Wave Frequency Research Articles

Improving multi-wavelength overlay measurement time by the development of color-mixing light source

This paper introduces an innovative approach to streamline the time-consuming process of multiple-wavelength measurement in semiconductor overlay metrology. To achieve this, a color-mixing light source was developed, which employed light sources of different wavelengths, each modulated with different sine wave frequencies. By aligning these sources and directing them simultaneously onto the test sample, we mixed all wavelength information into a single test signal. Leveraging the known modulation frequencies, we can accurately extract the amplitudes of each wavelength using a three-parameter sine wave fitting method. These amplitudes effectively represent the sought-after signal for each wavelength. A 4-wavelength mixed light source was developed to demonstrate this method's feasibility. Compared with the intensities received independently for each wavelength, the reconstructed amplitude error was below 5 %. Finally, in the test of multiple-wavelength overlay measurement, the overlay difference between this and traditional methods was only 0.078 nm. The experimental results confirm that this method enables a reduction in the measurement time for multiple wavelengths from 0.8 sec to 0.2 sec, i.e., a 75 % reduction).

Self-Adaptive Intelligent Metasurface Cloak System with Integrated Sensing Units.

Metasurfaces, which are ultrathin planar metamaterials arranged in certain global sequences, interact uniquely with the surrounding light field and exhibit unusual effects of light modulation. Many interesting applications have been discovered based on metasurfaces, particularly in invisibility cloaks. However, most invisibility cloaks are limited to working in specific directions. Achieving effectiveness in multiple directions requires the metasurface to be designed with both perception and modulation capabilities. Current multi-directional metasurface cloak systems are implemented with discrete components rather than an integrated sensing component. Here, we propose an intelligent metasurface cloak system that integrates sensing units, resulting in the cloaking effect with the help of a real-time direction sensor and an adaptive feedback control system. A reconfigurable reflective meta-atom based on phase modulation is presented. Sensing units replace parts of the meta-atoms in the designed tunable metasurface, integrating with an FPGA responsible for measuring the direction and frequency of the incident wave, constituting a closed-loop system together with the feedback parts. Experimental results demonstrate that the metasurface cloak system can recognize the different directions of the incoming wave, and can adaptively manipulate the reflected phase of EM waves to conceal objects without any human participation.

Rapid Transport of Energetic Electrons to Low L $L$‐Shells: The Key Role of Electric Fields

AbstractThe dynamics of the outer radiation belt are traditionally associated with wave‐particle resonant interactions, which provide local electron acceleration and losses through very low‐frequency waves, and electron radial transport by ultra‐low frequency waves. However, these processes cannot explain observations of rapid radial transport of energetic electrons (on a time‐scale of a couple of hours), deep into the inner magnetosphere (down to , mapping to magnetic latitude in the ionosphere). This transport is likely associated with strong convection electric fields forming around the plasmapause. To investigate these rapid, low‐latitude electron transport, we combine low‐altitude observations of energetic electron fluxes by the ELFIN CubeSats and DMSP satellites, SuperDARN measurements of ionospheric plasma flows (electric fields), and equatorial measurements of energetic electrons and electric fields by THEMIS. Our findings demonstrate that the rapid filling of the slot region by keV electrons is directly associated with electric field penetration to low latitudes (down to ). The proposed electron transport scenario, the direct penetration of energetic electrons by strong, localized electric fields, underscores the importance of ionosphere‐magnetosphere coupling in radiation belt dynamics.

Influence of Initial Proton Energy on the Nonlinear Interactions Between Ring Current Protons and He+ Band EMIC Waves

AbstractThe energy of ring current protons is believed to influence the pitch angle scattering due to electromagnetic ion cyclotron (EMIC) waves and is typically analyzed using quasi‐linear theory. However, nonlinear behavior becomes significant as the wave amplitude intensifies. In this study, we aim to explore how the nonlinear behavior depends on the initial proton energy under various background plasma density conditions. The frequency of EMIC waves is 0.96ΩHe (where ΩHe is the gyrofrequency of He+ at the equator). It is found that the higher energy protons with nonlinear phase trapping experience more resonances, causing these trapped protons to move away from the loss cone more quickly compared to lower energy protons. However, the proportion of phase‐trapped protons significantly decreases as the initial proton energy increases. This declining trend is more pronounced for a background plasma condition in the plasmapause than within the plasmasphere. The number of phase‐trapped protons goes to zero as initial proton energy increases to above approximately 60 keV. Additionally, nonlinear phase bunching is more pronounced for lower energy protons (e.g., below 60 keV) compared to higher energy protons. As a result, both nonlinear phase trapping and phase bunching contribute to larger standard deviations in the net changes of equatorial pitch angle (Δαeq), suggesting a larger pitch agnel diffusion coefficient compared to the prediction of quasi‐linear theory.

