Showing papers by "Nanjing University of Science and Technology published in 2017"

Image Super-Resolution via Deep Recursive Residual Network

Abstract: Recently, Convolutional Neural Network (CNN) based models have achieved great success in Single Image Super-Resolution (SISR). Owing to the strength of deep networks, these CNN models learn an effective nonlinear mapping from the low-resolution input image to the high-resolution target image, at the cost of requiring enormous parameters. This paper proposes a very deep CNN model (up to 52 convolutional layers) named Deep Recursive Residual Network (DRRN) that strives for deep yet concise networks. Specifically, residual learning is adopted, both in global and local manners, to mitigate the difficulty of training very deep networks, recursive learning is used to control the model parameters while increasing the depth. Extensive benchmark evaluation shows that DRRN significantly outperforms state of the art in SISR, while utilizing far fewer parameters. Code is available at https://github.com/tyshiwo/DRRN_CVPR17.

MemNet: A Persistent Memory Network for Image Restoration

Abstract: Recently, very deep convolutional neural networks (CNNs) have been attracting considerable attention in image restoration. However, as the depth grows, the longterm dependency problem is rarely realized for these very deep models, which results in the prior states/layers having little influence on the subsequent ones. Motivated by the fact that human thoughts have persistency, we propose a very deep persistent memory network (MemNet) that introduces a memory block, consisting of a recursive unit and a gate unit, to explicitly mine persistent memory through an adaptive learning process. The recursive unit learns multi-level representations of the current state under different receptive fields. The representations and the outputs from the previous memory blocks are concatenated and sent to the gate unit, which adaptively controls how much of the previous states should be reserved, and decides how much of the current state should be stored. We apply MemNet to three image restoration tasks, i.e., image denosing, super-resolution and JPEG deblocking. Comprehensive experiments demonstrate the necessity of the MemNet and its unanimous superiority on all three tasks over the state of the arts. Code is available at https://github.com/tyshiwo/MemNet.

Parameter-less Auto-weighted multiple graph regularized Nonnegative Matrix Factorization for data representation

Abstract: Recently, multiple graph regularizer based methods have shown promising performances in data representation However, the parameter choice of the regularizer is crucial to the performance of clustering and its optimal value changes for different real datasets To deal with this problem, we propose a novel method called Parameter-less Auto-weighted Multiple Graph regularized Nonnegative Matrix Factorization (PAMGNMF) in this paper PAMGNMF employs the linear combination of multiple simple graphs to approximate the manifold structure of data as previous methods do Moreover, the proposed method can automatically learn an optimal weight for each graph without introducing an additive parameter Therefore, the proposed PAMGNMF method is easily applied to practical problems Extensive experimental results on different real-world datasets have demonstrated that the proposed method achieves better performance than the state-of-the-art approaches

50-Fold EQE Improvement up to 6.27% of Solution-Processed All-Inorganic Perovskite CsPbBr3 QLEDs via Surface Ligand Density Control

Abstract: Solution-processed CsPbBr3 quantum-dot light-emitting diodes with a 50-fold external quantum efficiency improvement (up to 6.27%) are achieved through balancing surface passivation and carrier injection via ligand density control (treating with hexane/ethyl acetate mixed solvent), which induces the coexistence of high levels of ink stability, photoluminescence quantum yields, thin-film uniformity, and carrier-injection efficiency.

Richer Convolutional Features for Edge Detection

Abstract: Edge detection is a fundamental problem in computer vision. Recently, convolutional neural networks (CNNs) have pushed forward this field significantly. Existing methods which adopt specific layers of deep CNNs may fail to capture complex data structures caused by variations of scales and aspect ratios. In this paper, we propose an accurate edge detector using richer convolutional features (RCF). RCF encapsulates all convolutional features into more discriminative representation, which makes good usage of rich feature hierarchies, and is amenable to training via backpropagation. RCF fully exploits multiscale and multilevel information of objects to perform the image-to-image prediction holistically. Using VGG16 network, we achieve state-of-the-art performance on several available datasets. When evaluating on the well-known BSDS500 benchmark, we achieve ODS F-measure of 0.811 while retaining a fast speed (8 FPS). Besides, our fast version of RCF achieves ODS F-measure of 0.806 with 30 FPS. We also demonstrate the versatility of the proposed method by applying RCF edges for classical image segmentation.

