Hybrid Surface Modification and Bulk Doping Enable Spent LiCoO2 Cathodes for High-Voltage Operation.

The emerging market demand for high-energy-density of energy storage devices is pushing the disposal of end-of-life LiCoO2 (LCO) to shift toward sustainable upgrading into structurally stable high-voltage cathode materials. Herein, an integrated bulk and surface commodification strategy is proposed to render spent LCO (S-LCO) to operate at high voltages, involving bulk Mn doping, near surface P gradient doping, and Li3PO4/CoP (LPO/CP) coating on the LCO surface to yield upcycled LCO (defined as MP-LCO@LPO/CP). Benefiting from hybrid surface coating with Li+-conductive Li3PO4 (LPO) and electron conductive CoP (CP) coupled with Mn and P co-doping, the optimized MP-LCO@LPO/CP cathode exhibits enhanced high-voltage performance, delivering an initial discharge capacity of 218.8 mAh g-1 at 0.2 C with excellent capacity retention of 80.9% (0.5 C) after 200 cycles at a cut-off voltage of 4.6 V, along with 96.3% of capacity retention over 100 cycles at 4.5 V. These findings may afford meaningful construction for the upcycling of commercial S-LCO into next-generation upmarket cathode materials through the elaborate surface and bulk modification design.

Toward High-Performance Hydrogenation at Room Temperature Through Tailoring Nickel Catalysts Stable in Aqueous Solution.

The development of highly active, reusable catalysts for aqueous-phase reactions is challenging. Herein, metallic nickel is encapsulated in a nitrogen-doped carbon-silica composite (SiO2@Ni@NC) as a catalyst for the selective hydrogenation of vanillin in aqueous media. The constructed catalyst achieved 99.8% vanillin conversion and 100% 4-hydroxymethyl-2-methoxyphenol selectivity at room temperature. Based on combined scanning transmission electron microscopy, X-ray photoelectron spectroscopy, and Raman analyses, the satisfactory catalytic performance is attributed to the composite structure consisting of an active metal, carbon, and silica. The hydrophilic silica core promoted dispersion of the catalyst in aqueous media. Moreover, the external hydrophobic NC layer has multiple functions, including preventing oxidation or leaching of the internal metal, acting as a reducing agent to reduce the internal metal, regulating the active-site microenvironment by enriching the concentrations of H2 and organic reactants, and modifying the electronic structure of the active metal via metal-support interactions. Density functional theory calculations indicated that NC facilitates vanillin adsorption and hydrogen dissociation to promote aqueous-phase hydrogenation. This study provides an efficient strategy for constructing encapsulated Ni-based amphiphilic catalysts to upgrade biomass-derived compounds.

Tri-enzyme fusion of tryptophan halogenase achieves a concise strategy for coenzyme self-sufficiency and the continuous halogenation of L-tryptophan.

The halogenase-based catalysis is one of the most environmentally friendly methods for the synthesis of halogenated products, among which flavin-dependent halogenases (FDHs) have attracted great interest as one of the most promising biocatalysts due to the remarkable site-selectivity and wide substrate range. However, the complexity of constructing the NAD+-NADH-FAD-FADH2 bicoenzyme cycle system has affected the engineering applications of FDHs. In this work, a coenzyme self-sufficient tri-enzyme fusion was constructed and successfully applied to the continuous halogenation of L-tryptophan. SpFDH was firstly identified derived from Streptomyces pratensis, a highly selective halogenase capable of generating 6-chloro-tryptophan from tryptophan. Then, using gene fusion technology, SpFDH was fused with glucose dehydrogenase (GDH) and flavin reductase (FR) to form a tri-enzyme fusion, which increased the yield by 1.46-fold and making the coenzymes self-sufficient. For more efficient halogenation of L-tryptophan, a continuous halogenation bioprocess of L-tryptophan was developed by immobilizing the tri-enzyme fusion and attaching it to a continuous catalytic device, which resulted in a reaction yield of 97.6% after 12 h reaction. An FDH from S. pratensis was successfully applied in the halogenation and our study provides a concise strategy for the preparation of halogenated tryptophan mediated by multienzyme cascade catalysis.

