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Helium (He) accumulation in tungsten-widely used as a plasma-facing material in fusion reactors-can lead to clustering, trap mutation, and eventual formation of helium bubbles, critically impacting material performance. To clarify the atomic-scale mechanisms governing this process, we conducted systematic molecular statics and molecular dynamics simulations across a wide range of vacancy cluster sizes (n = 1-27) and temperatures (500-2000 K). We identified the onset of trap mutation through abrupt increases in tungsten atomic displacement. At 0 K, the critical helium-to-vacancy (He/V) ratio required to trigger mutation was found to scale inversely with cluster size, converging to ~5.6 for large clusters. At elevated temperatures, thermal activation lowered the mutation threshold and introduced a distinct He/V stability window. Below this window, clusters tend to dissociate; above it, trap mutation occurs with near certainty. This critical He/V ratio exhibits a linear dependence on temperature and can be described by a size- and temperature-dependent empirical relation. Our results provide a quantitative framework for predicting trap mutation behavior in tungsten, offering key input for multiscale models and informing the design of radiation-resistant materials for fusion applications.
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http://dx.doi.org/10.3390/ma18153518 | DOI Listing |
Biochem Pharmacol
September 2025
Department of Biosciences, JIS University, 81, Nilgunj Road, Agarpara, Kolkata, West Bengal 700109, India. Electronic address:
The malignant manifestation of breast cancer is driven by complex molecular alterations that extend beyond genetic mutations to include epigenetic dysregulation. Among these, DNA methylation is a critical and reversible epigenetic modification that significantly influences breast cancer initiation, progression, and therapeutic resistance. This process, mediated by DNA methyltransferases (DNMTs), involves the addition of methyl groups to cytosine residues within CpG dinucleotides, resulting in transcriptional repression of genes.
View Article and Find Full Text PDFSmall
September 2025
Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems, Department of Mechanical and Energy Engineering, SUSTech Energy Institute for Carbon Neutrality, Southern University of Science and Technology, Shenzhen, 518055, China.
The surface passivation with phenethylammonium halides has proven effective in reducing defect density and trap-assisted recombination, enabling outstanding efficiency in perovskite solar cells. Despite its promise, it is ambiguous whether this strategy can improve the stability of devices under rigorous conditions, such as light soaking and thermal aging. A critical issue is whether the interface is robust in structure and morphology under light illumination.
View Article and Find Full Text PDFNPJ Parkinsons Dis
August 2025
Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada.
Parkinson's Disease (PD) is a neurodegenerative disorder often preceded by gastrointestinal dysfunction. Mutations in leucine-rich repeat kinase 2 (LRRK2) are known risk factors for both PD and inflammatory bowel disease (IBD), suggesting a link between PD and the gastrointestinal tract. Using single-cell RNA-sequencing and spectral flow cytometry, we demonstrated that the Lrrk2 Gly2019Ser (G2019S) mutation is associated with an increased neutrophil presence in the colonic lamina propria during Citrobacter rodentium infection.
View Article and Find Full Text PDFBMC Oral Health
August 2025
Department of Oral and Maxillofacial Surgery, Affiliated Stomatological Hospital of Kunming Medical University, Kunming, 650031, China.
Background: To date, genetic studies on florid cemento-osseous dysplasia (FCOD) remain limited. This study aimed to elucidate the clinical features and genetic basis of FCOD in Chinese populations, with particular emphasis on identifying pathogenic variants and their mechanistic contributions to disease development.
Methods: Clinical data from 17 FCOD patients diagnosed between May 2015 and December 2024 at Kunming Medical University Affiliated Stomatological Hospital were retrospectively analyzed.
IEEE Trans Comput Biol Bioinform
January 2025
Considering the high cost associated with determining reaction affinities through in vitro experiments, virtual screening of potential drugs bound to specific protein pockets from vast compounds is critical in AI-assisted drug discovery. Deep-learning approaches have been proposed for predicting Drug-Target Interactions (DTIs). However, they have shown an overestimated accuracy due to the drug-bias trap, a challenge where traditional multimodal models overly rely on the drug branch while underutilizing protein information.
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