The significance of identifying the fundamental mechanism of interactions between adjacent catalytic active centers has long been underestimated. Utilizing density functional theory calculations, we ...demonstrate controllable cooperative interaction between two nearby Fe centers embedded on nitrogenated graphene aided by CO adsorption. The interconnected adjacent Fe atoms respond cooperatively to CO molecules with communicative structural self-adaption and electronic transformation. The adsorbed CO changes not only the spin of the active site it is attached to but also that of its adjacent site. Consequently, the two adjacent Fe atoms feature unique oscillatory long-range spin coupling. Our theoretical investigation suggests cooperative communication between adjacent active sites on a single-atom catalyst is nontrivial.
Nitrogen fixation is one of the most important issues but a long-standing challenge in chemistry. Here, we propose FeN3-embedded graphene as the catalyst for nitrogen fixation from first-principles ...calculations. Results show that in view of the chemical coordination, the FeN3 center is highly spin-polarized with a localized magnetic moment substantially to promote N2 adsorption and activate its inert N-N triple bond. The synergy between the graphene and FeN3 equips the system with novel features for the catalytic conversion of the activated N2 into NH3 via a six-proton and six-electron process, following three possible reaction pathways at room temperature. Our findings provide a rational paradigm for catalytic nitrogen fixation that would be conducive to ammonia production.
Exploring the impact of active site density on catalytic reactions is crucial for reaching a more comprehensive understanding of how single-atom catalysts work. Utilizing density functional theory ...calculations, we have systematically investigated the neighboring effects between two adjacent Fe–N–C sites of monodispersed Fe–N–C single-atom catalysts on oxygen reduction reaction (ORR). While the thermodynamic limiting potential (U L) is strongly dependent on the intersite distance and the nature of adjacent active sites in FeN3, it is almost invariable in FeN4 until two FeN4 sites are ∼4 Å apart. Further, under certain conditions, an otherwise unfavorable physisorbed-O2-initiated 2e– pathway becomes feasible due to charge transfer between reactive species and graphene support. Our results cast new insight into the rational design of high-density single-atom catalysts and may create an alternative route to manipulate their catalytic activities.
Cooperative effects of adjacent active centers are critical for single-atom catalysts (SACs) as active site density matters. Yet, how it affects scaling relationships in many important reactions such ...as the nitrogen reduction reaction (NRR) is underexplored. Herein we elucidate how the cooperation of two active centers can attenuate the linear scaling effect in the NRR through a first-principle study on 39 SACs comprised of two adjacent (∼4 Å apart) four N-coordinated metal centers (MN4 duo) embedded in graphene. Bridge-on adsorption of dinitrogen-containing species appreciably tilts the balance of adsorption of N2H and NH2 toward N2H and thus substantially loosens the restraint of scaling relationships in the NRR, achieving low onset potential (V) and direct NN cleavage (Mo, Re) at room temperature, respectively. The potential of the MN4 duo in the NRR provides new insight into circumventing the limitations of scaling relationships in heterogeneous catalysis.
In contrast with nature scenes, aerial scenes are often composed of many objects crowdedly distributed on the surface in bird's view, the description of which usually demands more discriminative ...features as well as local semantics. However, when applied to scene classification, most of the existing convolution neural networks (ConvNets) tend to depict global semantics of images, and the loss of low- and mid-level features can hardly be avoided, especially when the model goes deeper. To tackle these challenges, in this paper, we propose a multiple-instance densely-connected ConvNet (MIDC-Net) for aerial scene classification. It regards aerial scene classification as a multiple-instance learning problem so that local semantics can be further investigated. Our classification model consists of an instance-level classifier, a multiple instance pooling and followed by a bag-level classification layer. In the instance-level classifier, we propose a simplified dense connection structure to effectively preserve features from different levels. The extracted convolution features are further converted into instance feature vectors. Then, we propose a trainable attention-based multiple instance pooling. It highlights the local semantics relevant to the scene label and outputs the bag-level probability directly. Finally, with our bag-level classification layer, this multiple instance learning framework is under the direct supervision of bag labels. Experiments on three widely-utilized aerial scene benchmarks demonstrate that our proposed method outperforms many state-of-the-art methods by a large margin with much fewer parameters.