[Site-specific mutation of ω-transaminase and the biocatalytic preparation of (S)-1-(2-fluorophenyl) ethylamine].

(S)-1-(2-fluorophenyl) ethylamine plays a crucial role as a chiral building block in pharmaceutical synthesis. ω-transaminases are widely recognized as environmentally friendly and efficient catalysts for the preparation of chiral amines. In this study, we isolated a novel ω-transaminase, PfTA, from Pseudogulbenkiania ferrooxidans through gene mining in the NCBI database. By employing semi-rational design, we obtained a Y168R/R416Q variant with enhanced enzyme activity. This variant exhibited the ability to catalyze the synthesis of (S)-1-(2-fluorophenyl) ethylamine from 2-fluorophenone, achieving a yield of 83.58% and an enantioselectivity exceeding 99% after a 10 h reaction. Compared to the wild type, the specific enzyme activity of the Y168R/R416Q variant reached 47.04 U/mg, which represents an increase of 11.65 times. Additionally, the catalytic efficiency, as measured by kcat/Km, was increased by 20.9 times. Molecular docking and structural simulation analysis revealed that the primary factor contributing to the improved catalytic efficiency is the expansion of the enzyme's active pocket and the alleviation of steric hindrance.

Mining and validation of prognosis of various visceral metastasis in renal cell carcinoma: a study based on SEER database.

Our study was aimed to analyze a substantial of renal cell carcinoma (RCC) patients, research the high-risk factors and prognostic factors of metastasis, and thoroughly examine the effects of primary site surgery, lymph node dissection (LND), and chemotherapy on the prognosis of different visceral metastases. The baseline characteristics were characterized, and logistic regression was used to predict the risk factors for metastasis. Prognostic factors of metastatic RCC were assessed using batch univariate and multivariate Cox regression, with adjustments made through PSM. Next, the Kaplan-Meier method was employed to assess OS and create the survival curve. Logistic regression identified risk factors for metastasis: male gender [OR, 1.223; P < 0.001], Hist clear (OR, 9.37; P < 0.001), Hist papillary (OR, 2.49; P < 0.001), and TTX (OR, 23.33; P < 0.001). We found several independent prognostic variables: among which chemotherapy (HR, 0.64), local LND (HR, 0.67), and primary site surgery (HR, 0.97) were associated with better OS. Further study results demonstrated that all kinds of visceral metastasis except for liver metastasis in the operation group had substantially better prognoses than those in the non-operation group (P < 0.05). Regional LND had no discernible impact on survival. Patients with liver, lung, and distant lymph node (LN) metastasis benefited from chemotherapy (P < 0.05), but the bone and brain metastasis did not significantly benefit from treatment (P > 0.05). We recommend primary surgery for different types of visceral metastases except liver metastasis. Routine regional LND is not recommended. Chemotherapy should be considered for patients with lung, distant LN, and liver metastases, but not for those with bone and brain metastases.

Three-dimensional titanium mesh-based flow electrode capacitive deionization for salt separation and enrichment in high salinity water.

