Optical Pattern Research Articles

A tactile perception method with flexible grating structural color

Abstract Affordable high-resolution cameras and state-of-the-art computer vision techniques have led to the emergence of various vision-based tactile sensors. However, current vision-based tactile sensors mainly depend on geometric optics or marker tracking for tactile assessments, resulting in limited performance. To solve this dilemma, we introduce optical interference patterns as the visual representation of tactile information for flexible tactile sensors. We propose a novel tactile perception method and its corresponding sensor combining structural colors from flexible blazed gratings with deep learning. The richer structural colors and finer data processing foster the tactile estimation performance. The proposed sensor has an overall normal force magnitude accuracy of 6 mN, a planar resolution of 79 μm, and a contact-depth resolution of 25 μm. This work presents a promising tactile method that combines wave optics, soft materials, and machine learning. It demonstrates well in tactile measurement, and can be expanded into multiple sensing fields.

Light patterning semiconductor nanoparticles by modulating surface charges.

Optical patterning of colloidal particles is a scalable and cost-effective approach for creating multiscale functional structures. Existing methods often use high-intensity light sources and customized optical setups, making them less feasible for large-scale microfabrication processes. Here, we report an optical patterning method for semiconductor nanoparticles by light-triggered modulation of their surface charge. Rather than using light as the primary energy source, this method utilizes UV-induced cleavage of surface ligands to modify surface charges, thereby facilitating the self-assembly of nanoparticles on a charged substrate via electrostatic interactions. By using citrate-treated ZnO nanoparticles, uniform ZnO patterns with variable thicknesses can be achieved. These multilayered ZnO patterns are fabricated into a UV detector with an on/off ratio exceeding 104. Our results demonstrate a simple yet effective way to pattern semiconductor nanoparticles, facilitating the large-scale integration of functional nanomaterials into emerging flexible and robotic microdevices.

Integrated sensor chip of a resonant cavity light emitter and photon detector for wearable optical medicine

This work presents an integrated chip of a resonant cavity light emitter and photon detector (RCLEPD) to address the requirements of wearable optical medical devices for compact size, high efficiency, and interference resistance sensors. The optical radiation pattern and light extraction efficiency of the resonant cavity light emitting diode (RCLED) as well as the optical absorption spectrum of the resonant cavity enhanced photon detector (RCEPD) are theoretically simulated. Additionally, the wavelength selectivity of the RCEPD absorption spectrum is analyzed. Material epitaxial growth of RCLEPD was performed using metal-organic chemical vapor deposition (MOCVD), and an integrated sensing chip with an area of 2 × 2 mm2 was fabricated. Experimental results demonstrate that RCLED achieves a maximum external quantum efficiency of 10.206%, consistent with the simulation results, while maintaining a peak wavelength at 677.5 nm within a current range of 0-20 mA. Furthermore, the RCEPD exhibits a peak response wavelength at 678 nm, matching that of the RCLED. Utilizing RCLEPD as the sensor, photoplethysmography (PPG) signals are collected from the human wrist under different RCLED driving currents resulting in an average period of 977 ms which aligns with a human pulse frequency of 61 beats/min. With further processing techniques applied to PPG signals, RCLEPD is expected to be used as a sensor in wearable blood pressure and glucose monitoring devices.

Formation and evolution of optical wave patterns in dispersion oscillating tapered fiber for dispersion managed applications

Formation and evolution of optical wave patterns in dispersion oscillating tapered fiber for dispersion managed applications

Hydroxypropyl Cellulose-Based Meter-Long Structurally Colored Fibers for Advanced Fabrics.

Structurally colored fibers are attractive alternatives to chemically colored fibers due to their rich optical properties, color stability, and environmental friendliness. However, the fabrication of structurally colored fibers using cost-effective raw materials with the possibility to scale up remains challenging. Here, a simple and scalable approach is developed to fabricate continuous meter-long structurally colored fibers exhibiting brilliant structural colors across the visible spectrum and helix orientation-dependent polarization states. The fibers are fabricated by extrusion of concentrated aqueous solutions of chemically crosslinked hydroxypropyl cellulose (HPC). The wavelengths and polarization states can be tuned by solution concentration, relaxation time, and collector's surface energy. The HPC-based structurally colored fibers display excellent optical stability to mechanical straining, repeated drying/water impregnation, and prolonged heating at 150°C. It is demonstrated that the HPC-based structurally colored fibers can be woven into structurally colored fabrics with wavelength- and polarization-coded optical patterns. The current work presents a strategy to tune the chiral nematic order, which constitutes an important step toward mass production of structurally colored fibers with stable and rich optical properties using easily available raw materials.

