Nanjing University of Posts and Telecommunications

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTLuminescent Chemodosimeters for BioimagingYuming Yang†, Qiang Zhao‡, Wei Feng†, and Fuyou Li*†View Author Information† Department of Chemistry and State Key Laboratory of Molecular Engineering of Polymers and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, P. R. China‡ Key Laboratory for Organic Electronics and Information Displays (KLOEID) and Institute of Advanced Materials (IAM), Nanjing University of Posts and Telecommunications, Nanjing 210046, P. R. China.*Fax: 86-21-55664621. Tel.: 86-21-55664185. E-mail: [email protected]Cite this: Chem. Rev. 2013, 113, 1, 192–270Publication Date (Web):June 18, 2012Publication History Received27 October 2011Published online18 June 2012Published inissue 9 January 2013https://pubs.acs.org/doi/10.1021/cr2004103https://doi.org/10.1021/cr2004103review-articleACS PublicationsCopyright © 2012 American Chemical SocietyRequest reuse permissionsArticle Views31453Altmetric-Citations2087LEARN 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-AlertscloseSupporting Info (1)»Supporting Information Supporting Information SUBJECTS:Fluorescence,Fluorescence detection,Ions,Luminescence,Mercury Get e-Alerts

The design and characterization of thermally activated delayed fluorescence (TADF) materials for optoelectronic applications represents an active area of recent research in organoelectronics. Noble metal-free TADF molecules offer unique optical and electronic properties arising from the efficient transition and interconversion between the lowest singlet (S1 ) and triplet (T1 ) excited states. Their ability to harvest triplet excitons for fluorescence through facilitated reverse intersystem crossing (T1 →S1 ) could directly impact their properties and performances, which is attractive for a wide variety of low-cost optoelectronic devices. TADF-based organic light-emitting diodes, oxygen, and temperature sensors show significantly upgraded device performances that are comparable to the ones of traditional rare-metal complexes. Here we present an overview of the quick development in TADF mechanisms, materials, and applications. Fundamental principles on design strategies of TADF materials and the common relationship between the molecular structures and optoelectronic properties for diverse research topics and a survey of recent progress in the development of TADF materials, with a particular emphasis on their different types of metal-organic complexes, D-A molecules, and fullerenes, are highlighted. The success in the breakthrough of the theoretical and technical challenges that arise in developing high-performance TADF materials may pave the way to shape the future of organoelectronics.

Photovoltaic (PV) technologies for solar energy conversion represent promising routes to green and renewable energy generation. Despite relevant PV technologies being available for more than half a century, the production of solar energy remains costly, largely owing to low power conversion efficiencies of solar cells. The main difficulty in improving the efficiency of PV energy conversion lies in the spectral mismatch between the energy distribution of photons in the incident solar spectrum and the bandgap of a semiconductor material. In recent years, luminescent materials, which are capable of converting a broad spectrum of light into photons of a particular wavelength, have been synthesized and used to minimize the losses in the solar-cell-based energy conversion process. In this review, we will survey recent progress in the development of spectral converters, with a particular emphasis on lanthanide-based upconversion, quantum-cutting and down-shifting materials, for PV applications. In addition, we will also present technical challenges that arise in developing cost-effective high-performance solar cells based on these luminescent materials.

Using a simple hydrothermal procedure, cobalt oxide (Co(3)O(4)) nanowires were in situ synthesized on three-dimensional (3D) graphene foam grown by chemical vapor deposition. The structure and morphology of the resulting 3D graphene/Co(3)O(4) composites were characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, and Raman spectroscopy. The 3D graphene/Co(3)O(4) composite was used as the monolithic free-standing electrode for supercapacitor application and for enzymeless electrochemical detection of glucose. We demonstrate that it is capable of delivering high specific capacitance of ∼1100 F g(-1) at a current density of 10 A g(-1) with excellent cycling stability, and it can detect glucose with a ultrahigh sensitivity of 3.39 mA mM(-1) cm(-2) and a remarkable lower detection limit of <25 nM (S/N = 8.5).

