Machine Learning-Assisted Optimization of Femtosecond Laser-Induced Superhydrophobic Microstructure Processing DOI Creative Commons
Lifei Wang,

Yucheng Gu,

Xiaoqing Tian

и другие.

Photonics, Год журнала: 2025, Номер 12(6), С. 530 - 530

Опубликована: Май 23, 2025

Superhydrophobic surfaces have garnered significant attention due to their pivotal roles in various fields. Femtosecond laser technology provides a feasible means for inducing superhydrophobic microstructures on material surfaces. However, the unclear influence mechanisms of process parameters, as well high cost and time-consuming nature experiments, identifying optimal femtosecond processing parameters within space remains challenge. To address this issue, optimization framework that couples machine learning genetic algorithms was proposed successfully applied laser-induced groove structures TC4 alloy Firstly, based 64 sets experimental data, effects power, scanning speed, interval micro-groove wetting properties were discussed detail. Furthermore, by utilizing small sample dataset, employed establish prediction model contact angle, among which support vector regression demonstrated predictive accuracy. Three additional dimensional variables, i.e., number effective pulses, energy deposition rate, roughness, also added original dataset vectors extra dimensions participate guide training process. The further coupled into algorithm achieve quantitative design processing. Compared best hydrophobicity angle designed improved 5.5%. method an ideal solution accurately predicting processes, thereby accelerating development application microstructures.

Язык: Английский

Femtosecond laser writing of telecom-band depressed-cladding waveguides and mode modulation in SK1310 glass DOI

Jiaxiang Zhou,

Weijie Liu,

Weizhao Cheng

и другие.

Optical Materials, Год журнала: 2025, Номер 159, С. 116651 - 116651

Опубликована: Янв. 7, 2025

Язык: Английский

Процитировано

0
Model Design and Study of a U-Channel Photonic Crystal Fib Optic Sensor for Measuring Glucose Concentration in Blood DOI Creative Commons
Lei Zhao, Xiaofeng Sun, Tangyou Sun

и другие.

Sensors, Год журнала: 2025, Номер 25(9), С. 2647 - 2647

Опубликована: Апрель 22, 2025

This research introduces a biosensor utilizing surface plasmon resonance in photonic crystal fiber (PCF) configuration. PCF uses fused silica as the base material, with layer of gold placed over U-channels cross-section to create resonance. There are three different sizes internal optic air hole diameters, larger channel circle below u-channel for formation an energy leakage window. COMSOL software 6.0 assisted us tuning structure and performance study, structural parameters analyzed mainly include diameter, spacing, profundity measurement polished layer, nanoscale size variation metal films. The results simulation study show that optical sensor achieves refractive index (RI) responsiveness across 1.30 1.41 range, RI interval 1.40 1.41, exhibits largest peak shift, its highest sensitivity reaches 10,200 nm/RIU, smallest full width at half (FWHM) corresponds 1.34 value 4.8 nm, figure merit (FOM) 895.83 (1/RIU). software, was used simulate changes blood corresponding glucose concentrations, detection concentrations tested. Then, concentration 75 mg/dL–175 mg/dL is 3750 where maximum 5455 nm/RIU. It shows can be applied field biomedical applications, convenience, fast response, high sensitivity, it has great potential development prospect market.

Язык: Английский

Процитировано

0
Multi-resonance enhanced photothermal synergistic fiber-optic Tamm plasmon polariton tip for high-sensitivity and rapid hydrogen detection DOI Creative Commons
Xinran Wei, Yuzhang Liang, Xuhui Zhang

и другие.

Opto-Electronic Science, Год журнала: 2025, Номер 0(0), С. 240029 - 240029

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Machine Learning-Assisted Optimization of Femtosecond Laser-Induced Superhydrophobic Microstructure Processing DOI Creative Commons
Lifei Wang,

Yucheng Gu,

Xiaoqing Tian

и другие.

Photonics, Год журнала: 2025, Номер 12(6), С. 530 - 530

Опубликована: Май 23, 2025

Superhydrophobic surfaces have garnered significant attention due to their pivotal roles in various fields. Femtosecond laser technology provides a feasible means for inducing superhydrophobic microstructures on material surfaces. However, the unclear influence mechanisms of process parameters, as well high cost and time-consuming nature experiments, identifying optimal femtosecond processing parameters within space remains challenge. To address this issue, optimization framework that couples machine learning genetic algorithms was proposed successfully applied laser-induced groove structures TC4 alloy Firstly, based 64 sets experimental data, effects power, scanning speed, interval micro-groove wetting properties were discussed detail. Furthermore, by utilizing small sample dataset, employed establish prediction model contact angle, among which support vector regression demonstrated predictive accuracy. Three additional dimensional variables, i.e., number effective pulses, energy deposition rate, roughness, also added original dataset vectors extra dimensions participate guide training process. The further coupled into algorithm achieve quantitative design processing. Compared best hydrophobicity angle designed improved 5.5%. method an ideal solution accurately predicting processes, thereby accelerating development application microstructures.

Язык: Английский

Процитировано

0