Surface functionalization through adsorption of ligands or non-metal atoms is considered to be an interesting and viable approach for tuning the physicochemical properties of gold clusters. Highly stable and magic numbered electronic configurations of thiolate protected gold clusters such as Au25(SR)18, Au38(SR)24etc. with intriguing properties are the direct manifestation of the rich chemistry of the Au-S interface. The present investigation discerns the CO oxidation activity of structurally well characterized sulphur functionalized gold cluster anions AumS4-, m = 6-10. To establish an in-depth understanding, their activities are analyzed and compared with the corresponding pristine gold clusters. It is seen that sulphur functionalization irrespective of a closed or open shell nature leads to a significant decrease in the O2 adsorption energies on the anionic gold clusters. However, in sharp contrast to O2 adsorption, surface functionalization gives rise to multifarious catalytic behavior in AumS4- clusters with catalytic activity ranging from low (for Au6S4-, Au8S4-) to moderate (for Au9S4-, Au10S4-) to very high (for Au7S4-) for CO oxidation. It is interesting to note that the closed shell Au7S4- and Au9S4- clusters with poor O2 adsorption show remarkably low activation barriers and enhanced catalytic activity as compared to the open shell AumS4- clusters with an odd number of electrons. In particular, in the case of Au7S4- the lowest activation energy barriers of 0.01 and 0.21 eV are obtained, making the CO oxidation reaction facile. Moreover, ab initio molecular dynamics are performed to confirm the enhanced catalytic behaviour of Au7S4- and its dynamical stability during the desorption of CO2 molecule from its surface.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1039/d0cp01918f | DOI Listing |
Nat Comput Sci
December 2024
Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Machine learning plays an important role in quantum chemistry, providing fast-to-evaluate predictive models for various properties of molecules; however, most existing machine learning models for molecular electronic properties use density functional theory (DFT) databases as ground truth in training, and their prediction accuracy cannot surpass that of DFT. In this work we developed a unified machine learning method for electronic structures of organic molecules using the gold-standard CCSD(T) calculations as training data. Tested on hydrocarbon molecules, our model outperforms DFT with several widely used hybrid and double-hybrid functionals in terms of both computational cost and prediction accuracy of various quantum chemical properties.
View Article and Find Full Text PDFInfect Control Hosp Epidemiol
December 2024
Department of Infectious Diseases, Infection Control, and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Objective: Whole genome sequencing (WGS) can help identify transmission of pathogens causing healthcare-associated infections (HAIs). However, the current gold standard of short-read, Illumina-based WGS is labor and time intensive. Given recent improvements in long-read Oxford Nanopore Technologies (ONT) sequencing, we sought to establish a low resource approach providing accurate WGS-pathogen comparison within a time frame allowing for infection prevention and control (IPC) interventions.
View Article and Find Full Text PDFLancet Digit Health
January 2025
Biomedical Engineering Department, Duke University, Durham, NC, USA; Biostatistics and Bioinformatics Department, Duke University, Durham, NC, USA. Electronic address:
Background: Longitudinal digital health studies combine passively collected information from digital devices, such as commercial wearable devices, and actively contributed data, such as surveys, from participants. Although the use of smartphones and access to the internet supports the development of these studies, challenges exist in collecting representative data due to low adherence and retention. We aimed to identify key factors related to adherence and retention in digital health studies and develop a methodology to identify factors that are associated with and might affect study participant engagement.
View Article and Find Full Text PDFSemin Hematol
November 2024
Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY. Electronic address:
Etiological links to multiple myeloma (MM) remain poorly understood, though emerging evidence suggests a significant hereditary component. This review integrates current literature on inherited factors contributing to MM risk, synthesizing both epidemiologic and genomic data. We examine familial clustering patterns, assess genome-wide association studies (GWAS) that reveal common genetic variants linked to MM, and explore rare, high-penetrance variants in key susceptibility genes.
View Article and Find Full Text PDFInorg Chem
December 2024
College of Energy Materials and Chemistry, Inner Mongolia University, Hohhot 010021, China.
Ligand-stabilized metal nanoclusters with atomic precision are considered to be promising materials in the field of light-emitting and harvesting. Among these, nanoclusters with thermally activated delayed fluorescence (TADF) properties are highly sought after. While several gold and silver nanoclusters with TADF properties have been reported in recent years, research on copper counterparts has significantly lagged behind.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!