launched on 10 November 2022. To ensure the required instrument performance, a series of Post-Launch Tests (PLTs) were performed and analyzed. The primary calibration source for NOAA-21 VIIRS Reflective Solar Bands (RSBs) is the Solar Diffuser (SD), which retains the prelaunch radiometric calibration standard from prelaunch to on-orbit. Upon reaching orbit, the SD undergoes degradation as a result of ultraviolet solar illumination. The rate of SD degradation (called the H-factor) is monitored by a Solar Diffuser Stability Monitor (SDSM). The initial H-factor’s instability was significantly improved by deriving a new sun transmittance function from the yaw maneuver and one-year SDSM data. The F-factors (normally represent the inverse of instrument gain) thus calculated for the Visible/Near-Infrared (VISNIR) bands were proven to be stable throughout the first year of the on-orbit operations. On the other hand, the Shortwave Infrared (SWIR) bands unexpectedly showed fast degradation, which is possibly due to unknown substance accumulation along the optical path. To mitigate these SWIR band gain changes, the NOAA VIIRS Sensor Data Record (SDR) team used an automated calibration software package called RSBautoCal. In March 2024, the second middle-mission outgassing event to reverse SWIR band degradation was shown to be successful and its effects are closely monitored. Finally, the deep convective cloud trends and lunar collection results validated the operational F-factors. This paper summarizes the preliminary on-orbit radiometric calibration updates and performance for the NOAA-21 VIIRS SDR products in the RSB.