A metal-free electrocatalyst has been developed by doping carbon nanotubes with electron-deficient boron. The good performance in the oxygen reduction reaction originates from the enhanced O2 chemisorption and effective utilization of π electrons in the conjugated carbon from the boron doping, as revealed by DFT calculations.

The application of phosphorescent heavy-metal complexes with d(6), d(8) and d(10) electron configurations for bioimaging is a new and promising research field and has been attracting increasing interest. In this critical review, we systematically evaluate the advantages of phosphorescent heavy-metal complexes as bioimaging probes, including their photophysical properties, cytotoxicity and cellular uptake mechanisms. The progress of research into the use of phosphorescent heavy-metal complexes for staining different compartments of cells, monitoring intracellular functional species, providing targeted bioimaging, two-photon bioimaging, small-animal bioimaging, multimodal bioimaging and time-resolved bioimaging is summarized. In addition, several possible future directions in this field are also discussed (133 references).

Recently, the use of phosphorescent heavy-metal complexes as chemosensors has attracted increasing interest due to their advantageous photophysical properties. This critical review focuses on the design principles and the recent development of phosphorescent chemosensors for metal cations, anions, pH, oxygen, volatile organic compounds and biomolecules based on some heavy-metal complexes (such as Pt(II)-, Ru(II)-, Re(I)-, Ir(III)-, Cu(I)-, Au(I)- and Os(II)-based complexes), in which the variation in phosphorescence signals induced by the interaction between heavy-metal complexes and analytes is utilized (217 references).

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Due to the broadcast nature of radio propagation, the wireless air interface is open and accessible to both authorized and illegitimate users. This completely differs from a wired network, where communicating devices are physically connected through cables and a node without direct association is unable to access the network for illicit activities. The open communications environment makes wireless transmissions more vulnerable than wired communications to malicious attacks, including both the passive eavesdropping for data interception and the active jamming for disrupting legitimate transmissions. Therefore, this paper is motivated to examine the security vulnerabilities and threats imposed by the inherent open nature of wireless communications and to devise efficient defense mechanisms for improving the wireless network security. We first summarize the security requirements of wireless networks, including their authenticity, confidentiality, integrity, and availability issues. Next, a comprehensive overview of security attacks encountered in wireless networks is presented in view of the network protocol architecture, where the potential security threats are discussed at each protocol layer. We also provide a survey of the existing security protocols and algorithms that are adopted in the existing wireless network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term evolution (LTE) systems. Then, we discuss the state of the art in physical-layer security, which is an emerging technique of securing the open communications environment against eavesdropping attacks at the physical layer. Several physical-layer security techniques are reviewed and compared, including information-theoretic security, artificial-noise-aided security, security-oriented beamforming, diversity-assisted security, and physical-layer key generation approaches. Since a jammer emitting radio signals can readily interfere with the legitimate wireless users, we also introduce the family of various jamming attacks and their countermeasures, including the constant jammer, intermittent jammer, reactive jammer, adaptive jammer, and intelligent jammer. Additionally, we discuss the integration of physical-layer security into existing authentication and cryptography mechanisms for further securing wireless networks. Finally, some technical challenges which remain unresolved at the time of writing are summarized and the future trends in wireless security are discussed.

The design and characterization of metal-organic complexes for optoelectronic applications is an active area of research. The metal-organic complex offers unique optical and electronic properties arising from the interplay between the inorganic metal and the organic ligand. The ability to modify chemical structure through control over metal-ligand interaction on a molecular level could directly impact the properties of the complex. When deposited in thin film form, this class of materials enable the fabrication of a wide variety of low-cost electronic and optoelectronic devices. These include light emitting diodes, solar cells, photodetectors, field-effect transistors as well as chemical and biological sensors. Here we present an overview of recent development in metal-organic complexes with controlled molecular structures and tunable properties. Advances in extending the control of molecular structures to solid materials for energy conversion and information technology applications will be highlighted.

