Spinel-structured lithium manganese oxide (LiMn2O4) cathodes have been successfully commercialized for various lithium battery applications and are among the strongest candidates for emerging ...large-scale applications. Despite its various advantages including high power capability, however, LiMn2O4 chronically suffers from limited cycle life, originating from well-known Mn dissolution. An ironical feature with the Mn dissolution is that the surface orientations supporting Li diffusion and thus the power performance are especially vulnerable to the Mn dissolution, making both high power and long lifetime very difficult to achieve simultaneously. In this investigation, we address this contradictory issue of LiMn2O4 by developing a truncated octahedral structure in which most surfaces are aligned to the crystalline orientations with minimal Mn dissolution, while a small portion of the structure is truncated along the orientations to support Li diffusion and thus facilitate high discharge rate capabilities. When compared to control structures with much smaller dimensions, the truncated octahedral structure as large as 500 nm exhibits better performance in both discharge rate performance and cycle life, thus resolving the previously conflicting aspects of LiMn2O4.
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Gaining a thorough understanding of the reactions on the electrode surfaces of lithium batteries is critical for designing new electrode materials suitable for high-power, long-life operation. A ...technique for directly observing surface structural changes has been developed that employs an epitaxial LiMn2O4 thin-film model electrode and surface X-ray diffraction (SXRD). Epitaxial LiMn2O4 thin films with restricted lattice planes (111) and (110) are grown on SrTiO3 substrates by pulsed laser deposition. In situ SXRD studies have revealed dynamic structural changes that reduce the atomic symmetry at the electrode surface during the initial electrochemical reaction. The surface structural changes commence with the formation of an electric double layer, which is followed by surface reconstruction when a voltage is applied in the first charge process. Transmission electron microscopy images after 10 cycles confirm the formation of a solid electrolyte interface (SEI) layer on both the (111) and (110) surfaces and Mn dissolution from the (110) surface. The (111) surface is more stable than the (110) surface. The electrode stability of LiMn2O4 depends on the reaction rate of SEI formation and the stability of the reconstructed surface structure.
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The wet‐chemical processability of sulfide solid electrolytes (SEs) provides intriguing opportunities for all‐solid‐state batteries. Thus far, sulfide SEs are wet‐prepared either from solid ...precursors suspended in solvents (suspension synthesis) or from homogeneous solutions using SEs (solution process) with restricted composition spaces. Here, a universal solution synthesis method for preparing sulfide SEs from precursors, not only Li2S, P2S5, LiCl, and Na2S, but also metal sulfides (e.g., GeS2 and SnS2), fully dissolved in an alkahest: a mixture solvent of 1,2‐ethylenediamine (EDA) and 1,2‐ethanedithiol (EDT) (or ethanethiol). Raman spectroscopy and theoretical calculations reveal that the exceptional dissolving power of EDA–EDT toward GeS2 is due to the nucleophilicity of the thiolate anions that is strong enough to dissociate the GeS bonds. Solution‐synthesized Li10GeP2S12, Li6PS5Cl, and Na11Sn2PS12 exhibit high ionic conductivities (0.74, 1.3, and 0.10 mS cm−1 at 30 °C, respectively), and their application for all‐solid‐state batteries is successfully demonstrated.
The universal solution synthesis of sulfide solid electrolytes is first demonstrated. The alkahest solvent, 1,2‐ethylenediamine–1,2‐ethanedithiol, fully dissolves not only Li2S (or Na2S), P2S5, and LiCl, but also metal sulfides (e.g., GeS2 and SnS2), forming homogeneous solid electrolyte solutions. Solution‐synthesized Li10GeP2S12, Li6PS5Cl, and Na11Sn2PS12 exhibit high ionic conductivities, and their applicability to all‐solid‐state batteries is successfully demonstrated.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Abstract The state-of-the-art all-solid-state batteries have emerged as an alternative to the traditional flammable lithium-ion batteries, offering higher energy density and safety. Nevertheless, ...insufficient intimate contact at electrode-electrolyte surface limits their stability and electrochemical performance, hindering the commercialization of all-solid-state batteries. Herein, we conduct a systematic investigation into the effects of shear force in the dry electrode process by comparing binder-free hand-mixed pellets, wet-processed electrodes, and dry-processed electrodes. Through digitally processed images, we quantify a critical factor, ‘coverage’, the percentage of electrolyte-covered surface area of the active materials. The coverage of dry electrodes was significantly higher (67.2%) than those of pellets (30.6%) and wet electrodes (33.3%), enabling superior rate capability and cyclability. A physics-based electrochemical model highlights the effects of solid diffusion by elucidating the impact of coverage on active material utilization under various current densities. These results underscore the pivotal role of the electrode fabrication process, with the focus on the critical factor of coverage.