Electron Density Profile Derived From Ionogram Using Ray Tracing Inversion Method

AbstractThe ionosonde is widely used for detecting electron density profiles below the F2 peak altitude. Extracting precise profiles from ionograms is crucial, as it serves as a significant data source for ionospheric studies and applications. In our study, we utilized the ray tracing profile inversion method (RTPI) to derive more realistic electron density profiles from the ionosonde observations. By comparing the electron density profiles inverted by RTPI method with and without geomagnetic field against the profiles observed by Incoherent Scatter Radar (ISR) plasma lines, we validated the high precision of the RTPI with magnetic field effect method. The results showed that the average height difference and average peak height difference between profiles inverted by RTPI and plasma line observations are less than 10 and 5 km, respectively. Additionally, we quantified the errors associated with the geomagnetic field effect. It would cause an ∼8–10 km overestimation in true height and a ∼10%–15% underestimation in electron density if the geomagnetic field effect is not considered. These errors induced by the magnetic field accumulate with the frequency of the radio waves. Moreover, we conducted a comparative analysis of simulated echo traces using profiles with different E‐layer shapes. It was demonstrated that the key parameters of the bottom structure have a significant impact on ionogram retrieval, while the E‐layer shape has negligible influence on inversion. Furthermore, we analyzed echo traces simulated using ray tracing with and without collision. The collision effect has weak effect on the delay of the radio waves.

Urban green space, human heat perception and sleep quality: A repeated cross-sectional study

Urban heat poses significant challenges to public health, as exposure to high temperatures is associated to heat stress, resulting in heat strain, sleep deprivation, and cardiovascular morbidity and mortality. As the frequency of heat waves is increasing due to global warming, urban green spaces are often proposed as a nature-based solution to mitigate urban heat stress. This study investigated the impact of urban green space on perceived heat stress and sleep quality, using questionnaires and detailed land cover data. We surveyed 584 respondents during four heat and four control events in the summers of 2021 and 2022, assessing perceived heat stress, sleep quality, and mental health. Using structural equation models, this study analysed the influence of both tree cover and grass and shrub cover on perceived heat stress and sleep quality, while controlling for risk and vulnerability factors. The outcomes revealed that during heat events, enhanced tree cover was associated with reduced heat stress (B = -0.484, 95% CI [-0.693, -0.275], p = 0.001), while increased grass and shrub cover was associated with both reduced heat stress (B = -0.361 [-0.529, -0.193], p = 0.000) and improved sleep quality (B = -0. 241 [-0.399, -0.083], p = 0.003). Conversely, during control events, stress indicators were more strongly associated with individual vulnerability factors rather than surrounding green space. These results emphasize the importance of combining trees with lower vegetation in urban planning to mitigate heat-related stress and enhance sleep quality, thereby improving overall well-being during heat events.

Fault location method for new distribution networks based on waveform matching of time–frequency travelling waves

AbstractSome existing fault location methods for distribution networks rely too much on the local wave head information of the time or frequency domain signals, making it difficult to adapt to the increasingly complex structure and operating conditions of the distribution network after the new energy access. For improvement, the travelling wave (TW) time and frequency ranges that can effectively avoid waveform distortion caused by new energy access are analysed. The one‐to‐one matching relationship between the TW waveforms in these ranges and the fault positions is revealed. A fault TW time–frequency matrix with specific time and frequency windows is constructed, and a new distribution network fault location method is proposed based on the matching technique of waveform features, which realises the accurate fault location by exploring the proportionality between the cumulative trend of the matrix energy amplitude deviation and the fault point position. Simulation test results show that the proposed method is not affected by the complex structure of distribution networks such as new energy access and overhead‐cable line mixing on fault location and flexibly transforms the fault location problem into a time–frequency TW waveform matching problem, which improves the accuracy and robustness of the fault location for new distribution networks to a degree.