Heterogeneous materials: a new class of materials with unprecedented mechanical properties

Abstract: Here we present a perspective on heterogeneous materials, a new class of materials possessing superior combinations of strength and ductility that are not accessible to their homogeneous counterpar...

Stabilizing Cesium Lead Halide Perovskite Lattice through Mn(II) Substitution for Air-Stable Light-Emitting Diodes.

Abstract: All-inorganic cesium lead halide perovskite (CsPbX3, X = Cl, Br, and I) quantum dots (QDs), possessing high photoluminescence quantum yields and tunable color output, have recently been endowed great promise for high-performance solar cells and light-emitting diodes (LEDs). Although moisture stability has been greatly improved through separating QDs with a SiO2 shell, the practical applications of CsPbX3 QDs are severely restricted by their poor thermal stability, which is associated with the intrinsically low formation energies of perovskite lattices. In this regard, enhancing the formation energies of perovskite lattices of CsPbX3 QDs holds great promise in getting to the root of their poor thermal stability, which hitherto remains untouched. Herein, we demonstrate an effective strategy through Mn2+ substitution to fundamentally stabilize perovskite lattices of CsPbX3 QDs even at high temperatures up to 200 °C under ambient air conditions. We employ first-principle calculations to confirm that the signi...

All Inorganic Halide Perovskites Nanosystem: Synthesis, Structural Features, Optical Properties and Optoelectronic Applications.

Abstract: The recent success of organometallic halide perovskites (OHPs) in photovoltaic devices has triggered lots of corresponding research and many perovskite analogues have been developed to look for devices with comparable performance but better stability. Upon the preparation of all inorganic halide perovskite nanocrystals (IHP NCs), research activities have soared due to their better stability, ultrahigh photoluminescence quantum yield (PL QY), and composition dependent luminescence covering the whole visible region with narrow line-width. They are expected to be promising materials for next generation lighting and display, and many other applications. Within two years, a lot of interesting results have been observed. Here, the synthesis of IHPs is reviewed, and their progresses in optoelectronic devices and optical applications, such as light-emitting diodes (LEDs), photodetectors (PDs), solar cells (SCs), and lasing, is presented. Information and recent understanding of their crystal structures and morphology modulations are addressed. Finally, a brief outlook is given, highlighting the presently main problems and their possible solutions and future development directions.

Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey

Abstract: Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data, text documents. Researchers have published many articles in the field of topic modeling and applied in various fields such as software engineering, political science, medical and linguistic science, etc. There are various methods for topic modeling, which Latent Dirichlet allocation (LDA) is one of the most popular methods in this field. Researchers have proposed various models based on the LDA in topic modeling. According to previous work, this paper can be very useful and valuable for introducing LDA approaches in topic modeling. In this paper, we investigated scholarly articles highly (between 2003 to 2016) related to Topic Modeling based on LDA to discover the research development, current trends and intellectual structure of topic modeling. Also, we summarize challenges and introduce famous tools and datasets in topic modeling based on LDA.

Phosphate Ion Functionalized Co3 O4 Ultrathin Nanosheets with Greatly Improved Surface Reactivity for High Performance Pseudocapacitors.

Abstract: A surface-modified Co3 O4 ultrathin nanosheet (denoted as PCO) is reported via controllable phosphate ion functionalization for pseudocapacitors. An energy density of 71.6 W h kg-1 (at 1500 W kg-1 ) is achieved by the PCO-based pseudocapacitor. The unique porous nanosheet morphology, high surface reactivity, and fast electrode kinetics of PCO are found to be responsible for the enhanced pseudocapacitive performance.

Grain boundary stability governs hardening and softening in extremely fine nanograined metals

Abstract: Conventional metals become harder with decreasing grain sizes, following the classical Hall-Petch relationship. However, this relationship fails and softening occurs at some grain sizes in the nanometer regime for some alloys. In this study, we discovered that plastic deformation mechanism of extremely fine nanograined metals and their hardness are adjustable through tailoring grain boundary (GB) stability. The electrodeposited nanograined nickel-molybdenum (Ni–Mo) samples become softened for grain sizes below 10 nanometers because of GB-mediated processes. With GB stabilization through relaxation and Mo segregation, ultrahigh hardness is achieved in the nanograined samples with a plastic deformation mechanism dominated by generation of extended partial dislocations. Grain boundary stability provides an alternative dimension, in addition to grain size, for producing novel nanograined metals with extraordinary properties.