Scalable Multistep Imprinting of Multiplexed Optical Anti-counterfeiting Patterns with Hierarchical Structures.

Multiplexed optical techniques with multichannel patterns provide powerful strategies for high-capacity anti-counterfeiting. However, it is still a big challenge to meet the demands of achieving high encryption levels, excellent readability, and simple preparation simultaneously. Herein, we use a multistep imprinting technique, leveraging surface work-hardening to massively produce multiplexed encrypted patterns with hierarchical structures. These patterns with coupled nano- and microstructures can be instantaneously decoded into different pieces of information at different view angles under white light illumination. By incorporating perpendicular nano- and microgratings, we achieve four-channel encoded patterns, enhancing anti-counterfeiting capacity. This versatile method works on various metal/polymer materials, offering high-density information storage, direct visibility, broad material compatibility, and low-cost mass production. Our high-performance anti-counterfeiting patterns show significant potential in real-world applications.

Central tendency and serial dependence in vestibular path integration.

Path integration, the process of updating one's position using successive self-motion signals, has previously been studied using visual distance reproduction tasks in which optic flow patterns provide information about traveled distance. These studies have reported that reproduced distances show two types of systematic biases: central tendency and serial dependence. In the present study, we investigated whether these biases are also present in vestibular path integration. Participants were seated on a linear motion platform and performed a distance reproduction task in total darkness. The platform first passively moved the participant a pre-defined stimulus distance which they then actively reproduced by steering the platform back the same distance. Stimulus distances were sampled from short- and long-distance probability distributions and presented in either a randomized order or in separate blocks to study the effect of presentation context. Similar to the effects observed in visual path integration, we found that reproduced distances showed an overall positive central tendency effect as well as a positive, attractive serial dependence effect. Furthermore, reproduction behavior was affected by presentation context. These results were mostly consistent with predictions of a Bayesian Kalman-filter model, originally proposed for visual path integration.

MicroLEDs for optical neuromorphic computing—application potential and present challenges

Abstract The slow non-radiative surface recombination velocity of gallium nitride (GaN) in combination with its highly efficient radiative recombination makes this material ideally suited for microLEDs with dimensions as small as 1 µm and even below, serving as the fundamental building block of micro-displays. However, due to their superior miniaturization potential and energy efficiency, GaN-based microLEDs have applications that extend well beyond display technology. Their capability to produce optical patterns with high resolution, which can be modulated at extremely high frequencies, makes them suitable for numerous other applications. We suggest exploiting these exciting properties for a new and potentially equally significant application: utilizing microLEDs in optical processing units for artificial intelligence workloads. In neuromorphic computing, relevant aspects of biological neural networks are emulated directly with either electronic circuits or photonic devices, avoiding the shortcomings of conventional digital computer technology for AI workloads, which generally require massively parallel information processing. GaN microLEDs are discussed here as a promising enabling technology for optical neuromorphic processing units. We see great potential to substantially decrease power consumption through massively parallel in-memory processing combined with efficient photon production and detection. A theoretical analysis of scalability and energy efficiency is provided. A macroscopic bench-top optical microLED demonstrator is presented, which experimentally proves the feasibility of our approach. Future potential and challenges associated with miniaturizing and scaling microLED-based optical processing units are discussed. Finally, we summarize the open research questions that require attention before fully functional and miniaturized optical neuromorphic processing units based on GaN microLEDs can be realized.

Scalable Photo-Responsive Physical Unclonable Functions via Particle Kinetics.

