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Cobalt sulfide (CoS2) is considered one of the most promising alternative anode materials for high-performance lithium-ion batteries (LIBs) by virtue of its remarkable electrical conductivity, high theoretical capacity, and low cost. However, it suffers from a poor cycling stability and low rate capability because of its volume expansion and dissolution of the polysulfide intermediates in the organic electrolytes during the battery charge/discharge process. In this study, a novel porous carbon/CoS2 composite is prepared by using nano metal-organic framework (MOF) templates for high-preformance LIBs. The as-made ultrasmall CoS2 (15 nm) nanoparticles in N-rich carbon exhibit promising lithium storage properties with negligible loss of capacity at high charge/discharge rate. At a current density of 100 mA g(-1), a capacity of 560 mA h g(-1) is maintained after 50 cycles. Even at a current density as high as 2500 mA g(-1), a reversible capacity of 410 mA h g(-1) is obtained. The excellent and highly stable battery performance should be attributed to the synergism of the ultrasmall CoS2 particles and the thin N-rich porous carbon shells derieved from nanosized MOF precusors.

h i g h l i g h t s g r a p h i c a l a b s t r a c tA series of Na-rich antiperovskites were developed as advanced solid electrolytes.The materials are nonflammable, low-cost and suitable for thermoplastic processing. Enhanced sodium ionic conductivity was achieved by structural manipulation approaches. The Na ionic conductivity of Na 2.9 Sr 0.05 OBr 0.6 I 0.4 reaches 1.9 Â 10 À3 S/cm at 200 C. a b s t r a c tHigh-performance solid electrolytes are critical for realizing all-solid-state batteries with enhanced safety and cycling efficiency. However, currently available candidates (sulfides and the NASICON-type ceramics) still suffer from drawbacks such as inflammability, high-cost and unfavorable machinability.Here we present the structural manipulation approaches to improve the sodium ionic conductivity in a series of affordable Na-rich antiperovskites. Experimentally, the whole solid solutions of Na 3 OX (X ¼ Cl, Br, I) are synthesized via a facile and timesaving route from the cheapest raw materials (Na, NaOH and NaX). The materials are nonflammable, suitable for thermoplastic processing due to low melting temperatures (<300 C) without decomposing. Notably, owing to the flexibility of perovskite-type structure, it's feasible to control the local structure features by means of size-mismatch substitution and unequivalent-doping for a favorable sodium ionic diffusion pathway. Enhancement of sodium ionic conductivity by 2 magnitudes is demonstrated by these chemical tuning methods. The optimized sodium ionic conductivity in Na 2.9 Sr 0.05 OBr 0.6 I 0.4 bulk samples reaches 1.9 Â 10 À3 S/cm at 200 C and even higher at elevated temperature. We believe further chemical tuning efforts on Na-rich antiperovskites will promote their performance greatly for practical all-solid state battery applications.

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Yolk-shell nanostructures have received great attention for boosting the performance of lithium-ion batteries because of their obvious advantages in solving the problems associated with large volume change, low conductivity, and short diffusion path for Li ion transport. A universal strategy for making hollow transition metal oxide (TMO) nanoparticles (NPs) encapsulated into B, N co-doped graphitic nanotubes (TMO@BNG (TMO = CoO, Ni O , Mn O ) through combining pyrolysis with an oxidation method is reported herein. The as-made TMO@BNG exhibits the TMO-dependent lithium-ion storage ability, in which CoO@BNG nanotubes exhibit highest lithium-ion storage capacity of 1554 mA h g at the current density of 96 mA g , good rate ability (410 mA h g at 1.75 A g ), and high stability (almost 96% storage capacity retention after 480 cycles). The present work highlights the importance of introducing hollow TMO NPs with thin wall into BNG with large surface area for boosting LIBs in the terms of storage capacity, rate capability, and cycling stability.

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Metal–organic framework derived cobalt phosphide nanoparticles encapsulated B/N co‐doped graphene nanotubes are fabricated through pyrolysis and phosphidation, which exhibit excellent electrocatalytic activity for hydrogen evolution reaction.

Fluorescence microscopy has enabled a dramatic development in modern biology. Due to its inherently weak signal, fluorescence microscopy is not only much noisier than photography, but also presented with Poisson-Gaussian noise where Poisson noise, or shot noise, is the dominating noise source. To get clean fluorescence microscopy images, it is highly desirable to have effective denoising algorithms and datasets that are specifically designed to denoise fluorescence microscopy images. While such algorithms exist, no such datasets are available. In this paper, we fill this gap by constructing a dataset -the Fluorescence Microscopy Denoising (FMD) dataset -that is dedicated to Poisson-Gaussian denoising. The dataset consists of 12,000 real fluorescence microscopy images obtained with commercial confocal, two-photon, and wide-field microscopes and representative biological samples such as cells, zebrafish, and mouse brain tissues. We use image averaging to effectively obtain ground truth images and 60,000 noisy images with different noise levels. We use this dataset to benchmark 10 representative denoising algorithms and find that deep learning methods have the best performance. To our knowledge, this is the first real microscopy image dataset for Poisson-Gaussian denoising purposes and it could be an important tool for high-quality, real-time denoising applications in biomedical research.