Yunnan Normal University

Glucose-derived water-soluble crystalline graphene quantum dots (GQDs) with an average diameter as small as 1.65 nm (∼5 layers) were prepared by a facile microwave-assisted hydrothermal method. The GQDs exhibits deep ultraviolet (DUV) emission of 4.1 eV, which is the shortest emission wavelength among all the solution-based QDs. The GQDs exhibit typical excitation wavelength-dependent properties as expected in carbon-based quantum dots. However, the emission wavelength is independent of the size of the GQDs. The unique optical properties of the GQDs are attributed to the self-passivated layer on the surface of the GQDs as revealed by electron energy loss spectroscopy. The photoluminescence quantum yields of the GQDs were determined to be 7-11%. The GQDs are capable of converting blue light into white light when the GQDs are coated onto a blue light emitting diode.

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTFluorescence and Colorimetric Chemosensors for Fluoride-Ion DetectionYing Zhou†‡, Jun Feng Zhang§, and Juyoung Yoon*†View Author Information† Department of Chemistry and Nano Science, Ewha Womans University, Seoul 120-750, Korea‡ Key Laboratory of Medicinal Chemistry for Natural Resource, School of Chemical Science and Technology, Yunnan University, Kunming, 650091, P. R. China§ College of Chemistry and Chemical Engineering, Yunnan Normal University, Kunming 650500, P. R. China*Phone: 82-2-3277-2400. Fax: 82-2-3277-2384. E-mail: [email protected]Cite this: Chem. Rev. 2014, 114, 10, 5511–5571Publication Date (Web):March 25, 2014Publication History Received23 January 2013Published online25 March 2014Published inissue 28 May 2014https://pubs.acs.org/doi/10.1021/cr400352mhttps://doi.org/10.1021/cr400352mreview-articleACS PublicationsCopyright © 2014 American Chemical SocietyRequest reuse permissionsArticle Views18726Altmetric-Citations908LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Absorption,Anions,Color,Fluorescence,Sensors Get e-Alerts

Due to the wide range of applications and biological significance, the development of optical probes for silver, gold and platinum ions has been an active research area in the past few years. This tutorial review focuses on the recent contributions concerning the fluorescent or colorimetric sensors for these metal ions, and is organized according to their structural classifications (for Ag(+) detection) and unique mechanisms between the sensors and metal ions (for Au(3+) and Pt(2+) detection).

Impacts of global climate change on terrestrial ecosystems are imperfectly constrained by ecosystem models and direct observations. Pervasive ecosystem transformations occurred in response to warming and associated climatic changes during the last glacial-to-interglacial transition, which was comparable in magnitude to warming projected for the next century under high-emission scenarios. We reviewed 594 published paleoecological records to examine compositional and structural changes in terrestrial vegetation since the last glacial period and to project the magnitudes of ecosystem transformations under alternative future emission scenarios. Our results indicate that terrestrial ecosystems are highly sensitive to temperature change and suggest that, without major reductions in greenhouse gas emissions to the atmosphere, terrestrial ecosystems worldwide are at risk of major transformation, with accompanying disruption of ecosystem services and impacts on biodiversity.

Material that can emit broad spectral wavelengths covering deep ultraviolet, visible, and near-infrared is highly desirable. It can lead to important applications such as broadband modulators, photodetectors, solar cells, bioimaging, and fiber communications. However, there is currently no material that meets such desirable requirement. Here, we report the layered structure of nitrogen-doped graphene quantum dots (N-GQDs) which possess broadband emission ranging from 300 to >1000 nm. The broadband emission is attributed to the layered structure of the N-GQDs that contains a large conjugated system and provides extensive delocalized π electrons. In addition, a broadband photodetector with responsivity as high as 325 V/W is demonstrated by coating N-GQDs onto interdigital gold electrodes. The unusual negative photocurrent is observed which is attributed to the trapping sites induced by the self-passivated surface states in the N-GQDs.

