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It is still a grand challenge to develop a highly efficient nonprecious-metal electrocatalyst to replace the Pt-based catalysts for oxygen reduction reaction (ORR). Here, we propose a surfactant-assisted method to synthesize single-atom iron catalysts (SA-Fe/NG). The half-wave potential of SA-Fe/NG is only 30 mV less than 20% Pt/C in acidic medium, while it is 30 mV superior to 20% Pt/C in alkaline medium. Moreover, SA-Fe/NG shows extremely high stability with only 12 mV and 15 mV negative shifts after 5,000 cycles in acidic and alkaline media, respectively. Impressively, the SA-Fe/NG-based acidic proton exchange membrane fuel cell (PEMFC) exhibits a high power density of 823 mW cm Combining experimental results and density-functional theory (DFT) calculations, we further reveal that the origin of high-ORR activity of SA-Fe/NG is from the Fe-pyrrolic-N species, because such molecular incorporation is the key, leading to the active site increase in an order of magnitude which successfully clarifies the bottleneck puzzle of why a small amount of iron in the SA-Fe catalysts can exhibit extremely superior ORR activity.

Simultaneously increasing the activity and stability of the single-atom active sites of M–N–C catalysts is critical but remains a great challenge. Here, we report an Fe–N–C catalyst with nitrogen-coordinated iron clusters and closely surrounding Fe–N4 active sites for oxygen reduction reaction in acidic fuel cells. A strong electronic interaction is built between iron clusters and satellite Fe–N4 due to unblocked electron transfer pathways and very short interacting distances. The iron clusters optimize the adsorption strength of oxygen reduction intermediates on Fe–N4 and also shorten the bond amplitude of Fe–N4 with incoherent vibrations. As a result, both the activity and stability of Fe–N4 sites are increased by about 60% in terms of turnover frequency and demetalation resistance. This work shows the great potential of strong electronic interactions between multiphase metal species for improvements of single-atom catalysts.

Single-atom catalysts (SACs) have sparked broad interest recently while the low metal loading poses a big challenge for further applications. Herein, a dual protection strategy has been developed to give high-content SACs by nanocasting SiO 2 into porphyrinic metal-organic frameworks (MOFs). The pyrolysis of SiO 2 @MOF composite affords singleatom Fe implanted N-doped porous carbon (Fe SA-N-C) with high Fe loading (3.46 wt%). The spatial isolation of Fe atoms centered in porphyrin linkers of MOF sets the first protective barrier to inhibit the Fe agglomeration during pyrolysis. The SiO 2 in MOF provides additional protection by creating thermally stable FeN 4 /SiO 2 interfaces. Thanks to the high-density Fe SA sites, Fe SA-N-C demonstrates excellent oxygen reduction performance in both alkaline and acidic medias. Meanwhile, Fe SA-N-C also exhibits encouraging performance in proton exchange membrane fuel cell, demonstrating great potential for practical application. More far-reaching, this work grants a general synthetic methodology toward high-content SACs (such as Fe SA , Co SA , Ni SA).

The active sites of Fe–N–C catalysts are nitrogen coordinated iron atoms, FeNx(x = 1–5), that have five possible coordination numbers, corresponding to different ORR activities and PEMFC performances.

The superior capability of cognitive experts largely depends on quick automatic processes. To reveal their neural bases, we used functional magnetic resonance imaging to study brain activity of professional and amateur players in a board game named shogi. We found two activations specific to professionals: one in the precuneus of the parietal lobe during perception of board patterns, and the other in the caudate nucleus of the basal ganglia during quick generation of the best next move. Activities at these two sites covaried in relevant tasks. These results suggest that the precuneus-caudate circuit implements the automatic, yet complicated, processes of board-pattern perception and next-move generation in board game experts.

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Here we present a detailed biophysical model of how brain electrical and vascular dynamics are generated within a basic cortical unit. The model was obtained from coupling a canonical neuronal mass and an expandable vasculature. In this proposal, we address several aspects related to electroencephalographic and functional magnetic resonance imaging data fusion: (1) the impact of the cerebral architecture (at different physical levels) on the observations; (2) the physiology involved in electrovascular coupling; and (3) energetic considerations to gain a better understanding of how the glucose budget is used during neuronal activity. The model has three components. The first is the canonical neural mass model of three subpopulations of neurons that respond to incoming excitatory synaptic inputs. The generation of the membrane potentials in the somas of these neurons and the electric currents flowing in the neuropil are modeled by this component. The second and third components model the electrovascular coupling and the dynamics of vascular states in an extended balloon approach, respectively. In the first part we describe, in some detail, the biophysical model and establish its face validity using simulations of visually evoked responses under different flickering frequencies and luminous contrasts. In a second part, a recursive optimization algorithm is developed and used to make statistical inferences about this forward/generative model from actual data.