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Unfavorable phase transformations and limited practical capacity remain significant challenges to the widespread application of layered oxides in sodium-ion batteries. Lithium doping has emerged as an effective strategy to suppress phase transformations and activate oxygen redox reactions. However, solid-state NMR reveals that Li gradually deintercalates from the bulk of the cathode during repeated cycles, ultimately compromising the efficacy of Li-doping. To address this, we introduce a straightforward yet effective approach involving the introduction of exogenous Li into the electrolyte, dynamically compensating for and mitigating undesired Li loss. Complementary solid-state NMR and XRD characterizations confirm that the exogenous Li preserves the bulk lithium content within the cathode, preventing structural degradation at both the long-range crystal structure and the local atomic environment. Additionally, interfacial characterization and electrochemical analysis demonstrate that exogenous Li optimizes the cathode-electrolyte interface and reduces interfacial impedance. As a result, the capacity retention of NaLiNiMnO improved significantly from 73.5% to 90.7% after 200 cycles. This study underscores the pivotal role of electrolytes in preserving the long-term effectiveness of structural modifications in the cathode, providing an approach to extending the cycling lifespan of high-performance sodium-ion batteries.
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http://dx.doi.org/10.1021/acsami.5c05388 | DOI Listing |
Biophys J
September 2025
Laboratory for Multiscale Mechanics and Medical Science, State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an, 710049, China. Electronic address:
The mechanical properties of cells are crucial for elucidating various physiological and pathological processes. Cells are found to exhibit a universal power-law rheological behavior at low frequencies. While they behave in a different manner at high frequency regimes, which leaves the transition region largely unexplored.
View Article and Find Full Text PDFDev Med Child Neurol
September 2025
School of Health and Social Development, Faculty of Health, Deakin University, Geelong, Australia.
Aim: To understand communication about sexuality for adolescents with cerebral palsy (CP) and complex communication needs.
Method: We systematically searched primary research on adolescents aged 10 to 24 years with CP and/or complex communication needs. We coded the primary evidence against themes derived from a theoretical framework analysis.
Nat Commun
September 2025
Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan.
The phase transformation of single-element systems is a fundamental natural process with broad implications, yet many aspects remain puzzling despite their simplicity. For instance, transition metals, Tantalum (Ta) and Zirconium (Zr), commonly form body-centred cubic crystals when supercooled. However, according to large-scale computer simulations, their crystallisation rates can differ by over 100 times.
View Article and Find Full Text PDFJ Phys Condens Matter
September 2025
Department of Physics, Punjabi University, Department of Physics, Punjabi University, Patiala-147002, Patiala, 147002, INDIA.
In the present work, DFT investigations were carried out to study the effect of doping on the structural, mechanical, and optical properties of a quaternary High Entropy Alloy (HEA), FeCoVNi, with substitution doping of Co and Ni elements by Se. The cubic phase of FeCoVNi transforms into an orthorhombic phase when Co and Ni sites are replaced with Se. The mechanical stability is retained for substitution of Co up to 37.
View Article and Find Full Text PDFComput Methods Programs Biomed
September 2025
eXiT Research Group, Universitat de Girona (UdG), EPS - Edifici P-IV, Carrer Universitat de Girona, 6, Girona, 17003, Catalunya, Spain.
Background And Objective: Hybrid forecasting methods aim to overcome the limitations of classical statistical approaches and deep learning models. While statistical methods provide interpretability, they often lack predictive power. Conversely, deep learning models achieve high accuracy but act as "black boxes.
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