Showing papers by "Kent State University published in 2019"

Cocatalysts for Selective Photoreduction of CO2 into Solar Fuels.

Abstract: Photoreduction of CO2 into sustainable and green solar fuels is generally believed to be an appealing solution to simultaneously overcome both environmental problems and energy crisis. The low selectivity of challenging multi-electron CO2 photoreduction reactions makes it one of the holy grails in heterogeneous photocatalysis. This Review highlights the important roles of cocatalysts in selective photocatalytic CO2 reduction into solar fuels using semiconductor catalysts. A special emphasis in this review is placed on the key role, design considerations and modification strategies of cocatalysts for CO2 photoreduction. Various cocatalysts, such as the biomimetic, metal-based, metal-free, and multifunctional ones, and their selectivity for CO2 photoreduction are summarized and discussed, along with the recent advances in this area. This Review provides useful information for the design of highly selective cocatalysts for photo(electro)reduction and electroreduction of CO2 and complements the existing reviews on various semiconductor photocatalysts.

Building Up a Picture of the Electrocatalytic Nitrogen Reduction Activity of Transition Metal Single-Atom Catalysts.

Abstract: The lack of chemical understanding and efficient catalysts impedes the development of electrocatalytic nitrogen reduction reaction (eNRR) for ammonia production. In this work, we employed density functional theory calculations to build up a picture (activity trends, electronic origins, and design strategies) of single-atom catalysts (SACs) supported on nitrogen-doped carbons as eNRR electrocatalysts. To construct such a picture, this work presents systematic studies of the eNRR activity of SACs covering 20 different transition metal (TM) centers coordinated by nitrogen atoms contained in three types of nitrogen-doped carbon substrates, which gives 60 SACs. Our study shows that the intrinsic activity trends could be established on the basis of the nitrogen adatom adsorption energy (Δ EN*). Furthermore, the influence of metal and support (ligands) on Δ EN* proved to be related to the bonding/antibonding orbital population and regulating the scaling relations for adsorption of intermediates, respectively. Accordingly, a two-step strategy is proposed for improving the eNNR activity of TM-SACs, which involves the following: (i) selection of the most promising family of SACs (g-C3N4 supported SACs as predicted in this work) and (ii) further improvement of the activity of the best candidate in the aforementioned family via tuning the adsorption strength of the key intermediates. Also, the stability of N-doped carbon supports and their selectivity in comparison to the competing hydrogen evolution need to be taken into consideration for screening the durable and efficient candidates. Finally, an effective strategy for designing active, stable, and selective SACs based on the mechanistic insights is elaborated to guide future eNRR studies.

Understanding the Roadmap for Electrochemical Reduction of CO2 to Multi-Carbon Oxygenates and Hydrocarbons on Copper-Based Catalysts

Abstract: Electrochemical reduction of CO2 to high-energy-density oxygenates and hydrocarbons beyond CO is important for long-term and large-scale renewable energy storage. However, the key step of the C–C bond formation needed for the generation of C2 products induces an additional barrier on the reaction. This inevitably creates larger overpotentials and greater variety of products as compared to the conversion of CO2 to C1 products. Therefore, an in-depth understanding of the catalytic mechanism is required for advancing the design of efficient electrocatalysts to control the reaction pathway to the desired products. Herein, we present a critical appraisal of reduction of CO2 to C2 products focusing on the connection between the fundamentals of reaction and efficient electrocatalysts. An in-depth discussion of the mechanistic aspects of various C2 reaction pathways on copper-based catalysts is presented together with consideration of practical factors under electrocatalytic operating conditions. By providing som...

Signatures of Quark-Hadron Phase Transitions in General-Relativistic Neutron-Star Mergers.

Abstract: Merging binaries of neutron-stars are not only strong sources of gravitational waves, but also have the potential of revealing states of matter at densities and temperatures not accessible in laboratories. A crucial and long-standing question in this context is whether quarks are deconfined as a result of the dramatic increase in density and temperature following the merger. We present the first fully general-relativistic simulations of merging neutron-stars including quarks at finite temperatures that can be switched off consistently in the equation of state. Within our approach, we can determine clearly what signatures a quark-hadron phase transition would leave in the gravitational-wave signal. We show that if after the merger the conditions are met for a phase transition to take place at several times nuclear saturation density, they would lead to a postmerger signal considerably different from the one expected from the inspiral, that can only probe the hadronic part of the equations of state, and to an anticipated collapse of the merged object. We also show that the phase transition leads to a very hot and dense quark core that, when it collapses to a black hole, produces a ringdown signal different from the hadronic one. Finally, in analogy with what is done in heavy-ion collisions, we use the evolution of the temperature and density in the merger remnant to illustrate the properties of the phase transition in a QCD phase diagram.