The term metaverse is described as the next iteration of the Internet. Metaverse is a virtual platform that uses extended reality technologies, i.e. augmented reality, virtual reality, mixed reality, 3D graphics, and other emerging technologies to allow real-time interactions and experiences in ways that are not possible in the physical world. Companies have begun to notice the impact of the metaverse and how it may help maximize profits. The purpose of this paper is to offer perspectives on several important areas, i.e. marketing, tourism, manufacturing, operations management, education, the retailing industry, banking services, healthcare, and human resource management that are likely to be impacted by the adoption and use of a metaverse. Each includes an overview, opportunities, challenges, and a potential research agenda.

BACKGROUND: With the rapid accumulation of biological datasets, machine learning methods designed to automate data analysis are urgently needed. In recent years, so-called topic models that originated from the field of natural language processing have been receiving much attention in bioinformatics because of their interpretability. Our aim was to review the application and development of topic models for bioinformatics. DESCRIPTION: This paper starts with the description of a topic model, with a focus on the understanding of topic modeling. A general outline is provided on how to build an application in a topic model and how to develop a topic model. Meanwhile, the literature on application of topic models to biological data was searched and analyzed in depth. According to the types of models and the analogy between the concept of document-topic-word and a biological object (as well as the tasks of a topic model), we categorized the related studies and provided an outlook on the use of topic models for the development of bioinformatics applications. CONCLUSION: Topic modeling is a useful method (in contrast to the traditional means of data reduction in bioinformatics) and enhances researchers' ability to interpret biological information. Nevertheless, due to the lack of topic models optimized for specific biological data, the studies on topic modeling in biological data still have a long and challenging road ahead. We believe that topic models are a promising method for various applications in bioinformatics research.

Abstract Potato ( Solanum tuberosum L.) is the world’s most important non-cereal food crop, and the vast majority of commercially grown cultivars are highly heterozygous tetraploids. Advances in diploid hybrid breeding based on true seeds have the potential to revolutionize future potato breeding and production 1–4 . So far, relatively few studies have examined the genome evolution and diversity of wild and cultivated landrace potatoes, which limits the application of their diversity in potato breeding. Here we assemble 44 high-quality diploid potato genomes from 24 wild and 20 cultivated accessions that are representative of Solanum section Petota , the tuber-bearing clade, as well as 2 genomes from the neighbouring section, Etuberosum . Extensive discordance of phylogenomic relationships suggests the complexity of potato evolution. We find that the potato genome substantially expanded its repertoire of disease-resistance genes when compared with closely related seed-propagated solanaceous crops, indicative of the effect of tuber-based propagation strategies on the evolution of the potato genome. We discover a transcription factor that determines tuber identity and interacts with the mobile tuberization inductive signal SP6A. We also identify 561,433 high-confidence structural variants and construct a map of large inversions, which provides insights for improving inbred lines and precluding potential linkage drag, as exemplified by a 5.8-Mb inversion that is associated with carotenoid content in tubers. This study will accelerate hybrid potato breeding and enrich our understanding of the evolution and biology of potato as a global staple food crop.

Graph neural networks (GNNs), as a branch of deep learning in non-Euclidean space, perform particularly well in various tasks that process graph structure data. With the rapid accumulation of biological network data, GNNs have also become an important tool in bioinformatics. In this research, a systematic survey of GNNs and their advances in bioinformatics is presented from multiple perspectives. We first introduce some commonly used GNN models and their basic principles. Then, three representative tasks are proposed based on the three levels of structural information that can be learned by GNNs: node classification, link prediction, and graph generation. Meanwhile, according to the specific applications for various omics data, we categorize and discuss the related studies in three aspects: disease prediction, drug discovery, and biomedical imaging. Based on the analysis, we provide an outlook on the shortcomings of current studies and point out their developing prospect. Although GNNs have achieved excellent results in many biological tasks at present, they still face challenges in terms of low-quality data processing, methodology, and interpretability and have a long road ahead. We believe that GNNs are potentially an excellent method that solves various biological problems in bioinformatics research.

