Urea oxidation reaction (UOR) is an ideal replacement of the conventional anodic oxygen evolution reaction (OER) for efficient hydrogen production due to the favorable thermodynamics. However, the UOR activity is severely limited by the high oxidation potential of Ni-based catalysts to form Ni 3+ , which is considered as the active site for UOR. Herein, by using in situ cryoTEM, cryo-electron tomography, and in situ Raman, combined with theoretical calculations, a multistep dissolution process of nickel molybdate hydrate is reported, whereby NiMoO 4 •xH 2 O nanosheets exfoliate from the bulk NiMoO 4 •H 2 O nanorods due to the dissolution of Mo species and crystalline water, and further dissolution results in superthin and amorphous nickel (II) hydroxide (ANH) flocculus catalyst. Owing to the superthin and amorphous structure, the ANH catalyst can be oxidized to NiOOH at a much lower potential than conventional Ni(OH) 2 and finally exhibits more than an order of magnitude higher current density (640 mA cm −2 ), 30 times higher mass activity, 27 times higher TOF than those of Ni(OH) 2 catalyst. The multistep dissolution mechanism provides an effective methodology for the preparation of highly active amorphous catalysts.
Although calcium pyrophosphates are commonly involved in crystal arthropathies, their formation mechanisms remain largely underexplored. Here, we investigated the crystallization pathway of calcium pyrophosphate tetrahydrate in the absence and presence...
Based on the significant improvement of model robustness by AT (Adversarial Training), various variants have been proposed to further boost the performance. Well-recognized methods have focused on different components of AT (e.g., designing loss functions and leveraging additional unlabeled data). It is generally accepted that stronger perturbations yield more robust models. However, how to generate stronger perturbations efficiently is still missed. In this paper, we propose an efficient automated attacker called A 2 to boost AT by generating the optimal perturbations on-the-fly during training. A 2 is a parameterized automated attacker to search in the attacker space for the best attacker against the defense model and examples. Extensive experiments across different datasets demonstrate that A 2 generates stronger perturbations with low extra cost and reliably improves the robustness of various AT methods against different attacks.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.