LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis.

In the field of lipidomics, where the complexity of lipid structures and functions presents significant analytical challenges, LipidSig stands out as the first web-based platform providing integrated, comprehensive analysis for efficient data mining of lipidomic datasets. The upgraded LipidSig 2.0 (https://lipidsig.bioinfomics.org/) simplifies the process and empowers researchers to decipher the complex nature of lipids and link lipidomic data to specific characteristics and biological contexts. This tool markedly enhances the efficiency and depth of lipidomic research by autonomously identifying lipid species and assigning 29 comprehensive characteristics upon data entry. LipidSig 2.0 accommodates 24 data processing methods, streamlining diverse lipidomic datasets. The tool's expertise in automating intricate analytical processes, including data preprocessing, lipid ID annotation, differential expression, enrichment analysis, and network analysis, allows researchers to profoundly investigate lipid properties and their biological implications. Additional innovative features, such as the 'Network' function, offer a system biology perspective on lipid interactions, and the 'Multiple Group' analysis aids in examining complex experimental designs. With its comprehensive suite of features for analyzing and visualizing lipid properties, LipidSig 2.0 positions itself as an indispensable tool for advanced lipidomics research, paving the way for new insights into the role of lipids in cellular processes and disease development.

Suppressing the Shuttle Effect of Aqueous Zinc-Iodine Batteries: Progress and Prospects.

Aqueous zinc-iodine batteries are considered to be one of the most promising devices for future electrical energy storage due to their low cost, high safety, high theoretical specific capacity, and multivalent properties. However, the shuttle effect currently faced by zinc-iodine batteries causes the loss of cathode active material and corrosion of the zinc anodes, limiting the large-scale application of zinc-iodine batteries. In this paper, the electrochemical processes of iodine conversion and the zinc anode, as well as the induced mechanism of the shuttle effect, are introduced from the basic configuration of the aqueous zinc-iodine battery. Then, the inhibition strategy of the shuttle effect is summarized from four aspects: the design of cathode materials, electrolyte regulation, the modification of the separator, and anode protection. Finally, the current status of aqueous zinc-iodine batteries is analyzed and recommendations and perspectives are presented. This review is expected to deepen the understanding of aqueous zinc-iodide batteries and is expected to guide the design of high-performance aqueous zinc-iodide batteries.

One-step sintering construction of electromagnetic synergistic Co7Fe3/Co@CBC nanocomposites for enhanced microwave absorption properties.

Based on the synergistic modulation of electromagnetic parameters and microstructure design, multidimensional porous magnetic carbon-based nanocomposites have become ideal materials with efficient absorption properties. What's more, a carbon-magnetic alloy composite is a commonly used and efficient microwave absorber. In this paper, Co7Fe3/Co@CBC (CFCC) nanocomposites with strong magnetism, a three-phase composition, and a three-dimensional porous structure were synthesized by reducing Fe2+ and Co2+ using chestnut-shell biomass carbon (CBC). Biomass carbon with a higher specific surface area provides numerous active sites for Co7Fe3 nanosheets and Co nanospheres to form three-dimensional ping-pong chrysanthemum-like nanocomposites, which generate rich heterogeneous interfaces and conductive network structures. By adjusting the amount of added biomass, the electromagnetic parameters can be effectively regulated to achieve efficient microwave absorption properties. When the amount of biomass added varies within the range of 1.0 to 2.5 g, all samples exhibit a favorable effective absorption bandwidth (EAB) of over 5.88 GHz. In particular, the CFCC-2.0 composite exhibits optimal microwave absorption properties, with a minimum reflection loss (RLmin) value of -59.25 dB and an EAB of 6.34 GHz at a thickness of 2.8 mm. The simulation and modeling analysis results of radar cross section (RCS) further confirm the exceptional attenuation capability of composite materials at multiple incident angles. The exceptional microwave absorption properties and stability of EAB for the Co7Fe3/Co@CBC nanocomposite make it a promising candidate in the field of absorbing materials. This work also provides some feasible ideas for designing stable broadband wave-absorbing materials.

Advances in Carbon Dot-Based Ratiometric Fluorescent Probes for Environmental Contaminant Detection: A Review.

