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The improvements of cyclability and rate capability of lithium ion batteries with spinel LiMn2O4 as cathode are imperative demands for the large-scale practical applications. Herein, ...a nickel (Ni) and magnesium (Mg) co-doping strategy was employed to synthesize LiNi0.03Mg0.05Mn1.92O4 cathode material via a facile solid-state combustion approach. The effects of the Ni-Mg co-doping on crystalline structure, micromorphology and electrochemical behaviors of the as-prepared LiNi0.03Mg0.05Mn1.92O4 are investigated by a series of physico-chemical characterizations and performance tests at high-rate and elevated-temperature. The resultant LiNi0.03Mg0.05Mn1.92O4 has the intrinsic spinel structure with no any impurities, and exhibits an elevated average valence of manganese in comparison to the pristine LiMn2O4. Owing to the Ni and Mg dual-doped merits, the LiNi0.03Mg0.05Mn1.92O4 sample demonstrates a robust spinel structure and high first discharge specific capacity of 112.3 mAh g−1, whilst undergoing a long cycling of 1000 cycles at 1 C. At a high current rate of 20 C, the capacity of 91.2 mAh g−1 with an excellent retention of 77% is obtained after 1000 cycles. Even at 10 C under 55 °C, an excellent capacity of 97.6 mAh g−1 is also delivered. These results offer a new opportunity for developing high-performance lithium ion batteries with respect to the Ni-Mg co-doping strategy.
Computed tomography (CT) is an important and valuable tool for detecting and diagnosing lung cancer at an early stage. Commonly, CT screenings with lower dose and resolution are used for preliminary ...screening. In particular, many hospitals in smaller towns only provide CT screenings at low resolution. However,when patients are diagnosed with suspected cancer, they are transferred or recommended to larger hospitals for more sophisticated examinations with high-resolution CT scans. Therefore, multi-resolution CT images deserve attention and are critical in clinical practice. Currently, the available open source datasets only contain high-resolution CT screening images. To address this problem, a multi-resolution CT screening image dataset called the DeepLNDataset is constructed. A three-level labeling criterion and a semi-automatic annotation system are presented to guarantee the correctness and efficiency of lung nodule annotation. Moreover, a novel framework called DeepLN is proposed to detect lung nodules in both low-resolution and high-resolution CT screening images. The multi-level features are extracted by a neural-network based detector to locate the lung nodules. Hard negative mining and a modified focal loss function are employed to solve the common category imbalance problem. A novel non-maximum suppression based ensemble strategy is proposed to synthesize the results from multiple neural network models trained on CT image datasets of different resolutions. To the best of our knowledge, this is the first work that considers the influence of multiple resolutions on lung nodule detection. The experimental results demonstrate that the proposed method can address this issue well.
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A series of single-crystal polyhedra spinel LiAlxMn2-xO4 (x = 0, 0.05, 0.10, 0.15 and 0.20) cathode materials have been rapidly prepared by a solution combustion technique using HNO3 solution as an ...auxiliary oxidant. The crystal structure and phase identification of as-prepared samples were characterized through X-ray diffraction (XRD), which shows that all samples present the characteristic diffraction peaks of spinel LiMn2O4. The morphology and particle size of as-prepared samples were observed by field emission scanning electron microscope (FESEM) and transmission electron microscope (TEM), which indicate that all samples have single-crystal polyhedra morphology and good crystallinity. The cycling performances of as-prepared samples were evaluated by galvanostatic charge/discharge cycling performance tests, which demonstrate that LiAl0.10Mn1.90O4 exhibits the optimal cycling and rate properties. It delivers a capacity retention rate of 60.7% after 2000 cycles with an initial discharge specific capacity of 99.5 mAh g−1 at 10 C (1 C = 148 mAh g−1) and 25 °C, while the capacity retention rate of pristine LiMn2O4 is only 9.6% with an initial discharge specific capacity of 81 mAh g−1 at the same conditions. The Al-doped samples show better elevated temperature cycling stability than pristine LiMn2O4. LiAl0.10Mn1.90O4 sample shows a capacity retention rate of 81.5% with a discharge specific capacity of 91.3 mAh g−1 after 500 cycles at 1 C and 55 °C, which is much superior compared with the capacity retention rate of 18.5% for pristine LiMn2O4. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) tests certify that LiAl0.10Mn1.90O4 presents the better electrode reversibility, more rapidly charge-transfer and Li+ diffusion kinetics processes.
