A large amount of lithium-ion storage in Si-based anodes promises high energy density yet also results in large volume expansion, causing impaired cyclability and conductivity. Instead of restricting pulverization of Si-based particles, herein, we disclose that single-walled carbon nanotubes (SWNTs) can take advantage of volume expansion and induce interfacial reactions that stabilize the pulverized Si-based clusters . Raman spectroscopy and density functional theory calculations reveal that the volume expansion by the lithiation of Si-based particles generates ∼14% tensile strains in SWNTs, which, in turn, strengthens the chemical interaction between Li and C. This chemomechanical coupling effect facilitates the transformation of sp-C at the defect of SWNTs to Li-C bonds with sp hybridization, which also initiates the formation of new Si-C chemical bonds at the interface. Along with this process, SWNTs can also induce reconstruction of the 3D architecture of the anode, forming mechanically strengthened networks with high electrical and ionic conductivities. As such, with the addition of only 1 wt % of SWNTs, graphite/SiO composite anodes can deliver practical performance well surpassing that of commercial graphite anodes. These findings enrich our understanding of strain-induced interfacial reactions, providing a general principle for mitigating the degradation of alloying or conversion-reaction-based electrodes.
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http://dx.doi.org/10.1021/jacs.4c01677 | DOI Listing |
Curr Neurovasc Res
January 2025
Center for Rehabilitation Medicine, Department of Neurology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China.
Objective: The concept of "time is brain" is crucial for the reperfusion therapy of ischemic stroke. However, the Infarct Growth Rate (IGR) varies among individuals, which is regarded as a more powerful factor than the time when determining infarct volume and its association with clinical outcomes. For stroke patients with a similar infarct volume, a longer time from stroke Onset to Imaging (OTI) correlates with a lower IGR, which may indicate a better prognosis.
View Article and Find Full Text PDFActa Crystallogr A Found Adv
March 2025
Pennsylvania State University, University Park, PA 16802, USA.
X-ray diffraction is ideal for probing the sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and because of the inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach that uses combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Mackay Memorial Hospital, Taipei, Taiwan.
Background: Cemento-osseous dysplasia (COD) is the most common apical radiopaque lesion that develops in the tooth-bearing area. However, large, destructive lesions are rare. Herein, we report a case in which COD extended to bilateral condyles, affecting the entire mandible, and was managed with denosumab rather than surgical resection.
View Article and Find Full Text PDFStroke
January 2025
Departments of Medicine and Neurology, Melbourne Brain Centre @ The Royal Melbourne Hospital, University of Melbourne, AUSTRALIA.
There is limited data on ultra-early hematoma growth dynamics and its clinical relevance in primary intracerebral hemorrhage (ICH). We aimed to estimate the incidence of hematoma expansion (HE) within the hyperacute period of ICH, describe hematoma dynamics over time, investigate the associations between ultra-early HE and clinical outcomes after ICH, and assess the effect of tranexamic acid on ultra-early HE. We performed a planned secondary analysis of the STOP-MSU international multicenter randomized controlled trial.
View Article and Find Full Text PDFFront Med (Lausanne)
January 2025
Department of Cardiology, Heart Center, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Introduction: In recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. Concurrently, the integration of artificial intelligence with the medical field has garnered increasing attention from medical experts. This study undertakes a dynamic and longitudinal bibliometric analysis of AI publications within the healthcare sector over the past three decades to investigate the current status and trends of the fusion between medicine and artificial intelligence.
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