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Uncertainty regarding the nature of structural defects in hematite and their specific impacts on material properties and photoelectrocatalytic water oxidation inhibits their development as photoanodes. We perform structure-property analysis on a series of hematite films fabricated by annealing lepidocrocite films with varied temperatures, annealing times and atmospheres and find a gradient in the magnitude of a crystal lattice distortion by tracking the relative intensity of a formally Raman inactive vibrational mode. Structure-property analysis reveals that this feature in the Raman spectrum correlates to photocurrent density, semiconductor band positions, and the onset of photoelectrocatalysis. We propose that the onset of photoelectrocatalysis is linked to the location of defects that act as intraband recombination sites; an increase in the degree of structural distortion shifts these states towards the conduction band, thereby facilitating recombination. Analysis of the nature of the key Raman vibrations, X-ray diffraction patterns, and the synthetic conditions leads us to assign the distortion to iron vacancies that are induced by the trapping of protons within the crystal lattice. The ability to rapidly diagnose a specific structural defect will aid in the optimization of fabrication protocols for hematite photoanodes.
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http://dx.doi.org/10.1039/c9sc04853g | DOI Listing |
J Chem Phys
September 2025
National Synchrotron Radiation Laboratory, State Key Laboratory of Advanced Glass Materials, Anhui Provincial Engineering Research Center for Advanced Functional Polymer Films, University of Science and Technology of China, Hefei, Anhui 230029, China.
Polymer density is a critical factor influencing material performance and industrial applications, and it can be tailored by modifying the chemical structure of repeating units. Traditional polymer density characterization methods rely heavily on domain expertise; however, the vast chemical space comprising over one million potential polymer structures makes conventional experimental screening inefficient and costly. In this study, we proposed a machine learning framework for polymer density prediction, rigorously evaluating four models: neural networks (NNs), random forest (RF), XGBoost, and graph convolutional neural networks (GCNNs).
View Article and Find Full Text PDFJ Phys Chem Lett
September 2025
Faculty of Chemistry, Wrocław University of Science and Technology, Wyb. Wyspiańskiego 27, PL-50370 Wrocław, Poland.
Computer simulations play an essential role in the interpretation of experimental multiphoton absorption spectra. In addition, models derived from theory allow for the establishment of "structure-property" relationships. This work contributes to these efforts and presents the results of an analysis of two- and three-photon absorptions for a set comprising 450 conjugated molecules performed at the CAM-B3LYP/aug-cc-pVDZ level.
View Article and Find Full Text PDFInt J Biol Macromol
September 2025
Natural Composites Research Group Lab, Department of Materials and Production Engineering, The Sirindhorn International Thai-German Graduate School of Engineering (TGGS), King Mongkut's University of Technology North Bangkok (KMUTNB), Bangkok, Thailand.
This review critically examines the rapidly advancing field of cellulosic natural fibre-reinforced polymer (NFRP) composites, with a particular emphasis on material innovation aligned with sustainability and environmental responsibility. The review presents a systematic analysis of recent literature evaluating the mechanical, thermal, water absorption, wear, and machining characteristics of NFRP composites, as well as the influence of advanced processing approaches such as additive manufacturing. Special attention is given to the structure-property relationships and hybridisation strategies employed to address limitations such as relatively lower mechanical performance and durability compared to synthetic fibre composites.
View Article and Find Full Text PDFLuminescence
September 2025
School of Textile Science and Engineering, Wuyi University, Jiangmen, Guangdong, China.
Acidochromic fluorescent membranes have garnered significant research interest owing to their potential in real-time environmental monitoring and smart sensing applications. However, the rational design of membranes to optimize their structure-property interplay for enhanced acidochromic performance remains further explored. Herein, we prepared various stimulus-responsive micro/nanofibrous membranes using electrospinning technology by incorporating a fluorescent small molecule (TPECNPy-2) with thermoplastic polyurethane (TPU) to obtain specific properties.
View Article and Find Full Text PDFJ Phys Chem B
September 2025
Zhejiang Key Laboratory of Data-Driven High-Safety Energy Materials and Applications, Ningbo Key Laboratory of Special Energy Materials and Chemistry, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
This study developed a high-precision deep potential (DP) model based on density functional theory (DFT) and the DP-GEN workflow to efficiently simulate the microscopic structures and thermophysical properties of LiF-NaF-KF molten salt systems with varying compositions. Through iterative optimization of the training data set using the DP-GEN active learning strategy, our DP model demonstrated excellent agreement with DFT calculations in predicting energies, forces, and stresses. Leveraging this model, we systematically investigated the local structures and properties of 22 FLiNaK molten salt compositions, including radial distribution functions (RDFs), coordination numbers (CNs), density (ρ), heat capacity (), self-diffusion coefficients (SDCs), electrical conductivity, and shear viscosity.
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