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.

Noise learning of instruments for high-contrast, high-resolution and fast hyperspectral microscopy and nanoscopy.

The low scattering efficiency of Raman scattering makes it challenging to simultaneously achieve good signal-to-noise ratio (SNR), high imaging speed, and adequate spatial and spectral resolutions. Here, we report a noise learning (NL) approach that estimates the intrinsic noise distribution of each instrument by statistically learning the noise in the pixel-spatial frequency domain. The estimated noise is then removed from the noisy spectra. This enhances the SNR by ca. 10 folds, and suppresses the mean-square error by almost 150 folds. NL allows us to improve the positioning accuracy and spatial resolution and largely eliminates the impact of thermal drift on tip-enhanced Raman spectroscopic nanoimaging. NL is also applicable to enhance SNR in fluorescence and photoluminescence imaging. Our method manages the ground truth spectra and the instrumental noise simultaneously within the training dataset, which bypasses the tedious labelling of huge dataset required in conventional deep learning, potentially shifting deep learning from sample-dependent to instrument-dependent.

Soluble Nanographene C222: Synthesis and Applications for Synergistic Photodynamic/Photothermal Therapy.

Nanographene C222, which consists of a planar graphenic plane containing 222 carbon atoms, holds the record as the largest planar nanographene synthesized to date. However, its complete insolubility makes the processing of C222 difficult. Here we addressed this issue by introducing peripheral substituents perpendicular to the graphene plane, effectively disrupting the interlayer stacking and endowing C222 with good solubility. We also found that the electron-withdrawing substituents played a crucial role in the cyclodehydrogenation process, converting the dendritic polyphenylene precursor to C222. After disrupting the interlayer stacking, the introduction of only a few peripheral carboxylic groups allowed C222 to dissolve in phosphate buffer saline, reaching a concentration of up to 0.5 mg/mL. Taking advantage of the good photosensitizing and photothermal properties of the inner C222 core, the resulting water-soluble C222 emerged as a single-component agent for both photothermal and photodynamic tumor therapy, exhibiting an impressive tumor inhibition rate of 96%.

Rapidly determining the 3D structure of proteins by surface-enhanced Raman spectroscopy.

Despite great advances in protein structure analysis, label-free and ultrasensitive methods to obtain the natural and dynamic three-dimensional (3D) structures are still urgently needed. Surface-enhanced Raman spectroscopy (SERS) can be a good candidate, whereas the complexity originated from the interactions between the protein and the gradient surface electric field makes it extremely challenging to determine the protein structure. Here, we propose a deciphering strategy for accurate determination of 3D protein structure from experimental SERS spectra in seconds by simply summing SERS spectra of isolated amino acids in electric fields of different strength with their orientations in protein. The 3D protein structure can be reconstructed by comparing the experimental spectra obtained in a well-defined gap-mode SERS configuration with the simulated spectra. The gradient electric field endows SERS with a unique advantage to section biomolecules with atomic precision, which makes SERS a competent tool for monitoring biomolecular events under physiological conditions.

Kinetic-Modulated Crystal Phase of Ru for Hydrogen Oxidation.

Crystal-phase-engineering provides a powerful strategy for regulating the catalytic performance yet remains great challenge. Herein, the kinetic-modulated crystal-phase-control of Ru nanosheet assemblies (Ru NAs) is demonstrated by simply altering the concentration of citric acid (CA). Detailed experimental results reveal that high concentration of CA retards the growth kinetics and thus leads to the formation of metastable face-centered cubic (fcc) Ru NAs, while low concentration of CA results in the fast growth kinetics and the preferential formation of Ru NAs with stable hexagonal close packed (hcp) phase. Moreover, Ru NAs with different phases are used as catalyst for hydrogen oxidation reaction (HOR) to evaluate the effects of crystal phase on catalytic performance. Impressively, Ru NAs with fcc phase display a mass activity of 2.75 A mgRu -1 at 50 mV, which is much higher than those of Ru NAs with fcc/hcp (1.02 A mgRu -1 ) and hcp (0.74 A mgRu -1 ) phases. Theoretical calculations show that fcc Ru NAs display weaker adsorption toward * H and lower energy barrier toward the rate-determining step (RDS) during HOR. This work provides a facile strategy for regulating the crystal phase of Ru nanocrystals, which may attract rapid interests of researchers in materials, chemistry, and catalysis.

In-situ Raman spectroscopic insight into charge delocalization-improved electrical conductivity in metal-cyanide frameworks.

Porous crystalline materials (PCMs) have attracted widespread attention due to their high porosity and chemical tunability. To solve the problem of the low electrical conductivity of traditional PCMs, a guest-promoted approach has been developed to impart electrical conductivity, whereas microscopic understanding of this process from experiments is largely lacking. Here we use in-situ electrochemical surface-enhanced Raman spectroscopy (EC-SERS) to investigate the microscopic mechanism of the enhanced electrical conductivity in metal-cyanide frameworks, in Prussian Blue (PB), induced by alkali metal ions. The EC-SERS result demonstrates that the charge is localized around the iron atom in PB and becomes delocalized on the CN bond after insertion of the alkali metal ions, verified by density functional theory (DFT) calculations. The enhanced electrical conductivity of PCMs promoted by the guest via the through-bond mechanism instead of the through-space hopping mechanism in pristine PB, offers a new approach to develop conductive PCMs.