Automatic Extraction of VLF Constant‐Frequency Electromagnetic Wave Frequency Based on an Improved Vgg16‐Unet

AbstractConstant Frequency Electromagnetic Waves (CFEWs) refer to electromagnetic waves with a constant frequency. Man‐made CFEWs are mainly used in wireless communication, scientific research, global navigation and positioning systems, and military radar. CFEWs exhibit horizontal line characteristics higher than the background on spectrograms. In this study, we focus on Very Low Frequency (VLF) waveform data and power spectral data collected by the China Seismo‐Electromagnetic Satellite (CSES) Electromagnetic Field Detector (EFD). We utilize deep learning techniques to construct an improved Vgg16‐Unet model for automatically detecting horizontal lines on time‐frequency spectrogram and extracting their frequencies. First, we transform waveform data into time‐frequency spectrogram with a duration of 2 s using Short‐Time Fourier Transform. Then, we manually label horizontal lines on the time‐frequency spectrogram using the Labelme tool to establish the dataset. Next, we establish and improve the Vgg16‐Unet deep learning model. Finally, we train and test the model using the dataset. Statistical experimental results show that the error rate of line detection is 0, indicating high reliability of the model, with fewer parameters and fast computation speed suitable for practical applications. Not only do we detect lines through the model, but we also obtain their frequencies. Additionally, in batch‐generated power spectrogram of CFEWs, we discover some unstable phenomena such as frequency shifts and fluctuations, which contribute to understanding the propagation mechanism of CFEWs in the ionosphere and improving the accuracy of related systems.

Physical modelling study on wave damping induced by an idealized floating kelp farm

A physical modelling study was carried out to investigate random wave damping promoted by an idealized floating kelp farm. The experimental conditions spanned intermediate water depths and both linear and nonlinear water waves. Unlike previous studies of wave damping promoted by vegetation, the floating kelp farm was placed close to the water surface with a ratio between vegetation height and water depth close to 0.25. The wave transmission coefficient induced by the floating kelp farm ranged between 0.56 and 0.96. This coefficient decreased for longer floating kelp farms and it was a function of the ratio between kelp farm length and incident wavelength and of the relative wave depth. Spectral analysis showed that wave damping was not frequency-dependent for wave frequencies close to the peak frequency. The wave transmission coefficients of a floating kelp farm with about 100 culture lines and with an extension of approximately 200 m were similar to those of submerged detached breakwaters with a relative crest freeboard smaller than -0.4. Furthermore, the bulk drag coefficient of near-surface idealized floating kelp farms can be modelled as a function of the Keulegan-Carpenter number. This study highlights the potential viability of nature-based solutions such as floating kelp farms for coastal protection.

Enhancing the effectiveness of heat adaptation strategies through citizen science-based outdoor thermal comfort

Urbanization and intensifying climate change expose populations in cities to escalating heat stress and associated health risks. Mitigating these challenges require comprehensive assessments that combine quantitative and qualitative data to develop effective heat wave response strategies and policies. Previous research has primarily focused on thermal sensation measured by individual biometrics within specific locations. However, limitations in data collection across large areas often lead to the neglect of the influence of diverse urban environments. This may disregard the importance of regional variations and citizen engagement in formulating effective heat wave mitigation strategies. This study explored the impact of heat wave frequency and intensity across various urban spatial types and assessed thermal sensation vote (TSV) among residents of Suwon City using a citizen science approach. Temperature measurements and subjective heat sensations were collected over a three-year period using homemade temperature sensors. The analysis investigated thermal sensation differences across spatial types—open high rise, open low rise, compact mid-rise, urban park, and lake park—utilizing boxplots, and examined TSV variations by age using the R program localized smoothing methodology. Results indicate significant variations in TSV across different urban areas, particularly when temperatures exceeded 32 °C. The TSV was highest in the lake park areas (average thermal sensation vote +3.5) and was comparatively lower in the open high-rise and open low-rise areas (average thermal sensation vote +2.0). A significant age-related trend was observed, with the highest TSV reported by the 19–30 age group. Heat sensitivity appeared to decrease among participants aged 41 and over. These findings highlight the limitations of traditional top-down heatwave response strategies, which may not adequately account for spatial variations and individual experiences. Conversely, a bottom-up approach that leverages citizen science can inform the development of tailored and proactive strategies that consider a region's specific conditions.