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci

Abstract: The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations.

Characterization of semiconductor photocatalysts

Abstract: The long-standing popularity of semiconductor photocatalysis due to its great potential in a variety of applications has resulted in the creation of numerous semiconductor photocatalysts, which stimulated the development of various characterization methods. This review aims to summarize the main characterization methods for assessing the most important properties of semiconductor photocatalysts, including their chemical composition (elemental composition, and chemical state/structure), physical properties (physical structure, crystallographic properties, optical absorption, charge dynamics, defects, and colloidal and thermal stability), and band structure (band gap, band edges/band edge offsets, and Fermi level). The discussion on each of these methods starts with a concise presentation of its fundamentals followed by carefully selected examples. At the end, a chart correlating the properties of a semiconductor with its potential characterization methods as well as outlook are provided. Overall, the aim of this review article is to help materials chemists and physicists, particularly students, in selecting suitable techniques for the characterization of semiconductor photocatalysts and potentially other relevant materials.

Deep learning for cardiovascular medicine: a practical primer.

Abstract: Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via multi-layered neural networks. Deep learning has accelerated by recent advances in computer hardware and algorithms and is increasingly applied in e-commerce, finance, and voice and image recognition to learn and classify complex datasets. The current medical literature shows both strengths and limitations of DL. Strengths of DL include its ability to automate medical image interpretation, enhance clinical decision-making, identify novel phenotypes, and select better treatment pathways in complex diseases. Deep learning may be well-suited to cardiovascular medicine in which haemodynamic and electrophysiological indices are increasingly captured on a continuous basis by wearable devices as well as image segmentation in cardiac imaging. However, DL also has significant weaknesses including difficulties in interpreting its models (the 'black-box' criticism), its need for extensive adjudicated ('labelled') data in training, lack of standardization in design, lack of data-efficiency in training, limited applicability to clinical trials, and other factors. Thus, the optimal clinical application of DL requires careful formulation of solvable problems, selection of most appropriate DL algorithms and data, and balanced interpretation of results. This review synthesizes the current state of DL for cardiovascular clinicians and investigators, and provides technical context to appreciate the promise, pitfalls, near-term challenges, and opportunities for this exciting new area.

Complex societies precede moralizing gods throughout world history

Abstract: The origins of religion and of complex societies represent evolutionary puzzles1–8. The ‘moralizing gods’ hypothesis offers a solution to both puzzles by proposing that belief in morally concerned supernatural agents culturally evolved to facilitate cooperation among strangers in large-scale societies9–13. Although previous research has suggested an association between the presence of moralizing gods and social complexity3,6,7,9–18, the relationship between the two is disputed9–13,19–24, and attempts to establish causality have been hampered by limitations in the availability of detailed global longitudinal data. To overcome these limitations, here we systematically coded records from 414 societies that span the past 10,000 years from 30 regions around the world, using 51 measures of social complexity and 4 measures of supernatural enforcement of morality. Our analyses not only confirm the association between moralizing gods and social complexity, but also reveal that moralizing gods follow—rather than precede—large increases in social complexity. Contrary to previous predictions9,12,16,18, powerful moralizing ‘big gods’ and prosocial supernatural punishment tend to appear only after the emergence of ‘megasocieties’ with populations of more than around one million people. Moralizing gods are not a prerequisite for the evolution of social complexity, but they may help to sustain and expand complex multi-ethnic empires after they have become established. By contrast, rituals that facilitate the standardization of religious traditions across large populations25,26 generally precede the appearance of moralizing gods. This suggests that ritual practices were more important than the particular content of religious belief to the initial rise of social complexity. Belief in moralizing gods followed the expansion of human societies and may have been preceded by doctrinal rituals that contributed to the initial rise of social complexity.

Anomalous hydrogen evolution behavior in high-pH environment induced by locally generated hydronium ions.