The increasing menace of counterfeiting and information theft underscores the urgent need for security platforms compatible with both micro- and nanoelectronics. Existing methods for anticounterfeiting labeling and cryptographic systems rely on unclonable patterns derived from the unpredictable variability of physical phenomena. However, these approaches impose limitations on the scalability of security components. Here we present a scalable platform for photoresponsive physically unclonable functions based on oxide particle kinetics in polymer solutions. The stochastic agglomeration process occurring during the formation of polymer films with dispersed oxide particles yields random patterns, with pixel sizes scalable from micro to nanoscales. We produce mechanically flexible and self-destructible optical unclonable function patterns utilizing oxide aggregates on a polymer film. Moreover, we establish a strategy for generating electrical unclonable patterns on a conducting polymer film. This involves covering the polymer film with an aggregate pattern mask, which serves as an ultraviolet-blocking layer for randomly exposing the film to ultraviolet ozone treatment. These unclonable patterns constitute robust and compact security systems, exhibiting effective resilience against machine-learning attacks (∼50% prediction error for training data sets of 1000). The developed scalable platforms for physically unclonable functions provide a hardware solution for robust cryptographic applications.

Learning to segment self-generated from externally caused optic flow through sensorimotor mismatch circuits

Efficient sensory detection requires the capacity to ignore task-irrelevant information, for example when optic flow patterns created by egomotion need to be disentangled from object perception. To investigate how this is achieved in the visual system, predictive coding with sensorimotor mismatch detection is an attractive starting point. Indeed, experimental evidence for sensorimotor mismatch signals in early visual areas exists, but it is not understood how they are integrated into cortical networks that perform input segmentation and categorization. Our model advances a biologically plausible solution by extending predictive coding models with the ability to distinguish self-generated from externally caused optic flow. We first show that a simple three neuron circuit produces experience-dependent sensorimotor mismatch responses, in agreement with calcium imaging data from mice. This microcircuit is then integrated into a neural network with two generative streams. The motor-to-visual stream consists of parallel microcircuits between motor and visual areas and learns to spatially predict optic flow resulting from self-motion. The second stream bidirectionally connects a motion-selective higher visual area (mHVA) to V1, assigning a crucial role to the abundant feedback connections to V1: the maintenance of a generative model of externally caused optic flow. In the model, area mHVA learns to segment moving objects from the background, and facilitates object categorization. Based on shared neurocomputational principles across species, the model also maps onto primate visual cortex. Our work extends Hebbian predictive coding to sensorimotor settings, in which the agent actively moves - and learns to predict the consequences of its own movements.

Association of Various Optical Coherence Tomographic Patterns of Diabetic Macular Edema With Central Subfield Thickness and Visual Acuity: A Cross-Sectional Observational Study.

Introduction Diabetic macular edema (DME) is the most common and vision-threatening complication in diabetic patients with diabetic retinopathy (DR), especially in those with Type 2 diabetes mellitus. Optical coherence tomography (OCT) is a reliable tool most commonly used for assessing macular morphology and provides quantitative information on the macula. OCT also examines the outer retinal layers, which can predict visual outcomes. Thus, our study aims to identify the association of various OCT-detected DME morphological patterns with central subfield thickness (CST) and visual acuity. Materials and methods This is a cross-sectional observational study of 50 patients with DME detected on OCT who visited the Ophthalmology Department of Saveetha Medical College and Hospitals for a period of six months, from November 2023 to April 2024. A complete ocular examination, including best corrected visual acuity, scored with the logMAR scale, anterior segment examination, and fundus biomicroscopy using 90D and 78D lenses, was performed. Early Treatment of Diabetic Retinopathy Study (ETDRS) grading of DR into mild to very severe non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR) was noted. Spectral-domain OCT was used to diagnose DME. The CST was measured, and DME was classified into four patterns: sponge-like retinal swelling (SLRS), cystoid macular edema (CME), subretinal fluid (SRF), and posterior hyaloid traction (PHT). Results In the present study, males represented 60%, and females represented 40%. The mean age of the patients was 58.07 ± 6.80 years, with a mean duration of diabetes of 11.91 ± 5.14 years. Of the 50 patients with 100 eyes, only 60 eyes showed DME on OCT. CME was the most common morphological pattern (37%), while the least common pattern was PHT (10%). No significant association was found between a specific morphological pattern and control of diabetes. The most common pattern observed was SLRS in moderate NPDR, CME in severe NPDR, SRF in very severe NPDR, and PHT in PDR. Very severe NPDR patients showed all patterns of DME, and the PHT pattern was observed only in very severe NPDR and PDR. The highest mean CST was observed in the very severe NPDR stage, and the least was in the moderate NPDR stage. The mean CST was highest in SRF patterns and lowest in SLRS patterns. The best mean visual acuity was observed in the SLRS pattern, while the worst mean visual acuity was observed in the SRF pattern, followed by the PHT pattern. Conclusion Our study highlights the importance of OCT in patients with diabetes, as OCT patterns of DME are critical for predicting visual outcomes in DR. Severe grades of DR are usually associated with SRF and PHT patterns. Since patients with SRF and PHT patterns have the worst visual outcomes, these patients, upon identification, need to be counseled about their poor visual prognosis. Those with less severe DR should be closely monitored and advised on effective diabetes control to prevent progression and protect their vision.

