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Artificial photosynthesis represents a sustainable strategy for accessing high-value chemicals; however, the conversion efficiency is significantly limited by its difficulty in the cycle of coenzymes such as NADH. In this study, we report a series of isostructural triazine covalent organic frameworks (COFs) and explore their N-substituted microenvironment-dependent photocatalytic activity for NADH regeneration. We discovered that the rational alteration of N-heterocyclic species, which are linked to the triazine center through an imine linkage, can significantly regulate both the electron band structure and planarity of a COF layer. This results in different separation efficiencies of the photoinduced electron-hole pairs and electron transfer behavior within and between individual layers. The optimal COF catalyst herein achieves an NADH regeneration capacity of 89% within 20 min, outperforming most of the reported nanomaterial photocatalysts. Based on this, an artificial photosynthesis system is constructed for the green synthesis of a high-value compound, L-glutamate, and its conversion efficiency significantly surpasses the enzymatic approach without the NADH photocatalytic cycle. This work offers new insights into the coenzyme regeneration by means of regulating the distal heterocyclic microenvironment of a COF skeleton, holding great potential for the green photosynthesis of important chemicals.
Assuntos
Estruturas Metalorgânicas , Triazinas , Triazinas/química , Catálise , Estruturas Metalorgânicas/química , NAD/química , NAD/metabolismo , Processos Fotoquímicos , Estrutura Molecular , Coenzimas/química , Coenzimas/metabolismo , FotossínteseRESUMO
We report the first experimental realization of equilibrium dynamics of mutually confined waves with signed analogous masses in an optical fiber. Our Letter is mainly demonstrated by considering a mutual confinement between a soliton pair and a dispersive wave experiencing opposite dispersion. The resulting wave-packet complex is found robust upon random perturbation and collision with other waves. The equilibrium dynamics are also extended to scenarios of more than three waves. Our finding may trigger fundamental interest in the dynamics of many-body systems arising from the concept of negative mass, which is promising for new applications based on localized nonlinear waves.
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The preparation of waste plastics-derived catalysts is an effective strategy for the waste reclamation. However, plastic-derived material is unsuitable for wastewater purification due to its small specific surface area (SSA) and inadequate active sites (such as N/O sites). Herein, we synthesized graphene-like nanosheets using g-C3N4 as the self-sacrificing soft template and plastic as the carbon precursor. Consequently, this strategy greatly promoted the efficiencies of the emerging organic pollutants degradation with the SSA and N content of the plastic-derived biochar increasing up to 1043.4 m2/g and 17.53 at.%, respectively. In detail, 100 % sulfadiazine (SD) removal could be achieved in 180 s via the activation of peroxymonosulfate (PMS) and the catalytic activity is far higher than previous research. Mechanism experiments corroborated that such a striking performance was attributed to the generation of SO4â¢-, O2â¢- and 1O2. Meanwhile, kinds of plastic precursors, even medical waste (i.e., masks, gauze, operating caps and degreasing cotton) were also applicable. And the practical application of the plastic-derived catalyst was further demonstrated by treating pollutants in a continuous flow mode with in situ fabricated membrane. This work provides valuable insights into waste plastics processing and water pollutants removal.
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Robotized intelligent manufacturing is a growing trend in the manufacturing of large and complex components in aviation, aerospace, marine engineering and other industries. With their expansive workspaces and flexible deployment, climbing manufacturing robots can create a revolutionary manufacturing paradigm for large and complex components. This paper defines the climbing manufacturing robot based on the application status of climbing robots and then analyzes four key technical requirements: adhesion, locomotion, localization and control. Subsequently, the current research status of climbing robots in these four areas is classified and reviewed, along with a clarification of the research frontiers and trends in each area, and the applicability of the relevant research to manufacturing-oriented climbing robotic systems is analyzed. Finally, by concluding the development trends of robotized intelligent manufacturing equipment in terms of manufacturing dimension and scale, environmental adaptability and cluster collaboration capability, we clarify the major challenges for climbing manufacturing robots in terms of adhesion principles, motion mechanisms, positioning technology and control methods, and propose future research directions in these fields.
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Traditional cervical cancer diagnosis mainly relies on human papillomavirus (HPV) concentration testing. Considering that HPV concentrations vary from individual to individual and fluctuate over time, this method requires multiple tests, leading to high costs. Recently, some scholars have focused on the method of cervical cytology for diagnosis. However, cervical cancer cells have complex textural characteristics and small differences between different cell subtypes, which brings great challenges for high-precision screening of cervical cancer. In this paper, we propose a high-precision cervical cancer precancerous lesion screening classification method based on ConvNeXt, utilizing self-supervised data augmentation and ensemble learning strategies to achieve cervical cancer cell feature extraction and inter-class discrimination, respectively. We used the Deep Cervical Cytological Levels (DCCL) dataset, which includes 1167 cervical cytology specimens from participants aged 32 to 67, for algorithm training and validation. We tested our method on the DCCL dataset, and the final classification accuracy was 8.85% higher than that of previous advanced models, which means that our method has significant advantages compared to other advanced methods.
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Since the discovery that Fe3 O4 nanoparticle has intrinsic natural peroxidase-like activity by Yan et al in 2007, mimicking native enzymes via nano-engineering (named as nanozyme) pays a new avenue to bypass the fragility and recyclability of natural enzymes and thus expedites the biocatalysis in multidisciplinary applications. In addition, the high programmability and structural stability attributes of nanozyme afford the ease of coupling with electromagnetic waves of different energies, providing great opportunities to construct photo-responsive nanozyme under user-defined electromagnetic waves, which is known as photo-nanozyme. In this concept, we aim to providing a summary of how electromagnetic waves with varying wavelengths can serve as external stimuli to induce or enhance the biocatalytic performance of photo-nanozymes, thereby offering fascinating functions that cannot be achieved by pristine nanozyme.