This review describes an in-depth overview and knowledge on the variety of synthetic strategies for forming metal sulfides and their potential use to achieve effective hydrogen generation and beyond.
Repeated exposure to broad-spectrum antibiotics at ages 0 to 23 months is associated with early childhood obesity. Because common childhood infections were the most frequent diagnoses co-occurring with broad-spectrum antibiotic prescription, narrowing antibiotic selection is potentially a modifiable risk factor for childhood obesity.
2D carbon nanomaterials such as graphene and its derivatives, have gained tremendous research interests in energy storage because of their high capacitance and chemical stability. However, scalable synthesis of ultrathin carbon nanosheets with well-defined pore architectures remains a great challenge. Herein, the first synthesis of 2D hierarchical porous carbon nanosheets (2D-HPCs) with rich nitrogen dopants is reported, which is prepared with high scalability through a rapid polymerization of a nitrogen-containing thermoset and a subsequent one-step pyrolysis and activation into 2D porous nanosheets. 2D-HPCs, which are typically 1.5 nm thick and 1-3 µm wide, show a high surface area (2406 m g ) and with hierarchical micro-, meso-, and macropores. This 2D and hierarchical porous structure leads to robust flexibility and good energy-storage capability, being 139 Wh kg for a symmetric supercapacitor. Flexible supercapacitor devices fabricated by these 2D-HPCs also present an ultrahigh volumetric energy density of 8.4 mWh cm at a power density of 24.9 mW cm , which is retained at 80% even when the power density is increased by 20-fold. The devices show very high electrochemical life (96% retention after 10000 charge/discharge cycles) and excellent mechanical flexibility.
Deep neural networks (DNN) have been shown to be useful in a wide range of applications. However, they are also known to be vulnerable to adversarial samples. By transforming a normal sample with some carefully crafted human imperceptible perturbations, even highly accurate DNN make wrong decisions. Multiple defense mechanisms have been proposed which aim to hinder the generation of such adversarial samples. However, a recent work show that most of them are ineffective. In this work, we propose an alternative approach to detect adversarial samples at runtime. Our main observation is that adversarial samples are much more sensitive than normal samples if we impose random mutations on the DNN. We thus first propose a measure of 'sensitivity' and show empirically that normal samples and adversarial samples have distinguishable sensitivity. We then integrate statistical hypothesis testing and model mutation testing to check whether an input sample is likely to be normal or adversarial at runtime by measuring its sensitivity. We evaluated our approach on the MNIST and CIFAR10 datasets. The results show that our approach detects adversarial samples generated by state-of-the-art attacking methods efficiently and accurately.
The separation of C2H2/CO2 is not only industrially important for acetylene purification but also scientifically challenging owing to their high similarities in physical properties and molecular sizes. Ultramicroporous metal-organic frameworks (MOFs) can exhibit a pore confinement effect to differentiate gas molecules of similar size. Herein, we report the fine-tuning of pore sizes in sub-nanometer scale on a series of isoreticular MOFs that can realize highly efficient C2H2/CO2 separation. The subtle structural differences lead to remarkable adsorption performances enhancement. Among four MOF analogs, by integrating appropriate pore size and specific binding sites, [Cu(dps)2(SiF6)] (SIFSIX-dps-Cu, SIFSIX = SiF62-, dps = 4.4’-dipyridylsulfide, also termed as NCU-100) exhibits the highest C2H2 uptake capacity and C2H2/CO2 selectivity. At room temperature, the pore space of SIFSIX-dps-Cu significantly inhibits CO2 molecules but takes up a large amount of C2H2 (4.57 mmol g−1), resulting in a high IAST selectivity of 1787 for C2H2/CO2 separation. The multiple host-guest interactions for C2H2 in both inter- and intralayer cavities are further revealed by dispersion-corrected density functional theory and grand canonical Monte Carlo simulations. Dynamic breakthrough experiments show a clean C2H2/CO2 separation with a high C2H2 working capacity of 2.48 mmol g−1.
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