Abstract High-entropy ceramics (HECs) are solid solutions of inorganic compounds with one or more Wyckoff sites shared by equal or near-equal atomic ratios of multi-principal elements. Although in the infant stage, the emerging of this new family of materials has brought new opportunities for material design and property tailoring. Distinct from metals, the diversity in crystal structure and electronic structure of ceramics provides huge space for properties tuning through band structure engineering and phonon engineering. Aside from strengthening, hardening, and low thermal conductivity that have already been found in high-entropy alloys, new properties like colossal dielectric constant, super ionic conductivity, severe anisotropic thermal expansion coefficient, strong electromagnetic wave absorption, etc., have been discovered in HECs. As a response to the rapid development in this nascent field, this article gives a comprehensive review on the structure features, theoretical methods for stability and property prediction, processing routes, novel properties, and prospective applications of HECs. The challenges on processing, characterization, and property predictions are also emphasized. Finally, future directions for new material exploration, novel processing, fundamental understanding, in-depth characterization, and database assessments are given.

This paper employs the Auto-Encoding Variational Bayes (AEVB) estimator based on Stochastic Gradient Variational Bayes (SGVB), designed to optimize recognition models for challenging posterior distributions and large-scale datasets. It has been applied to the mnist dataset and extended to form a Dynamic Bayesian Network (DBN) in the context of time series. The paper delves into Bayesian inference, variational methods, and the fusion of Variational Autoencoders (VAEs) and variational techniques. Emphasis is placed on reparameterization for achieving efficient optimization. AEVB employs VAEs as an approximation for intricate posterior distributions.

The synthesis of lanthanide-activated phosphors is pertinent to many emerging applications, ranging from high-resolution luminescence imaging to next-generation volumetric full-color display. In particular, the optical processes governed by the 4f-5d transitions of divalent and trivalent lanthanides have been the key to enabling precisely tuned color emission. The fundamental importance of lanthanide-activated phosphors for the physical and biomedical sciences has led to rapid development of novel synthetic methodologies and relevant tools that allow for probing the dynamics of energy transfer processes. Here, we review recent progress in developing methods for preparing lanthanide-activated phosphors, especially those featuring 4f-5d optical transitions. Particular attention will be devoted to two widely studied dopants, Ce3+ and Eu2+. The nature of the 4f-5d transition is examined by combining phenomenological theories with quantum mechanical calculations. An emphasis is placed on the correlation of host crystal structures with the 5d-4f luminescence characteristics of lanthanides, including quantum yield, emission color, decay rate, and thermal quenching behavior. Several parameters, namely Debye temperature and dielectric constant of the host crystal, geometrical structure of coordination polyhedron around the luminescent center, and the accurate energies of 4f and 5d levels, as well as the position of 4f and 5d levels relative to the valence and conduction bands of the hosts, are addressed as basic criteria for high-throughput computational design of lanthanide-activated phosphors.

Solar nitrogen (N2) fixation is the most attractive way for the sustainable production of ammonia (NH3), but the development of a highly active, long-term stable and low-cost catalyst remains a great challenge. Current research efforts for N2 reduction mainly focus on the metal-based catalysts using the electrochemical approach, while metal-free or solar-driven catalysts have been rarely explored. Herein, on the basis of a concept of electron “acceptance-donation”, a metal-free photocatalyst, namely, boron (B) atom, decorated on the optically active graphitic-carbon nitride (B/g-C3N4), for the reduction of N2 is proposed by using extensive first-principles calculations. Our results reveal that gas phase N2 can be efficiently reduced into NH3 on B/g-C3N4 through the enzymatic mechanism with a record low onset potential (0.20 V). Moreover, the B-decorated g-C3N4 can significantly enhance the visible light absorption, rendering them ideal for solar-driven reduction of N2. Importantly, the as-designed catalyst is further demonstrated to hold great promise for synthesis due to its extremely high stability. Our work is the first report of metal-free single atom photocatalyst for N2 reduction, offering cost-effective opportunities for advancing sustainable NH3 production.

Two kinds of boron and nitrogen co-doped carbon nanotubes (CNTs) dominated by bonded or separated B and N are intentionally prepared, which present distinct oxygen reduction reaction (ORR) performances. The experimental and theoretical results indicate that the bonded case cannot, while the separated one can, turn the inert CNTs into ORR electrocatalysts. This progress demonstrates the crucial role of the doping microstructure on ORR performance, which is of significance in exploring the advanced C-based metal-free electrocatalysts.

