Single-atom catalysts (SACs) have attracted considerable attention in the catalysis community. However, fabricating intrinsically stable SACs on traditional supports (N-doped carbon, metal oxides, etc.) remains a formidable challenge, especially under hightemperature conditions. Here, we report a novel entropy-driven strategy to stabilize Pd single-atom on the high-entropy fluorite oxides (CeZrHfTiLa)O x (HEFO) as the support by a combination of mechanical milling with calcination at 900°C. Characterization results reveal that single Pd atoms are incorporated into HEFO (Pd 1 @HEFO) sublattice by forming stable Pd-O-M bonds (M = Ce/Zr/La). Compared to the traditional support stabilized catalysts such as Pd@CeO 2 , Pd 1 @HEFO affords the improved reducibility of lattice oxygen and the existence of stable Pd-O-M species, thus exhibiting not only higher low-temperature CO oxidation activity but also outstanding resistance to thermal and hydrothermal degradation. This work therefore exemplifies the superiority of high-entropy materials for the preparation of SACs.

A facile ultrasonication‐assisted wet chemistry method for preparing multicomponent alloy nanoparticles (NPs) including high‐entropy alloys (HEAs) is reported. PtAuPdRhRu alloy (HEA), quaternary PtAuPdRh alloy, and ternary PtAuPd alloy NPs are produced with ≈3 nm in diameter. Taking advantage of the acoustic cavitation phenomenon in ultrasonication process, noble metal precursors could be co‐reduced by chemical reductants and transform to alloy structures under operation at room conditions. The instantaneous massive energy (≈5000 °C, 2000 atm) occurring in momentary timespans (≤10−9 s) contributes to the formation of multimetallic mixed nanomaterials driven by entropy maximization. Owing to strong synergistic effects, the catalysts with the HEA NPs supported on carbons exhibit prominent electrocatalytic activities for hydrogen evolution reaction.

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The solid-solution metal oxide (NiMgCuZnCo)O is the first known high-entropy (HE) metal oxide synthesized, forming a poster child of the emerging high-entropy oxide materials, which is derived from high-temperature synthesis methodologies (>900 °C). In this work, we report the mechanochemical synthesis of this known HE metal oxide (NiMgCuZnCo)O under ambient conditions. The advantage of this approach was further demonstrated by the introduction of up to 5 wt % noble metal into (NiMgCuZnCo)O, as single atoms or nanoclusters, which showed good stability at high temperature and produced a high catalytic activity in the hydrogenation of atmospheric CO 2 to CO. The latter work demonstrated the unique advantage of using HE materials to disperse catalysis centers.

BackgroundPyroptosis is a new programmed cell death discovered in recent years. Pyroptosis plays an important role in various diseases. Nevertheless, there are few bibliometric analysis systematically studies this field. We aimed to visualize the research hotspots and trends of pyroptosis using a bibliometric analysis to help understand the future development of basic and clinical research.MethodsThe articles and reviews regarding pyroptosis were culled from Web of Science Core Collection. Countries, institutions, authors, references and keywords in this field were visually analyzed by using CtieSpace and VOSviewer software.ResultsA total of 2845 articles and reviews were included. The number of articles regarding pyroptosis significantly increased yearly. These publications mainly come from 70 countries led by China and the USA and 418 institutions. We identified 605 authors, among which Thirumaladevi Kanneganti had the most significant number of articles, and Shi JJ was co-cited most often. Frontiers in immunology was the journal with the most studies, and Nature was the most commonly cited journal. After analysis, the most common keywords are nod like receptor family pyrin domain containing 3 inflammasome, apoptosis, cell death, gasdermin D, mechanism, caspase-1, and others are current and developing areas of study.ConclusionResearch on the pyroptosis is flourishing. Cooperation and exchanges between countries and institutions must be strengthened in the future. The related pathway mechanism of pyroptosis, the relationship between pyroptosis and other types of programmed cell deaths as well as the role of pyroptosis in various diseases have been the focus of current research and developmental trends in the future research.

Combination chemotherapy has been proposed to achieve synergistic effect and minimize drug dose for cancer treatment in clinic application. In this article, the stimuli-responsive polymeric nanogels (<100 nm in size) based on poly(acrylic acid) were designed as codelivery system for doxorubicin and cisplatin to overcome drug resistance. By chelation, electrostatic interaction, and π-π stacking interactions, the nanogels could encapsulate doxorubicin and cisplatin with designed ratio and high capacity. Compared with free drugs, the nanogels could deliver more drugs into MCF-7/ADR cells. Significant accumulation in tumor tissues was observed in the biodistribution experiments. The in vitro antitumor studies demonstrated the superior cell-killing activity of the nanogel drug delivery system with a combination index of 0.84, which indicated the great synergistic effect. All the antitumor experimental data revealed that the combination therapy was effective for the multidrug-resistant MCF-7/ADR tumor with reduced side effects.

In this article, the authors adopt deep reinforcement learning algorithms to design trading strategies for continuous futures contracts. Both discrete and continuous action spaces are considered, and volatility scaling is incorporated to create reward functions that scale trade positions based on market volatility. They test their algorithms on 50 very liquid futures contracts from 2011 to 2019 and investigate how performance varies across different asset classes, including commodities, equity indexes, fixed income, and foreign exchange markets. They compare their algorithms against classical timeseries momentum strategies and show that their method outperforms such baseline models, delivering positive profits despite heavy transaction costs. The experiments show that the proposed algorithms can follow large market trends without changing positions and can also scale down, or hold, through consolidation periods. • In this article, the authors introduce reinforcement learning algorithms to design trading strategies for futures contracts. They investigate both discrete and continuous action spaces and improve reward functions by using volatility scaling to scale trade positions based on market volatility. • The authors discuss the connection between modern portfolio theory and the reinforcement learning reward hypothesis and show that they are equivalent if a linear utility function is used. • The authors back test their methods on 50 very liquid futures contracts from 2011 to 2019, and their algorithms deliver positive profits despite heavy transaction costs.

In this work, supported Cu–Ni bimetallic catalysts were synthesized and evaluated for the in situ hydrogenation and decarboxylation of oleic acid using methanol as a hydrogen donor.