Abstract The electrochemical hydrogen evolution reaction (HER) is an attractive technology for the mass production of hydrogen. Ru‐based materials are promising electrocatalysts owing to the similar bonding strength with hydrogen but much lower cost than Pt catalysts. Herein, an ordered macroporous superstructure of N‐doped nanoporous carbon anchored with the ultrafine Ru nanoclusters as electrocatalytic micro/nanoreactors is developed via the thermal pyrolysis of ordered macroporous single crystals of ZIF‐8 accommodating Ru(III) ions. Benefiting from the highly interconnected reticular macro–nanospaces, this superstrucure affords unparalleled performance for pH‐universal HER, with order of magnitude higher mass activity compared to the benchmark Pt/C. Notably, an exceptionally low overpotential of only 13 mV@10 mA cm −2 is required for HER in alkaline solution, with a low Tafel slope of 40.41 mV dec −1 and an ultrahigh turnover frequency value of 1.6 H 2 s −1 at 25 mV, greatly outperforming Pt/C. Furthermore, the hydrogen generation rates are almost twice those of Pt/C during practical overall alkaline water splitting. A solar‐to‐hydrogen system is also demonstrated to further promote the application. This research may open a new avenue for the development of advanced electrocatalytic micro/nanoreactors with controlled morphology and excellent performance for future energy applications.

Deposition of reactive nitrogen from human activities occurred in the preindustrial era.

Abstract The excessive enrichment of nitrate in the environment can be converted into ammonia (NH 3 ) through electrochemical processes, offering significant implications for modern agriculture and the potential to reduce the burden of the Haber–Bosch (HB) process while achieving environmentally friendly NH 3 production. Emerging research on electrocatalytic nitrate reduction (eNitRR) to NH 3 has gained considerable momentum in recent years for efficient NH 3 synthesis. However, existing reviews on nitrate reduction have primarily focused on limited aspects, often lacking a comprehensive summary of catalysts, reaction systems, reaction mechanisms, and detection methods employed in nitrate reduction. This review aims to provide a timely and comprehensive analysis of the eNitRR field by integrating existing research progress and identifying current challenges. This review offers a comprehensive overview of the research progress achieved using various materials in electrochemical nitrate reduction, elucidates the underlying theoretical mechanism behind eNitRR, and discusses effective strategies based on numerous case studies to enhance the electrochemical reduction from NO 3 ˗ to NH 3 . Finally, this review discusses challenges and development prospects in the eNitRR field with an aim to guide design and development of large‐scale sustainable nitrate reduction electrocatalysts.

Chiral metal-organic framework coated open tubular columns are used in the high-resolution gas chromatographic separation of chiral compounds. The columns have excellent selectivity and also possess good recognition ability toward a wide range of organic compounds such as alkanes, alcohols, and isomers.

The doping of carbon-based materials is of great importance due to its ability to modulate their optical, electrical and optoelectronic properties. Nitrogen-doped graphene quantum dots (N-GQDs) have received significant attention due to their superior electrocatalytic activity, optical properties and biocompatibility. The energy-level structure of N-GQDs remains unknown, which hinders the development of N-GQDs for various applications. Here, we report a one-pot synthesis method to prepare large-quantity N-GQDs at room temperature and atmospheric pressure under a prolonged reaction time. Using this approach, we can effectively dope N into the N-GQDs. As revealed by electron energy loss spectroscopy, N-doping introduces a new energy level into the electronic structure, which is responsible for tuning the optical properties of the N-GQDs.

