Supersaturation-Dependent Surface Structure Evolution: From Ionic, Molecular to Metallic Micro/Nanocrystals

Deduced from thermodynamics and the Thomson–Gibbs equation that the surface energy of crystal face is in proportion to the supersaturation of crystal growth units during the crystal growth, we propose that the exposed crystal faces can be simply tuned by controlling the supersaturation, and higher supersaturation will result in the formation of crystallites with higher surface-energy faces. We have successfully applied it for the growth of ionic (NaCl), molecular (TBPe), and metallic (Au, Pd) micro/nanocrystals with high-surface-energy faces. The above proposed strategy can be rationally designed to synthesize micro/nanocrystals with specific crystal faces and functionality toward specific applications

Signal2signal: Pushing the Spatiotemporal Resolution to the Limit by Single Chemical Hyperspectral Imaging

There is growing interest in developing a high-performance self-supervised denoising algorithm for real-time chemical hyperspectral imaging. With a good understanding of the working function of the zero-shot Noise2Noise-based denoising algorithm, we developed a self-supervised Signal2Signal (S2S) algorithm for real-time denoising with a single chemical hyperspectral image. Owing to the accurate distinction and capture of the weak signal from the random fluctuating noise, S2S displays excellent denoising performance, even for the hyperspectral image with a spectral signal-to-noise ratio (SNR) as low as 1.12. Under this condition, both the image clarity and the spatial resolution could be significantly improved and present an almost identical pattern with a spectral SNR of 7.87. The feasibility of real-time denoising during imaging was well demonstrated, and S2S was applied to monitor the photoinduced exfoliation of transition metal dichalcogenide, which is hard to accomplish by confocal Raman spectroscopy. In general, the real-time denoising capability of S2S offers an easy way toward in situ/in vivo/operando research with much improved spatial and temporal resolution. S2S is open-source at https://github.com/3331822w/Signal2signal and will be accessible online at https://ramancloud.xmu.edu.cn/tutorial