High-Performance 2.6 V Aqueous Asymmetric Supercapacitors based on In Situ Formed Na0.5MnO2 Nanosheet Assembled Nanowall Arrays

Abstract: The voltage limit for aqueous asymmetric supercapacitors is usually 2 V, which impedes further improvement in energy density. Here, high Na content Birnessite Na0.5 MnO2 nanosheet assembled nanowall arrays are in situ formed on carbon cloth via electrochemical oxidation. It is interesting to find that the electrode potential window for Na0.5 MnO2 nanowall arrays can be extended to 0-1.3 V (vs Ag/AgCl) with significantly increased specific capacitance up to 366 F g-1 . The extended potential window for the Na0.5 MnO2 electrode provides the opportunity to further increase the cell voltage of aqueous asymmetric supercapacitors beyond 2 V. To construct the asymmetric supercapacitor, carbon-coated Fe3 O4 nanorod arrays are synthesized as the anode and can stably work in a negative potential window of -1.3 to 0 V (vs Ag/AgCl). For the first time, a 2.6 V aqueous asymmetric supercapacitor is demonstrated by using Na0.5 MnO2 nanowall arrays as the cathode and carbon-coated Fe3 O4 nanorod arrays as the anode. In particular, the 2.6 V Na0.5 MnO2 //Fe3 O4 @C asymmetric supercapacitor exhibits a large energy density of up to 81 Wh kg-1 as well as excellent rate capability and cycle performance, outperforming previously reported MnO2 -based supercapacitors. This work provides new opportunities for developing high-voltage aqueous asymmetric supercapacitors with further increased energy density.

Metal–organic frameworks based membranes for liquid separation

Abstract: Metal–organic frameworks (MOFs) represent a fascinating class of solid crystalline materials which can be self-assembled in a straightforward manner by the coordination of metal ions or clusters with organic ligands. Owing to their intrinsic porous characteristics, unique chemical versatility and abundant functionalities, MOFs have received substantial attention for diverse industrial applications, including membrane separation. Exciting research activities ranging from fabrication strategies to separation applications of MOF-based membranes have appeared. Inspired by the marvelous achievements of MOF-based membranes in gas separations, liquid separations are also being explored for the purpose of constructing continuous MOFs membranes or MOF-based mixed matrix membranes. Although these are in an emerging stage of vigorous development, most efforts are directed towards improving the liquid separation efficiency with well-designed MOF-based membranes. Therefore, as an increasing trend in membrane separation, the field of MOF-based membranes for liquid separation is highlighted in this review. The criteria for judicious selection of MOFs in fabricating MOF-based membranes are given. Special attention is paid to rational design strategies for MOF-based membranes, along with the latest application progress in the area of liquid separations, such as pervaporation, water treatment, and organic solvent nanofiltration. Moreover, some attractive dual-function applications of MOF-based membranes in the removal of micropollutants, degradation, and antibacterial activity are also reviewed. Finally, we define the remaining challenges and future opportunities in this field. This Tutorial Review provides an overview and outlook for MOF-based membranes for liquid separations. Further development of MOF-based membranes for liquid separation must consider the demands of strict separation standards and environmental safety for industrial application.

One-Pot Synthesis of Zeolitic Imidazolate Framework 67-Derived Hollow Co3S4@MoS2 Heterostructures as Efficient Bifunctional Catalysts

Abstract: Herein, we present a facile metal–organic framework-engaged strategy to synthesize hollow Co3S4@MoS2 heterostructures as efficient bifunctional catalysts for both H2 and O2 generation. The well-known cobalt-based metal–organic zeolitic imidazolate frameworks (ZIF-67) are used not only as the morphological template but also as the cobalt precursor. During the two-step temperature-raising hydrothermal process, ZIF-67 polyhedrons are first transformed to hollow cobalt sulfide polyhedrons by sulfidation, and then molybdenum disulfide nanosheets further grow and deposit on the surface of hollow cobalt sulfide polyhedrons at the increased temperature. The crystalline hollow Co3S4@MoS2 heterostructures are finally obtained after subsequent thermal annealing under a N2 atmosphere. Due to the synergistic effects between the hydrogen evolution reaction active catalyst of MoS2 and the oxygen evolution reaction active catalyst of Co3S4, the obtained hollow Co3S4@MoS2 heterostructures exhibit outstanding bifunctional ...

