Efficient and wavelength-tunable second-harmonic generation towards the green gap
Data files
May 26, 2025 version files 376.49 MB
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data_green_light_science_advance.zip
376.49 MB
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README.md
2.71 KB
Abstract
Achieving compact and efficient visible laser sources is crucial for a wide range of applications. However traditional semiconductor laser technology faces difficulties in producing high-brightness green light, leaving a “green gap” in wavelength coverage. Second-harmonic generation (SHG) offers a promising alternative by converting near-infrared sources to visible wavelengths with high efficiency and spectral purity. Here, we demonstrate efficient and tunable SHG within the green spectrum using a high-Q Si3N4 microresonator On chip green power as high as 5.3 mW is generated with a conversion efficiency of 141%/W (absolute 7.9%). A space-charge grating induced by the photogalvanic effect realizes reconfigurable grating numbers and flexible wavelength tuning over a range of 2.6 THz. Additionally, grating formation dynamics and competition is observed. These findings underscore the potential of Si3N4 as a robust, integrative platform for on-chip, tunable green light sources.
Dataset DOI: 10.5061/dryad.12jm63z8s
Description of the data and file structure
This is the data for Efficient and wavelength-tunable second-harmonic generation towards the green gap.
the data include the the Fig 1, Fig 2, and Fig3.
Files and variables
File: data_green_light_science_advance.zip
Description
This archive contains all the data and MATLAB scripts needed to reproduce every figure in the paper, including dispersion profiles, quality‐factor (Q) traces, and all other measurement traces.
Files & Usage
- Fig1.m, Fig2.m, Fig3.m
- Each script generates one of the paper’s figures.
- All necessary raw data have been pre-integrated: simply open the script in MATLAB and run each section in order.
- In-script comments explain what each block does and the meaning of each plotted trace.
- Data files (.fig, .mat)
- Collected directly from the Optical Spectrum Analyzer (OSA) or Oscilloscope (OSC).
- Stored in double-precision format.
- No need to manually load variables—each script will automatically import its required .mat/.fig files.
Naming Conventions
- Any variable beginning with Q refers to a quality factor.
- All other variable names are literal descriptions of the quantity they represent (e.g., “dispersion”, “frequency”, “power_trace”, etc.).
In Fig1 Folder:
Fig1.m: used to plot the each figure in paper Figure 1.
Q1064.fig：for Fig1.D 1064 Q
Q_0.1_5.fig：for Fig1.D 532 Q
chip4_q_distribution.fig : for Fig1.C dispersion 1064
Q_select_3.mat : for Fig1.E plot disp 532
trans_30.7C_YDFA50mW.mat : for Fig1.F plot trans
In Fig2 Folder:
Fig2.m: used to plot the each figure in paper Figure 2.
sweep249.mat & sweep234.mat & sweep223.mat : for Fig2.C fine tuning
tuning_all.mat : for Fig2.B coarse tune
In Fig3 Folder:
Fig3.m: used to plot the each figure in paper Figure 3.
43.3C_18_200-4000mVpp_triangle_10s.mat : for plotting Fig3.D
W0004.CSV : for Fig3.C OSA 1065
W0000.CSV : for Fig3.C OSA 1064
baseline_201.mat & wave_select_baseline201.mat & trans_wave.mat & trans_1um.mat : for Fig3.A dispersion compare
data_12_short.mat : for Fig3.D
Q_after_opt.mat & Q_after_opt_mod.mat: for plotting Q distribution in Fig 1.
Code/software
all codes for picture plotting are included. Please use MATLAB (suggested using the version later than R2022b )
Access information
Other publicly accessible locations of the data:
- only this
Data was derived from the following sources: