This timely and comprehensive review mainly summarizes advances in heterogeneous electroreduction of CO2: from fundamentals to value-added products.

A novel OER electrocatalyst, namely oxygen-incorporated amorphous cobalt sulfide porous nanocubes (A-CoS O PNCs), show advantages over the benchmark RuO catalyst in alkaline/neutral medium. Experiments combining with calculation demonstrate that the desirable O* adsorption energy, associated with the distorted CoS O octahedron structure and the oxygen doping, contribute synergistically to the outstanding electrocatalytic activity.

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Background It is important to measure the public response to the COVID-19 pandemic. Twitter is an important data source for infodemiology studies involving public response monitoring. Objective The objective of this study is to examine COVID-19–related discussions, concerns, and sentiments using tweets posted by Twitter users. Methods We analyzed 4 million Twitter messages related to the COVID-19 pandemic using a list of 20 hashtags (eg, “coronavirus,” “COVID-19,” “quarantine”) from March 7 to April 21, 2020. We used a machine learning approach, Latent Dirichlet Allocation (LDA), to identify popular unigrams and bigrams, salient topics and themes, and sentiments in the collected tweets. Results Popular unigrams included “virus,” “lockdown,” and “quarantine.” Popular bigrams included “COVID-19,” “stay home,” “corona virus,” “social distancing,” and “new cases.” We identified 13 discussion topics and categorized them into 5 different themes: (1) public health measures to slow the spread of COVID-19, (2) social stigma associated with COVID-19, (3) COVID-19 news, cases, and deaths, (4) COVID-19 in the United States, and (5) COVID-19 in the rest of the world. Across all identified topics, the dominant sentiments for the spread of COVID-19 were anticipation that measures can be taken, followed by mixed feelings of trust, anger, and fear related to different topics. The public tweets revealed a significant feeling of fear when people discussed new COVID-19 cases and deaths compared to other topics. Conclusions This study showed that Twitter data and machine learning approaches can be leveraged for an infodemiology study, enabling research into evolving public discussions and sentiments during the COVID-19 pandemic. As the situation rapidly evolves, several topics are consistently dominant on Twitter, such as confirmed cases and death rates, preventive measures, health authorities and government policies, COVID-19 stigma, and negative psychological reactions (eg, fear). Real-time monitoring and assessment of Twitter discussions and concerns could provide useful data for public health emergency responses and planning. Pandemic-related fear, stigma, and mental health concerns are already evident and may continue to influence public trust when a second wave of COVID-19 occurs or there is a new surge of the current pandemic.

instance, lithium-ion hybrid capacitors (LIHCs) consisting of an activated carbon (AC) cathode and a prelithiated graphite anode have been successfully commercialized and widely applied in small portable electronics. [2a] Nevertheless, the limited reserves and high cost of Li resources likely hinder them from applying in large-scale energy storage devices. As a new class of hybrid capacitors, potassium-ion hybrid capacitors (PIHCs) show great potential as alternative to LIHCs due to the profusion and low cost of potassium resources. [3] In addition, the redox potential of the K + /K (−2.936 V vs standard hydrogen electrode) is quite close to that of Li + /Li (−3.040 V), indicating PIHCs can afford a considerably high working voltage and energy density. [4] Unfortunately, the relatively large radius of K + (1.38 Å) tends to behave sluggish redox reaction kinetics for most of potassium-ion batteries (PIBs) anodes.As compared to LIHCs, the research regarding PIHCs is still in its infant stage and thus calls for extensive exploration on newly favorable electrode materials, in the hope to enhance the kinetics of K + insertion/extraction so that it can match with the fast kinetics of capacitor-style cathodes. To date, various electrode materials, such as carbonaceous materials, [5] metal alloys, [6] oxides, [7] sulfides, [8] and MXene, [9] have been extensively studied as battery-type anodes. Among them, carbon-based material, thanks to the merits of abundant resources, low cost, and high conductivity, has been regarded as one of the most promising electrode materials for the practical application of PIHCs. [10] However, the implementation of carbon-based electrode material for high-performance PIBs requires high conductivity and a rather large interlayer spacing for facilitating insertion and extraction of bulky K + and improving the redox reaction Kinetics. Therefore, it still remains a grand challenge to address the major issues existed in carbon-based anodes, including limited reversible capacities, unsatisfactory cycling stability, and poor rate performance, which result from the large volume change (61% caused by KC 8 vs 10% by LiC 6 ). [5] Heteroatom-doped carbonbased materials have exhibited the enhanced electrochemical properties for potassium-ion storage due to the increased electric conductivity and more active sites for potassium-ion storage by generating extrinsic defects. [11] In comparison with nitrogen, sulfur has a relatively large size but small electronegativity, Potassium-ion hybrid capacitors (PIHCs) hold the advantages of high-energy density of batteries and high-power output of supercapacitors and thus present great promise for the next generation of electrochemical energy storage devices. One of the most crucial tasks for developing a highperformance PIHCs is to explore a favorable anode material with capability to balance the kinetics mismatch between battery-type anodes and capacitortype cathode. Herein, a reliable route for fabricating sulfur and nitrogen codoped 3D porous carbon nanosheets...

The study aims to understand Twitter users' discourse and psychological reactions to COVID-19. We use machine learning techniques to analyze about 1.9 million Tweets (written in English) related to coronavirus collected from January 23 to March 7, 2020. A total of salient 11 topics are identified and then categorized into ten themes, including "updates about confirmed cases," "COVID-19 related death," "cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive measures," "authorities," and "supply chain." Results do not reveal treatments and symptoms related messages as prevalent topics on Twitter. Sentiment analysis shows that fear for the unknown nature of the coronavirus is dominant in all topics. Implications and limitations of the study are also discussed.

Nanocarbons doped with nitrogen (N) and/or metal-N coordination structures hold great promise in replacing Pt for catalyzing the oxygen reduction reaction (ORR) in fuel cells. The lack of clear views on the natures of ORR active sites in these materials has hindered the progress in reducing their activity gap to Pt through a rational desire of doping structures. Using 14 types of N and Fe−N doping structures in graphene as model systems, systematic densityfunctional-theory (DFT) calculations are performed within a unified electrochemical thermodynamic framework and the same reaction mechanism to gain insights into ORR active sites in doped nanocarbons. Scaling relations are obtained between the calculated adsorption free energy of key ORR intermediates at surface sites associated with various graphene doping structures. Reaction free energy analysis indicates that the proton−electron transfer coupled O 2 adsorption and/or reduction of adsorbed hydroxyl group (*OH) are the activitydetermining steps in the ORR on most doped graphenes and that the ORR activity of various graphene doping structures can be described with a single thermodynamic descriptor, namely, the adsorption free energy of *OH (ΔG *OH ). A model volcano plot of ORR activity as a function of ΔG *OH is established for active sites in doped graphenes, which indicates that the surface sites associated with a few edge N-doping structures, such as armchair graphitic N, zigzag pyridinic N, and zigzag pyridinic N oxide, offer optimized binding strength of oxygenated species for catalyzing the ORR. Some other structures, such as in-plane graphitic N and the Fe−N 4 complex and hydrogenated zigzag pyridinic N, are also expected to form ORR activity sites. The possible electronic structure origin of the differing binding strength of oxygenated species on various graphene doping structures is analyzed in terms of the density of p z states near the Fermi level of active carbon atoms. These results may serve as guidance for designing ORR electrocatalysts of doped nanocarbons. Especially, it is revealed that merely N doping indeed can produce highly active electrocatalytic sites for the ORR in nanocarbons.

Hierarchical porous carbon nanofibers can efficiently eliminate kinetics and capacity mismatches between the anode and cathode of the potassium-ion hybrid capacitor.