ABSTRACT
Artificial photosynthesis for hydrogen peroxide (H2O2) presents a sustainable and environmentally friendly approach to generate clean fuel and chemicals. However, the catalytic activity is hindered by challenges such as severe charge recombination, insufficient active sites, and poor selectivity. Here, a robust strategy is proposed to regulate the electronic structure of catalyst by the collaborative effect of defect engineering and dopant. The well designed oxygen-doped CdS nanorods with S2- defects and Cd2+ 4d10 electron configuration (CdS-O,Sv) is successfully synthesized, and the Cd2+ active sites around S defects or oxygen atoms exhibit rapid charge separation, suppressed carrier recombination, and enhanced charge utilization. Consequently, a remarkable H2O2 production rate of 1.62 mmol g-1 h-1 under air conditions is acquired, with an apparent quantum yield (AQY) of 9.96% at a single wavelength of 450 nm. This work provides valuable insights into the synergistic effect between defect and doping on catalytic activity.
ABSTRACT
Immobilizing Fe-based nanoparticles on electron-rich biochar has becoming an attractive heterogeneous Fenton-like catalysts (Fe/BC) for wastewater decontamination. However, the insufficient graphitization of biochar causing low electron transfer and by slow H2O2 activation limited its application. Herein, we firstly constructed FeS/biochar composite through all-solid molten salt method (Fe/MSBCs), which can provide strong polarization force and liquid reaction environment to improve carbonization. As expected, the obtained Fe/MSBCs exhibits high surface area and fast interfacial electron transfer between FeS and biochar. More importantly, the partially oxidized FeS (001) facet facilitate H2O2 adsorption and thermodynamically easily decomposition into â¢OH. Such a synergistic effect endowed them excellent photo-Fenton degradation performance for methyl orange (MO) with large kinetic rate constants (0.079 min-1) and high H2O2 utilization efficiency (95.9%). This study first demonstrated the critical regulatory role of molten salt method in iron-based biochar composites, which provide an alternative for H2O2 activator in water pollutant control.
Subject(s)
Electrons , Hydrogen Peroxide , Ferrous Compounds , Charcoal , Oxidation-ReductionABSTRACT
Hepatocellular carcinoma (HCC) is the fifth most common malignancy and the third leading cause of cancer-related death worldwide. HCC exhibits strong inter-tumor heterogeneity, with different biological characteristics closely associated with prognosis. In addition, patients with HCC often distribute at different stages and require diverse treatment options at each stage. Due to the variability in tumor sensitivity to different therapies, determining the optimal treatment approach can be challenging for clinicians prior to treatment. Artificial intelligence (AI) technology, including radiomics and deep learning approaches, has emerged as a unique opportunity to improve the spectrum of HCC clinical care by predicting biological characteristics and prognosis in the medical imaging field. The radiomics approach utilizes handcrafted features derived from specific mathematical formulas to construct various machine-learning models for medical applications. In terms of the deep learning approach, convolutional neural network models are developed to achieve high classification performance based on automatic feature extraction from images. Magnetic resonance imaging offers the advantage of superior tissue resolution and functional information. This comprehensive evaluation plays a vital role in the accurate assessment and effective treatment planning for HCC patients. Recent studies have applied radiomics and deep learning approaches to develop AI-enabled models to improve accuracy in predicting biological characteristics and prognosis, such as microvascular invasion and tumor recurrence. Although AI-enabled models have demonstrated promising potential in HCC with biological characteristics and prognosis prediction with high performance, one of the biggest challenges, interpretability, has hindered their implementation in clinical practice. In the future, continued research is needed to improve the interpretability of AI-enabled models, including aspects such as domain knowledge, novel algorithms, and multi-dimension data sources. Overcoming these challenges would allow AI-enabled models to significantly impact the care provided to HCC patients, ultimately leading to their deployment for clinical use. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.
Subject(s)
Carcinoma, Hepatocellular , Deep Learning , Liver Neoplasms , Humans , Radiomics , Artificial Intelligence , Prognosis , Magnetic Resonance ImagingABSTRACT
To investigate the long-term effects of 2 commonly used low-osmolar contrast media, iohexol and iopromide, on renal function and survival in patients who underwent coronary angiography. A total of 14,141 cardiology patients from 2006 to 2013 were recruited, of whom 1,793 patients (679 patients on iohexol and 1,114 on iopromide) were evaluated for long-term renal impairment and 5,410 patients (1,679 patients on iohexol and 3,731 on iopromide) were admitted for survival analyses spanning as long as 15 years. Univariate and multivariate logistic regression were used to explore the risk factors for long-term renal impairment. Cox proportional hazard regression was used to investigate the risk factors affecting survival. Propensity score matching and inverse probability of treatment weighting were applied to balance the baseline clinical characteristics. Patients receiving iohexol demonstrated a greater occurrence of renal impairment compared with those who received iopromide. Such difference remained consistent both before and after propensity score matching or inverse probability of treatment weighting, with a statistical significance of p <0.05. Among clinical variables, receiving contrast-enhanced contrast tomography/magnetic resonance imaging during follow-up, antihypertensive medication usage, presence of proteinuria, and anemia were identified as risk factors for long-term renal impairment (p = 0.041, 0.049, 0.006, and 0.029, respectively). During survival analyses, the difference was insignificant after propensity score matching and inverse probability of treatment weighting. In conclusion, administration of iohexol was more likely to induce long-term renal impairment than iopromide, particularly among patients diagnosed with anemia and proteinuria and those taking antihypertensive medication and with additional contrast exposure. The all-cause mortality, however, showed no significant difference between iohexol and iopromide administration.