Detecting environmental contaminants is crucial for protecting ecosystems and human health. While traditional carbon dot (CD) fluorescent probes are versatile, they may suffer from limitations like fluctuations in signal intensity, leading to detection inaccuracies. In contrast, ratiometric fluorescent probes, designed with internal self-calibration mechanisms, offer enhanced sensitivity and reliability. This review focuses on the design and applications of ratiometric fluorescent probes based on CDs for environmental monitoring. Our discussion covers construction strategies, ratiometric fluorescence principles, and applications in detecting various environmental contaminants, including organic pollutants, heavy metal ions, and other substances. We also explore associated advantages and challenges and provide insights into potential solutions and future research directions.

DriverDBv4: a multi-omics integration database for cancer driver gene research.

Advancements in high-throughput technology offer researchers an extensive range of multi-omics data that provide deep insights into the complex landscape of cancer biology. However, traditional statistical models and databases are inadequate to interpret these high-dimensional data within a multi-omics framework. To address this limitation, we introduce DriverDBv4, an updated iteration of the DriverDB cancer driver gene database (http://driverdb.bioinfomics.org/). This updated version offers several significant enhancements: (i) an increase in the number of cohorts from 33 to 70, encompassing approximately 24 000 samples; (ii) inclusion of proteomics data, augmenting the existing types of omics data and thus expanding the analytical scope; (iii) implementation of multiple multi-omics algorithms for identification of cancer drivers; (iv) new visualization features designed to succinctly summarize high-context data and redesigned existing sections to accommodate the increased volume of datasets and (v) two new functions in Customized Analysis, specifically designed for multi-omics driver identification and subgroup expression analysis. DriverDBv4 facilitates comprehensive interpretation of multi-omics data across diverse cancer types, thereby enriching the understanding of cancer heterogeneity and aiding in the development of personalized clinical approaches. The database is designed to foster a more nuanced understanding of the multi-faceted nature of cancer.

Guiding the Driving Factors on Plasma Super-Photothermal S-Scheme Core-Shell Nanoreactor to Enhance Photothermal Catalytic H2 Evolution and Selective CO2 Reduction.

Light-induced heat has a non-negligible role in photocatalytic reactions. However, it is still challenging to design highly efficient catalysts that can make use of light and thermal energy synergistically. Herein, the study proposes a plasma super-photothermal S-scheme heterojunction core-shell nanoreactor based on manipulation of the driving factors, which consists of α-Fe2 O3 encapsulated by g-C3 N4 modified with gold quantum dots. α-Fe2 O3 can promote carrier spatial separation while also acting as a thermal core to radiate heat to the shell, while Au quantum dots transfer energetic electrons and heat to g-C3 N4 via surface plasmon resonance. Consequently, the catalytic activity of Au/α-Fe2 O3 @g-C3 N4 is significantly improved by internal and external double hot spots, and it shows an H2 evolution rate of 5762.35 µmol h-1 g-1 , and the selectivity of CO2 conversion to CH4 is 91.2%. This work provides an effective strategy to design new plasma photothermal catalysts for the solar-to-fuel transition.

Edge sulfur vacancies riched MoS2 nanosheets assist PEDOT:PSS flexible film ammonia sensing enhancement for wireless greenhouse vegetables monitoring.

Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is a promising NH3 sensing material owing to its super high electrical conductivity, excellent environmental stability, and reversible doping/dedoping nature. However, the low sensitivity and sluggish recovery rate limit its further application in gas sensors. Herein, exfoliated layered MoS2 nanosheets with large-specific surface area and abundant edge sulfur (S) vacancies are utilized to assist PEDOT:PSS and achieve ideal improvement in NH3 sensing performance at room temperature (RT), including high response values, fast response/recovery ability, and excellent sensing stability in complex environment. MoS2 nanosheets are combined with PEDOT:PSS to construct p-n heterojunction, the S vacancies can improve carrier transfer rate and serve as conductive bridge, effective active sites for NH3 adsorption, this series of performance improvement strategies is the significance of this work. Meanwhile, the density-functional theory (DFT), current-voltage (I-V), and in-situ FITR are firstly employed to discuss the sensing mechanisms in detail. Furthermore, integrating MoS2/PEDOT:PSS flexible sensor into a designed printed circuit board to intelligent, visual, and wireless real-time monitoring the NH3 resistance information in a simulated greenhouse vegetables equipment through the smartphone APP has also been successfully implemented.

