An eco-friendly and high-yield extraction of rare earth from the leaching solution of ion adsorbed minerals.

Ion-adsorbed rare earth minerals are rich in medium and heavy rare earth (RE), which are important strategic resources. In this article, a novel approach for the extraction of RE from ion adsorbed minerals was developed. Through a comprehensive assessment of their extraction and separation performance, the hydrophobic deep eutectic solvents (HDES) with a composition of trioctylphosphine oxide (TOPO): dodecanol (LA): 2-thiophenoyltrifluoroacetone (HTTA) = 1:1:1 was determined as the optimal configuration. Under optimized conditions, only RE were extracted by the HDES, while Al, Ca, Mg were not extracted at all. The HDES based extraction obviated the need for diluent such as kerosene, eliminating the generation of impurity removal residues. The RE in the stripping solution could be successfully enriched by saponified lauric acid, achieving an impressive precipitation rate of 99.7%. The RE precipitate underwent further enrichment, resulting in a RE concentration of 176 g/L (REO = 210 g/L). Unlike industrial precipitants such as oxalic acid and ammonium bicarbonate, lauric acid can be effectively recycled, thereby avoiding a large amount of wastewater and carbon dioxide emissions. The obtained RE solution product exhibits high yield and purity, this study provides an eco-friendly and high-yield approach for extracting RE.

Ts2O mediated deoxygenative C2-dithiocarbamation of quinoline N-oxides with CS2 and amines.

A general, efficient and practical protocol for Ts2O promoted deoxygenative dithiocarbamation of quinoline N-oxides with in situ generated dithiocarbamic acids from CS2 and amines is reported. The reaction proceeded well under transition-metal free conditions to obtain a variety of novel quinoline-dithiocarbamate compounds with wide functional group tolerance and good to high yields.

Rapid Sample Pretreatment Facilitating SERS Detection of Trace Weak Organic Acids/Bases in Complex Matrices.

Fast and efficient sample pretreatment is the prerequisite for realizing surface-enhanced Raman spectroscopy (SERS) detection of trace targets in complex matrices, which is still a big issue for the practical application of SERS. Recently, we have proposed a highly performed liquid-liquid extraction (LLE)-back extraction (BE) for weak acids/bases extraction in drinking water and beverage samples. However, the performance efficiency decreased drastically on facing matrices like food and biological blood. Based on the total interaction energies among target, interferent, and extractant molecules, solid-phase extraction (SPE) with a higher selectivity was introduced in advance of LLE-BE, which enabled the sensitive (µg L-1 level) and rapid (within 10 min) SERS detection of both koumine (a weak base) and celastrol (a weak acid) in different food and biological samples. Further, the high SERS sensitivity was determined unmanned by Vis-CAD (a machine learning algorithm), instead of the highly demanded expert recognition. The generality of SPE-LLE-BE for various weak acids/bases (2 < pKa < 12), accompanied by the high efficiency, easy operation, and low cost, offers SERS as a powerful on-site and efficient inspection tool in food safety and forensics.

What Elements Really Intercalate into Pd Lattice When Heated in Dimethylformamide?

Palladium hydrides (PdHx) are pivotal in both fundamental research and practical applications across a wide spectrum. PdHx nanocrystals, synthesized by heating in dimethylformamide (DMF), exhibit remarkable stability, granting them widespread applications in the field of electrocatalysis. However, this stability appears inconsistent with their metastable nature. The substantial challenges in characterizing nanoscale structures contribute to the limited understanding of this anomalous phenomenon. Here, through a series of well-conceived experimental designs and advanced characterization techniques, including aberration-corrected scanning transmission electron microscopy (AC-STEM), in situ X-ray diffraction (XRD), and time-of-flight secondary ion mass spectrometry (TOF-SIMS), we have uncovered evidence that indicates the presence of C and N within the lattice of Pd (PdCxNy), rather than H (PdHx). By combining theoretical calculations, we have thoroughly studied the potential configurations and thermodynamic stability of PdCxNy, demonstrating a 2.5:1 ratio of C to N infiltration into the Pd lattice. Furthermore, we successfully modulated the electronic structure of Pd nanocrystals through C and N doping, enhancing their catalytic activity in methanol oxidation reactions. This breakthrough provides a new perspective on the structure and composition of Pd-based nanocrystals infused with light elements, paving the way for the development of advanced catalytic materials in the future.