Subject(s)
Anemia , Renal Insufficiency , Humans , Iohexol/adverse effects , Coronary Angiography/adverse effects , Coronary Angiography/methods , Contrast Media/adverse effects , Antihypertensive Agents , Renal Insufficiency/chemically induced , Renal Insufficiency/epidemiology , Proteinuria/chemically induced , Triiodobenzoic Acids/adverse effectsABSTRACT
Modulation of the nanozyme's catalytic activity is crucial for its real applications in detecting target analytes. Herein, we fabricated the nanocomposite (NSC/Co6Ni3S8) of N, S co-doped carbon and Co6Ni3S8 by a facile sol-gel approach. Compared to NSC/Ni9S8, NSC/Co6Ni3S8 with bimetallic active sites displayed better enzyme-mimetic activity. This nanocomposite could catalyze O2 to form ·O2- and oxidize colorless 3, 3', 5, 5'-tetramethylbenzidine (TMB) into blue oxTMB. The other two free radicals (h+ and ·OH) played minor roles during the catalytic reaction. Hg2+ could integrate with S2- to form HgS and the surface charges of O2 were transferred to Hg2+ to promote O2 adsorption. DFT theoretical calculations highlight that the main reasons for the enhancing effect of Hg2+ on color development results from electron transfer and increased adsorption energy of O2 molecules onto the surface of NSC/Co6Ni3S8. By employing the oxidase-like activity of NSC/Co6Ni3S8 and Hg2+-triggered promoting effect, a colorimetric sensing platform was established for Hg2+ assay with a linear range of 10-200 µg/L and detection limit of 3 µg/L. Through integration with a smartphone-based APP "Thing Identify" software, a visual colorimetric assay for Hg2+ was constructed with a detection limit of 5 µg/L. Compared to the data detected by the mercury vapor meter, the relative recoveries of 92.4-108.1% evidenced the higher accuracy of this smartphone-based visual detection. Overall, the NSC/Co6Ni3S8-based colorimetric assay is convenient, rapid, and visual, and can be applied for routine monitoring of Hg2+ in real-world waters under outdoor conditions.
Subject(s)
Mercury , Nanocomposites , Smartphone , ColorimetryABSTRACT
Cobalt (Co) and oxides are the most common catalysts for activating peroxymonosulfate (PMS). However, practical applications of Co-based PMS-advanced oxidation processes are difficult to realize the degradation of the targeted pollutants due to poor yield of reactive oxygen species (ROS) and inaccessible active sites. Here, we designed 3D oxygen vacancy-rich (Vo-rich) variable Co species@carbon foam (CoxOy@CF) via coupling solvent-free and pyrolysis strategies for degrading tetracycline by PMS activation. The kinetic rate of optimized (Co@CoO) CoxOy@CF-1.0 (1.0 presented the molar ratio of Co2+ and 2-methylimidazole) enhanced by an order of magnitude compared to that of ZIFs derivatives (ZIFs-500) (0.073 vs 0.155 min-1) due to the special structure. The flow-through unit maintained over 90% removal within 12 h, which was far better than that of ZIFs-500/PMS system. We used electrochemical analysis, quenching experiment, in-situ FTIR and Raman spectra to further investigate the possible mechanism of the 3D CoxOy@CF-1.0/PMS system. 3D CoxOy@CF-1.0 stimulated the production of the metastable catalyst-PMS* complex obtained O2- as intermediates accompanied by the redox cycling of Co2+/Co3+, which created the dominant ROS (more 1O2) in the presence of Vo, which was completely different for ZIFs-500/PMS with coordinated and dominant radical and non-radical pathways. This study could large-scale generate variable cobalt-based catalysts for enhanced ROS generation, leading the new insight for boosting practical applications.