Flow electrode capacitive deionization (FCDI) is a highly promising desalination technique known for its exceptional electrosorption capacity, making it suitable for efficient salt separation in high salinity water. However, the unsatisfactory charge transfer process between the flow electrode and current collector severely curtails the salt separation and enrichment performance of the FCDI device. To address this issue, three-dimensional titanium mesh (3D-TM) was proposed as a novel current collector for FCDI device, which significantly amplifies the charge transfer area and exhibits excellent salt separation performance. The 3D-TM current collector promotes the electron transfer, charge percolation, and ion migration processes through the electroconvection generated by the turbulence effect on the flow electrode. In the specific case of the 20-mesh 3D-TM, which is composed of 12 stacking layers of titanium mesh, the remarkable average salt removal rate and charge efficiency were achieved 5.06 µmol cm-2 min-1 and 92.9 % under an appropriate applied voltage of 2.0 V, respectively. Dramatically, the desalination performance maintained above 76.4 % over 100 desalination cycles at 2.0 V, demonstrating the exceptional cyclic stability of the 3D-TM FCDI cell. In the seawater desalination, the 3D-TM FCDI cell exhibited an impressive salt removal efficiency of 97.5 % (from 34.2 g L-1 to 0.84 g L-1) for 1 L East China seawater at 2.0 V for 24 h. For lithium-ion enrichment, the FCDI continuous desalting system achieved an astonishing concentration of 17.3 g L-1 for Li+ ions enrichment from an initial concentration of 1.30 g L-1, obtaining the average salt treating rate of 23.6 g m-2h-1 and charge efficiency of 80.0 %. Moreover, the lithium-sodium ions and lithium-magnesium ions enrichments were both conducted, yielding an enriched concentration of 10.4 g L-1 and 7.30 g L-1 for Li+ ions, respectively. These findings highlight the enormous potential of FCDI technology in industrial engineering applications, further establishing it as a highly viable solution.

Oxygen-Coordinated Single Mn Sites for Efficient Electrocatalytic Nitrate Reduction to Ammonia.

Electrocatalytic nitrate reduction reaction has attracted increasing attention due to its goal of low carbon emission and environmental protection. Here, we report an efficient NitRR catalyst composed of single Mn sites with atomically dispersed oxygen (O) coordination on bacterial cellulose-converted graphitic carbon (Mn-O-C). Evidence of the atomically dispersed Mn-(O-C2)4 moieties embedding in the exposed basal plane of carbon surface is confirmed by X-ray absorption spectroscopy. As a result, the as-synthesized Mn-O-C catalyst exhibits superior NitRR activity with an NH3 yield rate (RNH3) of 1476.9 ± 62.6 µg h-1 cm-2 at - 0.7 V (vs. reversible hydrogen electrode, RHE) and a faradaic efficiency (FE) of 89.0 ± 3.8% at - 0.5 V (vs. RHE) under ambient conditions. Further, when evaluated with a practical flow cell, Mn-O-C shows a high RNH3 of 3706.7 ± 552.0 µg h-1 cm-2 at a current density of 100 mA cm-2, 2.5 times of that in the H cell. The in situ FT-IR and Raman spectroscopic studies combined with theoretical calculations indicate that the Mn-(O-C2)4 sites not only effectively inhibit the competitive hydrogen evolution reaction, but also greatly promote the adsorption and activation of nitrate (NO3-), thus boosting both the FE and selectivity of NH3 over Mn-(O-C2)4 sites.

Scorpion venom heat-resistant peptide alleviates mitochondrial dynamics imbalance induced by PM2.5 exposure by downregulating the PGC-1α/SIRT3 signaling pathway.

Background: Epidemiological inquiry reveals that neuroinflammation and mitochondrial dysfunction caused by PM2.5 exposure are associated with Alzheimer's disease. Nevertheless, the molecular mechanisms of mitochondrial dynamics and neuroinflammation induced by PM2.5 exposure remain elusive. In this study, our objective was to explore the impact of PM2.5 on mitochondrial dynamics and neuroinflammation, while also examining the reparative potential of scorpion venom heat-resistant synthetic peptide (SVHRSP). Methods: Western blot and quantitative reverse transcription polymerase chain reaction (RT-qPCR) were employed to ascertain the protein and gene levels of IL-1ß, IL-6, and TNF-α in BV2 cells. The concentration of IL-6 in the supernatant of the BV2 cell culture was measured by enzyme-linked immunosorbent assay. For the assessment of mitochondrial homeostasis, western blot, RT-qPCR, and cellular immunohistochemistry methods were utilized to investigate the protein and gene levels of DRP1 and MFN-2 in HT22 cells. In the context of signal pathway analyses, western blot, RT-qPCR, and immunofluorescence techniques were employed to detect the protein and gene expressions of PGC-1α and SIRT3 in HT22 cells, respectively. Following the transfection with siPGC-1αRNA, downstream proteins of PGC-1α/SIRT3 pathway in HT22 cells were investigated by Western blot and RT-qPCR. Results: The experimental findings demonstrated that exposure to PM2.5 exacerbated neuroinflammation, resulting in elevated levels of IL-1ß, IL-6, and TNF-α. Furthermore, it perturbed mitochondrial dynamics, as evidenced by increased DRP1 expression and decreased MFN-2 expression. Additionally, dysfunction was observed in the PGC-1α/SIRT3 signal pathway. However, intervention with SVHRSP ameliorated the cellular damage induced by PM2.5 exposure. Conclusions: SVHRSP alleviated neuroinflammation and mitochondrial dynamics imbalance induced by PM2.5 exposure by downregulating the PGC-1α/SIRT3 signaling pathway.