•Spinel LiAlxMn2-xO4 were rapidly prepared by a solution combustion route.•As-prepared samples had single-crystal polyhedra morphology.•LiAl0.10Mn1.90O4 exhibited the optimal cycling and rate properties.•LiAl0.10Mn1.90O4 showed more rapidly charge-transfer and Li+ diffusion kinetics.
A series of aluminum and nickel (Al–Ni) co-doped LiAl
0.15
Ni
x
Mn
1.85−
x
O
4
composites are prepared through a facile solid-state combustion method. All the as-obtained materials show a spinel ...structure and analogous spherical morphology with uniform particle distribution. Moreover, the synergistic merits of Al and Ni dual substitutions endow the spinel LiMn
2
O
4
with an elevated Mn average valence state of 3.59 and relatively alleviative Jahn–Teller distortion. Among these samples, the LiAl
0.15
Ni
0.03
Mn
1.82
O
4
(LANMO-0.03) cathode exhibits an optimal electrochemical performance with the discharge capacities of 103.3 mAh g
−1
and 102 mAh g
−1
at 1 C and 5 C in the first cycle, and the capacity retentions are 72.0% and 68.6% after 1000 cycles, respectively. Even at 1 C and high temperature of 55 °C, an excellent capacity retention remained to be 76.6% after 200 cycles. Furthermore, the LANMO-0.03 has good Li
+
diffusion capability during charge/discharge, the D
Li
+
value of the LANMO-0.03 (1.65 × 10
–11
cm
2
∙s
−1
) is higher than that of the LiAl
0.15
Mn
1.85
O
4
(LAMO) (8.12 × 10
–12
cm
2
∙s
−1
), and the charge transfer resistances of the LAMO and LANMO-0.03 samples are almost the same at 150 Ω before cycling but decrease to 130 Ω and 95 Ω after 1000 cycles at 1 C, respectively. These results demonstrate that the Al–Ni co-doped strategy can enhance the structural stability and provide stable Li
+
diffusion channel during the long cycles even at elevated temperature. Meanwhile, the facile solid-state combustion approach can also be extended to the preparation of other dual cation-doped electrode materials.
Li
1.05
Cu
0.05
Mn
1.90
O
4
cathode materials were synthesized by liquid phase combustion method at different temperatures from 400 to 700 °C. All samples show good crystallinity and conform to the ...Fd3m space group of spinel LiMn
2
O
4
. The Li
1.05
Cu
0.05
Mn
1.90
O
4
sample prepared at 600 °C has a sharp diffraction peak compared to the pristine LiMn
2
O
4
, while no impurities are detected. Both the Li–Cu co-doping and calcination temperature have effects on the morphology and particle size distribution. The electrochemical properties reveal that initial discharge capacity of the Li
1.05
Cu
0.05
Mn
1.90
O
4
is 102.4 mAh g
−1
and pristine LiMn
2
O
4
electrode is 105.3 mAh g
−1
. After 1000 cycles, the capacity retention rate of the pristine LiMn
2
O
4
(63.0%) has less than 74.3% of the Li
1.05
Cu
0.05
Mn
1.90
O
4
sample. The lithium-ion diffusion coefficient indicates that the as-prepared Li
1.05
Cu
0.05
Mn
1.90
O
4
electrode (1.58 × 10
−10
cm
2
s
−1
) at 600 °C displays better Li
+
diffusion ability when compared with the pristine LiMn
2
O
4
(8.06 × 10
−11
cm
2
s
−1
). Simultaneously, the apparent activation energy further demonstrates that the Li
1.05
Cu
0.05
Mn
1.90
O
4
(22.84 kJ/mol) electrode has lower polarization when compared with the LiMn
2
O
4
(34.95 kJ/mol) electrode. These results show that synergistic effect of the Li
+
and Cu
2+
enhances the cycle reversibility and kinetics properties in cycle of the electrode.
Spinel LiMn2O4 cathode material was rapidly synthesized in 1h by solid-state combustion synthesis using metal carbonates as metal ion sources and glucose as a fuel. The effect of different amounts of ...glucose on the structure and electrochemical performance of as-prepared LiMn2O4 was investigated by X-ray diffraction (XRD), scanning electron micrographs (SEM), galvanostatic charge–discharge test, cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). LiMn2O4 spinel was identified as the main crystalline phase with the presence of minor Mn3O4. The amount of glucose greatly affected the formation of Mn3O4. The optimal content of glucose was found to be 10wt%. Under this condition, the Mn3O4 peaks almost disappeared, and high-purity spinel LiMn2O4 was obtained. Its initial discharge specific capacity of was 125.9mAh/g, and discharge specific capacity retained at 105.2mAh/g after 40 cycles. The detail influence of glucose on the electrochemical activity, reversibility and cycling performance of LiMn2O4 was discussed.
