Yb doped perovskite nanocrystals (PNCs) serve as efficient photoconverters, exhibiting quantum cutting emission at ∼980 nm, which aligns precisely with the optimal response region of silicon solar cells (SSCs). However, severe nonradiative recombination caused by defects in the crystal lattice and film boundaries, along with limitations in small-scale film preparation, restricts their commercial application. Here, we used Ru to mitigate lattice defects in CsPbCl PNCs and adjusted the quantum cutting luminescence, achieving a 175% photoluminescence quantum yield (PLQY). The results show that Ru ions enter the perovskite lattice, fill lead vacancies, and passivate the lattice defects. Furthermore, cysteine effectively eliminates surface defects in PNCs by forming Pb-S bonds, resulting in films with a remarkable 117% PLQY, demonstrating strong photoconversion capabilities. Uniformly knife-coated on 20 × 20 cm photovoltaic glass, these films increased SSC efficiency from 21.45% to 23.15%. This study showcases a cost-effective photoconverter and a scalable coating method to boost the photovoltaic efficiency of large-area SSCs.
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http://dx.doi.org/10.1021/acs.jpclett.4c01600 | DOI Listing |
Comput Struct Biotechnol J
December 2024
NovaMechanics Ltd, Nicosia 1070, Cyprus.
The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs, enhancing both regulatory compliance and international collaboration. By building on established nanoinformatics frameworks, such as those developed in the H2020-funded projects NanoSolveIT and NanoCommons, CompSafeNano addresses critical challenges in nanosafety through development and integration of innovative methodologies, including advanced models, approaches including machine learning (ML) and artificial intelligence (AI)-driven predictive models and 1st-principles computational modelling of NMs properties, interactions and effects on living systems.
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January 2025
State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China.
Traditional energy-integration X-ray imaging systems rely on total X-ray intensity for image contrast, ignoring energy-specific information. Recently developed multilayer stacked scintillators have enabled multispectral, large-area flat-panel X-ray imaging (FPXI), enhancing material discrimination capabilities. However, increased layering can lead to mutual excitation, which may affect the accurate discrimination of X-ray energy.
View Article and Find Full Text PDFSci Rep
January 2025
IBM T. J. Watson Research Center, Yorktown Heights, NY, 10598, USA.
The development of high-brightness electron sources is critical to state-of-the-art electron accelerator applications like X-ray free electron laser (XFEL) and ultra-fast electron microscopy. Cesium telluride is chosen as the electron source material for multiple cutting-edge XFEL facilities worldwide. This manuscript presents the first demonstration of the growth of highly crystalized and epitaxial cesium telluride thin films on 4H-SiC and graphene/4H-SiC substrates with ultrasmooth film surfaces.
View Article and Find Full Text PDFiScience
January 2025
School of Physics and Electronic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China.
Efficiently generating energetically stable crystal structures has long been a challenge in material design, primarily due to the immense arrangement of atoms in a crystal lattice. To facilitate the discovery of stable materials, we present a framework for the generation of synthesizable materials leveraging a point cloud representation to encode intricate structural information. At the heart of this framework lies the introduction of a diffusion model as its foundational pillar.
View Article and Find Full Text PDFInt J Radiat Oncol Biol Phys
January 2025
National Cancer Institute, Bethesda, MD. Electronic address:
This white paper examines the potential of pioneering technologies and artificial intelligence (AI)-driven solutions in advancing clinical trials involving radiotherapy. As the field of radiotherapy evolves, the integration of cutting-edge approaches such as radiopharmaceutical dosimetry, FLASH radiotherapy, image-guided radiation therapy (IGRT), and AI promises to improve treatment planning, patient care, and outcomes. Additionally, recent advancements in quantum science, linear energy transfer/relative biological effect (LET/RBE), and the combination of radiotherapy and immunotherapy create new avenues for innovation in clinical trials.
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