Atomically Dispersed Iron Regulating Electronic Structure of Iron Atom Clusters for Electrocatalytic H2 O2 Production and Biomass Upgrading.

The integration of highly active single atoms (SAs) and atom clusters (ACs) into an electrocatalyst is critically important for high-efficiency two-electron oxygen reduction reaction (2e- ORR) to hydrogen peroxide (H2 O2 ). Here we report a tandem impregnation-pyrolysis-etching strategy to fabricate the oxygen-coordinated Fe SAs and ACs anchored on bacterial cellulose-derived carbon (BCC) (FeSAs/ACs-BCC). As the electrocatalyst, FeSAs/ACs-BCC exhibits superior electrocatalytic activity and selectivity toward 2e- ORR, affording an onset potential of 0.78 V (vs. RHE) and a high H2 O2 selectivity of 96.5 % in 0.1 M KOH. In a flow cell reactor, the FeSAs/ACs-BCC also achieves high-efficiency H2 O2 production with a yield rate of 12.51±0.18 mol gcat -1 h-1 and a faradaic efficiency of 89.4 %±1.3 % at 150 mA cm-2 . Additionally, the feasibility of coupling the produced H2 O2 and electro-Fenton process for the valorization of ethylene glycol was explored in detail. The theoretical calculations uncover that the oxygen-coordinated Fe SAs effectively regulate the electronic structure of Fe ACs which are the 2e- ORR active sites, resulting in the optimal binding strength of *OOH intermediate for high-efficiency H2 O2 production.

Tailoring ionomer distribution in the catalyst layer via heteroatom-functionalization toward superior PEMFC performance.

We investigate in detail the influence of O, S, and N functionalization of Pt3Co/C catalysts on the proton exchange membrane fuel cell (PEMFC). The results demonstrated that N-functionalization is more beneficial for the distribution of the ionomer in the catalyst layer, resulting in a trade-off between oxygen and hydronium ion transport.

Vanadium Nitride Nanoparticles Grown on Carbon Fiber Cloth as an Advanced Binder-Free Anode for the Storage of Sodium and Potassium Ions.

The escalating demand for sustainable and high-performance energy storage systems has led to the exploration of alternative battery technologies for lithium-ion batteries. Sodium-ion batteries (SIBs) and potassium-ion batteries (PIBs) have emerged as promising candidates because of their abundant Na/K resources, inexpensive costs, and similar chemistries to lithium-ion batteries. However, inherent challenges, such as large ionic radii, sluggish kinetics, and serious volume expansion, necessitate the development of robust and efficient anode materials for SIBs and PIBs. Vanadium nitride has attracted increasing attention as a viable anode due to its high electronic conductivity and potential capacity. In this study, we report on a flexible electrode for SIBs and PIBs that creates binder-free anodes by synthesizing vanadium nitride nanoparticles grown directly on carbon fiber cloths (VN/CFC). The unique architecture and binder-free nature of this anode ensure a robust electrode-electrolyte interface and enhance its electron/ion transport kinetics. The results demonstrate that the material exhibits an outstanding specific discharge capacity of 227 mAh g-1 after undergoing 1000 cycles at a current density of 2 A g-1 for SIBs. An electrochemical analysis indicated that the excellent performance of the material is attributed to the bind-free structure of carbon fiber cloth and the fast kinetics of surface pseudo-capacitive contribution. Furthermore, the material continues to demonstrate an impressive performance, even for PIBs, with a specific discharge capacity of 125 mAh g-1 after 1000 cycles at a current density of 1 A g-1. This study provides a new perspective for designing and developing advanced binder-free anodes for the storage of sodium and potassium ions, paving the way for high-performance energy storage applications.

piRNA-1742 promotes renal cell carcinoma malignancy by regulating USP8 stability through binding to hnRNPU and thereby inhibiting MUC12 ubiquitination.