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.

Adsorption structures, vibrational Raman spectra and chemical binding properties of thioglycolic acid on Cu(111) surfaces: A DFT study.

Copper is widely used in everyday life and industrial production because of its good electrical and thermal conductivity. To overcome copper oxidation and maintain its good physical properties, small organic molecules adsorbed on the surface of copper make a passivated layer to further avoid copper corrosion. In this work, we have investigated thioglycolic acid (TGA, another name is mercaptoacetic acid) adsorbed on copper surfaces by using density functional theory (DFT) calculations and a periodical slab model. We first get five stable adsorption structures, and the binding interaction between TGA and Cu(111) surfaces by using density of states (DOS), indicating that the most stable configuration adopts a triple-end binding model. Then, we analyze the vibrational Raman spectra of TGA adsorbed on the Cu(111) surface and make vibrational assignments according to the vibrational vectors. Finally, we explore the temperature effect of the thermodynamically Gibbs free energy of TGA on the Cu(111) surface and the antioxidant ability of the small organic molecular layer of copper oxidation on the copper surface. Our calculated results further provide evidences to interpret the stability of adsorption structures and antioxidant properties of copper.

Efficient synthesis of SCF3-containing 3-alkenylquinoxalinones via three-component radical cascade reaction.

An efficient and practical method for the synthesis of 3-alkenylquinoxalinones containing the SCF3 group has been readily developed through a three-component radical cascade reaction involving quinoxalinones, alkynes and AgSCF3. The reaction was found to be compatible with a variety of substrates and exhibited a high functional group tolerance and complete E-selectivity. The preliminary study suggests the involvement of a SCF3 radical in the transformation.

Machine Learning Molecular Dynamics Shows Anomalous Entropic Effect on Catalysis through Surface Pre-melting of Nanoclusters.

Due to the superior catalytic activity and efficient utilization of noble metals, nanocatalysts are extensively used in the modern industrial production of chemicals. The surface structures of these materials are significantly influenced by reactive adsorbates, leading to dynamic behavior under experimental conditions. The dynamic nature poses significant challenges in studying the structure-activity relations of catalysts. Herein, we unveil an anomalous entropic effect on catalysis via surface pre-melting of nanoclusters through machine learning accelerated molecular dynamics and free energy calculation. We find that due to the pre-melting of shell atoms, there exists a non-linear variation in the catalytic activity of the nanoclusters with temperature. Consequently, two notable changes in catalyst activity occur at the respective temperatures of melting for the shell and core atoms. We further study the nanoclusters with surface point defects, i.e. vacancy and ad-atom, and observe significant decrease in the surface melting temperatures of the nanoclusters, enabling the reaction to take place under more favorable and milder conditions. These findings not only provide novel insights into dynamic catalysis of nanoclusters but also offer new understanding of the role of point defects in catalytic processes.

Relationship between changes in late-life blood pressure and the risk of frailty and mortality among older population in China: a cohort study based on CLHLS.

The evidence regarding the effects of blood pressure changes on older individuals remains inconclusive, and the impact of frailty throughout the life course is not known. We investigated the associations of different change patterns of blood pressure during 3-year intervals with frailty and mortality. Participants included 7335 persons from 2008 to 2014 of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Change in blood pressure was calculated as the difference between follow-up and baseline. Frailty was evaluated using a 40-item frailty index. Mortality status was ascertained up to December 31, 2014. The mean age of participants was 82.6 ± 10.7 years. The optimal blood pressure level (SBP, 130-150 mmHg; DBP, 70-90 mmHg) was associated with the lowest risk of frailty while decreasing follow-up SBP and DBP were significantly correlated with frailty. Lower baseline blood pressure levels (SBP < 130 mmHg; DBP < 70 mmHg) were associated with decreased mortality risk when participants increased their blood pressure to optimal levels during follow-up SBP and DBP (0.78, 0.63-0.98), compared to maintaining a steady low SBP (< 130 mmHg) and DBP (< 70 mmHg). For those with DBP around 70-90 mmHg, decreasing follow-up DBP (< 70 mmHg) was associated with higher mortality (1.23, 1.07-1.42) compared to maintaining stable follow-up DBP (70-90 mmHg). These results remain significant after adjusting for frailty. Optimal blood pressure levels were associated with the lowest risk of frailty. The association between lower blood pressure and increased mortality risk persisted even after accounting for frailty. We used a nationally representative longitudinal cohort study by using 2008-2014 of the Chinese Longitudinal Healthy Longevity in China. Change in blood pressure was calculated as the difference between follow-up and baseline. We investigated the associations of different change patterns of blood pressure during 3-year intervals with frailty and mortality.

