Enabling heterogeneous catalysis to achieve carbon neutrality: Directional catalytic conversion of CO_(2) into carboxylic acids

The increase in anthropogenic carbon dioxide(CO_(2))emissions has exacerbated the deterioration of the global environment,which should be controlled to achieve carbon neutrality.Central to the core goal of achieving carbon neutrality is the utilization of CO_(2) under economic and sustainable conditions.Recently,the strong need for carbon neutrality has led to a proliferation of studies on the direct conversion of CO_(2) into carboxylic acids,which can effectively alleviate CO_(2) emissions and create high-value chemicals.The purpose of this review is to present the application prospects of carboxylic acids and the basic principles of CO_(2) conversion into carboxylic acids through photo-,electric-,and thermal catalysis.Special attention is focused on the regulation strategy of the activity of abundant catalysts at the molecular level,inspiring the preparation of high-performance catalysts.In addition,theoretical calculations,advanced technologies,and numerous typical examples are introduced to elaborate on the corresponding process and influencing factors of catalytic activity.Finally,challenges and prospects are provided for the future development of this field.It is hoped that this review will contribute to a deeper understanding of the conversion of CO_(2) into carboxylic acids and inspire more innovative breakthroughs.

Pathologically successful conversion hepatectomy for advanced giant hepatocellular carcinoma after multidisciplinary therapy:A case report and review of literature

BACKGROUND Hepatocellular carcinoma(HCC)is one of the leading causes of death due to its complexity,heterogeneity,rapid metastasis and easy recurrence after surgical resection.We demonstrated that combination therapy with transcatheter arterial chemoembolization(TACE),hepatic arterial infusion chemotherapy(HAIC),Epclusa,Lenvatinib and Sintilimab is useful for patients with advanced HCC.CASE SUMMARY A 69-year-old man who was infected with hepatitis C virus(HCV)30 years previously was admitted to the hospital with abdominal pain.Enhanced computed tomography(CT)revealed a low-density mass in the right lobe of the liver,with a volume of 12.9 cm×9.4 cm×15 cm,and the mass exhibited a“fast-in/fast-out”pattern,with extensive filling defect areas in the right branch of the portal vein and an alpha-fetoprotein level as high as 657 ng/mL.Therefore,he was judged to have advanced HCC.During treatment,the patient received three months of Epclusa,three TACE treatments,two HAIC treatments,three courses of sintilimab,and twenty-one months of lenvatinib.In the third month of treatment,the patient developed severe side effects and had to stop immunotherapy,and the Lenvatinib dose had to be halved.Postoperative pathological diagnosis indicated a complete response.The patient recovered well after the operation,and no tumor recurrence was found.CONCLUSION Multidisciplinary conversion therapy for advanced enormous HCC caused by HCV infection has a significant effect.Individualized drug adjustments should be made during any treatment according to the patient's tolerance to treatment.

Two-photon live imaging of direct glia-to-neuron conversion in the mouse cortex

Over the past decade,a growing number of studies have reported transcription factor-based in situ reprogramming that can directly conve rt endogenous glial cells into functional neurons as an alternative approach for n euro regeneration in the adult mammalian central ne rvous system.Howeve r,many questions remain regarding how a terminally differentiated glial cell can transform into a delicate neuron that forms part of the intricate brain circuitry.In addition,concerns have recently been raised around the absence of astrocyte-to-neuron conversion in astrocytic lineage-tra cing mice.In this study,we employed repetitive two-photon imaging to continuously capture the in situ astrocyte-to-neuron conversion process following ecto pic expression of the neural transcription factor NeuroD1 in both prolife rating reactive astrocytes and lineage-tra ced astrocytes in the mouse cortex.Time-lapse imaging over several wee ks revealed the ste p-by-step transition from a typical astrocyte with numero us short,tapered branches to a typical neuro n with a few long neurites and dynamic growth cones that actively explored the local environment.In addition,these lineage-converting cells were able to migrate ra dially or to ngentially to relocate to suitable positions.Furthermore,two-photon Ca2+imaging and patch-clamp recordings confirmed that the newly generated neuro ns exhibited synchronous calcium signals,repetitive action potentials,and spontaneous synaptic responses,suggesting that they had made functional synaptic connections within local neural circuits.In conclusion,we directly visualized the step-by-step lineage conversion process from astrocytes to functional neurons in vivo and unambiguously demonstrated that adult mammalian brains are highly plastic with respect to their potential for neuro regeneration and neural circuit reconstruction.

