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Mechanoluminescence (ML) phosphors have made significant progress in various fields, such as artificial intelligence, the Internet of Things, and biotechnology. However, enhancing their weak ML intensity still remains a challenge. Here, we report a new series of NaMgNbO:Pr ( = 0.00, 0.10, 0.20, 0.40, 0.60, 0.80, and 1.00 mol %) heterojunction systems, which exhibit significant ML enhancement as compared with either the Pr-doped NaNbO or MgNbO, and the physical mechanisms behind the ML enhancement have been explored comprehensively from both the experiment and theory points of view. Experimental tests, including thermoluminescence and positron annihilation lifetime measurements, combined with first-principles calculations, consistently indicate that the ML enhancement observed in these newly reported systems is due to the formation of heterojunctions, which plays a crucial role in modulating the defect configuration of the phosphors and facilitating efficient charge transfer. By controlling the Na/Mg ratio in conjunction with Pr doping, continuous changes in the band offset and the concentrations of certain types of traps in the forbidden gap are achieved, leading to the optimum conditions in the 8/2 ratio samples. These findings demonstrate a novel type of ML phosphor and provide a theoretical basis for the design of high-performance ML phosphor.
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http://dx.doi.org/10.1021/acsami.3c01282 | DOI Listing |
Proc Natl Acad Sci U S A
September 2025
Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520.
A frequent goal of phage biology is to quantify how well a phage kills a population of host bacteria. Unfortunately, traditional methods to quantify phage success can be time-consuming, limiting the throughput of experiments. Here, we use theory to show how the effects of phages on their hosts can be quantified using bacterial population dynamics measured in a high-throughput microplate reader (automated spectrophotometer).
View Article and Find Full Text PDFPLoS One
September 2025
Information Technologies and Programming Faculty, ITMO University, Saint Petersburg, Russia.
In the paper we consider the well-known Influence Maximization (IM) and Target Set Selection (TSS) problems for Boolean networks under Deterministic Linear Threshold Model (DLTM). The main novelty of our paper is that we state these problems in the context of pseudo-Boolean optimization and solve them using evolutionary algorithms in combination with the known greedy heuristic. We also propose a new variant of (1 + 1)-Evolutionary Algorithm, which is designed to optimize a fitness function on the subset of the Boolean hypercube comprised of vectors of a fixed Hamming weight.
View Article and Find Full Text PDFPLoS One
September 2025
McMaster Education Research, Innovation & Theory (MERIT) Program, McMaster University, Hamilton, Ontario, Canada.
Introduction: Research on listening to podcasts while driving suggested no significant difference compared to undistracted listening. However, these studies were conducted in non-controlled driving environments, limiting the evaluation of the environment's impact. This study aimed to compare knowledge acquisition and retention among resident physicians and undergraduate students while listening to medical education podcasts in a controlled, simulator-based, driving environment versus an undistracted listening condition.
View Article and Find Full Text PDFJ Chem Phys
September 2025
Fukui Institute for Fundamental Chemistry, Kyoto University, Takano-nishibiraki-cho 34-4, Sakyo-ku, Kyoto 606-8103, Japan.
Linear carbon cluster anions, such as C6-, have been considered to be promising candidate interstellar molecules. Recent experiments have demonstrated that in a collision-free vacuum environment, C6- exhibits fast radiative cooling from its highly vibrationally excited states through inverse internal conversion (IIC). Since IIC is driven by vibronic coupling, the understanding of vibronic structures of C6- is of theoretical significance.
View Article and Find Full Text PDFJ Chem Phys
September 2025
Institute of Materials Chemistry, Vienna University of Technology, Vienna, Austria.
Accurately modeling volume-dependent properties of water remains a challenge for density functional theory (DFT), with widely used functionals failing to reproduce key features of the water density isobar, including its shape, density, and temperature of the density maximum. Here, we compare the performance of the RPBE-D3 and vdW-DF-cx functionals using replica exchange molecular dynamics (MD) driven by machine-learned force fields. Our simulations reveal that vdW-DF-cx predicts the water density more accurately than RPBE-D3 and reproduces the isobar closely between 307 and 340 K.
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