Accumulating studies have confirmed that PIWI-interacting RNAs (piRNAs) are considered epigenetic effectors in cancer. We performed piRNA microarray expression analysis on renal cell carcinoma (RCC) tumor tissues and paired normal tissues and performed a series of in vivo and in vitro experiments to explore piRNAs associated with RCC progression and investigate their functional mechanisms. We found that piR-1742 was highly expressed in RCC tumors and that patients with high piR-1742 expression had a poor prognosis. Inhibition of piR-1742 significantly reduced tumor growth in RCC xenograft and organoid models. Mechanistically, piRNA-1742 regulates the stability of USP8 mRNA by binding directly to hnRNPU, which acts as a deubiquitinating enzyme that inhibits the ubiquitination of MUC12 and promotes the development of malignant RCC. Subsequently, nanotherapeutic systems loaded with piRNA-1742 inhibitors were found to effectively inhibit the metastasis and growth of RCC in vivo. Therefore, this study highlights the functional importance of piRNA-related ubiquitination in RCC and demonstrates the development of a related nanotherapeutic system, possibly contributing to the development of therapeutic approaches for RCC.

Pt nanoparticle dispersed Ni(OH)2 nanosheets via a pulsed laser deposition method efficiently enhanced hydrogen evolution reaction performance in alkaline conditions.

The use of electrochemical water is a very attractive and environmentally friendly solution for hydrogen fuel production. Platinum (Pt) catalysts are considered to be the most active catalyst for the hydrogen evolution reaction (HER) but suffer from low efficiency and slow kinetics. Herein, Pt nanoparticles dispersed Ni(OH)2 nanosheets (Pt-Ni(OH)2-X) with different deposition times were designed and developed via a vapour-phase hydrothermal method, followed by a pulsed laser deposition method. The Pt-Ni(OH)2-5 only needs overpotentials of 247.5 ± 43 and 512.5 ± 18 mV to reach current densities of 10 and 100 mA cm-2, respectively, outperforming the commercial Pt/C at a current density of 100 mA cm-2. Furthermore, the infrared spectrum revealed that the adsorption of water molecules becomes stronger at the surface of the Pt-Ni(OH)2-5 nanosheets, and the hydrogen protons overflow onto the Pt surface and facilitate the HER process. This work suggests that moderate Pt nanoparticle dispersed Ni(OH)2 nanosheet help to promote the hydrogen production process.

Robust Face Alignment via Inherent Relation Learning and Uncertainty Estimation.

Human tends to locate the facial landmarks with heavy occlusion by their relative position to the easily identified landmarks. The clue is defined as the landmark inherent relation while it is ignored by most existing methods. In this paper, we present Dynamic Sparse Local Patch Transformer (DSLPT), a novel face alignment framework for the inherent relation learning and uncertainty estimation. Unlike most existing methods that regress facial landmarks directly from global features, the DSLPT first generates a rough representation of each landmark from a local patch cropped from the feature map and then adaptively aggregates them by a case dependent inherent relation. Finally, the DSLPT predicts the coordinate and uncertainty of each landmark by regressing their probability distribution from the output features. Moreover, we introduce a coarse-to-fine framework to incorporate with DSLPT for an improved result. In the framework, the position and size of each patch are determined by the probability distribution of the corresponding landmark predicted in the previous stage. The dynamic patches will ensure a fine-grained landmark representation for inherent relation learning so that a rough prediction result can gradually converge to the target facial landmarks. We integrate the coarse-to-fine model into an end-to-end training pipeline and carry out experiments on the mainstream benchmarks. The results demonstrate that the DSLPT achieves state-of-the-art performance with much less computational complexity. The codes and models are available at https://github.com/Jiahao-UTS/DSLPT.