Machine Learning and Radiomics of Bone Scintigraphy: Their Role in Predicting Recurrence of Localized or Locally Advanced Prostate Cancer.

BACKGROUND: Machine-learning (ML) and radiomics features have been utilized for survival outcome analysis in various cancers. This study aims to investigate the application of ML based on patients' clinical features and radiomics features derived from bone scintigraphy (BS) and to evaluate recurrence-free survival in local or locally advanced prostate cancer (PCa) patients after the initial treatment. METHODS: A total of 354 patients who met the eligibility criteria were analyzed and used to train the model. Clinical information and radiomics features of BS were obtained. Survival-related clinical features and radiomics features were included in the ML model training. Using the pyradiomics software, 128 radiomics features from each BS image's region of interest, validated by experts, were extracted. Four textural matrices were also calculated: GLCM, NGLDM, GLRLM, and GLSZM. Five training models (Logistic Regression, Naive Bayes, Random Forest, Support Vector Classification, and XGBoost) were applied using K-fold cross-validation. Recurrence was defined as either a rise in PSA levels, radiographic progression, or death. To assess the classifier's effectiveness, the ROC curve area and confusion matrix were employed. RESULTS: Of the 354 patients, 101 patients were categorized into the recurrence group with more advanced disease status compared to the non-recurrence group. Key clinical features including tumor stage, radical prostatectomy, initial PSA, Gleason Score primary pattern, and radiotherapy were used for model training. Random Forest (RF) was the best-performing model, with a sensitivity of 0.81, specificity of 0.87, and accuracy of 0.85. The ROC curve analysis showed that predictions from RF outperformed predictions from other ML models with a final AUC of 0.94 and a p-value of <0.001. The other models had accuracy ranges from 0.52 to 0.78 and AUC ranges from 0.67 to 0.84. CONCLUSIONS: The study showed that ML based on clinical features and radiomics features of BS improves the prediction of PCa recurrence after initial treatment. These findings highlight the added value of ML techniques for risk classification in PCa based on clinical features and radiomics features of BS.

BLPSeg: Balance the Label Preference in Scribble-Supervised Semantic Segmentation.

Scribble-supervised semantic segmentation is an appealing weakly supervised technique with low labeling cost. Existing approaches mainly consider diffusing the labeled region of scribble by low-level feature similarity to narrow the supervision gap between scribble labels and mask labels. In this study, we observe an annotation bias between scribble and object mask, i.e., label workers tend to scribble on the spacious region instead of corners. This label preference makes the model learn well on those frequently labeled regions but poor on rarely labeled pixels. Therefore, we propose BLPSeg to balance the label preference for complete segmentation. Specifically, the BLPSeg first predicts an annotation probability map to evaluate the rarity of labels on each image, then utilizes a novel BLP loss to balance the model training by up-weighting those rare annotations. Additionally, to further alleviate the impact of label preference, we design a local aggregation module (LAM) to propagate supervision from labeled to unlabeled regions in gradient backpropagation. We conduct extensive experiments to illustrate the effectiveness of our BLPSeg. Our single-stage method even outperforms other advanced multi-stage methods and achieves state-of-the-art performance.

A Review on Multiple I-III-VI Quantum Dots: Preparation and Enhanced Luminescence Properties.

I-III-VI type QDs have unique optoelectronic properties such as low toxicity, tunable bandgaps, large Stokes shifts and a long photoluminescence lifetime, and their emission range can be continuously tuned in the visible to near-infrared light region by changing their chemical composition. Moreover, they can avoid the use of heavy metal elements such as Cd, Hg and Pb and highly toxic anions, i.e., Se, Te, P and As. These advantages make them promising candidates to replace traditional binary QDs in applications such as light-emitting diodes, solar cells, photodetectors, bioimaging fields, etc. Compared with binary QDs, multiple QDs contain many different types of metal ions. Therefore, the problem of different reaction rates between the metal ions arises, causing more defects inside the crystal and poor fluorescence properties of QDs, which can be effectively improved by doping metal ions (Zn2+, Mn2+ and Cu+) or surface coating. In this review, the luminous mechanism of I-III-VI type QDs based on their structure and composition is introduced. Meanwhile, we focus on the various synthesis methods and improvement strategies like metal ion doping and surface coating from recent years. The primary applications in the field of optoelectronics are also summarized. Finally, a perspective on the challenges and future perspectives of I-III-VI type QDs is proposed as well.