Dealuminated Hβ zeolite for selective conversion of fructose to furfural and formic acid

The fructose-to-furfural transformation is facing major challenges in the selectivity and high efficiency. Herein, we have developed a simple and effective approach for the selective conversion of fructose to furfural using Hβ zeolite modified by organic acids for dealuminization to regulate its textural and acidic properties. It was found that citric acid-dealuminized Hβ zeolite possessed high specific surface areas, wide channels and high Brønsted acid amount, which facilitated the selective conversion of fructose to furfural with a maximum yield of 76.2% at433 K for 1 h in the γ-butyrolactone(GBL)-H_(2)O system, as well as the concomitant formation of 83.0% formic acid. The^(13)C-isotope labelling experiments and the mechanism revealed that the selective cleavage of C1–C2 or C5–C6 bond on fructose was firstly occurred to form pentose or C5 intermediate by weak Brønsted acid, which was then dehydrated to furfural by strong Brønsted acid. Also this dealuminized Hβ catalyst showed the great recycling performance and was active for the conversion of glucose and mannose.

Oxygen functionalization-assisted anionic exchange toward unique construction of flower-like transition metal chalcogenide embedded carbon fabric for ultra-long life flexible energy storage and conversion

The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.

Reversible solid-liquid conversion enabled by self-capture effect for stable non-flow zinc-bromine batteries

Non-flow aqueous zinc-bromine batteries without auxiliary components(e.g.,pumps,pipes,storage tanks)and ion-selective membranes represent a cost-effective and promising technology for large-scale energy storage.Unfortunately,they generally suffer from serious diffusion and shuttle of polybromide(Br^(-),Br^(3-))due to the weak physical adsorption between soluble polybromide and host carbon materials,which results in low energy efficiency and poor cycling stability.Here,we develop a novel self-capture organic bromine material(1,10-bis[3-(trimethylammonio)propyl]-4,4'-bipyridinium bromine,NVBr4)to successfully realize reversible solid complexation of bromide components for stable non-flow zinc-bromine battery applications.The quaternary ammonium groups(NV^(4+)ions)can effectively capture the soluble polybromide species based on strong chemical interaction and realize reversible solid complexation confined within the porous electrodes,which transforms the conventional“liquid-liquid”conversion of soluble bromide components into“liquid-solid”model and effectively suppresses the shuttle effect.Thereby,the developed non-flow zinc-bromide battery provides an outstanding voltage platform at 1.7 V with a notable specific capacity of 325 mAh g^(-1)NVBr4(1 A g^(-1)),excellent rate capability(200 mAh g^(-1)NVBr4 at 20 A g^(-1)),outstanding energy density of 469.6 Wh kg^(-1)and super-stable cycle life(20,000 cycles with 100%Coulombic efficiency),which outperforms most of reported zinc-halogen batteries.Further mechanism analysis and DFT calculations demonstrate that the chemical interaction of quaternary ammonium groups and bromide species is the main reason for suppressing the shuttle effect.The developed strategy can be extended to other halogen batteries to obtain stable charge storage.

Conversion therapy of a giant hepatocellular carcinoma with portal vein thrombus and inferior vena cava thrombus:A case report and review of literature

BACKGROUND The prognosis of hepatocellular carcinoma(HCC)combined with portal and hepatic vein cancerous thrombosis is poor,for unresectable patients the combination of targeted therapy and immune therapy was the first-line recommended treatment for advanced HCC,with a median survival time of only about 2.7-6 months.In this case report,we present the case of a patient with portal and hepatic vein cancerous thrombosis who achieved pathologic complete response after conversion therapy.CASE SUMMARY In our center,a patient with giant HCC combined with portal vein tumor thrombus and hepatic vein tumor thrombus was treated with transcatheter arterial chemoembolization(TACE),radiotherapy,targeted therapy and immunotherapy,and was continuously given icaritin soft capsules for oral regulation.After 7 months of conversion therapy,the patient's tumor shrank and the tumor thrombus subsided significantly.The pathology of surgical resection was in complete remission,and there was no progression in the postoperative follow-up for 7 months,which provided a basis for the future strategy of combined conversion therapy.CONCLUSION In this case,atezolizumab,bevacizumab,icaritin soft capsules combined with radiotherapy and TACE had a good effect.For patients with hepatocellular carcinoma combined with hepatic vein/inferior vena cava tumor thrombus,adopting a high-intensity,multimodal proactive strategy under the guidance of multidisciplinary team(MDT)is an important attempt to break through the current treatment dilemma.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Epidemic Characteristics and Spatio-Temporal Patterns of HFRS in Qingdao City,China,2010-2022

Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.

Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting

Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.

Ultra-broadband and wide-angle reflective terahertz polarization conversion metasurface based on topological optimization

Terahertz polarization conversion devices have significant potential applications in various fields such as terahertzimaging and spectroscopy.In this paper,we utilize genetic algorithms to topologically optimize the metasurface unit cellsand design a reflective linear polarization conversion metasurface with ultra-broadband and wide-angle characteristics.By partitioning the metallic pattern layer into quadrants,the encoding length is effectively reduced,resulting in a shorteroptimization time.The research results indicate that the converter possesses a polarization conversion efficiency ratio higherthan 90%and a relative bandwidth ratio of 125%in a range of 0.231-0.995 THz.Meanwhile,it can maintain excellentpolarization conversion properties when the incident angle of terahertz waves is less than 45°and the polarization angle isless than 15°,demonstrating excellent practicality.New insights are provided for the design of terahertz wide-angle ultrawidebandpolarization conversion devices,and the proposed metasurfce has potential applications in terahertz polarizationimaging,spectroscopy and communication fields.

An Intelligent Framework for Resilience Recovery of FANETs with Spatio-Temporal Aggregation and Multi-Head Attention Mechanism

Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution.

1.42-fold enhancement of formate selectivity by linker conversion on the Zn-based metal organic framework catalyst

Electro-reduction of carbon dioxide(ERCO_(2)) is considered an effective method to alleviate the greenhouse effect and produce value-added chemicals.Achieving the dominant selectivity of Zn-based catalysts for formate remains a challenge.In this article,the ZnIn-E_(12) catalyst is successfully prepared by solvent assisted ligand exchange(SALE) method to convert organic ligands,achieving a Faradaic efficiency of 72.28% for formate at-1.26 V vs.RHE(V_(RHE)),which is 1.42 times higher than the original catalyst.Evidence shows that the successful conversion of organic ligands can transform the catalyst from the original large size polyhedron to cross-linked network of particles with a diameter of about 30 nm.The increased specific surface area can expose more active sites and facilitate the electrocatalytic conversion of CO_(2) to formate.This work is expected to provide inspiration for the regulation of formate selectivity and catalyst size in Zn-based catalysts.

Warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography

High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.

Intrinsic polarization conversion and avoided-mode crossing in X-cut lithium niobate microrings

Compared with well-developed free space polarization converters, polarization conversion between TE and TM modes in the waveguide is generally considered to be caused by shape birefringence, like curvature, morphology of waveguide cross section and scattering. Here, we study the polarization conversion mechanism in 1-THz-FSR X-cut lithium niobate microrings with multiple-resonance condition, that is the conversion can be implemented by birefringence of waveguides,which will also introduce an avoided-mode crossing. In the experiment, we find that this mode crossing results in severe suppression of one sideband in local nondegenerate four-wave mixing and disrupts the cascaded four-wave mixing on this side. Simultaneously, we propose one two-dimensional method to simulate the eigenmodes(TE and TM) in X-cut microrings, and the mode crossing point. This work will provide one approach to the design of polarization converters and simulation for monolithic photonics integrated circuits, and may be helpful to the studies of missed temporal dissipative soliton formation in X-cut lithium niobate rings.

Hollow Metal-Organic Framework/MXene/Nanocellulose Composite Films for Giga/Terahertz Electromagnetic Shielding and Photothermal Conversion

With the continuous advancement of communication technology,the escalating demand for electromagnetic shielding interference(EMI)materials with multifunctional and wideband EMI performance has become urgent.Controlling the electrical and magnetic components and designing the EMI material structure have attracted extensive interest,but remain a huge challenge.Herein,we reported the alternating electromagnetic structure composite films composed of hollow metal-organic frameworks/layered MXene/nanocellulose(HMN)by alternating vacuum-assisted filtration process.The HMN composite films exhibit excellent EMI shielding effectiveness performance in the GHz frequency(66.8 dB at Kaband)and THz frequency(114.6 dB at 0.1-4.0 THz).Besides,the HMN composite films also exhibit a high reflection loss of 39.7 dB at 0.7 THz with an effective absorption bandwidth up to 2.1 THz.Moreover,HMN composite films show remarkable photothermal conversion performance,which can reach 104.6℃under 2.0 Sun and 235.4℃under 0.8 W cm^(−2),respectively.The unique micro-and macrostructural design structures will absorb more incident electromagnetic waves via interfacial polarization/multiple scattering and produce more heat energy via the local surface plasmon resonance effect.These features make the HMN composite film a promising candidate for advanced EMI devices for future 6G communication and the protection of electronic equipment in cold environments.