Electrochemical oxygen reduction to hydrogen peroxide is now being studied as a promising renewable and localized alternative for the traditional complex anthraquinone process. Catalysts for this ...two-electron reduction pathway with high selectivity are required to achieve industrialization. Here, we disclose an inexpensive metal-free catalyst that is synthesized from commercial carbon black (CB) with a one-step plasma method for the affordable electrochemical generation of hydrogen peroxide in 100% Faradaic efficiency. This catalyst shows a high onset potential (0.1 mA cm–2 at 0.80 V vs reversible hydrogen electrode (RHE)) and the highest mass activity (300 A g–1 at 0.60 V vs reversible hydrogen electrode) among state-of-the-art catalysts. The performance could be maintained after the removal of oxygen-containing groups. Microscopic and spectroscopic characterizations as well as density functional theory (DFT) calculations indicate that the performance comes from the defective structure after plasma treatment.
We generalized the recently introduced "radiation model", as an analog to the generalization of the classic "gravity model", to consolidate its nature of universality for modeling diverse mobility ...systems. By imposing the appropriate scaling exponent λ, normalization factor κ and system constraints including searching direction and trip OD constraint, the generalized radiation model accurately captures real human movements in various scenarios and spatial scales, including two different countries and four different cities. Our analytical results also indicated that the generalized radiation model outperformed alternative mobility models in various empirical analyses.
Anomalous taxi trajectories are those chosen by a small number of drivers that are different from the regular choices of other drivers. These anomalous driving trajectories provide us an opportunity ...to extract driver or passenger behaviors and monitor adverse urban traffic events. Because various trajectory clustering methods have previously proven to be an effective means to analyze similarities and anomalies within taxi GPS trajectory data, we focus on the problem of detecting anomalous taxi trajectories, and we develop our trajectory clustering method based on the edit distance and hierarchical clustering. To achieve this objective, first, we obtain all the taxi trajectories crossing the same source–destination pairs from taxi trajectories and take these trajectories as clustering objects. Second, an edit distance algorithm is modified to measure the similarity of the trajectories. Then, we distinguish regular trajectories and anomalous trajectories by applying adaptive hierarchical clustering based on an optimal number of clusters. Moreover, we further analyze these anomalous trajectories and discover four anomalous behavior patterns to speculate on the cause of an anomaly based on statistical indicators of time and length. The experimental results show that the proposed method can effectively detect anomalous trajectories and can be used to infer clearly fraudulent driving routes and the occurrence of adverse traffic events.
The production of ammonia from nitrogen reduction reaction (NRR) under mild conditions is one of the most challenging issues in modern chemistry. The linear scaling relationship between the ...adsorption energies of −N2H and −NH2 on a single active site is a well-established bottleneck. By investigating a series of densely monodispersed Mo–N–C sites embedded in graphene using first-principles calculations, we found that previously underappreciated neighboring effects between adjacent active sites may help break the limit: they not only improve the energetics of potential determining steps of NRR but also promote an alternative associative mechanism based on a cooperative bridge-on adsorption of N2 by two Mo–N–C sites of ∼6 Å apart. Further, a barrier of 0.71 eV for N–N bond dissociation is achieved by proper ratio of coordinated C/N atoms of Mo. Our work suggests the cooperation of two adjacent active sites may offer an alternative strategy of nitrogen fixation.
Most neutralizing antibodies against Middle East respiratory syndrome coronavirus (MERS-CoV) target the receptor-binding domain (RBD) of the spike glycoprotein and block its binding to the cellular ...receptor dipeptidyl peptidase 4 (DPP4). The epitopes and mechanisms of mAbs targeting non-RBD regions have not been well characterized yet. Here we report the monoclonal antibody 7D10 that binds to the N-terminal domain (NTD) of the spike glycoprotein and inhibits the cell entry of MERS-CoV with high potency. Structure determination and mutagenesis experiments reveal the epitope and critical residues on the NTD for 7D10 binding and neutralization. Further experiments indicate that the neutralization by 7D10 is not solely dependent on the inhibition of DPP4 binding, but also acts after viral cell attachment, inhibiting the pre-fusion to post-fusion conformational change of the spike. These properties give 7D10 a wide neutralization breadth and help explain its synergistic effects with several RBD-targeting antibodies.
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