1T'-transition metal dichalcogenide monolayers stabilized on 4H-Au nanowires for ultrasensitive SERS detection.

Unconventional 1T'-phase transition metal dichalcogenides (TMDs) have aroused tremendous research interest due to their unique phase-dependent physicochemical properties and applications. However, due to the metastable nature of 1T'-TMDs, the controlled synthesis of 1T'-TMD monolayers (MLs) with high phase purity and stability still remains a challenge. Here we report that 4H-Au nanowires (NWs), when used as templates, can induce the quasi-epitaxial growth of high-phase-purity and stable 1T'-TMD MLs, including WS2, WSe2, MoS2 and MoSe2, via a facile and rapid wet-chemical method. The as-synthesized 4H-Au@1T'-TMD core-shell NWs can be used for ultrasensitive surface-enhanced Raman scattering (SERS) detection. For instance, the 4H-Au@1T'-WS2 NWs have achieved attomole-level SERS detections of Rhodamine 6G and a variety of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins. This work provides insights into the preparation of high-phase-purity and stable 1T'-TMD MLs on metal substrates or templates, showing great potential in various promising applications.

Ts2O Promoted Deoxygenative C-H Dithiocarbonation of Quinoline N-Oxides with Potassium O-Alkyl Xanthates.

A simple, efficient, and practical method for the synthesis of S-quinolyl xanthates was developed via Ts2O-promoted deoxygenative C-H dithiocarbonation of quinoline N-oxides with various potassium O-alkyl xanthates. The reaction performed well under transition-metal-free, base-free, and room-temperature conditions with wide substrate tolerance. Employing potassium O-tert-butyl xanthate (tBuOCS2K) as a nucleophile, some valuable quinoline-2-thiones were unexpectedly obtained in a one-pot reaction without any additional base.

Contact-Electro-Catalysis for Direct Oxidation of Methane under Ambient Conditions.

The conversion of methane under ambient conditions has attracted significant attention. Although advancements have been made using active oxygen species from photo- and electro- chemical processes, challenges such as complex catalyst design, costly oxidants, and unwanted byproducts remain. This study exploits the concept of contact-electro-catalysis, initiating chemical reactions through charge exchange at a solid-liquid interface, to report a novel process for directly converting methane under ambient conditions. Utilizing the electrification of commercially available Fluorinated Ethylene Propylene (FEP) with water under ultrasound, we demonstrate how this interaction promote the activation of methane and oxygen molecules. Our results show that the yield of HCHO and CH3OH can reach 467.5 and 151.2 µmol ⋅ gcat -1, respectively. We utilized electron paramagnetic resonance (EPR) to confirm the evolution of hydroxyl radicals (⋅OH) and superoxide radicals (⋅OOH). Isotope mass spectrometry (MS) was employed to analyze the elemental origin of CH3OH, which can be further oxidized to HCHO. Additionally, we conducted density functional theory (DFT) simulations to assess the reaction energies of FEP with H2O, O2, and CH4 under these conditions. The implications of this methodology, with its potential applicability to a wider array of gas-phase catalytic reactions, underscore a significant advance in catalysis.

Causal connectivity measures for pulse-output network reconstruction: Analysis and applications.