Boosting Material Utilization via Direct Growth of Zn2 (V3 O8 )2 on the Carbon Cloth as a Cathode to Achieve a High-Capacity Aqueous Zinc-Ion Battery.

Aqueous zinc-ion batteries (AZIBs) have attracted the attention of researchers because of their high theoretical capacity and safety. Among the many vanadium-based AZIB cathode materials, zinc vanadate is of great interest as a typical phase in the dis-/charge process. Here, a remarkable method to improve the utilization rate of zinc vanadate cathode materials is reported. In situ growth of Zn2 (V3 O8 )2 on carbon cloth (CC) as the cathode material (ZVO@CC) of AZIBs. Compared with the Zn2 (V3 O8 )2 cathode material bonded on titanium foil (ZVO@Ti), the specific capacity increases from 300 to 420 mAh g-1 , and the utilization rate of the material increases from 69.60% to 99.2%. After the flexible device is prepared, it shows the appropriate specific capacity (268.4 mAh g-1 at 0.1 A g-1 ) and high safety. The method proposed in this work improves the material utilization rate and enhances the energy density of AZIB and also has a certain reference for the other electrochemical energy storage devices.

A Highly Selective Electrochemical Sensor Based on Molecularly Imprinted Copolymer Functionalized with Arginine for the Detection of Chloramphenicol in Honey.

Developing an efficient method for chloramphenicol (CAP) detection is of great significance for food safety. Arginine (Arg) was selected as a functional monomer. Benefiting from its excellent electrochemical performance, which is different from traditional functional monomers, it can be combined with CAP to form a highly selective molecularly imprinted polymer (MIP) material. It overcomes the shortcoming of poor MIP sensitivity faced by traditional functional monomers, and achieves high sensitivity detection without compounding other nanomaterials, greatly reducing the preparation difficulty and cost investment of the sensor. The possible binding sites between CAP and Arg molecules were calculated by molecular electrostatic potential (MEP). A low-cost, non-modified MIP electrochemical sensor was developed for the high-performance detection of CAP. The prepared sensor has a wide linear range from 1 × 10-12 mol L-1 to 5 × 10-4 mol L-1, achieves a very low concentration CAP detection, and the detection limit is 1.36 × 10-13 mol L-1. It also exhibits excellent selectivity, anti-interference, repeatability, and reproducibility. The detection of CAP in actual honey samples was achieved, which has important practical value in food safety.

Charges Transfer in Interfaces for Energy Generating.

Under the threat of energy crisis and environmental pollution, the technology for sustainable and clean energy extraction has received considerable attention. Owing to the intensive exploration of energy conversion strategies, expanded energy sources are successfully converted into electric energy, including mechanical energy from human motion, kinetic energy of falling raindrops, and thermal energy in the ambient. Among these energy conversion processes, charge transfer at different interfaces, such as solid-solid, solid-liquid, liquid-liquid, and gas-contained interfaces, dominates the power-generating efficiency. In this review, the mechanisms and applications of interfacial energy generators (IEGs) with different interface types are systematically summarized. Challenges and prospects are also highlighted. Due to the abundant interfacial interactions in nature, the development of IEGs offers a promising avenue of inexhaustible and environmental-friendly power generation to solve the energy crisis.

Recent Advances in Carbon Nitride-Based S-scheme Photocatalysts for Solar Energy Conversion.

Energy shortages are a major challenge to the sustainable development of human society, and photocatalytic solar energy conversion is a potential way to alleviate energy problems. As a two-dimensional organic polymer semiconductor, carbon nitride is considered to be the most promising photocatalyst due to its stable properties, low cost, and suitable band structure. Unfortunately, pristine carbon nitride has low spectral utilization, easy recombination of electron holes, and insufficient hole oxidation ability. The S-scheme strategy has developed in recent years, providing a new perspective for effectively solving the above problems of carbon nitride. Therefore, this review summarizes the latest progress in enhancing the photocatalytic performance of carbon nitride via the S-scheme strategy, including the design principles, preparation methods, characterization techniques, and photocatalytic mechanisms of the carbon nitride-based S-scheme photocatalyst. In addition, the latest research progress of the S-scheme strategy based on carbon nitride in photocatalytic H2 evolution and CO2 reduction is also reviewed. Finally, some concluding remarks and perspectives on the challenges and opportunities for exploring advanced nitride-based S-scheme photocatalysts are presented. This review brings the research of carbon nitride-based S-scheme strategy to the forefront and is expected to guide the development of the next-generation carbon nitride-based S-scheme photocatalysts for efficient energy conversion.