A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion

To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.

Self-Attention Spatio-Temporal Deep Collaborative Network for Robust FDIA Detection in Smart Grids

False data injection attack(FDIA)can affect the state estimation of the power grid by tampering with the measured value of the power grid data,and then destroying the stable operation of the smart grid.Existing work usually trains a detection model by fusing the data-driven features from diverse power data streams.Data-driven features,however,cannot effectively capture the differences between noisy data and attack samples.As a result,slight noise disturbances in the power grid may cause a large number of false detections for FDIA attacks.To address this problem,this paper designs a deep collaborative self-attention network to achieve robust FDIA detection,in which the spatio-temporal features of cascaded FDIA attacks are fully integrated.Firstly,a high-order Chebyshev polynomials-based graph convolution module is designed to effectively aggregate the spatio information between grid nodes,and the spatial self-attention mechanism is involved to dynamically assign attention weights to each node,which guides the network to pay more attention to the node information that is conducive to FDIA detection.Furthermore,the bi-directional Long Short-Term Memory(LSTM)network is introduced to conduct time series modeling and long-term dependence analysis for power grid data and utilizes the temporal selfattention mechanism to describe the time correlation of data and assign different weights to different time steps.Our designed deep collaborative network can effectively mine subtle perturbations from spatiotemporal feature information,efficiently distinguish power grid noise from FDIA attacks,and adapt to diverse attack intensities.Extensive experiments demonstrate that our method can obtain an efficient detection performance over actual load data from New York Independent System Operator(NYISO)in IEEE 14,IEEE 39,and IEEE 118 bus systems,and outperforms state-of-the-art FDIA detection schemes in terms of detection accuracy and robustness.

Electronic structure engineering of transition metal dichalcogenides for boosting hydrogen energy conversion electrocatalysts

Electrocatalytic water splitting for hydrogen production is an appealing strategy to reduce carbon emissions and generate renewable fuels.This promising process,however,is limited by its sluggish reaction kinetics and high-cost catalysts.The two-dimensional(2D)transition metal dichalcogenides(TMDCs)have presented great potential as electrocatalytic materials due to their tunable bandgaps,abundant defective active sites,and good chemical stability.Consequently,phase engineering,defect engineering and interface engineering have been adopted to manipulate the electronic structure of TMDCs for boosting their exceptional catalytic performance.Particularly,it is essential to clarify the local structure of catalytically active sites of TMDCs and their structural evolution in catalytic reactions using atomic resolution electron microscopy and the booming in situ technologies,which is beneficial for exploring the underlying reaction mechanism.In this review,the growth regulation,characterization,particularly atomic configurations of active sites in TMDCs are summarized.The significant role of electron microscopy in the understanding of the growth mechanism,the controlled synthesis and functional optimization of 2D TMDCs are discussed.This review will shed light on the design and synthesis of novel electrocatalysts with high performance,as well as prompt the application of advanced electron microscopy in the research of materials science.

Insight into structure evolution of carbon nitrides and its energy conversion as luminescence

A series of carbon nitride(CN)materials represented by graphitic carbon nitride(g-C_(3)N_(4))have been widely used in bioimaging,biosensing,and other fields in recent years due to their nontoxicity,low cost,and high luminescent quantum efficiency.What is more attractive is that the luminescent properties such as wavelength and intensity can be regulated by controlling the structure at the molecular level.Hence,it is time to summarize the related research on CN structural evolution and make a prospect on future developments.In this review,we first summarize the research history and multiple structural evolution of CN.Then,the progress of improving the luminescence performance of CN through structural evolution was discussed.Significantly,the relationship between CN structure evolution and energy conversion in the forms of photoluminescence,chemiluminescence,and electrochemiluminescence was reviewed.Finally,key challenges and opportunities such as nanoscale dispersion strategy,luminous efficiency improving methods,standardization evaluation,and macroscopic preparation of CN are highlighted.