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The low olefin selectivity of Pd-based catalysts is a long-term challenge for the selective hydrogenation of 1,3-butadiene.

Inspired by the alveolar configuration, an alveoli-like ZSM-5 and the corresponding platinum encapsulated nanocomposite (Pt@PZ5) were fabricated via a dual-template method and a controlled selective desilication-recrystallization strategy. The dimensions of...

As an abundant and renewable biological resource, straw has been attracting wide attention due to its distinctive tubular structure and property. Herein, soybean straw was pretreated by KOH and was used as a support for Pt nanoparticles (NPs) to realize efficient benzene combustion. The scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images of straw-derived samples illustrated the channel wall with open macropores and uniform distribution of Pt NPs in the straw skeleton. As a result, the temperature for 90% benzene conversion (T 90%) by Pt/KAC-3 (Pt/KAC-n, where n represents the mass ratio of straw to KOH that was varied between 1:1, 1:2, and 1:3) was determined to be 179 °C under a space velocity (SV) of 120 000 mL/(g·h). Additionally, thermal stability was enhanced to nearly 96 h. This performance is predominantly attributed to its inherent channel structure, which has open and accessible pores, resulting in a uniform distribution of Pt NPs. Such structure enables the rapid transfer of benzene molecules between channels and ensures the accessibility of Pt NPs. Furthermore, the diffusion properties were confirmed by Fick’s second law. This study demonstrated a design of more efficient catalysts while using a renewable and abundant biomaterial.

IntroductionThe dynamic reconfiguration of network oscillations is connected with cognitive processes. Changes in how neural networks and signaling pathways work are crucial to how epilepsy and related conditions develop. Specifically, there is evidence that prolonged or recurrent seizures may induce or exacerbate cognitive impairment. However, it still needs to be determined how the seizure brain configures its functional structure to shape the battle of strong local oscillations vs. slow global oscillations in the network to impair cognitive function.MethodsIn this paper, we aim to deduce the network mechanisms underlying seizure-induced cognitive impairment by comparing the evolution of strong local oscillations with slow global oscillations and their link to the resting state of healthy controls. Here, we construct a dynamically efficient network of pathological seizures by calculating the synchrony and directionality of information flow between nine patients’ SEEG signals. Then, using a pattern-based method, we found hierarchical modules in the brain’s functional network and measured the functional balance between the network’s local strong and slow global oscillations.Results and discussionAccording to the findings, a tremendous rise in strong local oscillations during seizures and an increase in slow global oscillations after seizures corresponded to the initiation and recovery of cognitive impairment. Specifically, during the interictal period, local strong and slow global oscillations are in metastable balance, which is the same as a normal cognitive process and can be switched easily. During the pre-ictal period, the two show a bimodal pattern of separate peaks that cannot be easily switched, and some flexibility is lost. During the seizure period, a single-peak pattern with negative peaks is showcased, and the network eventually transitions to a very intense strong local oscillation state. These results shed light on the mechanism behind network oscillations in epilepsy-induced cognitive impairment. On the other hand, the differential (similarity) of oscillatory reorganization between the local (non) epileptogenic network and the global network may be an emergency protective mechanism of the brain, preventing the spread of pathological information flow to more healthy brain regions.