Super-Photothermal Effect-Mediated Fast Reaction Kinetic in S-Scheme Organic/Inorganic Heterojunction Hollow Spheres Toward Optimized Photocatalytic Performance.

Using full solar spectrum for energy conversion and environmental remediation is a major challenge, and solar-driven photothermal chemistry is a promising route to achieve this goal. Herein, this work reports a photothermal nano-constrained reactor based on hollow structured g-C3 N4 @ZnIn2 S4 core-shell S-scheme heterojunction, where the synergistic effect of super-photothermal effect and S-scheme heterostructure significantly improve the photocatalytic performance of g-C3 N4 . The formation mechanism of g-C3 N4 @ZnIn2 S4 is predicted in advance by theoretical calculations and advanced techniques, and the super-photothermal effect of g-C3 N4 @ZnIn2 S4 and its contribution to the near-field chemical reaction is confirmed by numerical simulations and infrared thermography. Consequently, the photocatalytic degradation rate of g-C3 N4 @ZnIn2 S4 for tetracycline hydrochloride is 99.3%, and the photocatalytic hydrogen production is up to 4075.65 µmol h-1 g-1 , which are 6.94 and 30.87 times those of pure g-C3 N4 , respectively. The combination of S-scheme heterojunction and thermal synergism provides a promising insight for the design of an efficient photocatalytic reaction platform.

Learning Curve of Transperineal MRI/US Fusion Prostate Biopsy: 4-Year Experience.

This study aimed to evaluate the learning curve of transperineal magnetic resonance imaging (MRI)/ultrasound (US) fusion biopsy in a team composed of a single surgeon, a single radiologist, and a single pathologist. We prospectively enrolled 206 patients undergoing MRI/US fusion prostate biopsy and divided them into four cohorts by the year of biopsy. We analyzed temporal changes in clinically significant prostate cancer (csPC) detection rate, percentage of positive cores on biopsy, and Gleason upgrading rate after radical prostatectomy. The csPC detection rate by MRI/US fusion targeted biopsy (TB) increased significantly (from 35.3% to 60.0%, p = 0.01). With increased experience, the csPC detection rates for small (≤1 cm) and anterior target lesions gradually increased (from 41.2% to 51.6%, p = 0.5; from 54.5% to 88.2%, p = 0.8, respectively). The percentage of positive cores on TB increased significantly (from 18.4% to 44.2%, p = 0.001). The Gleason upgrading rate gradually decreased (from 22.2% to 11.1%, p = 0.4). In conclusion, with accumulated experience and teamwork, the csPC detection rate by TB significantly increased. Multidisciplinary team meetings and a free-hand biopsy technique were the key factors for overcoming the learning curve.

Full-Length Transcriptomes and Sex-Based Differentially Expressed Genes in the Brain and Ganglia of Giant River Prawn Macrobrachium rosenbergii.

Macrobrachium rosenbergii is an important aquaculture prawn that exhibits sexual dimorphism in growth, with males growing much faster than females. However, the mechanisms controlling these complex traits are not well understood. The nervous system plays an important role in regulating life functions. In the present work, we applied PacBio RNA-seq to obtain and characterize the full-length transcriptomes of the brains and thoracic ganglia of female and male prawns, and we performed comparative transcriptome analysis of female and male prawns. A total of 159.1-Gb of subreads were obtained with an average length of 2175 bp and 93.2% completeness. A total of 84,627 high-quality unigenes were generated and annotated with functional databases. A total of 6367 transcript factors and 6287 LncRNAs were predicted. In total, 5287 and 6211 significantly differentially expressed genes (DEGs) were found in the brain and thoracic ganglion, respectively, and confirmed by qRT-PCR. Of the 435 genes associated with protein processing pathways in the endoplasmic reticula, 42 DEGs were detected, and 21/26 DEGs with upregulated expression in the male brain/thoracic ganglion. The DEGs in this pathway are regulated by multiple LncRNAs in polypeptide folding and misfolded protein degradation in the different organs and sexes of the prawn. Our results provide novel theories and insights for studying the nervous system, sexual control, and growth dimorphism.

