Synthesis, characterization, and application of Cu-substituted LaNiO3 perovskites as photocatalysts and/or catalysts for persulfate activation towards pollutant removal.

The presence of emerging contaminants in environmental aqueous matrices is an ever-growing problem, since conventional wastewater treatment methods fail to adequately remove them. Therefore, the application of non-conventional methodologies such as advanced oxidation processes is of great importance to tackle this modern problem. Photocatalysis as well as catalytic activation of persulfates are promising techniques in this field as they are capable of eliminating various emerging contaminants, and current research aims to develop new materials that can be utilized for both processes. In this light, the present study focused on the use of a simple sol-gel-combustion methodology to synthesize Cu-substituted LaNiO3 perovskite materials in an attempt to improve the photocatalytic and catalytic performance of pure LaNiO3, using molar ratios of Cu:Ni that have not been previously reported in the literature. The morphological, structural, and optical features of the synthesized materials were characterized by a series of analytical techniques (e.g., X-ray diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy, diffuse reflectance spectroscopy, etc.). Also, their performance as photocatalysts, persulfate anion activators and simultaneously as photocatalysts/persulfate anion activators (hybrid) was evaluated by conducting laboratory-scale experiments using phenol (phenolics) as a model emerging contaminant. Interestingly, the results revealed that LaCu0.25Ni0.75O3 exhibited the best efficiency in all the applied processes, which was mainly attributed to the introduction of oxygen vacancies in the structure of the substituted material. The contribution of selected reactive species in the hybrid photocatalytic/catalytic experiments utilizing LaCu0.25Ni0.75O3 as a (photo)catalyst was investigated using appropriate scavengers, and the results suggested that singlet oxygen is the most dominant. Additionally, the stability of all synthesized perovskites was assessed by monitoring the concentration of the leached Cu and/or Ni cations at the end of every applied process. Finally, the reusability of LaCu0.25Ni0.75O3 was evaluated in three consecutive catalytic cycles using the hybrid experiment methodology, as this process demonstrated the best efficiency in terms of phenolics removal, and the results were rather promising.

Local Trust in Internet of Things Based on Contract Theory.

Autonomous trust mechanisms enable Internet of Things (IoT) devices to function cooperatively in a wide range of ecosystems, from vehicle-to-vehicle communications to mesh sensor networks. A common property desired in such networks is a mechanism to construct a secure, authenticated channel between any two participating nodes to share sensitive information, nominally a challenging proposition for a large, heterogeneous network where node participation is constantly in flux. This work explores a contract-theoretic framework that exploits the principles of network economics to crowd-source trust between two arbitrary nodes based on the efforts of their neighbors. Each node in the network possesses a trust score, which is updated based on useful effort contributed to the authentication step. The scheme functions autonomously on locally adjacent nodes and is proven to converge onto an optimal solution based on the available nodes and their trust scores. Core building blocks include the use of Stochastic Learning Automata to select the participating nodes based on network and social metrics, and the formulation of a Bayesian trust belief distribution from the past behavior of the selected nodes. An effort-reward model incentivizes selected nodes to accurately report their trust scores and contribute their effort to the authentication process. Detailed numerical results obtained via simulation highlight the proposed framework's efficacy and performance. The performance achieved near-optimal results despite incomplete information regarding the IoT nodes' trust scores and the presence of malicious or misbehaving nodes. Comparison metrics demonstrate that the proposed approach maximized the overall social welfare and achieved better performance compared to the state of the art in the domain.