Abstract: Most fundamental studies of electrocatalysis are based on the experimental and simulation results obtained for bulk model materials. Some of these mechanistic understandings are inapplicable for more active nanostructured electrocatalysts. Herein, considering the simplest and most typical electrocatalytic process, the hydrogen evolution reaction, an alternative reaction mechanism is proposed for nanomaterials based on the identification of a new intermediate, which differs from those commonly known for the bulk counterparts. In-situ Raman spectroscopy and electrochemical thermal/kinetic measurements were conducted on a series of nanomaterials under different conditions. In high-pH electrolytes with negligible hydronium (H3O+) concentration in bulk phase, massive H3O+ intermediates are found generating on the catalytic surface during water dissociation and hydrogen adsorption processes. These H3O+ intermediates create a unique acid-like local reaction environment on nanostructured catalytic surfaces and cut the energy barrier of the overall reaction. Such phenomena on nanostructured electrocatalysts explain their widely observed anomalously high activity under high-pH conditions. Most of the current understanding on electrocatalysis is obtained on bulk catalysts but has not been fully verified on nanostructured materials. An alternative alkaline hydrogen evolution reaction mechanism is proposed here for nanostructured catalysts.

Global patterns and drivers of ecosystem functioning in rivers and riparian zones

Abstract: River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth’s biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented “next-generation biomonitoring” by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.

The Application of Hollow Structured Anodes for Sodium-Ion Batteries: From Simple to Complex Systems.

Abstract: Hollow structures exhibit fascinating and important properties for energy-related applications, such as lithium-ion batteries, supercapacitors, and electrocatalysts. Sodium-ion batteries, as analogs of lithium-ion batteries, are considered as promising devices for large-scale electrical energy storage. Inspired by applications of hollow structures as anodes for lithium-ion batteries, the application of these structures in sodium-ion batteries has attracted great attention in recent years. However, due to the difference in lithium and sodium-ion batteries, there are several issues that need to be addressed toward rational design of hollow structured sodium anodes. Herein, this research news article presents the recent developments in the synthesis of hollow structured anodes for sodium-ion batteries. The main strategies for rational design of materials for sodium-ion batteries are presented to provide an overview and perspectives for the future developments of this research area.

Polarization of Λ (Λ[over ¯]) Hyperons along the Beam Direction in Au+Au Collisions at sqrt[s_{NN}]=200 GeV.

Abstract: The Λ (Λ[over ¯]) hyperon polarization along the beam direction has been measured in Au+Au collisions at sqrt[s_{NN}]=200 GeV, for the first time in heavy-ion collisions. The polarization dependence on the hyperons' emission angle relative to the elliptic flow plane exhibits a second harmonic sine modulation, indicating a quadrupole pattern of the vorticity component along the beam direction, expected due to elliptic flow. The polarization is found to increase in more peripheral collisions, and shows no strong transverse momentum (p_{T}) dependence at p_{T} greater than 1 GeV/c. The magnitude of the signal is about 5 times smaller than those predicted by hydrodynamic and multiphase transport models; the observed phase of the emission angle dependence is also opposite to these model predictions. In contrast, the kinematic vorticity calculations in the blast-wave model tuned to reproduce particle spectra, elliptic flow, and the azimuthal dependence of the Gaussian source radii measured with the Hanbury Brown-Twiss intensity interferometry technique reproduce well the modulation phase measured in the data and capture the centrality and transverse momentum dependence of the polarization signal.

Microplastic surface properties affect bacterial colonization in freshwater

Abstract: Microplastics are a global concern in aquatic ecology and are readily colonized by bacteria in the environment. There is a lack of information on bacterial colonization of eroded and un-eroded microplastics in freshwater. In this study, six types of microplastics were incubated for 8 weeks in microcosms with water from Lake Erie. Microcosms were inoculated with one of three species: Acinetobacter (A.) calcoaceticus, Burkholderia (B.) cepacia, and Escherichia (E.) coli. These bacterial species are ubiquitous in water bodies associated with human populations. Bacterial surface coverage was determined using electron and fluorescent microscopy. Quantifications of EPS and surface roughness were performed by confocal microscopy and measuring contact angles (θw ) of water droplets on microplastics, respectively. Analyses revealed surface coverage differed among bacterial species and plastic types after 8 weeks. As the study progressed, E. coli remained the most abundant while A. calcoaceticus gradually decreased on most surfaces. Analyses of microcosms revealed polypropylene disks had lower bacterial abundance. Conversely, eroded polypropylene disks had highest bacterial abundance, indicating importance of surface roughness (lower θw values) and surface physicochemical properties of microplastics in bacterial colonization. Our results demonstrated that bacterial colonization of microplastics is affected by both the physicochemical properties of microplastics and the physiological properties of colonizing bacteria.