Learning Graph Representations Through Learning and Propagating Edge Features.

Graph convolutional networks have achieved considerable success in various graph domain tasks. Recently, numerous types of graph convolutional networks have been developed. A typical rule for learning a node's feature in these graph convolutional networks is to aggregate node features from the node's local neighborhood. However, in these models, the interrelation information between adjacent nodes is not well-considered. This information could be helpful to learn improved node embeddings. In this article, we present a graph representation learning framework that generates node embeddings through learning and propagating edge features. Instead of aggregating node features from a local neighborhood, we learn a feature for each edge and update a node's representation by aggregating local edge features. The edge feature is learned from the concatenation of the edge's starting node feature, the input edge feature, and the edge's end node feature. Unlike node feature propagation-based graph networks, our model propagates different features from a node to its neighbors. In addition, we learn an attention vector for each edge in aggregation, enabling the model to focus on important information in each feature dimension. By learning and aggregating edge features, the interrelation between a node and its neighboring nodes is integrated in the aggregated feature, which helps learn improved node embeddings in graph representation learning. Our model is evaluated on graph classification, node classification, graph regression, and multitask binary graph classification on eight popular datasets. The experimental results demonstrate that our model achieves improved performance compared with a wide variety of baseline models.

Boosting Electroreduction Kinetics of Nitrogen to Ammonia via Atomically Dispersed Sn Protuberance.

Atomically dispersed metal catalysts show potential advantages in N2 reduction reaction (NRR) due to their excellent activity and efficient metal utilization. Unfortunately, the reported catalysts usually exhibit unsatisfactory NRR activity due to their poor N2 adsorption and activation. Herein, we report a novel Sn atomically dispersed protuberance (ADP) by coordination with substrate C and O to induce positive charge accumulation on Sn site for improving its N2 adsorption, activation and NRR performance. The extended X-ray absorption fine structure (EXAFS) spectra confirmed the local coordination structure of the Sn ADPs. NRR activity was significantly promoted via Sn ADPs, exhibiting a remarkable NH3 yield (RNH3 ) of 28.3 µg h-1 mgcat -1 (7447 µg h-1 mgSn -1 ) at -0.3 V. Furthermore, the enhanced N2 Hx intermediates was verified by in situ experiments, yielding consistent results with DFT calculation. This work opens a new avenue to regulate the activity and selectivity of N2 fixation.

Ni-Co Alloy Nanoparticles Catalyze Selective Electrochemical Coupling of Nitroarenes into Azoxybenzene Compounds in Aqueous Electrolyte.

In theory, electrocatalysts in their metallic forms should be the most stable chemical state under cathodic potentials. It is known that the highly dispersed nanoparticle (NP) types of electrocatalysts often possess higher activity than their bulk counterparts. However, facilely and controllably fabricating well-dispersed nonprecious metal NPs with superior electrocatalytic activity, selectivity, and durability is highly challenging. Here, we report a facile reductive pyrolysis approach to controllably synthesize NiCo alloy NPs confined on the tip of N-doped carbon nanotubes (N-CNTs) from a bimetal-MOF precursor. The electrocatalytic performance of the resultant NiCo@N-CNTs are evaluated by a wide spectrum of nitroarene reductive coupling reactions to produce azoxy-benzenes, a class of precious chemicals for textile, food, cosmetic, and pharmaceutical industries. The superior electrocatalytic stability, full conversion of nitroarenes, >99% selectivities, and >97% faradic efficiencies toward the targeted azoxy-benzene products are readily attainable by NiCo@N-CNTs, attributable to the alloying-induced synergetic effect. The presence of a CNT confinement effect in NiCo@N-CNTs induces high stability. This added to the metallic states of NiCo empowers NiCo@N-CNTs with excellent electrochemical stability under reductive reaction conditions. In an effort to enhance the energy utilization efficiency, we construct a NiCo@N-CNTs||Ni(OH)2/NF two-electrode electrolyzer to simultaneously reduce nitrobenzene at the cathode and 5-hydroxymethylfurfural with >99% yields for both azoxy-benzene and 2,5-furandicarboxylic acid.