Multi-layer thin films of LiMn2O4/SrRuO3 have been epitaxially grown on SrTiO3 (111) substrates using a pulsed laser deposition method. The multi-layer electrodes show excellent electrochemical ...properties due to introduction of an electronic conducting buffer layer between the lithium cathode film and semiconducting substrate. Moreover, the electrochemical characteristics of the lithium cathode materials are strongly dependent on the electronic contact. Thus, the epitaxially grown electrodes can be used as ideal crystalline models to obtain information about the lattice plane, surface roughness, and thickness of electrodes. This information can be used to elucidate the reaction mechanisms of lithium batteries.
► Multi-layer LiMn2O4/SrRuO3 epitaxial film electrode was successfully fabricated. ► SrRuO3 as an electronic conducting buffer layer improved electrochemical property. ► No effects on the LiMn2O4 structure with the stacking of the buffer layer. ► Electrochemical property depends on an electronic contact of the substrate/electrode.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Agriculture, alongside construction and mining, is one of the three most hazardous industries, and is characterized by numerous risk factors for occupational accidents. Unlike other industries, ...agriculture faces significant safety concerns related to the natural environment. Determining the causes of accidents is therefore imperative for accident prevention. However, the difficulty in investigating accidents owing to inadequate reporting and management systems among self-employed farmers hampers the determination of their causes. This study aims to determine the factors influencing agricultural accidents through a literature review. A systematic literature search was conducted according to the PRISMA guidelines. The initial search yielded 165 articles of which 34 papers were selected after removing those by applying the selection criteria. The selected papers were categorized into three domains: work accidents, machinery accidents, and farmer safety promotion. Accident causes were classified using the 4M technique: machine, media, man, and management. The results were visualized with a heat map. The main causes of accidents thus identified were insufficient operation/management, inappropriate work situation, and insufficient education/training. The findings of this study can serve as foundational data for developing measures to improve working environments not only in agriculture but also in other high-hazard industries.
Lithium-rich layered rocksalt oxides are promising cathode materials for lithium-ion batteries, owing to their high charge–discharge capacities of over 250 mA h g–1. However, their poor rate ...capability remains to be addressed. Here, we investigate the effects of surface modification by amorphous Li3PO4 on the structures and electrochemical reactions in the surface region of an epitaxial Li2RuO3(010) film electrode fabricated by pulsed laser deposition. Structural characterization using surface X-ray diffraction (XRD), hard X-ray photoemission spectroscopy, and neutron reflectometry shows that surface modification by 3 nm thick Li3PO4 resulted in the partial substitution of P for Li in the surface region of Li2RuO3. The modified (010) surface exhibits better rate capability at 20 C (41% of the discharge capacity at 0.3 C) compared to the unmodified surface (5% of that at 0.3 C). In situ surface XRD confirmed that highly reversible structural changes occurred at the modified surface during lithium (de)intercalation, whereas the unmodified surface showed irreversible structural changes. These results demonstrate that this surface modification stabilizes the crystal structure in the surface region, and it can improve the rate capability of lithium-rich layered rocksalt oxide cathodes.