CONCEPTUAL ANALYSIS ON THE IMPACT OF ACOUSTIC LINERS IN FAN FLUTTER

Abstract This work investigates the impact of acoustically treated intakes on fan flutter. The propagation of the fan acoustic perturbations is studied using a simplified model, where the frequency of the waves in the intake is the natural frequency of the fan blade in the stationary frame of reference. The model consists of a constant cross-section annular duct, where the acoustic modes are computed for hard wall and lined wall regions, assuming a uniform axial flow. The interfaces between the lined and hard wall sections are solved by doing mode matching. The acoustic reflections in the zero-thickness intake are computed using the Wiener-Hopf technique following Rienstra's model. Analytical results show that the waves propagating from the fan are reflected and scattered radially at the interfaces between the hard wall and the liner. Furthermore, the liner damps and changes the phase velocity of acoustic modes. Due to the low frequency of the flutter waves, the radial scattering can activate different cut-off modes, which need to be retained in order to make accurate predictions. The likelihood of fan flutter is estimated using the phase of the reflected cut-on waves reaching the fan. This strategy is used to assess the impact of the acoustic liners on the stability of a realistic fan. It is concluded that the impact of the phasing and reflections induced by the acoustic liners is comparable to that of the intake and can alter the flutter characteristics of the fan significantly.

Brain electrical activity in female Major Depressive Disorder patients

Background: Quantitative EEG provides insight to the brain activity associated with depressive illness. Frontal asymmetry and changes of slow wave frequencies brain activity have been found as the characteristic features of Major Depressive Disorder (MDD). Objective: To assess the brain activity by power spectral analysis of EEG in female patients with MDD. Methods: This observational study was carried on 20 female MDD patients (age 20-40 years) enrolled from the Department of Psychiatry, Bangabandhu Sheikh Mujib Medical University, Shahbag, Dhaka. Twenty (20) healthy volunteers of the same age were considered the control group. For the study, EEG was recorded for 3 minutes in eye closed position by EEG data acquisition device, EEG Traveler BrainTech 32+ CMEEG-01, India. Power spectral analysis of EEG data was done by BT40 analysis software. For statistical analysis, the Mann-Whitney U test was done. Results: Significantly higher Absolute power of delta and theta brain wave, and lower alpha and beta brain wave activity was observed in female MDD patients compared to control in all most all electrodes in all cortical regions. Conclusion: MDD patients showed low excitable brain state and characteristic feature of high slow frequency wave and low fast frequency wave in MDD which can be diagnosed by quantitative EEG analysis. J Bangladesh Soc Physiol 2023;18(2): 53-62

Phononic crystal-based acoustic demultiplexer design via bandgap-passband topology optimization

The wave demultiplexer, which selectively transports specific frequencies from incident waves, has garnered considerable interest for its applications across various engineering disciplines. This study introduces a new customizable design method for acoustic demultiplexers based on the topology optimization of phononic crystals (PnCs). To achieve an acoustic demultiplexer capable of filtering multiple frequencies, a topological design model for PnCs that simultaneously considers bandgaps and passbands is proposed. By assembling the optimized PnCs within the structure, the demultiplexer can separate sound waves of different frequencies into distinct output channels. In the optimization model, an objective function based on transmission rates is proposed to determine whether specific frequencies fall within the specified bandgap or passband. To solve this complex topology optimization problem, the Kriging-based material-field series expansion (KG-MFSE) approach is used to describe the material distribution and optimization of PnCs. The designed PnC unit cells can be directly integrated into the demultiplexer without requiring additional space. Based on specified combinations of passbands and bandgaps, different PnCs are designed to realize a programmable acoustic demultiplexer capable of filtering various sound waves. Numerical analyses demonstrate that the constructed acoustic demultiplexer effectively separates the specified frequencies. Finally, experimental validation of the 3D printed acoustic demultiplexer model confirms the effectiveness of the proposed optimization method.

