Zero thermal expansion (ZTE) is an intriguing phenomenon by virtue of its peculiar lack of expansion and contraction with temperature. The achievement of ZTE in a metallic material is a desired but challenging task. Here we report the ZTE behavior of a single-phase metallic VB compound, stacking with the V and B atomic layers along the direction (α = 2.18 × 10 K, 5-150 K). Neutron powder diffraction demonstrates that the ZTE behavior is entangled in the direct blocking of the lattice expansion along all crystallographic directions with temperature. X-ray photoelectron spectroscopy and density functional theory calculations indicate that strong covalent binding adheres the nearest-neighbor B-B and V-B pairs, which is proposed to control the ZTE within both the basal plane and the direction. An intimate correlation is revealed between the covalent binding and the lattice parameters. Our work indicates the opportunity to design metallic ZTE with strong chemical binding in the future.
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http://dx.doi.org/10.1021/acs.inorgchem.1c01261 | DOI Listing |
Nat Commun
January 2025
Department of Environment, Zhejiang University of Technology, Hangzhou, 310014, China.
The generation of radicals through photo-Fenton-like reactions demonstrates significant potential for remediating emerging organic contaminants (EOCs) in complex aqueous environments. However, the excitonic effect, induced by Coulomb interactions between photoexcited electrons and holes, reduces carrier utilization efficiency in these systems. In this study, we develop Cu single-atom-loaded covalent organic frameworks (Cu/COFs) as models to modulate excitonic effects.
View Article and Find Full Text PDFCarbohydr Res
January 2025
Université Paris Cité and Université des Antilles and Université de la Réunion, INSERM, BIGR, F-75015 Paris, France. Electronic address:
Protein-carbohydrate interactions play a crucial role in numerous fundamental biological processes. Thus, description and comparison of the carbohydrate binding site (CBS) architecture is of great importance for understanding of the underlying biological mechanisms. However, traditional approaches for carbohydrate-binding protein analysis and annotation rely primarily on the sequence-based methods applied to specific protein classes.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules, Shanghai Jiao Tong University, Shanghai, 200240, China.
Sulfur-fluoride exchange (SuFEx) reaction is an emerging class of click chemistry reaction. Owing to its efficient reactivity under physiological conditions, SuFEx reaction is used to construct covalent protein drugs. Herein, a covalent affibody-molecular glue drug conjugate nanoagent is reported, which can irreversibly bind with its target protein through proximity-enabled SuFEx reaction.
View Article and Find Full Text PDFBiometals
January 2025
Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX, USA.
Mercury is widely known for its detrimental effects on living organisms, whether in its elemental or bonded states. Recent comparative studies have shed light on the biochemical implications of mercury ingestion, both in low, persistent concentrations and in elevated acute dosages. Studies have presented models that elucidate how mercury disrupts healthy cells.
View Article and Find Full Text PDFCurr Pharm Des
January 2025
Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University, Yangling, Shaanxi, 712100, China.
Introduction: The COVID-19 pandemic has necessitated rapid advancements in therapeutic discovery. This study presents an integrated approach combining machine learning (ML) and network pharmacology to identify potential non-covalent inhibitors against pivotal proteins in COVID-19 pathogenesis, specifically B-cell lymphoma 2 (BCL2) and Epidermal Growth Factor Receptor (EGFR).
Method: Employing a dataset of 13,107 compounds, ML algorithms such as k-Nearest Neighbors (kNN), Support Vector Machine (SVM), Random Forest (RF), and Naïve Bayes (NB) were utilized for screening and predicting active inhibitors based on molecular features.
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