Pt/MoS2/Polyaniline Nanocomposite as a Highly Effective Room Temperature Flexible Gas Sensor for Ammonia Detection.

A Pt/MoS2/polyaniline (Pt/MoS2/PANI) nanocomposite is successfully synthesized by the hydrothermal process combined with the in situ polymerization method, and then Pt particles are decorated on its surface. The Pt/MoS2/PANI nanocomposite is deposited on a flexible Au-interdigitated electrode of a polyimide (PI) film. The flexible sensor exhibits a higher response value and fast response/recovery time to NH3 at room temperature (RT). It results in 2.32-fold and 1.13-fold improvement in the gas-sensing response toward 50 ppm NH3 compared to those of PANI and MoS2/PANI-based gas sensors. The detection limit is 250 ppb. The enhancement sensing mechanisms are attributed to the p-n heterojunction and the Schottky barrier between the three components, which has been confirmed by the current-voltage (I-V) curves. A satisfactory selectivity to NH3 against trimethylamine (TMA) and triethylamine (TEA) is obtained according to density functional theory (DFT), Bader's analysis, and differential charge density to illustrate the adsorption behavior and charge transfer of gas molecules on the surface of the sensing materials. The sensor retains the excellent sensing response value even under high relative humidity and sensing stability at higher bending angle/numbers to NH3 gas. Hence, Pt/MoS2/PANI can be regarded as a promising sensing material for high-performance NH3 detection at room temperature applied in flexible wearable electronics.

High sensitivity electrochemical detection of ultra-trace imidacloprid in fruits and vegetables using a Fe-rich FeCoNi-MOF.

High sensitivity and ultra-trace detection of imidacloprid are important and challenging in the field of food. In this study, we prepared a Fe-rich FeCoNi-MOF in-situ modified nickel foam working electrode by one-step hydrothermal method, and achieved a highly sensitive detection of the imidacloprid. The characterization techniques confirmed that Fe-rich FeCoNi-MOF had excellent crystallinity, tighter structure, and exposed rich active sites. The detection results showed that Fe-rich FeCoNi-MOF electrochemical sensor had a minimum detection limit of 0.04 pmol/L (100 times lower than that of the bioelectrochemical sensors), a wide response range (1 pmol/L-120 µmol/L), and high sensitivity (124 µA pmol/L-1 cm-2). These advantages of the electrochemical sensor were revealed theoretically by the valence change of active metal and the first principle calculation. Lastly, the Fe-rich FeCoNi-MOF electrochemical sensor was applied to detect imidacloprid in apple, fresh tea leaves, tomato, cucumber, and had an excellent recovery of 98-102.8 %.

Plasma Ag-Modified α-Fe2O3/g-C3N4 Self-Assembled S-Scheme Heterojunctions with Enhanced Photothermal-Photocatalytic-Fenton Performances.

Low spectral utilization and charge carrier compounding limit the application of photocatalysis in energy conversion and environmental purification, and the rational construction of heterojunction is a promising strategy to break this bottleneck. Herein, we prepared surface-engineered plasma Ag-modified α-Fe2O3/g-C3N4 S-Scheme heterojunction photothermal catalysts by electrostatic self-assembly and light deposition strategy. The local surface plasmon resonance effect induced by Ag nanoparticles broadens the spectral response region and produces significant photothermal effects. The temperature of Ag/α-Fe2O3/g-C3N4 powder is increased to 173 °C with irradiation for 90 s, ~3.2 times higher than that of the original g-C3N4. The formation of 2D/2D structured S-Scheme heterojunction promotes rapid electron-hole transfer and spatial separation. Ternary heterojunction construction leads to significant enhancement of photocatalytic performance of Ag/α-Fe2O3/g-C3N4, the H2 photocatalytic generation rate up to 3125.62 µmol g-1 h-1, which is eight times higher than original g-C3N4, and the photocatalytic degradation rate of tetracycline to reach 93.6%. This thermally assisted photocatalysis strategy improves the spectral utilization of conventional photocatalytic processes and provides new ideas for the practical application of photocatalysis in energy conversion and environmental purification.