Correlation coefficient-directed label-free characterization of native proteins by surface-enhanced Raman spectroscopy.

Investigation of proteins in their native state is the core of proteomics towards better understanding of their structures and functions. Surface-enhanced Raman spectroscopy (SERS) has shown its unique advantages in protein characterization with fingerprint information and high sensitivity, which makes it a promising tool for proteomics. It is still challenging to obtain SERS spectra of proteins in the native state and evaluate the native degree. Here, we constructed 3D physiological hotspots for a label-free dynamic SERS characterization of a native protein with iodide-modified 140 nm Au nanoparticles. We further introduced the correlation coefficient to quantitatively evaluate the variation of the native degree, whose quantitative nature allows us to explicitly investigate the Hofmeister effect on the protein structure. We realized the classification of a protein of SARS-CoV-2 variants in 15 min, which has not been achieved before. This study offers an effective tool for tracking the dynamic structure of proteins and biomedical research.

Interface engineering of snow-like Ru/RuO2 nanosheets for boosting hydrogen electrocatalysis.

Ru has recently been regarded as a promising catalyst for hydrogen oxidation reaction (HOR) and hydrogen evolution reaction (HER) due to its similar binding energy towards *H but lower price compared to Pt. Nevertheless, the quest of high-efficiency Ru-based catalysts for HOR and HER is driven by the current disadvantages including low activity and unsatisfactory stability. Herein, we have fabricated and engineered two-dimensional (2D) Ru-based snow-like nanosheets with Ru/RuO2 interface (Ru/RuO2 SNSs) via a post-annealing treatment. Detailed characterizations and theoretical calculations indicate that the interfacial synergy, which is dependent on the temperature for annealing, can alter the hydrogen binding energy (HBE) and hydroxide binding energy (OHBE), as a result of the enhanced HOR and HER performance. Impressively, the optimal Ru/RuO2 SNSs display a mass activity of 9.13 A mgRu-1 at an overpotential of 50 mV in 0.1 mol L-1 KOH for HOR, which is 65, 304, and 21 times higher than those of Ru SNSs (0.14 A mgRu-1), RuO2 SNSs (0.03 A mgRu-1), and commercial Pt/C (0.43 A mgRu-1), respectively. Moreover, Ru/RuO2 SNSs display improved HER activity with a low overpotential of 20.2 mV for achieving 10 mA cm-2 in 1 mol L-1 KOH. This work not only provides an efficient catalyst for HOR and HER, but also promotes fundamental research on the fabrication and modification of catalysts in heterogeneous catalysis.

Quantitatively Deciphering Electronic Properties of Defects at Atomically Thin Transition-Metal Dichalcogenides.

Defects can locally tailor the electronic properties of 2D materials, including the band gap and electron density, and possess the merit for optical and electronic applications. However, it is still a great challenge to realize rational defect engineering, which requires quantitative study of the effect of defects on electronic properties under ambient conditions. In this work, we employed tip-enhanced photoluminescence (TEPL) spectroscopy to obtain the PL spectra of different defects (wrinkle and edge) in mechanically exfoliated thin-layer transition metal dichalcogenides (TMDCs) with nanometer spatial resolution. We quantitatively obtained the band gap and electron density at defects by analyzing the wavelength and intensity ratio of excitons and trions. We further visualized the strain distribution across a wrinkle and the edge-induced reconstructive regions of the band gap and electron density by TEPL line scans. The doping effect on the Fermi level and optical performance was unveiled through comparative studies of edges on TMDC monolayers of different doping types. These quantitative results are vital to guide defect engineering and design and fabrication of TMDC-based optoelectronics devices.

Superlattice in a Ru Superstructure for Enhancing Hydrogen Evolution.

Superlattices are attracting extensive attention due to their unique properties. Nevertheless, the observations of superlattices are limited to those layered structures with weak interlayered interactions, and the effect of the superlattice in metal-based nanostructures on catalysis is unexplored yet. We here report a facile wet-chemical method for synthesizing two-dimensional Ru multilayered nanosheets (Ru MNSs) with a superlattice. Characterizations reveal that the superlattice is formed by stacking Ru layers with twisted angles from 2° to 30°. Owing to the strong synergy between the adjacent layers, Ru MNSs can serve as an efficient catalyst for the alkaline hydrogen evolution reaction (HER). Theoretical calculations reveal that the superlattice can induce the strain effect, which leads to lattice contraction and weak *H adsorption ability, as a result of improved HER performance. This work sheds new light on the utilization of the superlattice on enhancing catalysis in metal-based materials.

Collaborative Low-Rank Matrix Approximation-Assisted Fast Hyperspectral Raman Imaging and Tip-Enhanced Raman Spectroscopic Imaging.

