The development of efficient photocatalysts for water purification remains challenged by rapid charge recombination and limited surface reactivity. Here, we report a rationally designed PHI/W₁₈O₄₉ heterojunction photocatalyst, integrating interfacial W–N bonds and oxygen vacancies to synergistically overcome these limitations. The optimized PHI/W₁₈O₄₉ heterojunction exhibits significantly enhanced visible-light absorption, efficient spatial charge separation, and improved surface reaction kinetics. Consequently, it demonstrates superior and versatile photocatalytic performance in degrading organic contaminants, along with stable recyclability and consistent performance in real water matrices, highlighting its potential for practical applications. Mechanistic studies combining DFT calculations and experimental characterization reveal that interfacial W–N bonds direct S-scheme electron transfer, while oxygen vacancies enhance reactant adsorption, jointly boosting charge separation and surface reactivity. This work establishes a design paradigm that couples’ defect-enhanced surface adsorption with directed interfacial electron flow, offering an effective strategy for developing robust photocatalysts for practical environmental remediation.
Starch retrogradation, driven by reassociation and recrystallization of gelatinized amylose and amylopectin chains, induces undesirable firming, syneresis, and sensory deterioration, ultimately shortening the shelf-life of starch-based foods. Enzymatic modification has emerged as a promising route to retard retrogradation, but its efficacy critically depends on the structural features targeted by the enzyme, the susceptibility of the starch substrate, and the accessibility of catalytic sites. This review systematically interprets the structure-dependent mechanisms underlying enzymatic retrogradation regulation, covering the differential regulatory patterns of various enzyme systems. This review further clarifies the essential distinction between substrate structural susceptibility and enzyme catalytic accessibility, and summarizes advanced modification strategies based on porous starch construction and controlled starch swelling to optimize enzyme-substrate interfacial contact efficiency. In addition, mainstream detection techniques are compared based on the different levels of the studied starch structure. Finally, the practical applicability of enzymatic anti-retrogradation technologies in diverse staple and processed starch-based food systems are also summarized. We propose that the key design principle is controlled structural remodeling enabled by enzyme action within a defined processing window, rather than indiscriminate starch degradation. This work provides systematic theoretical insights and practical guidance for the quality stabilization and shelf-life extension of starch-based food products.
Industrial fault diagnosis often faces the challenge of limited fault samples. Most existing closed-set diagnosis approaches focus on weighting and aligning source domains with the target domain. However, the domain shifts among multiple source domains are often overlooked. To address these issues, this paper proposes a Task-Structured Prototype Evolution with Dual-Stage Reconstruction (TSPE-DSR) framework for multi-source cross-domain few-shot closed-set fault diagnosis. First, a cross-domain task division mechanism is designed to construct meta-tasks from multiple source domains. The mechanism iteratively assigns pseudo-source and pseudo-target domains to form auxiliary tasks. These tasks exploit shared knowledge across domains and facilitate rapid adaptation to the target domain. Second, a dual-stage attention prototype reconstruction network is developed to model prototype evolution. A self-attention mechanism is introduced to achieve a progressive transition from embedding learning to prototype reconstruction. This process enables adaptive transfer of source-domain prototypes and effectively reduces cross-domain discrepancies. Finally, a joint training strategy is adopted by combining weighted prototype similarity loss and classification loss. This strategy improves classification performance, alleviates overfitting, and enhances model robustness. The effectiveness of TSPE-DSR is validated on the Tennessee Eastman Process(TEP), Case Western Reserve University(CWRU), and Aluminum Electrolysis Process(AEP) datasets. Experimental results demonstrate that TSPE-DSR outperforms existing methods in classification performance, achieving average accuracy improvements of 5.52%, 3.12%, and 4.79% over the strongest baseline on the TEP, CWRU, and AEP datasets, respectively. Our code is at https://github.com/Luce-hub/DAPRN.
Multi-band elastic optical networks (MB-EONs) are a promising technology for future backbone networks. Routing, band, modulation level and spectrum assignment (RBMSA) problem is one of the key issues in MB-EONs. Due to the significant increase of total power in fiber links, nonlinear interference (NLI) must be considered when determining the highest available modulation level. Generally, two NLI-aware modulation selection methods are used in existing works, namely the AccurateSNR and FixedReach methods. The former is with high computational cost, while the latter is with low spectral efficiency. In this paper, we propose a novel NLI-aware modulation-selection method named dynamic reachable distance estimation (DRDE). The DRDE method can dynamically estimate reachable distances of modulation levels under realtime NLI by a simple formula. We further design a DRDE-based RBMSA algorithm to demonstrate the usage of the DRDE method for modulation level selection. Simulations show that the DRDE-based RBMSA algorithm outperforms the FixedReach-based RBMSA algorithm in terms of bandwidth blocking probability, and outperforms the AccurateSNR-based RBMSA algorithm in terms of average running time. Hence, the proposed DRDE method is not only computationally efficient but also spectrally efficient.
Nitrogen and phosphorus co-doped carbon dots (N/P-CD) were successfully synthesized via a facile and controllable electrochemical exfoliation strategy. In this approach, heteroatom doping is achieved through electrolyte engineering. Compared with conventional high-temperature or multistep synthetic methods, this strategy enables precise regulation of nitrogen and phosphorus incorporation simply by tuning the electrolyte composition, thereby providing an effective platform for the controllable modulation of the electronic structure of carbon dots. The electrocatalytic performance of N/P-CD toward the oxygen reduction reaction (ORR) was systematically evaluated in alkaline media. Benefiting from the synergistic effect between nitrogen and phosphorus dopants, the catalyst exhibits significantly enhanced intrinsic activity. Specifically, compared with undoped carbon dots, the onset potential and half-wave potential are positively shifted by 142 mV and 141 mV. Moreover, compared with the singly doped samples (N-CD and P-CD), N/P-CD exhibits a higher onset potential (0.86 V) and half-wave potential (0.76 V), demonstrating electrocatalytic activity comparable to that of the commercial Pt/C electrode. N/P-CD also demonstrated excellent electrochemical stability, as no significant shift in the CV curves was observed after 5,000 cycles, indicating the outstanding stability of the material. This study demonstrates that N/P-CD, as a low-cost and non-precious metal ORR electrocatalyst, shows promising potential in alkaline oxygen reduction systems and can serve as a scalable and environmentally friendly alternative to conventional Pt-based catalytic systems.
