Research highlights

Chu et al. (2025c) developed a novel method for laser-induced generation of surface acoustic waves (SAWs) using a beam splitter–based diffractive optical element (DOE). The comb-like design of the DOE was tailored to match the SAW wavelength (or frequency), providing a valuable reference for its application in nondestructive testing (NDT).

Chu et al. (2025b) optimizes the Eddy Dissipation Rate (EDR) retrieval algorithm using a genetic adaptive approach. With the new EDR retrieval algorithm, this study significantly expands the potential of using Doppler lidar wind-field data to estimate EDR. This study examined EDR’s seasonal and diurnal changes with height and ABL stage. The daily evolution of EDR reveals a distinct diurnal pattern in its variation. The seasonal EDR exhibits distinct differences, with higher values in summer and lower values in winter.

Chu et al. (2025a) integrates the XGBoost and cross-validation to analyze the relative importance of ABL driving factors in atmospheric research. This study represents the first application of machine learning to investigate the relative importance of various meteorological parameters on ABL development across different locations and seasons. The findings enhance understanding of boundary layer evolution and contribute to improved boundary layer parameterization.

Chu et al. (2024a) utilized a gold film on the fiber end-face to develop an angle-tuned reflectivity configuration. Building upon this work, Alshammari and Chu et al. (2024b) designed a novel fiber-optic ultrasonic sensor, which was successfully applied in the study titled "Real-time In-situ Phase Sensitivity Calibration of Interferometric Fiber-Optic Ultrasonic Sensors." This article was selected as an Editor’s Pick by Optics Letters, highlighting its significance in the field.

Guo Lin, Zhien Wang and Yufei Chu et al., (2024) used airborne in situ measurements with the wavelet technique to investigate scale-dependent relationships among latent heat flux , vertical velocity variance, and water vapor variance at 100 m altitude over a heterogeneous surface. 

Chu et al. (2022) develops a novel methodology for accurately determining the Planetary Boundary Layer Height (PBLH) and Mixing Layer Height (MLH) to characterize the evolution of the warm-season boundary layer. This new approach demonstrates strong compatibility with the proposed algorithms by integrating measurements of water vapor mixing ratio (WVMR) from Raman lidar (RL) and vertical velocity from Doppler lidar (DL) at the Southern Great Plains (SGP) Atmospheric Observatory. The resulting dataset of reliable PBLH and MLH offers valuable insights for studies on PBL processes, model evaluations, and enhancements in PBL parameterization.