An advanced high-rate capability sodium-ion anode: Few-layered NbSe2 with a mechanism of parallel running intercalation and conversion.

The unique superconductivity and charge density wave transition characteristics of NbSe2 make it worthy of exploring its electrochemical performance and potential applications in the field of batteries. Herein, the bulk NbSe2 was successfully exfoliated into few-layered NbSe2 nanostructures by wet grinding exfoliation approach, which solved the issues of its long activation period and poor cycle stability. The strong Nb-Se bond in the plane and weak van der Waals force between the adjacent layers could render the fast Na+ diffusion, provide abundant reaction sites and multi-directional migration paths, thus accelerate the ionic conductivity. The theoretical calculations verified the high Na+ adsorption tendency between the NbSe2 interlayers stemming from the continuous region of charge accumulation. Thanks to the unique electronic and two-dimensional few-layered structures, the exfoliated NbSe2 exhibited a high cyclic stability with a capacity of 502 mA h g-1 over 2800 cycles at 10 A/g. In addition, the reaction mechanism was studied by in-situ X-ray diffraction and other tests, indicating a reaction mechanism containing of simultaneous intercalation (NbSe2↔NaxNbSe2↔NaNbSe2↔Na1+xNbSe2) and conversion processes in NbSe2. This parallelly running mechanism not only alleviates the volume change but also ensures a high specific capacity. Additionally, different lattice planes of the NaNbSe2 intermediate in the intercalation process experience varying degrees of contraction and expanding in d-spacing due to the influence of Coulombic force.

Differentiation Between Phyllodes Tumors and Fibroadenomas of Breast Using Mammography-based Machine Learning Methods: A Preliminary Study.

OBJECTIVE: To investigate the diagnostic performance of a mammography-based radiomics model for distinguishing phyllodes tumors (PTs) from fibroadenomas (FAs) of the breast. MATERIALS AND METHODS: A total of 156 patients were retrospectively included (75 with PTs, 81 with FAs) and divided into training and validation groups at a ratio of 7:3. Radiomics features were extracted from craniocaudal and mediolateral oblique images. The least absolute shrinkage and selection operator (LASSO) algorithm and principal component analysis (PCA) were performed to select features. Three machine learning classifiers, including logistic regression (LR), K-nearest neighbor classifier (KNN) and support vector machine (SVM), were implemented in the radiomics model, imaging model and combined model. Receiver operating characteristic curves, area under the curve (AUC), sensitivity and specificity were computed. RESULTS: Among 1084 features, the LASSO algorithm selected 17 features, and PCA further selected 6 features. Three machine learning classifiers yielded the same AUC of 0.935 in the validation group for the radiomics model. In the imaging model, KNN yielded the highest accuracy rate of 89.4% and AUC of 0.947 in the validation set. For the combined model, the SVM classifier reached the highest AUC of 0.918 with an accuracy rate of 86.2%, sensitivity of 83.9%, and specificity of 89.4% in the training group. In the validation group, LR yielded the highest AUC of 0.973. The combined model had a relatively higher AUC than the radiomics model or imaging model, especially in the validation group. CONCLUSIONS: Mammography-based radiomics features demonstrate good diagnostic performance for discriminating PTs from FAs.

In situ TEM observation of alpha-particle induced annealing of radiation damage in Durango apatite.

A major issue in thermochronology and U-Th-Pb dating is the effect of radiation damage, created by α-recoils from α-decay events, on the diffusion of radiogenic elements (e.g., He and Pb) in host mineral. Up until now, thermal events have been considered as the only source of energy for the recovery of radiation-damage. However, irradiation, such as from the α-particle of the α-decay event, can itself induce damage recovery. Quantification of radiation-induced recovery caused by α-particles during α-decay events has not been possible, as the recovery process at the atomic-scale has been difficult to observe. Here we present details of the dynamics of the amorphous-to-crystalline transition process during α-particle irradiations using in situ transmission electron microscopy (TEM) and consecutive ion-irradiations: 1 MeV Kr2+ (simulating α-recoil damage), followed by 400 keV He+ (simulating α-particle annealing). Upon the He+ irradiation, partial recrystallization of the original, fully-amorphous Durango apatite was clearly evident and quantified based on the gradual appearance of new crystalline domains in TEM images and new diffraction maxima in selected area electron diffraction patterns. Thus, α-particle induced annealing occurs and must be considered in models of α-decay event damage and its effect on the diffusion of radiogenic elements in geochronology and thermochronology.