(1) Training datasets for RNNs; intermediate and final results of the inverse design of direct narrow-gap semiconductors for optical applications. (2) Benchmark data: reconstruction benchmark, materials generation benchmark, property optimization benchmark.
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资源简介：
The training data for the general RNN and specialized RNN is in "1_augmentation" folder. The intermediate and final results of the inverse design of direct narrow-gap semiconductors for optical applications are in all other folders. 08/19/2023: Add benchmark data including: (1) Reconstruction benchmark on the filtered MP-21-40 and QMOF-21-40. (2) Materials generation benchmark on SLICES-based unconditional RNN. (3) Property optimization benchmark on SLICES-based conditional RNN.
创建时间：
2023-05-21