Bismuth Incorporation Stabilized α-CsPbI3 for Fully Inorganic Perovskite Solar Cells

Abstract: All-inorganic CsPbI3 perovskite is emerging to be an alternative light-harvesting material in solar cells owing to the enhanced stability and comparable photovoltaic performance compared to organic–inorganic hybrid perovskites. However, the desirable black phase α-CsPbI3 is not stable at room temperature and degrades rapidly to a nonperovskite yellow phase δ-CsPbI3. Herein, we introduce a compositional engineering approach via incorporating Bi3+ in CsPbI3 to stabilize the α-phase at room temperature. Fully inorganic solar cells based on the Bi-incorporated α-CsPb1–xBixI3 compounds demonstrate a high PCE of 13.21% at an optimal condition (incorporation of 4 mol % Bi3+) and maintain 68% of the initial PCE for 168 h under ambient conditions without encapsulation. This is the first attempt of partial substitution of the “B”-site of the perovskite to stabilize the α-CsPbI3, which paves the way for further developments of such perovskites and other optoelectronic devices.

MemNet: A Persistent Memory Network for Image Restoration

Abstract: Recently, very deep convolutional neural networks (CNNs) have been attracting considerable attention in image restoration. However, as the depth grows, the long-term dependency problem is rarely realized for these very deep models, which results in the prior states/layers having little influence on the subsequent ones. Motivated by the fact that human thoughts have persistency, we propose a very deep persistent memory network (MemNet) that introduces a memory block, consisting of a recursive unit and a gate unit, to explicitly mine persistent memory through an adaptive learning process. The recursive unit learns multi-level representations of the current state under different receptive fields. The representations and the outputs from the previous memory blocks are concatenated and sent to the gate unit, which adaptively controls how much of the previous states should be reserved, and decides how much of the current state should be stored. We apply MemNet to three image restoration tasks, i.e., image denosing, super-resolution and JPEG deblocking. Comprehensive experiments demonstrate the necessity of the MemNet and its unanimous superiority on all three tasks over the state of the arts. Code is available at this https URL.

High Energy and High Power Lithium‐Ion Capacitors Based on Boron and Nitrogen Dual‐Doped 3D Carbon Nanofibers as Both Cathode and Anode

Abstract: High energy density at high power density is still a challenge for the current Li-ion capacitors (LICs) due to the mismatch of charge-storage capacity and electrode kinetics between capacitor-type cathode and battery-type anode. In this work, B and N dual-doped 3D porous carbon nanofibers are prepared through a facile method as both capacitor-type cathode and battery-type anode for LICs. The B and N dual doping has profound effect in tuning the porosity, functional groups, and electrical conductivity for the porous carbon nanofibers. With rational design, the developed B and N dual-doped carbon nanofibers (BNC) exhibit greatly improved electrochemical performance as both cathode and anode for LICs, which greatly alleviates the mismatch between the two electrodes. For the first time, a 4.5 V “dual carbon” BNC//BNC LIC device is constructed and demonstrated, exhibiting outstanding energy density and power capability compared to previously reported LICs with other configurations. In specific, the present BNC//BNC LIC device can deliver a large energy density of 220 W h kg−1 and a high power density of 22.5 kW kg−1 (at 104 W h kg−1) with reasonably good cycling stability (≈81% retention after 5000 cycles).

Synthesis and characterization of the pentazolate anion cyclo-N5ˉ in (N5)6(H3O)3(NH4)4Cl

Abstract: The flip side of the robust stability of N2 is the instability of any larger molecules composed exclusively of nitrogen. These molecules nonetheless remain enticing targets for explosive and propellant applications. Zhang et al. successfully prepared the pentazolate ion, a negatively charged ring of five nitrogens, by oxidative cleavage of a C–N bond in an aryl-substituted precursor (see the Perspective by Christe). The molecule was stabilized and isolated in the solid state as a hydrated ammonium chloride salt. Spectroscopic and crystallographic characterization confirmed the ring's planar geometry. Science , this issue p. [374][1]; see also p. [351][2] [1]: /lookup/doi/10.1126/science.aah3840 [2]: /lookup/doi/10.1126/science.aal5057