The causal connectivity of a network is often inferred to understand network function. It is arguably acknowledged that the inferred causal connectivity relies on the causality measure one applies, and it may differ from the network's underlying structural connectivity. However, the interpretation of causal connectivity remains to be fully clarified, in particular, how causal connectivity depends on causality measures and how causal connectivity relates to structural connectivity. Here, we focus on nonlinear networks with pulse signals as measured output, e.g., neural networks with spike output, and address the above issues based on four commonly utilized causality measures, i.e., time-delayed correlation coefficient, time-delayed mutual information, Granger causality, and transfer entropy. We theoretically show how these causality measures are related to one another when applied to pulse signals. Taking a simulated Hodgkin-Huxley network and a real mouse brain network as two illustrative examples, we further verify the quantitative relations among the four causality measures and demonstrate that the causal connectivity inferred by any of the four well coincides with the underlying network structural connectivity, therefore illustrating a direct link between the causal and structural connectivity. We stress that the structural connectivity of pulse-output networks can be reconstructed pairwise without conditioning on the global information of all other nodes in a network, thus circumventing the curse of dimensionality. Our framework provides a practical and effective approach for pulse-output network reconstruction.

TsCl promoted deoxygenative phosphorothiolation of quinoline N-oxides towards S-quinolyl phosphorothioates.

A convenient, efficient and practical approach for the synthesis of S-quinolyl phosphorothioates via cheap TsCl promoted deoxygenative C2-H phosphorothiolation of quinoline N-oxides with readily available triethylammonium O,O-dialkylphosphorothioates was developed. The reaction performed well under transition-metal-free conditions at room temperature with a very short reaction time (10-20 min). Preliminary studies showed that the current transformation underwent a nucleophilic substitution process.

Revealing the Denoising Principle of Zero-Shot N2N-Based Algorithm from 1D Spectrum to 2D Image.

Denoising is a necessary step in image analysis to extract weak signals, especially those hardly identified by the naked eye. Unlike the data-driven deep-learning denoising algorithms relying on a clean image as the reference, Noise2Noise (N2N) was able to denoise the noise image, providing sufficiently noise images with the same subject but randomly distributed noise. Further, by introducing data augmentation to create a big data set and regularization to prevent model overfitting, zero-shot N2N-based denoising was proposed in which only a single noisy image was needed. Although various N2N-based denoising algorithms have been developed with high performance, their complicated black box operation prevented the lightweight. Therefore, to reveal the working function of the zero-shot N2N-based algorithm, we proposed a lightweight Peak2Peak algorithm (P2P) and qualitatively and quantitatively analyzed its denoising behavior on the 1D spectrum and 2D image. We found that the high-performance denoising originates from the trade-off balance between the loss function and regularization in the denoising module, where regularization is the switch of denoising. Meanwhile, the signal extraction is mainly from the self-supervised characteristic learning in the data augmentation module. Further, the lightweight P2P improved the denoising speed by at least ten times but with little performance loss, compared with that of the current N2N-based algorithms. In general, the visualization of P2P provides a reference for revealing the working function of zero-shot N2N-based algorithms, which would pave the way for the application of these algorithms toward real-time (in situ, in vivo, and operando) research improving both temporal and spatial resolutions. The P2P is open-source at https://github.com/3331822w/Peak2Peakand will be accessible online access at https://ramancloud.xmu.edu.cn/tutorial.

Sixty years of electrochemical optical spectroscopy: a retrospective.

Sixty years ago, Reddy, Devanatan, and Bockris performed the first in situ electrochemical ellipsometry experiment, which ushered in a new era in the study of electrochemistry, using optical spectroscopy. After six decades of development, electrochemical optical spectroscopy, particularly electrochemical vibrational spectroscopy, has advanced from a phase of immaturity with few methods and limited applications to a phase of maturity with excellent substrate generality and significantly improved resolutions. Here, we divide the development of electrochemical optical spectroscopy into four phases, focusing on the proof-of-concept of different electrochemical optical spectroscopy studies, the emergence of plasmonic enhancement-based electrochemical optical spectroscopic (in particular vibrational spectroscopic) methods, the realization of electrochemical vibrational spectroscopy on well-defined surfaces, and the efforts to achieve operando spectroelectrochemical applications. Finally, we discuss the future development trend of electrochemical optical spectroscopy, as well as examples of new methodology and research paradigms for operando spectroelectrochemistry.

Association of macronutrient consumption quality, food source and timing with depression among US adults: A cross-sectional study.

