Carbon nanotube@silicon carbide coaxial heterojunction nanotubes as metal-free photocatalysts for enhanced hydrogen evolution

Pd(II) coordination molecule modified g-C3N4 for boosting photocatalytic hydrogen production

The photocatalytic H2 production activity of polymer carbon nitride (g-C3N4) is limited by the rapid recombination of photoelectron-hole pairs and slow surface reduction dynamic process. Here, a supramolecular complex (named R-TAP-Pd(II)) was fabricated via self-assembly of (R)-N-(1-phenylethyl)-4-(4-(pyridin-2-yl)-1H-1,2,3-triazol-1-yl)benzamide (R-TAP) with Pd(II) and used to modify g-C3N4. In the R-TAP-Pd(II)@g-C3N4 composite photocatalyst, the spin polarization of R-TAP-Pd(II) can promote charge transfer and inhibit photogenerated carrier recombination, as confirmed by spectral tests and photoelectrochemical performance tests. Electrochemical tests and in situ X-ray photoelectron spectroscopy (XPS) tests proved that the Pd(II) ion in the R-TAP-Pd(II) molecule can serve as active sites to accelerate H2 production. The R-TAP-Pd(II)@g-C3N4 presented a photocatalytic H2 generation rate of 1085 μmol g-1 h-1 when exposed to visible light, which was a about 278-fold increase compared with g-C3N4. This work finds a new approach to boost the photocatalytic efficiency of g-C3N4 via supramolecular self-assembly.

Machine learning-enhanced drug testing for simultaneous morphine and methadone detection in urinary biofluids

The simultaneous identification of drugs has considerable difficulties due to the intricate interplay of analytes and the interference present in biological matrices. In this study, we introduce an innovative electrochemical sensor that overcomes these hurdles, enabling the precise and simultaneous determination of morphine (MOR), methadone (MET), and uric acid (UA) in urine samples. The sensor harnesses the strategically adapted carbon nanotubes (CNT) modified with graphitic carbon nitride (g-C3N4) nanosheets to ensure exceptional precision and sensitivity for the targeted analytes. Through systematic optimization of pivotal parameters, we attained accurate and quantitative measurements of the analytes within intricate matrices employing the fast Fourier transform (FFT) voltammetry technique. The sensor's performance was validated using 17 training and 12 test solutions, employing the widely acclaimed machine learning method, partial least squares (PLS), for predictive modeling. The root mean square error of cross-validation (RMSECV) values for morphine, methadone, and uric acid were significantly low, measuring 0.1827 µM, 0.1951 µM, and 0.1584 µM, respectively, with corresponding root mean square error of prediction (RMSEP) values of 0.1925 µM, 0.2035 µM, and 0.1659 µM. These results showcased the robust resiliency and reliability of our predictive model. Our sensor's efficacy in real urine samples was demonstrated by the narrow range of relative standard deviation (RSD) values, ranging from 3.71 to 5.26%, and recovery percentages from 96 to 106%. This performance underscores the potential of the sensor for practical and clinical applications, offering precise measurements even in complex and variable biological matrices. The successful integration of g-C3N4-CNT nanocomposites and the robust PLS method has driven the evolution of sophisticated electrochemical sensors, initiating a transformative era in drug analysis.

Near-Infrared-Responsive Photocatalysts

Broadening the absorption of light to the near-infrared (NIR) region is important in photocatalysis to achieve efficient solar-to-fuel conversion. NIR-responsive photocatalysts that can utilize diffusive solar energy are attractive for alleviating the energy crisis and environmental pollution. Over the past few years, considerable progress on the component and structural design of NIR-responsive photocatalysts have been reported. This study aims to systematically summarize recent progress toward the material design and mechanism optimization of NIR-responsive photocatalysts in this area. Depending on the main strategies for harvesting NIR photons, NIR-responsive photocatalysts can be categorized as direct NIR-light photocatalysts, indirect NIR-light photocatalysts, and photothermal photocatalysts. Furthermore, the construction and application of different NIR-responsive photocatalytic systems are summarized. Conclusions and perspectives are presented to further explore the potential of NIR-responsive photocatalysts in this field.

Theoretically guiding the construction of a novel Cu2O@Cu97P3@Cu3P heterojunction with a 3D hierarchical structure for efficient photocatalytic hydrogen evolution

Using photocatalysis to produce clean H2 energy has been considered as one of the ideal strategies to alleviate the energy crisis and environmental pollution. In this work, the density functional theory (DFT) calculation was used as a guide to determine the experimental scheme of surface modification of Cu2O with Cu3P. With Cu2O as the core and Cu3P as the shell, the precursor was constructed by electrostatic self-assembly at first. After secondary calcination, Cu97P3 was formed from the compact interface between Cu2O and Cu3P, thus the 3D hierarchical structure of Cu-O-P(Cu2O@Cu97P3@Cu3P) was successfully constructed. The generation of Cu97P3 significantly increases the photocatalytic H2 production of Cu2O@Cu97P3@Cu3P under visible light irradiation. The photocatalytic activity of the composite with optimal ratio increased about 17 times as much as that of pure Cu2O. The separation and transportation efficiency of its photogenerated charges has been significantly improved. The 3D hierarchical core-shell structure is not only beneficial to strengthen the interface contact between different semiconductors but also to improve the transferability of photogenerated electrons. Through a series of experimental results, the strategy has proved to be successful that Cu3P was introduced onto the surface of the Cu2O octahedron to change the adsorption free energy of H atoms, reduce the overpotential of hydrogen evolution, and increase the active sites of hydrogen production. At the same time, the isolated interfaces are integrated by calcination to obtain Cu97P3 bridged substances derived from the interfaces. The presence of Cu97P3 establishes a new fast channel for electron flow between semiconductors, significantly accelerates the transfer of electrons, and ultimately improves the performance of photocatalytic hydrogen evolution. This work provides new insights into the design and flexible synthesis of inexpensive copper-based nano-photocatalysts.

In Situ Photodeposited Construction of Pt-CdS/g-C3N4-MnOx Composite Photocatalyst for Efficient Visible-Light-Driven Overall Water Splitting

For converting the renewable solar energy to hydrogen (H₂) energy by photocatalytic (PC) overall water splitting (OWS), visible-light-driven photocatalysts are especially desired. Herein, a model CdS/g-C₃N₄ photocatalyst with a type II heterojunction is first demonstrated via a facile coupling of g-C₃N₄ nanosheets and CdS nanorods. After being combined with in situ photodeposited 3 wt % Pt and 4 wt % MnO_x dual cocatalysts simultaneously, the optimal visible-light-driven (λ > 400 nm) composite photocatalyst of Pt-CdS/g-C₃N₄-MnO_x gives a H₂ generation rate of 9.244 μmol h^-1 (924.4 μmol h^-1 g^-1) and a O₂ evolution rate of 4.6 μmol h^-1 (460 μmol h^-1 g^-1) in pure water, which is over 420 times higher than that of pure CdS nanorods loaded with 0.5 wt % Pt. The apparent quantum efficiency (AQE) reaches about 3.389% (at 400 nm) and 1.745% (at 420 nm), respectively. The combination of a type II heterojunction and simultaneous in situ photodeposition of the dual cocatalysts results in a dramatically improved PC efficiency and a long-term stability of the CdS/g-C₃N₄ visible-light-driven photocatalyst for OWS.