Fast acquisition of Raman images is essential for accurately characterizing the analytes' information. In this paper, we developed a collaborative low-rank matrix approximation method for fast hyperspectral Raman imaging as well as tip-enhanced Raman spectroscopy (TERS) imaging. This method combines high signal-to-noise ratio (SNR) data with the target data to perform collaborative singular value decomposition. The high-quality reference data can impose constraints on factorization, which will force its components to approximate the true signal or noise components. The simulation demonstrated that this method offers state-of-the-art signal extraction performance and, thus, can be used to accelerate data acquisition. Specifically, the results indicate that the CLRMA can largely decrease the root-mean-square error by 20.92-54.12% compared with the baseline method of our previous study. We then applied this method to the fast TERS imaging of a Au/Pd bimetallic surface and significantly decreased the integration time down to 0.1 s/pixel, which is about 10 times faster than that of conventional experiments. High-SNR TERS spectra and clear TERS images that are well consistent with scanning tunneling microscopy (STM) images can be obtained even under such a weak signal condition. We further applied this method to the fast Raman imaging of HeLa cells and obtained clear Raman images at a short integration time of 2 s/line, which is about 5 times faster than that of conventional experiments. This method offers a promising tool for TERS imaging as well as conventional Raman imaging where fast data acquisition is required.

Low-Background Tip-Enhanced Raman Spectroscopy Enabled by a Plasmon Thin-Film Waveguide Probe.

Tip-enhanced Raman spectroscopy (TERS) is a nano-optical approach to extract spatially resolved chemical information with nanometer precision. However, in the case of direct-illumination TERS, which is often employed in commercial TERS instruments, strong fluorescence or far-field Raman signals from the illuminated areas may be excited as a background. They may overwhelm the near-field TERS signal and dramatically decrease the near-field to far-field signal contrast of TERS spectra. It is still challenging for TERS to study the surface of fluorescent materials or a bulk sample that cannot be placed on an Au/Ag substrate. In this study, we developed an indirect-illumination TERS probe that allows a laser to be focused on a flat interface of a thin-film waveguide located far away from the region generating the TERS signal. Surface plasmon polaritons are generated stably on the waveguide and eventually accumulated at the tip apex, thereby producing a spatially and energetically confined hotspot to ensure stable and high-resolution TERS measurements with a low background. With this thin-film waveguide probe, TERS spectra with obvious contrast from a diamond plate can be acquired. Furthermore, the TERS technique based on this probe exhibits excellent TERS signal stability, a long lifetime, and good spatial resolution. This technique is expected to have commercial potential and enable further popularization and development of TERS technology as a powerful analytical method.

Atomic Force Microscopy Based Top-Illumination Electrochemical Tip-Enhanced Raman Spectroscopy.

Electrochemical tip-enhanced Raman spectroscopy (EC-TERS) is a powerful technique for the in situ study of the physiochemical properties of the electrochemical solid/liquid interface at the nanoscale and molecular level. To further broaden the potential window of EC-TERS while extending its application to opaque samples, here, we develop a top-illumination atomic force microscopy (AFM) based EC-TERStechnique by using a water-immersion objective of a high numerical aperture to introduce the excitation laser and collect the signal. This technique not only extends the application of EC-TERS but also has a high detection sensitivity and experimental efficiency. We coat a SiO2 protection layer over the AFM-TERS tip to improve both the mechanical and chemical stability of the tip in a liquid TERS experiment. We investigate the influence of liquid on the tip-sample distance to obtain the highest TERS enhancement. We further evaluate the reliability of the as-developed EC-AFM-TERS technique by studying the electrochemical redox reaction of polyaniline. The top-illumination EC-AFM-TERS is promising for broadening the application of EC-TERS to more practical systems, including energy storage and (photo)electrocatalysis.

Detection of leucine aminopeptidase activity in serum using surface-enhanced Raman spectroscopy.

Leucine aminopeptidase (LAP), an important proteolytic enzyme, is closely associated with diverse physiological and pathological disorders such as liver injury and cancers. Hence, it is imperative to develop an effective method to detect LAP activity for early diagnosis of diseases. In this work, we report a novel SERS probe bis-s-s'-[(s)-2-amino-N-(3-thiophenyl)-Leu]. (b-(s)-ANT-Leu) with an l-leucine amide group, which can specially respond to LAP, to assay the LAP activity according to the SERS spectral changes between the probe molecule and its corresponding hydrolysis product resulting from the catalysis of LAP. This SERS approach features high selectivity on account of the specificity of the reaction combined with the instinctive fingerprinting ability of SERS and shows a good linear relationship in a wide range from 0.2 to 100 mU mL-1 with a detection limit as low as 0.16 mU mL-1. In addition, the SERS-based strategy can be competent for LAP activity detection in clinical patient serum samples and LAP inhibitor evaluation, demonstrating its great potential in the pathological analysis for diseases involving LAP and the screening of LAP inhibitors.