ABSTRACT
Photocatalytic hydrogen peroxide (H2O2) production will become a burgeoning strategy for solar energy utilization by selective oxygen reduction reaction (ORR). Polymeric carbon nitride (PCN) shows relatively high two-electron ORR selectivity for H2O2 production but still limited low H2O2 production efficiency due to slow exciton dissociation. Herein, we constructed a heptazine/triazine layer stacked carbon nitride heterojunction with fluorine/potassium (F/K) dual sites (FKHTCN). The introduction of F/K not only can regulate layer components to enhance the charge separation efficiency but, more importantly, also optimize the adsorption of surface oxygen molecules and intermediate *OOH during H2O2 production. Consequently, FKHTCN efficiently improves the photocatalytic H2O2 production rate up to 3380.9 µmol h-1 g-1, nearly 15 times higher than that of traditional PCN. Moreover, a production-utilization cascade system was designed to explore their practical application in environmental remediation. This work lays out the importance of engineering a layer-stacked configuration and active sites for enhancing photocatalysis.
ABSTRACT
The enhancement of the self-cleaning ability of photocatalytic membranes and their degradation efficiency over tetracycline (TC) still remains a challenge. In this study, an alternative silver vanadate quantum dots (AgVO3 QDs) doped reduced graphene oxide (RGO) and graphitic carbon nitride (C3N4) nanocomposites modified polyvinylidene fluoride (PVDF) membrane (AgVO3/RGO/C3N4-PVDF) was successfully fabricated to enhance the photocatalytic activity. The AgVO3/RGO/C3N4 nanocomposites were functioned as the active component for the photocatalytic membrane. The unique Z-scheme heterostructure of AgVO3/RGO/C3N4 and the porous PVDF framework synergistically enhanced the separation and transport efficiency of photogenerated carriers and facilitated the interaction between the photocatalyst and the pollutant. As a result, the degradation efficiency of TC for the AgVO3/RGO/C3N4-PVDF reached 88.53% within 120 min, which was higher than those of the binary component membranes (64.8% for RGO/C3N4-PVDF and 79.18% AgVO3/C3N4-PVDF). In addition, AgVO3/RGO/C3N4-PVDF exhibited high permeability (1977 L·m-2·h-1·bar-1) and excellent antifouling activity. Under visible-light irradiation, the flux recovery rate (FRR) increased from 92.4% to 99.1%. Furthermore, AgVO3/RGO/C3N4-PVDF could reject 97.4% of Escherichia coli (E. coli) owning to its self-cleaning capacity, and eliminated the E. coli under visible-light irradiation trough the photogeneration of h+. This study highlights a highly efficient photocatalytic membrane based on a Z-scheme heterostructure, which may have a great potential application in practical wastewater treatment.
Subject(s)
Quantum Dots , Catalysis , Escherichia coli , Fluorocarbon Polymers , Graphite , Nitrogen Compounds , Polyvinyls , Silver Compounds , VanadatesABSTRACT
Photocatalytic materials can be used as self-cleaning functional materials to alleviate the irreversible fouling of ultrafiltration membranes. In this work, the small size g-C3N4/Bi2MoO6 (SCB) blended polysulfone (PSF) ultrafiltration membranes was fabricated by hydrothermal and phase inversion methods. As a functional filler of ultrafiltration membranes, the small size g-C3N4 nanosheet decorated on the surface of Bi2MoO6 can enhance the photocatalytic performance for bovine serum albumin (BSA) degradation, and remove irreversible fouling under visible light irradiation. In addition, the introduction of SCB microspheres into PSF matrix obviously increased the porosity of ultrafiltration membranes. Therefore, the SCB-PSF ultrafiltration membranes displayed excellent antifouling performance (flux recovery ratio is 82.53%) and BSA rejection rates (94.77%). SCB-PSF also had high photocatalytic self-cleaning activity, indicating excellent application prospects in organic wastewater treatment.
ABSTRACT
Designing photocatalytic membranes with excellent photocatalytic and self-cleaning ability based on the synergistic effect between the crystal structure of membrane matrix and photocatalyst is highly desirable. Herein, Z-scheme 2D/3D g-C3N4/BiOI heterojunction blended in beta-phase polyvinylidene fluoride membrane (ß-phase PVDF) was prepared via solvent crystallization and phase inversion technique. As expected, the designed g-C3N4/BiOI/ß-phase PVDF photocatalytic membranes (CN/BI/ß-phase PVDF PMs) achieved exceptional photocatalytic degradation efficiency for tetracycline (94.6%) as compared to the CN/BI heterojunction power (84.0%) and two other control membrane matrixes (CN/BI/PAN and CN/BI/CA PMs) within 120 min. Meanwhile, the dynamic cyclic degradation system of CN/BI/ß-phase PVDF PMs was also investigated that reached to be 94.8% in 80 min. Besides, the CN/BI/ß-phase PVDF PMs not only had outstanding self-cleaning activity and remarkable permeability (up to 30,688 L·m-2·h-1) but also had high stability and reusability even after five runs. Importantly, the hydroxyl radical detection and ESR analysis identified that the ß-phase PVDF membrane could promote photoinduced carrier separation efficiency of 2D/3D g-C3N4/BiOI heterojunction. This work may open up a novel strategy for designing and constructing high-efficient photocatalytic membranes for water treatment.