Replacing the organic linker in sodalite-type zinc 2-methylimidazolate by 3-methyl-1,2,4-triazolate produces isomorphous pure triazolate or solid solution imidazolate/triazolate frameworks functionalized by uncoordinated nitrogen donors. These show dramatically enhanced and fine-tuned sorption performance for practical adsorptive applications. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

A new rhodamine-based derivative bearing a 1,8-naphthalimide group (1) was synthesized as a dual-mode Cu(2+)-selective sensor via the rhodamine ring-opening approach and ratiometric displacement. A colorimetric and "off-on" signal for Cu(2+) through rhodamine ring opening in 1 and ratiometric fluorescent signal output when Cu(2+) displaces the bound Zn(2+) in the 1-Zn(2+) complex can be observed.

Sulphur-doped carbon-based materials have attracted a great deal of interest because of their important applications in the fields of oxygen reduction reactions, hydrogen storage, supercapacitors, photocatalysts and lithium ion batteries. Here, we report a new member of sulphur-doped carbon-based materials, i.e. sulphur doped graphene quantum dots (S-GQDs). The S-GQDs were prepared by a hydrothermal method using fructose and sulphuric acid as source materials. Absorption and photoluminescence investigations show that inter-band crossings are responsible for the observed multiple emission peaks. The incorporation of ∼1 at% of S into the quantum dots can effectively modify the electronic structure of the S-GQDs by introducing S-related energy levels between π and π* of C. The additional energy levels in the S-GQDs lead to efficient and multiple emission peaks.

A naphthalimide-based highly selective colorimetric and ratiometric fluorescent probe for the fluoride ion displayed both one- and two-photon ratiometric changes. Upon reaction with the F(-) (TBA(+) and Na(+) salts) anion in CH(3)CN as well as in aqueous buffer solution, probe 1 shows dramatic color changes from colorless to jade-green and remarkable ratiometric fluorescence enhancements signals. These properties are mechanistically ascribed to a fluoride-triggered Si-O bond cleavage that resulted in a green fluorescent 4-amino-1,8-naphthalimide.

Using a bis-triazolate ligand and tetrahedral Zn(II) ion, we synthesized a flexible porous coordination polymer functionalized with pairs of uncoordinated triazolate N-donors that can be used as guest chelating sites to give very high CO(2) adsorption enthalpy and CO(2)/N(2) selectivity. The dynamic CO(2) sorption behavior could be monitored well by single-crystal X-ray diffraction.

Key ecological function areas are responsible for protecting and restoring ecosystems and alleviating regional ecological deterioration. Revealing the inherent relationship between land use/cover (LULC) change and ecosystem service value (ESV) in such areas is of great significance for sustainable development. We used LULC and other data from 2000, 2010, and 2018 to analyze the spatiotemporal evolution of ESV in China’s Sichuan-Yunnan Ecological Barrier based on six LULC types: Farmland, Forest, Grassland, Water, Built-up land, and Other. With the goal of maximizing both ESV and economic benefits, we used coupled gray multi-objective optimization (GMOP) and patch-generating land-use simulation (PLUS) models to assess three scenarios (business-as-usual, BAU; ecological development priority, EDP; and ecological and economic balance, EEB) in terms of the spatial distribution and optimization of LULC structure in 2026. The study area was dominated by Forest and Grassland, with major LULC changes from 2000 to 2018 mainly deriving from transfers between Farmland, Forest, and Grassland along with Farmland conversion to Built-up land. ESV trended upward during the study period, mainly due to contributions from Forest and Water. Under EDP scenario in 2026, the expansion Built-up land was eased, which expansion area is the smallest among the 3 scenarios at 643.03 km2, the Forest area increased by 673.80 km2, the overall LULC structure was improved, and the total ESV increased by 2.502 billion yuan. Under EEB scenario, Forest area decreased by 405.95 km2, but the economic benefits increased remarkably, showing the effect of supporting larger-scale economic growth with less land resource consumption. Under EDP scenario, ESV changes were most dramatic at local scales. The use of coupled GMOP-PLUS models for LULC optimization allowed improved assessment of social, economic, and environmental factors and provided a new way to address key technical problem in land-use planning in large-scale ecological function areas.