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The electrocatalytic conversion of formate in alkaline solutions is of paramount significance in the realm of fuel cell applications. Nonetheless, the adsorptive affinity of adsorbed hydrogen (H ad ) on the catalyst surface has traditionally impeded the catalytic efficiency of formate in such alkaline environments. To circumvent this challenge, our approach introduces an interfacial push-pull effect on the catalyst surface. This mechanism involves two primary actions: First, the anchoring of palladium (Pd) nanoparticles on a phosphorus-doped TiO 2 substrate (Pd/TiO 2 -P) promotes the formation of electron-rich Pd with a downshifted d band center, thereby "pushing" the desorption of H ad from the Pd active sites. Second, the TiO 2 -P support diminishes the energy barrier for H ad transfer from the Pd sites to the support itself, "pulling" H ad to effectively relocate from the Pd active sites to the support. The resultant Pd/TiO 2 -P catalyst showcases a remarkable mass activity of 4.38 A mg Pd -1 and outperforms the Pd/TiO 2 catalyst (2.39 A mg Pd -1 ) by a factor of 1.83. This advancement not only surmounts a critical barrier in catalysis but also delineates a scalable pathway to bolster the efficacy of Pd-based catalysts in alkaline media.

Highly active nonprecious-metal single-atom catalysts (SACs) toward catalytic transfer hydrogenation (CTH) of α,β-unsaturated aldehydes are of great significance but still are deficient. Herein, we report that Zn-N-C SACs containing Zn-N 3 moieties can catalyze the conversion of cinnamaldehyde to cinnamyl alcohol with a conversion of 95.5% and selectivity of 95.4% under a mild temperature and atmospheric pressure, which is the first case of Zn-species-based heterogeneous catalysts for the CTH reaction. Isotopic labeling, in situ FT-IR spectroscopy, and DFT calculations indicate that reactants, coabsorbed at the Zn sites, proceed CTH via a "Meerwein-Ponndorf-Verley" mechanism. DFT calculations also reveal that the high activity over Zn-N 3 moieties stems from the suitable adsorption energy and favorable reaction energy of the rate-determining step at the Zn active sites. Our findings demonstrate that Zn-N-C SACs hold extraordinary activity toward CTH reactions and thus provide a promising approach to explore the advanced SACs for high-value-added chemicals.

In the quest for proficient electrocatalysts for ammonia's electrocatalytic nitrogen reduction, cobalt oxides, endowed with a rich d-electron reservoir, have emerged as frontrunners. Despite the previously evidenced prowess of CoO in this realm, its ammonia yield witnesses a pronounced decline as the reaction unfolds, a phenomenon linked to the electron attrition from its Co 2+ active sites during electrocatalytic nitrogen reduction reaction (ENRR). To counteract this vulnerability, we harnessed electron-laden phosphorus (P) elements as dopants, aiming to recalibrate the electronic equilibrium of the pivotal Co active site, thereby bolstering both its catalytic performance and stability. Our empirical endeavors showcased the doped P-CoO's superior credentials: it delivered an impressive ammonia yield of 49.6 and, notably, a Faradaic efficiency (FE) of 9.6% at -0.2 V versus RHE, markedly eclipsing its undoped counterpart. Probing deeper, a suite of ex-situ techniques, complemented by rigorous theoretical evaluations, was deployed. This dual-pronged analysis unequivocally revealed CoO's propensity for an electron-driven valence metamorphosis to Co 3+ post-ENRR. In stark contrast, P-CoO, fortified by P doping, exhibits a discernibly augmented ammonia yield. Crucially, P's intrinsic ability to staunch electron leakage from the active locus during ENRR ensures the preservation of the valence state, culminating in enhanced catalytic dynamism and fortitude. This investigation not only illuminates the intricacies of active site electronic modulation in ENRR but also charts a navigational beacon for further enhancements in this domain.