BACKGROUND: Growing evidence suggests that meal timing may influence dietary choices and mental health. Thus, this study examined the association between macronutrient consumption quality, food source, meal timing, and depression prevalence in Americans. METHODS: 23,313 National Health and Nutrition Survey participants from 2007 to 2016 were included in this cross-sectional study. Macronutrient intake was calculated for all day, dinner, and breakfast and subtypes into 4 classes. Based on the Patient Health Questionnaire, depression was defined as a 9-item score ≥ 10 on the PHQ-9. The correlation between macronutrients and depression prevalence was estimated with multivariable logistic regression models and isocaloric substitution effects. RESULTS: Low-quality carbohydrates (OR = 1.54, 95 % CI: 1.11, 2.12) were positively linked to depression compared with the lowest quartile, after adjusting for age and other covariates. In contrast, total high-quality carbohydrate (OR = 0.52, 95 % CI: 0.40, 0.66), total animal protein (OR = 0.60, 95 % CI: 0.45, 0.80), and total vegetable protein (OR = 0.61, 95 % CI: 0.43, 0.85) were negatively associated with depression was negatively associated. Replacing low-quality carbohydrates with high-quality carbohydrates throughout the day reduced the risk of depression by approximately 15 %. LIMITATIONS: Cross-sectional data. CONCLUSION: All in all, diet plays a crucial role in the prevention and treatment of depression. Especially in terms of macronutrient intake, high-quality, moderate intake can reduce the risk of depression. However, different subtypes of macronutrient consumption may have different effects on depression, so it becomes crucial to carefully consider the selection and combination of macronutrients.

Utilization of charged microdroplets for the controlled rapid synthesis of hollow sodium chloride single crystals.

Charged microdroplets are favored in microfluidic control, biomedicine, chemistry and materials processing due to their unique physicochemical environment, including interface double layers, high electric fields, surface concentration enrichment, and more. Herein, we investigated the crystallization of charged sodium chloride microdroplets and achieved the formation of hollow single crystals in a single-step process lasting only a few seconds, without the use of templates. Additionally, we discussed the plausible crystal growth mechanism, which appears to be an unconventional outward-inward growth process.

Charged Microdroplets as Microelectrochemical Cells for CO2 Reduction and C-C Coupling.

Charged microdroplets offer novel electrochemical environments, distinct from traditional solid-liquid or solid-liquid-gas interfaces, due to the intense electric fields at liquid-gas interfaces. In this study, we propose that charged microdroplets serve as microelectrochemical cells (MECs), enabling unique electrochemical reactions at the gas-liquid interface. Using electrospray-generated microdroplets, we achieved multielectron CO2 reduction and C-C coupling to synthesize ethanol using molecular catalysts. These catalysts effectively harness and relay electrons, enhancing the longevity of solvated electrons and enabling multielectron reactions. Importantly, we revealed the intrinsic relationship between the size and charge density of a MEC and its reaction selectivity. Employing in situ mass spectrometry, we identified reaction intermediates (molecular catalyst adducts with HCOO) and oxidation products, elucidating the CO2 reduction mechanism and the comprehensive reaction procedure. Our research underscores the promising role of charged microdroplets in pioneering new electrochemical systems.

What can molecular assembly learn from catalysed assembly in living organisms?

Molecular assembly is the process of organizing individual molecules into larger structures and complex systems. The self-assembly approach is predominantly utilized in creating artificial molecular assemblies, and was believed to be the primary mode of molecular assembly in living organisms as well. However, it has been shown that the assembly of many biological complexes is "catalysed" by other molecules, rather than relying solely on self-assembly. In this review, we summarize these catalysed-assembly (catassembly) phenomena in living organisms and systematically analyse their mechanisms. We then expand on these phenomena and discuss related concepts, including catalysed-disassembly and catalysed-reassembly. Catassembly proves to be an efficient and highly selective strategy for synergistically controlling and manipulating various noncovalent interactions, especially in hierarchical molecular assemblies. Overreliance on self-assembly may, to some extent, hinder the advancement of artificial molecular assembly with powerful features. Furthermore, inspired by the biological catassembly phenomena, we propose guidelines for designing artificial catassembly systems and developing characterization and theoretical methods, and review pioneering works along this new direction. Overall, this approach may broaden and deepen our understanding of molecular assembly, enabling the construction and control of intelligent assembly systems with advanced functionality.