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The electrocatalytic oxygen evolution reaction from H2O (OER) is essential in a number of areas like electrocatalytic hydrogen production from H2O. A Ni oxyhydroxide nanosheet (NiNS) is among the most widely studied OER catalysts but still suffers from low activity, sluggish kinetics, and poor stability. Herein, we incorporate MoO3patches into NiNS to form a nanosheet with an intimate Ni–Mo interface (NiMoNS) for the OER. The overpotential at 10 mA cm–2and Tafel slope on NiMoNS (260 mV, 54.7 mV dec–1) are lower than those on NiNS (296 mV, 89.3 mV dec–1), implying that higher activity and faster kinetics are achieved on NiMoNS. There is no change in electrocatalytic efficiency of NiMoNS after 18 h of OER, but the electrocatalytic efficiency of NiNS decreases by 56% after only 8 h of OER. Thus, NiMoNS has better stability. The intimate Ni–Mo interface promotes two-dimensional lateral growth of NiMoNS to form a surface area 1.5 times larger than that of NiNS, and facilitates electron transfer from Ni to Mo. This makes the Ni3+/Ni2+ratio on the NiMoNS surface (1.32) higher than that on the NiNS surface (0.68). Moreover, the Ni3+/Ni2+ratio on NiMoNS surface increases to 1.81 after 18 h of OER but the Ni3+/Ni2+ratio on the NiNS surface decreases to 0.51 after 8 h of OER. Therefore, the NiMoNS surface has more abundant and stable Ni3+sites which are catalytically active toward OER. This could be the reason for the enhanced activity, kinetics, and stability of NiMoNS. The results are very valuable for fabricating more efficient catalysts for electrocatalysis.

In this study, we present an efficient, fast, and fully explicit adaptive numerical scheme for solving a recently developed novel phase-field model of crystal growth in both two-dimensional (2D) and three-dimensional (3D) spaces. The novel phase-field model employed in this research incorporates a term specifically designed to eliminate the artificial curvature effect, thereby facilitating accelerated evolution when compared to traditional models. This enhancement significantly enhances the efficiency and speed of the simulation, leading to more expedited results. The crystal growth model employed in this study incorporates a phase-field equation to accurately represent the crystal interface, in addition to a heat equation that effectively models the distribution of temperature. To effectively solve the phase-field equation, we employ an adaptive numerical algorithm that optimizes the computational process. Our numerical scheme, specifically tailored for simulating dendritic growth, incorporates an adaptive narrow-band domain approach to accurately resolve the interfacial transition layer of the phase field. Furthermore, we enhance computational efficiency by implementing a double-sized grid for the temperature distribution, further improving the overall efficiency of the model. By combining these strategies, we achieve accurate and efficient solutions for the dendritic growth model. To validate the accuracy and efficiency of our proposed adaptive numerical method for solving the phase-field equation of dendritic growth, we conduct a series of numerical experiments in both 2D and 3D spaces. In these experiments, we assess the performance of our algorithm, analyzing its ability to accurately capture the intricate dynamics of dendritic growth while maintaining computational efficiency. By thoroughly evaluating the results obtained from these experiments, we provide strong evidence supporting the reliability and effectiveness of our adaptive numerical algorithm. • A fast adaptive numerical method for a novel phase-field model of crystal growth. • We apply a crystal growth model without artificial curvature term. • We propose a buffer parameter based on the interfacial thickness. [ABSTRACT FROM AUTHOR]

This paper aims to present an efficient numerical method for solving the Cahn–Hilliard equation incorporating a data assimilation term. The data assimilation term employs a feedback control strategy to guide the computational solution towards the observed data. The Crank–Nicolson formula is employed for discretizing the equation system, while a scalar auxiliary variable approach is adopted to ensure energy dissipation preservation. The proposed scheme attains second-order accuracy in both temporal and spatial dimensions. The unconditional energy stability of the scheme is proven theoretically. Numerous numerical experiments are conducted to illustrate the efficacy of the proposed scheme.

Nitric oxide (NO) is an antimicrobial agent that possesses tissue-regenerating ability. However, it also has a short half-life and storage difficulties as disadvantages to its application. To overcome these limitations, a new type of hydrogel-forming microneedle (HFMN) is proposed that can be fabricated by integrating polyvinyl alcohol (PVA) hydrogels (a highly biocompatible drug carrier) with S-nitrosoglutathione (GSNO, a NO releasing agent), and graphene oxide (GO) at freezing temperatures (GO-GNSO-HFMNs). Results show that GSNO-GO-HFMNs release NO gradually with increasing temperature and, more importantly, can be warmed up by mild infrared irradiation to accelerate subcutaneous release of NO from the heat-sensitive GSNO. Biofilm-infected wounds often present obstacles to drug delivery, whereas the microneedle (MN) structure disrupts the biofilm and directly releases NO into the wound. This inhibits bacterial growth and increases tissue regeneration while shortening the healing time of biofilm-infected wounds. Therefore, this type of patch can be regarded as a novel, heat-sensitive, light-regulated, NO-releasing MN patch.

In the simulation of microstructural evolutions, detailed priori knowledge for the model parameters and initial states is difficult to be observed by experiments. For an improved simulation, we present a data assimilation framework for the phase field crystal model with the effect of stochastic noise. A sequential data assimilation method based on the ensemble Kalman filter is applied to integrate phase field simulation and observational data from experiments. Furthermore, we couple the present framework with a second-order accurate unconditional-energy stable scheme, and thus the issue of stability restriction can be avoided. A series of twin experiments are performed to demonstrate the performance of our present framework. The results reveal that our framework can successfully improve the simulation accuracy, even when some parameters are uncertain and the initial value significantly deviates from the observed situation. • We establish a novel data assimilation framework for the phase field crystal model. • We propose a second-order accurate unconditional-energy stable scheme. • The method improve the simulation with uncertain parameters and initial condition. [ABSTRACT FROM AUTHOR]