Parent-child attachment and children's experience and regulation of emotion: A meta-analytic review

Abstract: Attachment relationships serve as contexts within which children develop emotional capacities This meta-analytic review assessed the strength of associations of parent-child attachment patterns with the experience and regulation of emotion in children under age 18 years In a series of meta-analyses (k = 72 studies, N's ranged from 87 to 9,167), we examined children's positive and negative affective experiences (assessed either globally or elicited in specific contexts), emotion regulation ability, and coping strategies More securely attached children experienced more global positive affect and less global negative affect, expressed less elicited negative affect, were better able to regulate emotions, and more often used cognitive and social support coping strategies More avoidantly attached children experienced less global positive affect, were less able to regulate emotions, and were less likely to use cognitive or social support coping strategies By contrast, more ambivalently attached children experienced more global and more elicited negative affect, and were less able to regulate emotions More disorganized children experienced less global positive affect and more global negative affect These robust findings provide evidence that attachments to parents have implications for children's emotional development, although more research is needed on whether insecure attachment patterns are associated with distinct emotion profiles (PsycINFO Database Record (c) 2019 APA, all rights reserved)

Understanding demographic and socioeconomic biases of geotagged Twitter users at the county level

Abstract: Massive social media data produced from microblog platforms provide a new data source for studying human dynamics at an unprecedented scale. Meanwhile, population bias in geotagged Twitter users is...

High-fidelity simulation and nursing students' anxiety and self-confidence: A systematic review.

Abstract: Background As a complementary teaching pedagogy, high-fidelity simulation remains as an effective form of simulation modality. Empirical evidence has additionally shown high-fidelity simulation (HFS) to be an effective contributor to students' learning outcomes. Purpose This paper critically appraised existing scientific articles that covered the influence of utilizing HFS on the effects of nursing students' anxiety and self-confidence during undergraduate nursing education. Methods This was a systematic review of scientific articles conducted from 2007 to 2017 on the topic of the influence of using HFS on students' self-confidence and anxiety. The literature of six electronic databases (Proquest, SCOPUS, MEDLINE, PubMed Central, CINAHL, and PsychINFO) was reviewed. Results Following the literature search, 35 articles were selected. This review provides updated evidence on the efficacy of HFS in reducing anxiety and enhancing self-confidence among nursing students when performing nursing duties or managing patients. Moreover, this review highlights the need for more research that examines the impact of HFS on students' anxiety. Conclusion As this form of simulation is found to be effective in the enhancement of nursing student self-confidence and the reduction of their anxiety when caring for patients and/or employing nursing skills, the inclusion of simulation-based activities in all clinical nursing courses is vital.

Complexities in understanding antimicrobial resistance across domesticated animal, human, and environmental systems

Abstract: Antimicrobial resistance (AMR) is a significant threat to both human and animal health. The spread of AMR bacteria and genes across systems can occur through a myriad of pathways, both related and unrelated to agriculture, including via wastewater, soils, manure applications, direct exchange between humans and animals, and food exposure. Tracing origins and drivers of AMR bacteria and genes is challenging due to the array of contexts and the complexity of interactions overlapping health practice, microbiology, genetics, applied science and engineering, as well as social and human factors. Critically assessing the diverse and sometimes contradictory AMR literature is a valuable step in identifying tractable mitigation options to stem AMR spread. In this article we review research on the nonfoodborne spread of AMR, with a focus on domesticated animals and the environment and possible exposures to humans. Attention is especially placed on delineating possible sources and causes of AMR bacterial phenotypes, including underpinning the genetics important to human and animal health.

Protein requirements of soccer

Abstract: Although the physical demands of soccer have been studied frequently over the years, there has been little attention to the dietary protein needs of soccer players. Recent data from both moderate-i...