Co 3 O 4 is a highly selective catalyst for the electrochemical conversion of N 2 to NH 3 . However, the large work function (WF) of Co 3 O 4 leads to unsatisfactory activity. To address this issue, a strong built-in electric field (BIEF) was constructed in Co 3 O 4 by doping C atoms (C-Co 3 O 4 ) to reduce the WF for improving the electrocatalytic performance. C-Co 3 O 4 exhibited a remarkable NH 3 yield of 38.5 μg h -1 mg cat -1 and a promoted FE of 15.1% at -0.3 V vs RHE, which were 2.2 and 1.9 times higher than those of pure Co 3 O 4 , respectively. Kelvin probe force microscopy (KPFM), zeta potential, and ultraviolet photoelectron spectrometry (UPS) confirmed the formation of strong BIEF and WF reduction in C-Co 3 O 4 . Additionally, in situ Raman measurements and density functional theory (DFT) calculations revealed the relationship between BIEF and WF and provided insights into the reaction mechanism. Our work offers valuable guidance for the design and development of more efficient nitrogen reduction catalysts.

Efficient conversion of carbon dioxide (CO 2 ) into value-added materials and feedstocks, powered by renewable electricity, presents a promising strategy to reduce greenhouse gas emissions and close the anthropogenic carbon loop. Recently, there has been intense interest in Cu 2 O-based catalysts for the CO 2 reduction reaction (CO 2 RR), owing to their capabilities in enhancing C-C coupling. However, the electrochemical instability of Cu + in Cu 2 O leads to its inevitable reduction to Cu 0 , resulting in poor selectivity for C 2+ products. Herein, we propose an unconventional and feasible strategy for stabilizing Cu + through the construction of a Ce 4+ 4f-O 2p-Cu + 3d network structure in Ce-Cu 2 O. Experimental results and theoretical calculations confirm that the unconventional orbital hybridization near E f based on the high-order Ce 4+ 4f and 2p can more effectively inhibit the leaching of lattice oxygen, thereby stabilizing Cu + in Ce-Cu 2 O, compared with traditional d-p hybridization. Compared to pure Cu 2 O, the Ce-Cu 2 O catalyst increased the ratio of C 2 H 4 /CO by 1.69-fold during the CO 2 RR at -1.3 V. Furthermore, in situ and ex situ spectroscopic techniques were utilized to track the oxidation valency of copper under CO 2 RR conditions with time resolution, identifying the well-maintained Cu + species in the Ce-Cu 2 O catalyst. This work not only presents an avenue to CO 2 RR catalyst design involving the high-order 4f and 2p orbital hybridization but also provides deep insights into the metal-oxidation-state-dependent selectivity of catalysts.

Transferring structural information from amino acid sequence to macroscale assembly is a challenging approach for designing protein quaternary structure. However, the pathway by which the slight variations in sequence result in a global perturbation effect on the assembled structure is unknown. Herein, we design two synthetic peptides, QNL-His and QNL-Arg, with one amino acid substitution and use scanning tunneling microscopy (STM) to image individual peptides in the assembled state. The submolecular resolution of STM enables us to determine the folding structure and β-sheet supramolecular organization of peptides. QNL-His and QNL-Arg differ in their β-strand length distribution in pleated β-sheet association. These structural variations lead to distinguishable outcomes in their β-sheet assembled fibrils and phase transitions. The comparison of QNL-His versus QNL-Arg structures and macroscopic properties unveils the role of assembly to amplify the structural variations associated with a single-site mutation from a single-molecule scale to a macroscopic scale.

In drug design, the design and manufacture of safe and effective compounds is a long-term, complex, and complicated process. Therefore, developing a new rapid and generalizable drug design method is of great value. This study aimed to propose a general model based on reinforcement learning combined with drug-target interaction, which could be used to design new molecules according to different protein targets. The method adopted recurrent neural network molecular modeling and took the drug-target affinity model as the reward function of optimal molecular generation. It did not need to know the three-dimensional structure and active sites of protein targets but only required the information of a one-dimensional amino acid sequence. This approach was demonstrated to produce drugs highly similar to marketed drugs and design molecules with a better binding energy., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)