Cu single-atom catalysts (Cu SACs) have been considered as promising catalysts for efficient electrocatalytic CO 2 reduction reactions (ECRRs). However, the reports on Cu SACs with an asymmetric atomic interface to obtain CO are few. Herein, we rationally designed two Cu SACs with different asymmetric atomic interfaces to explore their catalytic performance. The catalyst of CuN 3 O/C delivers high ECRR selectivity with an FE CO value of above 90% in a wide potential window from −0.5 to −0.9 V vs RHE (in particular, 96% at −0.8 V), while CuCO 3 /C delivers poor selectivity for CO production with a maximum FE CO value of only 20.0% at −0.5 V vs RHE. Besides, CuN 3 O/C exhibited a large turnover frequency (TOF) up to 2782.6 h −1 at −0.9 V vs RHE, which is much better than the maximum 4.8 h −1 of CuCO 3 /C. Density functional theory (DFT) results demonstrate that the CuN 3 O site needs a lower Gibbs free energy than CuCO 3 in the rate-determining step of CO desorption, leading to the outstanding performance of CuN 3 O/C on the process of ECRR-to-CO. This work provides an efficient strategy to improve the selectivity and activity of the ECRR via regulating asymmetric atomic interfaces of SACs by adjusting the coordination atoms.

The electrocatalytic CO 2 reduction reaction (ECRR) becomes an effective way to reduce excess CO 2 in the air and a promising strategy to maintain carbon balance. Carbonsupported single-atom catalysts (C-SACs) is a kind of cost savings and most promising catalysts for ECRR. For C-SACs, the key to achieving efficient ECRR performance is to adjusting the electronic structure of the central metal atoms by modulating their microenvironment of the catalysts. Not only the coordination numbers and hetero-atom coordination, but also the regulation of diatomic sites have a great influence on the performance of C-SACs. This review mainly focuses on recent studies for the microenvironment modulation in C-SACs for efficient ECRR. We hope that this review can contribute readers a comprehensive insight in the current research status of C-SACs for ECRR, as well as provide help for the rational design of C-SACs with better ECRR performance.

Resting‐state functional connectivity (rsFC) approaches provide informative estimates of the functional architecture of the brain, and recently‐proposed cofluctuation analysis temporally unwraps FC at every moment in time, providing refined information for quantifying brain dynamics. As a brain network disorder, autism spectrum disorder (ASD) was characterized by substantial alteration in FC, but the contribution of moment‐to‐moment‐activity cofluctuations to the overall dysfunctional connectivity pattern in ASD remains poorly understood. Here, we used the cofluctuation approach to explore the underlying dynamic properties of FC in ASD, using a large multisite resting‐state functional magnetic resonance imaging (rs‐fMRI) dataset (ASD = 354, typically developing controls [TD] = 446). Our results verified that the networks estimated using high‐amplitude frames were highly correlated with the traditional rsFC. Moreover, these frames showed higher average amplitudes in participants with ASD than those in the TD group. Principal component analysis was performed on the activity patterns in these frames and aggregated over all subjects. The first principal component (PC1) corresponds to the default mode network (DMN), and the PC1 coefficients were greater in participants with ASD than those in the TD group. Additionally, increased ASD symptom severity was associated with the increased coefficients, which may result in excessive internally oriented cognition and social cognition deficits in individuals with ASD. Our finding highlights the utility of cofluctuation approaches in prevalent neurodevelopmental disorders and verifies that the aberrant contribution of DMN to rsFC may underline the symptomatology in adolescents and youths with ASD.