Identification of mineralogical ore varieties using ultrasonic measurement results

Purpose. To improve the measurement and information base of ultrasonic measurements rock characteristics to assess their mineralogical varieties. It is proposed to use a combination of measurement results of the acoustic quality factor of the test sample in relation to longitudinal and transverse ultrasonic waves, as well as the characteristic coefficient based on the dispersion and the average amplitude value of the received signal, for fuzzy identification of mineralogical and technological varieties of iron ore. Methods. As elastic waves propagate through the rock mass, they undergo attenuation due to absorption and dissipation of ultrasonic signal energy. The degree of attenuation, as well as the wave propagation velocity, is dependent on the physical-mechanical and chemical-mineralogical properties of the medium through which they travel. In this paper, we analyze a rock characterized by a complex structure comprising ore inclusions and surrounding matrix, each of which differs in its physical-mechanical and chemical-mineralogical properties. In particular, in iron ore samples, the distribution of mineral grains and aggregates exhibits significant heterogeneity in terms of both amount and size. Findings. An iterative method of fuzzy identification of mineralogical-technological iron ore varieties, based on the analysis of their properties in vector space of features, allows, by minimizing the sums of weighted distances between the analyzed and reference values of ultrasonic measurement results, to attribute them with a certain degree of belonging to the main technological types of ores mined at the deposit, and define them as magnetite quartzite with a confidence probability of 0.93. Originality. As an information base for identification of mineralogical iron ore varieties, the results of measuring the velocity and attenuation of longitudinal and transverse ultrasonic waves of appropriate frequency are used, on the basis of which the acoustic quality factor of the rock sample is calculated, as well as the characteristic parameter S, which is determined by the dispersion and average values of the received ultrasonic signal intensity, which has traveled a certain distance in the studied environment. Practical implications. The results of tests and practical approbation of the method for identifying mineralogical iron ore varieties based on the data of ultrasonic well logging testify to its high efficiency, which allows recommending the developed scientific-technical solutions for wide industrial application at mining enterprises.

Computations of fields induced in biological tissues by electromagnetic (EM) wave in multilayered structure

The assessment of the fields induced in biological tissue by an electromagnetic (EM) wave is a major issue, not only for its relevance in medical research, but also for its implications on the setting of industrial standards. This paper describes the analysis of electromagnetic (EM) absorption properties of biological multilayered structure. The biological structure comprises three different tissues of skin, fat and muscle. A step-by-step approach for the computation of the EM fields within the multilayered structure is presented. The estimated specific absorption rate (SAR) distribution in tissues due to exposure from plane waves of frequencies 433, 900, 1300, 1800, and 2450 MHz, based on an incident power density 4.5 [mW/cm2], are also presented.

On the electromagnetic wave interaction with subluminal, luminal, and superluminal mirrors

As predicted by A. Einstein [Ann. Phys. (Leipzig) 17, 891 (1905)], the electromagnetic wave reflected at a moving mirror is frequency-upshifted and intensified as high as the mirror velocity is close to the speed of light in vacuum. However, at this limit the mirror reflectivity vanishes, because the higher the wave frequency the more transparent matter is. To resolve this paradox, we analyse the electromagnetic wave propagation in medium where the refractive index modulation moves at the speed of light in vacuum. Although the luminal and superluminal modulations are unconditionally transparent for the incident radiation, they both can reflect. We find the new type of the electromagnetic wave reflection with the increasing in time frequency inside the luminal mirror. If the modulation disappears the high frequency radiation is released as a short wavepacket.

A graphics processing unit accelerated sparse direct solver and preconditioner with block low rank compression

We present the GPU implementation efforts and challenges of the sparse solver package STRUMPACK. The code is made publicly available on github with a permissive BSD license. STRUMPACK implements an approximate multifrontal solver, a sparse LU factorization which makes use of compression methods to accelerate time to solution and reduce memory usage. Multiple compression schemes based on rank-structured and hierarchical matrix approximations are supported, including hierarchically semi-separable, hierarchically off-diagonal butterfly, and block low rank. In this paper, we present the GPU implementation of the block low rank (BLR) compression method within a multifrontal solver. Our GPU implementation relies on highly optimized vendor libraries such as cuBLAS and cuSOLVER for NVIDIA GPUs, rocBLAS and rocSOLVER for AMD GPUs and the Intel oneAPI Math Kernel Library (oneMKL) for Intel GPUs. Additionally, we rely on external open source libraries such as SLATE (Software for Linear Algebra Targeting Exascale), MAGMA (Matrix Algebra on GPU and Multi-core Architectures), and KBLAS (KAUST BLAS). SLATE is used as a GPU-capable ScaLAPACK replacement. From MAGMA we use variable sized batched dense linear algebra operations such as GEMM, TRSM and LU with partial pivoting. KBLAS provides efficient (batched) low rank matrix compression for NVIDIA GPUs using an adaptive randomized sampling scheme. The resulting sparse solver and preconditioner runs on NVIDIA, AMD and Intel GPUs. Interfaces are available from PETSc, Trilinos and MFEM, or the solver can be used directly in user code. We report results for a range of benchmark applications, using the Perlmutter system from NERSC, Frontier from ORNL, and Aurora from ALCF. For a high frequency wave equation on a regular mesh, using 32 Perlmutter compute nodes, the factorization phase of the exact GPU solver is about 6.5× faster compared to the CPU-only solver. The BLR-enabled GPU solver is about 13.8× faster than the CPU exact solver. For a collection of SuiteSparse matrices, the STRUMPACK exact factorization on a single GPU is on average 1.9× faster than NVIDIA’s cuDSS solver.

Auditory Cognition

Following vision, audition is often regarded as a secondary sensory system in the study of cognitive science and behavioral neuroscience. Auditory cognition tasks relate to the discernment of finite differences in frequency, duration, or rhythmic pattern. They suggest that there is a wide range of auditory functions required to mediate auditory responses. Auditory perception is the ability to interpret information that is received from the environment, and it is in this interpretation that audible frequency waves through the air or otherwise, follow a series of processes that allow for the acuity of sound. Several mechanisms are employed in the processing of acoustic information to extricate the many sources present and to assess the properties of individual events or sequences of events presenting themselves from a source. From a cognitive level, the sequential relations among events in longer sequences must be advanced to comprehend the nature of actions on objects that are extended in time.

Characterization of Seismic Signal Patterns and Dynamic Pore Pressure Fluctuations Due to Wave-Induced Erosion on Non-Cohesive Slopes

Wave erosion of slopes can easily trigger landslides into marine environments and pose severe threats to both the ecological environment and human activities. Therefore, near-shore slope monitoring becomes crucial for preventing and alerting people to these potential disasters. To achieve a comprehensive understanding, it is imperative to conduct a detailed investigation into the dynamics of wave erosion processes acting on slopes. This research is conducted through flume tests, using a wave maker to create waves of various heights and frequencies to erode the slope models. During the tests, seismic signals, acoustic signals, and pore pressure generated by wave erosion and slope failure are recorded. Seismic and acoustic signals are analyzed, and time-frequency spectra are calculated using the Hilbert–Huang Transform to identify the erosion events and signal frequency ranges. Arias Intensity is used to assess seismic energy and explore the relationship between the amount of erosion and energy. The results show that wave height has a more decisive influence on erosion behavior and retreat than wave frequency. Rapid drawdown may potentially cause the slope to slide during cyclic swash and backwash wave action. As wave erosion changes from swash to impact, there is a significant increase in the spectral magnitude and Power Spectral Density (PSD) of both seismic and acoustic signals. An increase in pore pressure is observed due to the rise in the run-up height of waves. The amplitude of pore pressure will increase as the slope undergoes further erosion. Understanding the results of this study can aid in predicting erosion and in planning effective management strategies for slopes subject to wave action.

Fluid-Infiltrated Metalens-Driven Reconfigurable Intelligent Surfaces for Optical Wireless Communications.

A reconfigurable intelligent surface (RIS), a leading-edge technology, represents a new paradigm for adaptive control of electromagnetic waves between a source and a user. While RIS technology has proven effective in manipulating radio frequency waves using passive elements such as diodes and MEMS, its application in the optical domain is challenging. The main difficulty lies in meeting key performance indicators, with the most critical being accurate and self-adjusting positioning. This work presents an alternative RIS design methodology driven by an all-silicon structure and fluid infiltration, to achieve real-time control of focal length toward a designated user, thereby enabling secure data transmission. To validate the concept, both numerical simulations and experimental investigations of the RIS design methodology are conducted to demonstrate the performance of fluid-infiltrated metalens-driven RIS for this application. When combined with different fluids, the resulting ultra-compact RIS exhibits exceptional varifocal abilities, ranging from 0.4 to 0.5 mm, thereby confirming the adaptive tuning capabilities of the design. This may significantly enhance the modulation of optical waves and promote the development of RIS-based applications in wireless communications and secure data-transmission integrated photonic devices.