RESUMO
Rational design of well-defined active sites is crucial for promoting sluggish oxygen reduction reactions. Herein, leveraging the surfactant-oriented and solvent-ligand effects, we develop a facile self-assembly strategy to construct a core-shell catalyst comprising a high-index Pt shell encapsulating a PtCu3 intermetallic core with efficient oxygen-reduction performance. Without undergoing a high-temperature route, the ordered PtCu3 is directly fabricated through the accelerated reduction of Cu2+, followed by the deposition of the remaining Pt precursor onto its surface, forming high-index steps oriented by the steric hindrance of surfactant. This approach results in a high half-wave potential of 0.911 V versus reversible hydrogen electrode, with negligible deactivation even after 15000-cycle operation. Operando spectroscopies identify that this core-shell catalyst facilitates the conversion of oxygen-involving intermediates and ensures antidissolution ability. Theoretical investigations rationalize that this improvement is attributed to reinforced electronic interactions around high-index Pt, stabilizing the binding strength of rate-determining OHads species.
RESUMO
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder. Functional magnetic resonance imaging (fMRI) can be used to measure the temporal correlation of blood-oxygen-level-dependent (BOLD) signals in the brain to assess the brain's intrinsic connectivity and capture dynamic changes in the brain. In this study, the hidden Markov model (HMM) and dynamic graph (DG) theory are used to study the spatial-temporal characteristics and dynamics of brain networks based on dynamic functional connectivity (DFC). By using HMM, we identified three typical brain states for ASD and healthy control (HC). Furthermore, we explored the correlation between HMM time-varying properties and clinical autism scale scores. Differences in brain topological characteristics and dynamics between ASD and HC were compared by DG analysis. The experimental results indicate that ASD is more inclined to enter a strongly connected HMM brain state, leading to the isolation of brain networks and alterations in the topological characteristics of brain networks, such as default mode network (DMN), ventral attention network (VAN), and visual network (VN). This work suggests that using different data-driven methods based on DFC to study brain network dynamics would have better information complementarity, which can provide a new direction for the extraction of neuro-biomarkers in the early diagnosis of ASD.
RESUMO
Manipulation of selectivity in the catalytic electrochemical carbon dioxide reduction reaction (eCO2RR) poses significant challenges due to inevitable structure reconstruction. One approach is to develop effective strategies for controlling reaction pathways to gain a deeper understanding of mechanisms in robust CO2RR systems. In this work, by precise introduction of 1,10-phenanthroline as a bidentate ligand modulator, the electronic property of the copper site was effectively regulated, thereby directing selectivity switch. By modification of [Cu3(btec)(OH)2]n, the use of [Cu2(btec)(phen)2]n·(H2O)n achieved the selectivity switch from ethylene (faradaic efficiency (FE) = 41%, FEC2+ = 67%) to methane (FECH4 = 69%). Various in situ spectroscopic characterizations revealed that [Cu2(btec)(phen)2]n·(H2O)n promoted the hydrogenation of *CO intermediates, leading to methane generation instead of dimerization to form C2+ products. Acting as a delocalized π-conjugation scaffold, 1,10-phenanthroline in [Cu2(btec)(phen)2]n·(H2O)n helps stabilize Cuδ+. This work presents a novel approach to regulate the coordination environment of active sites with the aim of selectively modulating the CO2RR.