The Li1.02Ni0.05Mn1.93O4 cathode material exhibits a better rate capability than that of the LiNi0.05Mn1.95O4. Moreover, the Li1.02Ni0.05Mn1.93O4 shows the well-developed crystal structure with the ...(111), (110) and (100) crystal planes. The (111) crystal planes possess the minimum Mn dissolution and the (110) and (100) crystal planes are well consistent with the Li+ diffusion channel.
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Various Li-rich spinel Li1+xNi0.05Mn1.95-xO4 (0 ≤ x ≤ 0.10) cathode materials with a truncated octahedron were synthesized by a solution combustion method. The relationship of crystalline structure, particles morphology and electrochemical properties of the as-prepared samples was investigated via a series of physicochemical characterizations. The Li-Ni co-doping changes the lattice parameters and atomic configuration, whilst resulting in a contraction of unit cell dimension and giving rise to a variation of bond length. In this regard, the shrinkage of octahedral MnO6 provides a robust structure and the expansion of tetrahedral LiO4 facilitates a fast electrochemical process. Additionally, the resulted polyhedral Li1+xNi0.05Mn1.95-xO4 samples present the exposed (110), (100), and (111) crystal planes, which provide the favorable Li+ ions diffusion/transmission channel and alleviate Mn dissolution. Owing to these merits of polyhedral structure and Li-Ni co-doping, the optimized Li1.02Ni0.05Mn1.93O4 exhibits good electrochemical performance with high initial discharge capacity of 119.8, 107.1 and 97.9 mAh·g−1 at 1, 5 and 10 C, respectively. Even at a high current rate of 15 C, an excellent capacity retention of 91.7% is obtained after 1000 cycles, whilst the high temperature performance was also improved.
Mortality of lung cancer can be decreased by early screening effectively. However, consistent and proficient standards & methods have not been established in China. This study was based on pulmonary ...nodules/lung cancer comprehensive management platform established by West China Hospital, Sichuan University. Early screening of pulmonary nodules was integrated into standard healthcare of lung cancer system, aiming to improve survivals of lung cancer patients.
Three cohorts were established: healthy populations, pulmonary nodules cohort and lung cancer patients cohort, and related clinical data will be collected and analyzed. Preliminary plan includes verifying effect of pulmonary nodules screening module.
Pulmonary nodules screening was performed in 2,836 employers (>40 years old) of West China Hospital. Lung cancers were diagnosed in 66 participants, all receiving surgery to remove the lesions. 65 of them were with early stage diseases, 1 with lung cancer and brain metastasis.
Proficient screening, follow-up and healthcare can be achieved via pulmonary nodules/lung cancer comprehensive management mode, which will be extended all over west China region in future.
•We provide another solution to solving the small data problem.•We generalize a new AUC surrogate loss to address imbalance issue.•We achieve state-of-the-art results on open source dataset.•A new ...dataset annotated using biopsy-based cytological analysis is constructed
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The accurate identification of malignant lung nodules using computed tomography (CT) screening images is vital for the early detection of lung cancer. It also offers patients the best chance of cure, because non-invasive CT imaging has the ability to capture intra-tumoral heterogeneity. Deep learning methods have obtained promising results for the malignancy identification problem; however, two substantial challenges still remain. First, small datasets cannot insufficiently train the model and tend to overfit it. Second, category imbalance in the data is a problem. In this paper, we propose a method called MSCS-DeepLN that evaluates lung nodule malignancy and simultaneously solves these two problems. Three light models are trained and combined to evaluate the malignancy of a lung nodule. Three-dimensional convolutional neural networks (CNNs) are employed as the backbone of each light model to extract the lung nodule features from CT images and preserve lung nodule spatial heterogeneity. Multi-scale input cropped from CT images enables the sub-networks to learn the multi-level contextual features and preserve diverse. To tackle the imbalance problem, our proposed method employs an AUC approximation as the penalty term. During training, the error in this penalty term is generated from each major and minor class pair, so that negatives and positives can contribute equally to updating this model. Based on these methods, we obtain state-of-the-art results on the LIDC-IDRI dataset. Furthermore, we constructed a new dataset collected from a grade-A tertiary hospital and annotated using biopsy-based cytological analysis to verify the performance of our method in clinical practice.
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