One step synthesis of oxygen doped porous graphitic carbon nitride with remarkable improvement of photo-oxidation activity: Role of oxygen on visible light photocatalytic activity

Abstract: A novel metal-free oxygen doped porous graphitic carbon nitride (OA-g-C3N4) was synthesized by condensation of oxalic acid and urea. The 40% OA-g-C3N4 catalyst can degrade bisphenol A (15 mg L−1) in 240 min with a mineralization rate as high as 56%. The markedly higher visible-light-driven oxidation activity of OA-g-C3N4 is attributed to the porous morphology and unique electrical structure. The porous structure of OA-g-C3N4 provides more active sites for adsorption and degradation of pollutants. Moreover, oxygen atoms in the tri-s-triazine units help to extend sufficient light absorption range up to 700 nm, improve the separation of charge-carriers and alter the position of valence band (VB) and conduction band (CB). The VB edge shifts from 1.95 eV to 2.46 eV due to the incorporation of O atoms, which leads to the change of active species in the photocatalytic reaction. Trapping experiment shows that superoxide radicals play the major role in the photocatalytic degradation of BPA on g-C3N4, while hydroxyl radical is the dominant active species in the photocatalytic degradation process over 40% OA-g-C3N4. This study presents a simple, economical and environment-friendly method to synthesized oxygen doped porous graphitic carbon nitride.

Cobalt Sulfide Quantum Dot Embedded N/S-Doped Carbon Nanosheets with Superior Reversibility and Rate Capability for Sodium-Ion Batteries

Abstract: Metal sulfides are promising anode materials for sodium-ion batteries due to their large specific capacities. The practical applications of metal sulfides in sodium-ion batteries, however, are still limited due to their large volume expansion, poor cycling stability, and sluggish electrode kinetics. In this work, a two-dimensional heterostructure of CoSx (CoS and Co9S8) quantum dots embedded N/S-doped carbon nanosheets (CoSx@NSC) is prepared by a sol–gel method. The CoSx quantum dots are in situ formed within ultrafine carbon nanosheets without further sulfidation, thus resulting in ultrafine CoSx particle size and embedded heterostructure. Meanwhile, enriched N and S codoping in the carbon nanosheets greatly enhances the electrical conductivity for the conductive matrix and creates more active sites for sodium storage. As a result, the hybrid CoSx@NSC electrode shows excellent rate capability (600 mAh g–1 at 0.2 A g–1 and 500 mAh g–1 at 10 A g–1) and outstanding cycling stability (87% capacity retention ...

A Perovskite Nanorod as Bifunctional Electrocatalyst for Overall Water Splitting

Abstract: The development of highly efficient and low-cost electrocatalysts for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) is paramount for water splitting associated with the storage of clean and renewable energy. Here, this study reports its findings in the development of a nanostructured perovskite oxide as OER/HER bifunctional electrocatalyst for overall water splitting. Prepared by a facile electrospinning method, SrNb0.1Co0.7Fe0.2O3- perovskite nanorods (SNCF-NRs) display excellent OER and HER activity and stability in an alkaline solution, benefiting from the catalytic nature of perovskites and unique structural features. More importantly, the SNCF-NR delivers a current density of 10 mA cm(-2) at a cell voltage of merely approximate to 1.68 V while maintaining remarkable durability when used as both anodic and cathodic catalysts in an alkaline water electrolyzer. The performance of this bifunctional perovskite material is among the best ever reported for overall water splitting, offering a cost-effective alternative to noble metal based electrocatalysts.

Recent Breakthroughs in Supercapacitors Boosted by Nitrogen-Rich Porous Carbon Materials

Abstract: Featured with unique mechanical, electronic and chemical properties, nitrogen-doped carbon materials have become the research hotspot of energy storage. As electrode materials in supercapacitors (SCs), N-doped carbons have demonstrated intriguing flexibility and superb performances in a wide electrochemical window, equipped with versatile properties as both cathodes and anodes for constructing high voltage devices. Compared with limited doping level, N-rich and porous carbon materials (NPCs) are of great desire to release the restricted properties of N species and obtain high specific capacitances (>600 F g−1), pushing the energy density towards the battery level without scarifying the capacitor-level power ability. In this Research News we firstly discuss the key factors influencing the performance of NPC electrodes to disclose related charge storage mechanisms. In addition, the trade-off among N-content, porous structure and electrical conductivity is involved as well as electrochemical behaviors in different electrolytes. Also, various progressive developments are highlighted systematically ranging from asymmetric to symmetric and hybrid configurations, covering both aqueous and non-aqueous systems. Finally, some stubborn and unsolved problems are summarized, with prospective research guidelines on NPC-based SCs.

