The ability to precisely engineer the doping of sub-nanometer bimetallic clusters offers exciting opportunities for tailoring their catalytic performance with atomic accuracy. However, the fabrication of singly dispersed bimetallic cluster catalysts with atomic-level control of dopants has been a long-standing challenge. Herein, we report a strategy for the controllable synthesis of a precisely doped single cluster catalyst consisting of partially ligand-enveloped AuPt clusters supported on defective graphene. This creates a bimetal single cluster catalyst (AuPt/G) with exceptional activity for electrochemical nitrogen (N) reduction. Our mechanistic study reveals that each N molecule is activated in the confined region between cluster and graphene. The heteroatom dopant plays an indispensable role in the activation of N via an enhanced back donation of electrons to the N LUMO. Moreover, besides the heteroatom Pt, the catalytic performance of single cluster catalyst can be further tuned by using Pd in place of Pt as the dopant.
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http://dx.doi.org/10.1038/s41467-020-18080-w | DOI Listing |
J Am Chem Soc
January 2025
College of Chemistry, Chemical Engineering and Materials Science, and State Key Laboratory of Radiation Medicine and Protection, Soochow University, Suzhou, Jiangsu 215123, P. R. China.
A thorium-carbon double bond that corresponds to the sum of theoretical covalent double bond radii has long been sought after in the study of actinide-ligand multiple bonding as a synthetic target. However, the stabilization of this chemical bond remains a great challenge to date, in part because of a relatively poor energetic matching between 5f-/6d- orbitals of thorium and the 2s-/2p- frontier orbitals of carbon. Herein, we report the successful synthesis of a thorium-carbon double bond in a carbon-bridged actinide-transition metal cluster, i.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Department of Medicine, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Importance: Blood culture (BC) use benchmarks in US hospitals have not been defined.
Objective: To characterize BC use in adult intensive care units (ICUs) and wards in US hospitals.
Design, Setting, And Participants: A retrospective cross-sectional study of BC use in adult medical ICUs, medical-surgical ICUs, medical wards, and medical-surgical wards from acute care hospitals from the 4 US geographic regions was conducted.
Med J Malaysia
January 2025
National University of Malaysia, Faculty of Medicine, Department of Medicine, Kuala Lumpur, Malaysia.
Introduction: Stroke is a major cause of morbidity and mortality worldwide. While electroencephalography (EEG) offers valuable data on post-stroke brain activity, qualitative EEG assessments may be misinterpreted. Therefore, we examined the potential of quantitative EEG (qEEG) to identify key band frequencies that could serve as potential electrophysiological biomarkers in stroke patients.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Departament de Ciència de Materials i Química Física & Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, c/Martí i Franquès 1-11, Barcelona 08028, Spain.
The oxygen reduction reaction (ORR) stands as a pivotal process in electrochemistry, finding applications in various energy conversion technologies such as fuel cells, metal-air batteries, and chlor-alkali electrolyzers. Hereby, a comprehensive density functional theory (DFT) investigation is presented into the proposed conventional and unconventional ORR mechanisms using single-atom catalysts (SACs) supported on nitrogen-doped graphene (NG) as model systems. Several reaction intermediates have been identified that appear to be more stable than the ones postulated in the conventional mechanism, which follows the *OOH, *O, and *OH intermediates.
View Article and Find Full Text PDFBiol Methods Protoc
January 2025
Department of Physics, George Washington University, Washington, DC 20052, United States.
A mixture-of-experts (MoE) approach has been developed to mitigate the poor out-of-distribution (OOD) generalization of deep learning (DL) models for single-sequence-based prediction of RNA secondary structure. The main idea behind this approach is to use DL models for in-distribution (ID) test sequences to leverage their superior ID performances, while relying on physics-based models for OOD sequences to ensure robust predictions. One key ingredient of the pipeline, named MoEFold2D, is automated ID/OOD detection via consensus analysis of an ensemble of DL model predictions without requiring access to training data during inference.
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