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IJS, KILJ, NUK, PNG, UL, UM
We propose a hybrid technique that employs artificial intelligence (AI)-based segmentation and machine learning classification using multiple features extracted from the foveal avascular zone (FAZ)-a ...retinal biomarker for Alzheimer's disease-to improve the disease diagnostic performance. Imaging data of optical coherence tomography angiography from 37 patients with Alzheimer's disease and 48 healthy controls were investigated. The presence or absence of brain amyloids was confirmed using amyloid positron emission tomography. In the superficial capillary plexus of the angiography scans, the FAZ was automatically segmented using an AI method to extract multiple biomarkers (area, solidity, compactness, roundness, and eccentricity), which were paired with clinical data (age and sex) as common correction variables. We used a light-gradient boosting machine (a light-gradient boosting machine is a machine learning algorithm based on trees utilizing gradient boosting) to diagnose Alzheimer's disease by integrating the corresponding multiple radiomic biomarkers. Fivefold cross-validation was applied for analysis, and the diagnostic performance for Alzheimer's disease was determined by the area under the curve. The proposed hybrid technique achieved an area under the curve of Formula: see text%, outperforming the existing single-feature (area) criteria by over 13%. Furthermore, in the holdout test set, the proposed technique exhibited a 14% improvement compared to single features, achieving an area under the curve of 72.0± 4.8%. Based on these facts, we have demonstrated the effectiveness of our technology in achieving significant performance improvements in FAZ-based Alzheimer's diagnosis research through the use of multiple radiomic biomarkers (area, solidity, compactness, roundness, and eccentricity).
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Automated segmentation and volumetry of brain magnetic resonance imaging (MRI) scans are essential for the diagnosis of Parkinson's disease (PD) and Parkinson's plus syndromes (P-plus). To enhance ...the diagnostic performance, we adopt deep learning (DL) models in brain MRI segmentation and compared their performance with the gold-standard non-DL method. We collected brain MRI scans of healthy controls (Formula: see text) and patients with PD (Formula: see text), multiple systemic atrophy (Formula: see text), and progressive supranuclear palsy (Formula: see text) at Samsung Medical Center from January 2017 to December 2020. Using the gold-standard non-DL model, FreeSurfer (FS), we segmented six brain structures: midbrain, pons, caudate, putamen, pallidum, and third ventricle, and considered them as annotated data for DL models, the representative convolutional neural network (CNN) and vision transformer (ViT)-based models. Dice scores and the area under the curve (AUC) for differentiating normal, PD, and P-plus cases were calculated to determine the measure to which FS performance can be reproduced as-is while increasing speed by the DL approaches. The segmentation times of CNN and ViT for the six brain structures per patient were 51.26 ± 2.50 and 1101.82 ± 22.31 s, respectively, being 14 to 300 times faster than FS (15,735 ± 1.07 s). Dice scores of both DL models were sufficiently high (> 0.85) so their AUCs for disease classification were not inferior to that of FS. For classification of normal vs. P-plus and PD vs. P-plus (except multiple systemic atrophy - Parkinsonian type) based on all brain parts, the DL models and FS showed AUCs above 0.8, demonstrating the clinical value of DL models in addition to FS. DL significantly reduces the analysis time without compromising the performance of brain segmentation and differential diagnosis. Our findings may contribute to the adoption of DL brain MRI segmentation in clinical settings and advance brain research.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Stridor is a rare but important non-motor symptom that can support the diagnosis and prediction of worse prognosis in multiple system atrophy. Recording sounds generated during sleep by ...video-polysomnography is recommended for detecting stridor, but the analysis is labor intensive and time consuming. A method for automatic stridor detection should be developed using technologies such as artificial intelligence (AI) or machine learning. However, the rarity of stridor hinders the collection of sufficient data from diverse patients. Therefore, an AI method with high diagnostic performance should be devised to address this limitation. We propose an AI method for detecting patients with stridor by combining audio splitting and reintegration with few-shot learning for diagnosis. We used video-polysomnography data from patients with stridor (19 patients with multiple system atrophy) and without stridor (28 patients with parkinsonism and 18 patients with sleep disorders). To the best of our knowledge, this is the first study to propose a method for stridor detection and attempt the validation of few-shot learning to process medical audio signals. Even with a small training set, a substantial improvement was achieved for stridor detection, confirming the clinical utility of our method compared with similar developments. The proposed method achieved a detection accuracy above 96% using data from only eight patients with stridor for training. Performance improvements of 4%-13% were achieved compared with a state-of-the-art AI baseline. Moreover, our method determined whether a patient had stridor and performed real-time localization of the corresponding audio patches, thus providing physicians with support for interpreting and efficiently employing the results of this method.
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