Fe2O3 Nanoneedles on Ultrafine Nickel Nanotube Arrays as Efficient Anode for High-Performance Asymmetric Supercapacitors

Abstract: High performance of electrochemical energy storage devices depends on the smart structure engineering of electrodes, including the tailored nanoarchitectures of current collectors and subtle hybridization of active materials. To improve the anode supercapacitive performance of Fe2O3 for high-voltage asymmetric supercapacitors, here, a hybrid core-branch nanoarchitecture is proposed by integrating Fe2O3 nanoneedles on ultrafine Ni nanotube arrays (NiNTAs@Fe2O3 nanoneedles). The fabrication process employs a bottom-up strategy via a modified template-assisted method starting from ultrafine ZnO nanorod arrays, ensuring the formation of ultrafine Ni nanotube arrays with ultrathin tube walls. The novel developed NiNTAs@Fe2O3 nanoneedle electrode is demonstrated to be a highly capacitive anode (418.7 F g−1 at 10 mV s−1), matching well with the similarly built NiNTAs@MnO2 nanosheet cathode. Contributed by the efficient electron collection paths and short ion diffusion paths in the uniquely designed anode and cathode, the asymmetric supercapacitors exhibit an excellent maximum energy density of 34.1 Wh kg−1 at the power density of 3197.7 W kg−1 in aqueous electrolyte and 32.2 Wh kg−1 at the power density of 3199.5 W kg−1 in quasi-solid-state gel electrolyte.

A series of energetic metal pentazolate hydrates

Abstract: Metal complexes of the pentazole anion exhibit multiple coordination modes, through ionic, covalent and hydrogen-bonding interactions, and good thermal stability with onset decomposition temperatures greater than 100 °C. Polynitrogen compounds can decompose to N2 with an extraordinarily large energy release, which makes them promising candidate materials for explosives but difficult to produce in a stable form. Compounds containing five-membered all-nitrogen rings have attracted particular interest in the search for a stable polynitrogen molecule. Yuangang Xu et al. report five metal complexes containing the pentazole anion, cyclo--N5−, four of which exhibit good thermal stability and a range of different bonding interactions for stabilization. Given their energetic properties and stability, and the adaptability of the cyclo-N5− species in terms of its bonding interactions, these complexes might lead to the development of a new class of high-energy-density materials and of other unusual polynitrogen complexes. Singly or doubly bonded polynitrogen compounds can decompose to dinitrogen (N2) with an extremely large energy release. This makes them attractive as potential explosives or propellants1,2,3, but also challenging to produce in a stable form. Polynitrogen materials containing nitrogen as the only element exist in the form of high-pressure polymeric phases4,5,6, but under ambient conditions even metastability is realized only in the presence of other elements that provide stabilization. An early example is the molecule phenylpentazole, with a five-membered all-nitrogen ring, which was first reported in the 1900s7 and characterized in the 1950s8,9. Salts containing the azide anion (N3−)10,11,12 or pentazenium cation (N5+)13 are also known, with compounds containing the pentazole anion, cyclo-N5−, a more recent addition14,15,16. Very recently, a bulk material containing this species was reported17 and then used to prepare the first example of a solid-state metal–N5 complex18. Here we report the synthesis and characterization of five metal pentazolate hydrate complexes [Na(H2O)(N5)]·2H2O, [M(H2O)4(N5)2]·4H2O (M = Mn, Fe and Co) and [Mg(H2O)6(N5)2]·4H2O that, with the exception of the Co complex, exhibit good thermal stability with onset decomposition temperatures greater than 100 °C. For this series we find that the N5− ion can coordinate to the metal cation through either ionic or covalent interactions, and is stabilized through hydrogen-bonding interactions with water. Given their energetic properties and stability, pentazole–metal complexes might potentially serve as a new class of high-energy density materials19 or enable the development of such materials containing only nitrogen20,21,22,23. We also anticipate that the adaptability of the N5− ion in terms of its bonding interactions will enable the exploration of inorganic nitrogen analogues of metallocenes24 and other unusual polynitrogen complexes.