Contents of the dataset:

Fig 3a-e.zip: Zip file containing a raw hyperspectral photoluminescence (PL) 3D cube of a self-assembled CsPbBr3 perovskite nanoplatelet film in Hierarchical Data Format (HDF5). Image pixel size is 66 nm. The wavelength range is 420-550 nm with a step size of 2 nm. The sample was unencapsulated and measured in air under a 405 nm continuous-wave (CW) laser with an excitation intensity of 100 mW/cm2.

SourceData_Fig1.xlsx: Non-blind denoising results on a 3D airborne hyperspectral remote sensing image of the Washington DC Mall (public dataset link: https://engineering.purdue.edu/~biehl/MultiSpec/hyperspectral.html).

SourceData_Fig2.xlsx: Blind denoising results on a 3D hyperspectral microscopy image of organic mCBP-doped 4CzIPN films.

SourceData_Fig3.xlsx: 1) Statistics on signal-to-noise ratio and PL peak prediction for PL mapping of self-assembled CsPbBr3 perovskite nanoplatelet film from 440 to 540 nm (dataset in Fig 3a-e.zip). 2) Raw PL spectrum over time of a thermally evaporated wide-gap FA0.7Cs0.3Pb(I0.6Br0.4)3 perovskite film for 20 min of laser exposure. The data was collected from a sub-micron region (330 x 330 nm) of an unencapsulated film in ambient condition.

SourceData_Fig4.xlsx: 1) Raw electroluminescence (EL) spectrum over time on mixed Br/Cl blue-emitting perovskite LEDs at a bias voltage of 6 V. 2) Statistics of local-EL peak over time on 14,044 local points (330 x 330 nm spatially resolved).

SourceData_ExData_Fig2.xlsx: Raw activation data from the first 32 channels of the first batch-normalization layer output of PA-Net and PA-CNN using noisy image inputs of various noise levels.

SourceData_ExData_Fig4.xlsx: Statistics of 119,931 local-PL peak predictions of CsPbBr3 perovskite nanoplatelet film (dataset in Fig 3a-e.zip).

SourceData_ExData_Fig5.xlsx: 1) Raw local-PL data of Cs0.05FA0.78MA0.17Pb(I0.83Br0.17)3 perovskite film on SnO2/ITO/glass substrates. 2) Statistics on signal-to-noise ratio against wavelength from 700 to 900 nm.

SourceData_ExData_Fig6.xlsx: EL peak prediction results across 500-pixel line scan (330 nm pixel size) of mixed Br/Cl blue-emitting perovskite LEDs at 0 min and 10 min of device operation.

Abstract of paper that the dataset supports:

Emerging functional materials such as halide perovskites are intrinsically unstable, causing long-term instability in optoelectronic devices made from these materials. This leads to difficulty in capturing useful information on device degradation through time-consuming optical characterisation in their operating environments. Despite these challenges, understanding the degradation mechanism is crucial for advancing the technology towards commercialisation. Here we present a self-supervised machine learning model that utilises a multi-channel correlation and blind denoising to recover images without high-quality references, enabling fast and low-dose measurements. We perform operando luminescence mapping of various emerging optoelectronic semiconductors, including organic and halide perovskite photovoltaic and light-emitting devices. By tracking the spatially resolved degradation in electroluminescence of mixed-halide perovskite blue light-emitting diodes, we discovered that lateral ion migration (perpendicular to the external electric field) during device operation triggers the formation of chloride-rich defective regions that emit poorly – a mechanism which would not be resolvable with conventional imaging approaches.