Articles
Measurement: Journal of the International Measurement Confederation (02632241)256
Dynamic light scattering (DLS) is a well-established technique for measuring particle sizes in colloidal suspensions, but its accuracy significantly diminishes for microparticles due to the dominance of multiple scattering, especially in high-volume samples. In this study, we introduce a data-driven approach using deep neural networks (DNNs) to enhance the performance of DLS for characterizing micron-sized particles. Silica microparticles of defined size ranges were prepared using a sieve tower and suspended in a water-glycerin mixture to ensure stability during measurements. Raw time-resolved scattering signals were recorded without pre-processing and used to train both classification and regression DNNs. Our results demonstrate high accuracy and repeatability in particle sizing for a wide range of sizes. Furthermore, by employing a moving sampling window across the scattering signal, we analyzed the effect of signal segments on classification performance and found that data corresponding to early-time single-scattering regions are crucial for model accuracy. This method opens new possibilities for in situ and real-time particle sizing in complex industrial environments where traditional DLS fails. © 2025 Elsevier Ltd
Optics and Laser Technology (00303992)181
Given the pivotal role and extensive applications of optical data routing and processing units in optical information technology, we propose a novel mechanism for switching the optical behavior of plasmonic nanoresonators within photonic integrated circuits. The key concept here is to utilize the Pockels effect not to induce a uniform change in the refractive index profile, but rather to establish an exponential refractive index profile across the nanodisk. This behavior resembles what happens in a mirage phenomenon: the light wave is unable to complete its full path around the nanodisk and is instead reflected back. The proposed plasmonic design bypasses low-transmitted signals and converts them into sharp-band reflected signals in response to a designed bias voltage. Moreover, to the best of our knowledge, our design is the first to achieve the EIT phenomenon and slow light effect using a single resonator, a significant simplification over conventional methods that typically necessitate the use of multiple resonators. This is achieved by creating interference between upward and mirage-induced downward waves, resulting in a transparency window and significant dispersion. © 2024 Elsevier Ltd
European Physical Journal Plus (21905444)140(8)
We present a theoretical and experimental study on the generation and propagation of nonuniform vortex beams (NUVBs) with controlled phase jump (PJ) positions. Unlike conventional Laguerre–Gaussian (LG) modes, NUVBs offer additional degrees of freedom by adjusting the azimuthal separation of PJs, enabling the creation of diverse intensity and phase distributions. We derive analytical expressions for the far-field amplitude of NUVBs and validate our findings through numerical simulations and experiments. Furthermore, we generate NUVBs and investigate their superpositions, demonstrating the impact of PJ positioning on intensity patterns. Our results indicate that varying PJ locations produces significantly lower correlation between intensity profiles, facilitating robust optical communication. A total of 256 optimal superposition states were selected to transmit an image, successfully decoded at the receiver without errors. © The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2025.
Applied Optics (21553165)63(21)pp. 5738-5745
In our study, we investigate the resonance modes of plasmonic nanodisks through numerical simulations and theoretical analysis. These tiny structures exhibit fascinating behavior, but relying solely on mode localization is not sufficient to classify their supported modes as plasmonic or dielectric. Our goal is to address this challenge by introducing a robust method for identifying each mode’s true nature. Moreover, through analysis of the field distribution, we introduce, to our knowledge, a novel metric designed for application in inverse problems within the realm of machine learning. This metric serves as a robust tool for optimizing the performance of photonic devices. © 2024 Optica Publishing Group.
Applied Optics (21553165)63(30)pp. 8007-8015
The management of orbital angular momentum (OAM) in frequency conversion processes is essential for numerous applications such as quantum and classical optical communications. This paper presents a wavefront modulation approach for the fundamental beam in second harmonic generation (SHG) to efficiently control the OAM spectrum. We employ an inverse design method to derive the necessary wavefront shape of the fundamental beam for achieving a desired SHG OAM spectrum. Specifically, we introduce an efficient inverse design technique based on physics-guided neural networks (PGNNs) that incorporates the coupled equations governing SHG, aimed at tailoring the OAM spectrum of SHG. Utilizing the proposed PGNN, we design the phase pattern for a spatial light modulator (SLM) to shape the wavefront of the fundamental beam. Furthermore, we present a novel loss function, to our knowledge, that effectively links the OAM of the SHG spectrum and efficiency to the SLM phase pattern and crystal temperature, independent of empirical weight coefficients. The proposed PGNN facilitates the purification of the SHG OAM spectrum, even when the fundamental beam comprises mixed Laguerre–Gaussian (LG) modes. Additionally, we demonstrate the generation of desired SHG spectra using the proposed PGNN framework. This study introduces what we believe to be a groundbreaking inverse design method for developing photonic devices with customized functionalities, addressing challenges associated with traditional data-driven deep learning techniques. © 2024 Optica Publishing Group.