Optical pattern formation of laser fields in the Rydberg atomic gases

We study the phenomena of long-wave and short-wave modulation instabilities (LMI and SMI) in Rydberg atomic gases within the framework of the nonlocal nonlinear Schrödinger equations in the local and nonlocal regions (characterized by the ratio of beam radius to radius of Rydberg blockade sphere), respectively. We further reveal the rich soliton dynamics arising from interactions of nonlinear waves triggered by LMI. We also show the variety of spatial self-organization pattern formations and their active manipulation due to SMI. Through a synthesis of theoretical analysis and numerical simulations, the self-organized optical structures reported here provide a way for realizing what we believe to be novel optical patterns and solitons based on Rydberg atomic gases.

Direct Synthesis of Perovskite Quantum Dot Photoresist for Direct Photolithography.

Perovskite quantum dots (PQDs) photoresists are promising building blocks for photolithographically patterned devices. However, their complex synthesis and combination processes limit their optical properties and potential patterning applications. Here, we present an exceptionally simple strategy for the synthesis of PQDs photoresist. Unlike traditional approaches that involve centrifugation, separation, and combination processes, our direct synthesis technique using polymerizable acrylic monomer as solvent to fabricate PQDs photoresists without complex post-synthesis process. We demonstrate that the change in solubility of the precursors is the main reason for the formation of PQDs in the polymerizable monomer. By direct photolithography, colorful PQD patterns with high photoluminescence quantum yields and excellent fluorescence uniformity are successfully demonstrated. This work opens a new avenue for the direct synthesis of PQDs photoresist, expanding their applications in various integrated applications, such as photonic, energy harvesting, and optoelectronic devices.

Direct Synthesis of Perovskite Quantum Dot Photoresist for Direct Photolithography

Perovskite quantum dots (PQDs) photoresists are promising building blocks for photolithographically patterned devices. However, their complex synthesis and combination processes limit their optical properties and potential patterning applications. Here, we present an exceptionally simple strategy for the synthesis of PQDs photoresist. Unlike traditional approaches that involve centrifugation, separation, and combination processes, our direct synthesis technique using polymerizable acrylic monomer as solvent to fabricate PQDs photoresists without complex post‐synthesis process. We demonstrate that the change in solubility of the precursors is the main reason for the formation of PQDs in the polymerizable monomer. By direct photolithography, colorful PQD patterns with high photoluminescence quantum yields and excellent fluorescence uniformity are successfully demonstrated. This work opens a new avenue for the direct synthesis of PQDs photoresist, expanding their applications in various integrated applications, such as photonic, energy harvesting, and optoelectronic devices.

Retraction Note: Optical pattern recognition image preprocessing based on hybrid cluster intelligent algorithm

Retraction Note: Optical pattern recognition image preprocessing based on hybrid cluster intelligent algorithm

Bioinspired transparent ultratough birefringent photonic films with engineerable interference colors derived from in-situ synthesis of CaCO3