CircCDR1as mediates PM2.5-induced lung cancer progression by binding to SRSF1.

Research indicates that particulate matter with an aerodynamic equivalent diameter of less than or equal to 2.5 µm in ambient air may induce lung cancer progression. Circular RNAs are a special kind of endogenous noncoding RNA, and their functions are reflected in various diseases and physiological processes, but there are still few studies related to PM2.5-induced lung cancer. Here, we identified that circCDR1as was upregulated in lung cancer cells stimulated with PM2.5 and positively correlated with the malignant features of lung cancer. The lower expression of CircCDR1as reduced the adverse progression of lung cancer cells after PM2.5 treatment; the lower expression of circCDR1as impaired the growth size and metastatic ability of lung cancer cells in mouse tumour models. Mechanistically, circCDR1as specifically bound to serine/arginine-rich splicing Factor 1 (SRSF1) and affected the splicing of vascular endothelial growth factor-A (VEGFA) by SRSF1. Furthermore, circCDR1as affected SRSF1 function by regulating PARK2-mediated SRSF1 ubiquitination, protein production and degradation. CircCDR1as also affected C-myc and cyclin D1 expression by regulating SRSF1 and affecting the wnt/ß-catenin signalling pathway, ultimately promoting malignant behavior and inhibiting the apoptosis of lung cancer cells, thereby causing PM2.5-induced lung cancer development.

Ambient Electrosynthesis of Urea with Nitrate and Carbon Dioxide over Iron-Based Dual-Sites.

The development of efficient electrocatalysts to generate key *NH2 and *CO intermediates is crucial for ambient urea electrosynthesis with nitrate (NO3 - ) and carbon dioxide (CO2 ). Here we report a liquid-phase laser irradiation method to fabricate symbiotic graphitic carbon encapsulated amorphous iron and iron oxide nanoparticles on carbon nanotubes (Fe(a)@C-Fe3 O4 /CNTs). Fe(a)@C-Fe3 O4 /CNTs exhibits superior electrocatalytic activity toward urea synthesis using NO3 - and CO2 , affording a urea yield of 1341.3±112.6 µg h-1 mgcat -1 and a faradic efficiency of 16.5±6.1 % at ambient conditions. Both experimental and theoretical results indicate that the formed Fe(a)@C and Fe3 O4 on CNTs provide dual active sites for the adsorption and activation of NO3 - and CO2 , thus generating key *NH2 and *CO intermediates with lower energy barriers for urea formation. This work would be helpful for design and development of high-efficiency dual-site electrocatalysts for ambient urea synthesis.

Hydrogen Peroxide Assisted Electrooxidation of Benzene to Phenol over Bifunctional Ni-(O-C2 )4 Sites.

Direct electrocatalytic oxidation of benzene has been regarded as a promising approach for achieving high-value phenol product, but remaining a huge challenge. Here an oxygen-coordinated nickel single-atom catalyst (Ni-O-C) is reported with bifunctional electrocatalytic activities toward the two-electron oxygen reduction reaction (2e- ORR) to H2 O2 and H2 O2 -assisted benzene oxidation to phenol. The Ni-(O-C2 )4 sites in Ni-O-C ar proven to be the catalytic active centers for bifunctional 2e- ORR and H2 O2 -assisted benzene oxidation processes. As a result, Ni-O-C can afford a benzene conversion as high as 96.4 ± 3.6% with a phenol selectivity of 100% and a Faradaic efficiency (FE) of 80.2 ± 3.2% with the help of H2 O2 in 0.1 m KOH electrolyte at 1.5 V (vs RHE). A proof of concept experiment with Ni-O-C concurrently as cathode and anode in a single electrochemical cell demonstrates a benzene conversion of 33.4 ± 2.2% with a phenol selectivity of 100% and a FE of 44.8 ± 3.0% at 10 mA cm-2 .