In this paper, we employ probabilistic neural network (PNN) with image and data processing techniques to implement a general purpose automated leaf recognition for plant classification. 12 leaf features are extracted and orthogonalized into 5 principal variables which consist the input vector of the PNN. The PNN is trained by 1800 leaves to classify 32 kinds of plants with an accuracy greater than 90%. Compared with other approaches, our algorithm is an accurate artificial intelligence approach which is fast in execution and easy in implementation.

Networked control systems are spatially distributed systems in which the communication between sensors, actuators, and controllers occurs through a shared band-limited digital communication network. Several advantages of the network architectures include reduced system wiring, plug and play devices, increased system agility, and ease of system diagnosis and maintenance. Consequently, networked control is the current trend for industrial automation and has ever-increasing applications in a wide range of areas, such as smart grids, manufacturing systems, process control, automobiles, automated highway systems, and unmanned aerial vehicles. The modelling, analysis, and control of networked control systems have received considerable attention in the last two decades. The ‘ control over networks ’ is one of the key research directions for networked control systems. This paper aims at presenting a survey of trends and techniques in networked control systems from the perspective of ‘ control over networks ’ , providing a snapshot of five control issues: sampled-data control, quantization control, networked control, event-triggered control, and security control. Some challenging issues are suggested to direct the future research.

In this Review article, we systematically summarize the design and applications of various kinds of long-lived emissive probes for bioimaging and biosensing via time-resolved photoluminescence techniques. The probes reviewed, including lanthanides, transition-metal complexes, organic dyes, carbon and silicon nanoparticles, metal clusters, and persistent phosphores, exhibit longer luminescence lifetimes than that of autofluorescence from biological tissue and organs. When these probes are internalized into living cells or animals, time-gated photoluminescence imaging selectively collects long-lived signals for intensity analysis, while photoluminescence lifetime imaging reports the decay details of each pixel. Since the long-lived signals are differentiated from autofluorescence in the time domain, the imaging contrast and sensing sensitivity are remarkably improved. The future prospects and challenges in this rapidly growing field are addressed.

Organic afterglow materials, developed recently by breaking through the difficulties in modulating ultrafast-decayed excited states, exhibit ultralong-lived emission for persistent luminescence with lifetimes of several orders of magnitude longer than traditional fluorescent and phosphorescent emissions at room temperature. Their exceptional properties, namely ultralong luminescent lifetime, large Stokes shifts, facile excited state transformation, and environmentally sensitive emission, have led to a diverse range of advanced optoelectronic applications. Here, the organic afterglow is reviewed from the perspective of fundamental concepts on both phenomenon and mechanism, examining the technical challenges in relation to excited state tuning and lifetime elongation. In particular, the advances in material design strategies that afford a large variety of organic afterglow materials for a broad utility in optoelectronics including lighting and displays, anti-counterfeiting, optical recording, chemical sensors and bio-imaging are highlighted.

The recent concept of massive multiple-input multiple-output (MIMO) can significantly improve the capacity of the communication network, and it has been regarded as a promising technology for the next-generation wireless communications. However, the fundamental challenge of existing massive MIMO systems is that high computational complexity and complicated spatial structures bring great difficulties to exploit the characteristics of the channel and sparsity of these multi-antennas systems. To address this problem, in this paper, we focus on channel estimation and direction-of-arrival (DOA) estimation, and a novel framework that integrates the massive MIMO into deep learning is proposed. To realize end-to-end performance, a deep neural network (DNN) is employed to conduct offline learning and online learning procedures, which is effective to learn the statistics of the wireless channel and the spatial structures in the angle domain. Concretely, the DNN is first trained by simulated data in different channel conditions with the aids of the offline learning, and then corresponding output data can be obtained based on current input data during online learning process. In order to realize super-resolution channel estimation and DOA estimation, two algorithms based on the deep learning are developed, in which the DOA can be estimated in the angle domain without additional complexity directly. Furthermore, simulation results corroborate that the proposed deep learning based scheme can achieve better performance in terms of the DOA estimation and the channel estimation compared with conventional methods, and the proposed scheme is well investigated by extensive simulation in various cases for testing its robustness.