Photocatalytic CO reduction into formate (HCOO) has been widely studied with semiconductor and molecule-based systems, but it is rarely investigated with covalent organic frameworks (COFs). Herein, we report a novel donor-acceptor COF named composed of isoindigo and metallated porphyrin subunits that exhibits high catalytic efficiency (∼50 μmol formate g h) at low-power visible-light irradiation and in the absence of rare metal cocatalysts. Density functional theory calculations and experimental diffuse-reflectance measurements are used to explain the origin of catalytic efficiency and the particularly low band gap (0.56 eV) in this material. The mechanism of photocatalysis is also studied experimentally and is found to involve electron transfer from the sacrificial agent to the excited . The observed high-efficiency conversion could be ascribed to the enhanced CO adsorption on the coordinatively unsaturated cobalt centers, the narrow band gap, and the efficient transfer of the charge originating from the postsynthetic metallation. It is anticipated that this study will pave the way toward the design of new simple and efficient catalysts for photocatalytic CO reduction into useful products.
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http://dx.doi.org/10.1021/acsami.1c20729 | DOI Listing |
Sci Technol Adv Mater
January 2025
Magnetic Functional Device Group, Research Center for Magnetic and Spintronic Materials (CMSM), National Institute for Materials Science (NIMS), Tsukuba, Japan.
We demonstrate high-throughput evaluation of the half-metallicity of CoMnSi Heusler alloys by spin-integrated hard X-ray photoelectron spectroscopy (HAXPES) of composition-spread films performed with high-brilliance synchrotron radiation at NanoTerasu, which identifies the optimum composition showing the best half-metallicity. Co Mn Si composition-spread thin films for = 10-40% with a thickness of 30 nm are fabricated on MgO(100) substrates using combinatorial sputtering technique. The 2-ordering and (001)-oriented epitaxial growth of CoMnSi are confirmed by X-ray diffraction for = 18-40%.
View Article and Find Full Text PDFJ Phys Chem Lett
January 2025
College of Chemistry and Materials Science, Hebei University, Baoding 071002, P. R. China.
The photoelectric conversion efficiency (PCE) of perovskites remains beneath the Shockley-Queisser limit, despite its significant potential for solar cell applications. The present focus is on investigating potential multicomponent perovskite candidates, particularly on the application of machine learning to expedite band gap screening. To efficiently identify high-performance perovskites, we utilized a data set of 1346 hybrid organic-inorganic perovskites and employed 11 machine learning models, including decision trees, convolutional neural networks (CNNs), and graph neural networks (GNNs).
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.
Majorana zero modes are predicted to emerge in semiconductor/superconductor interfaces, such as InAs/Al. Majorana modes could be utilized for fault tolerant topological qubits. However, their realization is hindered by materials challenges.
View Article and Find Full Text PDFSci Rep
January 2025
Saint Petersburg State University, St. Petersburg, 198504, Russia.
Using angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT), an experimental and theoretical study of changes in the electronic structure (dispersion dependencies) and corresponding modification of the energy band gap at the Dirac point (DP) for topological insulator (TI) [Formula: see text] have been carried out with gradual replacement of magnetic Mn atoms by non-magnetic Ge atoms when concentration of the latter was varied from 10% to 75%. It was shown that when Ge concentration increases, the bulk band gap decreases and reaches zero plateau in the concentration range of 45-60% while trivial surface states (TrSS) are present and exhibit an energy splitting of 100 and 70 meV in different types of measurements. It was also shown that TSS disappear from the measured band dispersions at a Ge concentration of about 40%.
View Article and Find Full Text PDFJ Phys Chem Lett
January 2025
Department of Physics, Rutgers University, Newark, New Jersey 07102, United States of America.
Graph Neural Networks (GNNs) have emerged as powerful tools for predicting material properties, yet they often struggle to capture many-body interactions and require extensive manual feature engineering. Here, we present EOSnet (Embedded Overlap Structures for Graph Neural Networks), a novel approach that addresses these limitations by incorporating Gaussian Overlap Matrix (GOM) fingerprints as node features within the GNN architecture. Unlike models that rely on explicit angular terms or human-engineered features, EOSnet efficiently encodes many-body interactions through orbital overlap matrices, providing a rotationally invariant and transferable representation of atomic environments.
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