Chameleons can rapidly modify their coloration by manipulating the arrangement of iridophores encompassing guanine crystals in their dermis, which enables incident light to undergo birefringence. Various biomaterials have been designed to mimic the arrangement of guanine crystals, yet instances of synthesizing bottom-up structures with anisotropy for optical functionality remain rare. In this study, we report a novel two-step gas diffusion method for in-situ synthesis of CaCO3 (Vaterite) within a hydrogel to fabricate a bio-photonic film displaying birefringence interference colors. This strategy enables the successful fabrication of an inorganic–organic photonic film with superior mechanical properties and flexibility, resulting in high transparency, superior toughness, and adjustable optical anisotropy. Through a combination of experiment and simulation results, we elucidated the critical role played by shape factor (distribution) and structural factor (particle size) in producing transmitted interference colors. Finally, the birefringent photonic films prepared using the dot-plate method can function as optical patterns accurately representing the “on”/“off” state within a binary system. This system offers high spatial resolution, excellent repeatability, and precise controllability of optical properties, making it applicable in fields such as information encryption and decrytion. Our study has successfully synthesized photonic material with anisotropic structure though in-situ method while elucidating the underlying mechanism governing their ability to generate transmission interference colors, thus opening up new avenues for transparent flexible polarized optics, imperceptible wearable devices, and advanced information encryption.

Simulations of the optical diffraction patterns produced by the pressure field of a clinical shock wave source

Today, shock waves are used to treat a wide variety of ailments. Consequently, there is a need to develop efficient methodologies for comparing and evaluating the pressure fields generated by different equipment. Hydrophones are commonly utilized for accurate pressure measurements although they can be damaged by pitting due to acoustic cavitation. Furthermore, the range of measurement is limited by the position of the device. Optical methods have also been proposed since the presence of a disturbing device in the wave propagation medium is not necessary, and they provide a broader registering field. Nevertheless, these methods do not provide accurate measurements compared with those obtained with polyvinylidene difluoride or fiber-optic hydrophones. Herein, an optical method for shock wave characterization based on diffraction analysis, that can lead to more precise results, is proposed. The phase fluctuations of a light wave produced when it traverses the shock wave pressure field are calculated. The diffraction patterns produced by this perturbed wave at an observation plane at different propagation distances are presented. Considering the state of the art of high-speed cameras, we conclude that an experimental setup, based on the results reported here, can contribute to the evaluation and comparison of shock wave generators for medical applications.

Research on high-precision angular measurement based on machine learning and optical vortex interference technology

Abstract The paper innovatively constructs a regression prediction model based on the Stacking ensemble learning algorithm by utilizing the distortion degree of vortex optical interference patterns, achieving high-precision measurement of small angles. It constructs a regression prediction model based on the Stacking ensemble learning algorithm. Initially, in the spiral optical conjugate interference system, minute variations in the optical axis yield corresponding interference patterns, within an angle range of 0.0006° to 0.3°. The angle formed between the centroids of the upper two petals in the deformed interference patterns and the center is extracted as a feature for feature extraction. A dataset is established and randomly divided into training, validation, and testing sets in a 6:2:2 ratio. Subsequently, four models—support vector regression, particle swarm optimization back propagation, Gaussian process regression, and the stacking ensemble algorithm—are optimized for hyperparameters, trained, and evaluated based on coefficients of determination, root mean square error, and mean absolute error to compare their predictive performance. Through multiple rounds of training and prediction on randomly partitioned datasets, it is evident that the ensemble model exhibits a reduction in relative error compared to single learners, demonstrating that the Stacking-based ensemble algorithm can combine the strengths of base learners, showcasing superior predictive performance and enhanced stability. Moreover, the Stacking ensemble model achieves a measurement precision of 0.0006°, with a relative error maintained within 0.6%, indicating the feasibility of achieving high-precision measurement of tiny angles in the optical axis using machine learning and spiral optical conjugate interference systems.

Optical solitons and optical patterns controlled by a moiré lattice potential in a Rydberg atomic gas

Optical solitons and optical patterns controlled by a moiré lattice potential in a Rydberg atomic gas

Optical Disc Structures and Diffraction Patterns: Theoretical Foundations and Experimental Applications

Abstract This investigation advances the experimental exploration of optical discs' diffraction phenomena, meticulously constructing optical pathways to ascertain the track pitch within the disc employing both transmission and reflection grating paradigms. Furthermore, this study devises a novel apparatus and methodology for the precise measurement of optical wavelengths, aiming to elucidate the intricate diffraction patterns and the underlying mechanisms of optical discs' structure. This endeavor not only validates the methodological soundness and efficacy of the proposed approach but also pioneers new avenues for research into physics experiments leveraging optical discs. The application of optical discs in educational settings transcends traditional experimental pedagogy, fostering students' capabilities to independently conceptualize experiments and delve into scientific explorations.