Abstract:Nitrogen-rich energetic compounds have received a lot of attention in the research fields of propellants， explosives and gas generant thanks to their high enthalpy of formation and clean decomposition products. However， as a significant branch of nitrogen-rich energetic materials， research and development on the compounds with all-nitrogen and chain-like nitrogen structures are hampered by the lack of suitable nitrogen sources and efficient synthetic methods for the construction of nitrogen chain backbone. In this review， the design ideas， synthetic methods， and breakthrough progress of all-nitrogen ionic energetic compounds and long nitrogen chains energetic materials containing at least six nitrogen atoms linked together are systematically analyzed， and the references for the design and development of milestone high energy density materials are offered.

Abstract:To enhance the photothermal response of hexanitrostilbene （HNS） under laser initiation， a core-shell composite（HNS@PDI） was prepared by a combining strategy of molecular structure regulation and self-assembly surface deposition method， and the influence of the molecular structure of PDI on its photothermal conversion efficiency and the laser ignition performance of HNS@PDI were systematically studied. The perylene imide （PDI-C12） modified with a dodecyl chain can easily assemble into a J-stacking structure that is conducive to non-radiative exciton transitions. Under 1064 nm laser irradiation， the composite modified with PDI-C12 exhibits a photothermal conversion efficiency of 69.3%， which is 110% higher than that of the short-chain analog PDI-C2（32.9%）. When the PDI loading was optimized to 5%， the laser ignition delay time was reduced to 22 ms at a laser power of 10 W and energy density of 80 W·cm^-2. The PDI shell also significantly improves the safety performance of this composite. The critical impact energy of the composite increases from 5 J to 30 J， and the critical friction force is above 360 N. In addition， the PDI layer effectively inhibits photodecomposition. This study effectively improved the laser ignition performance of HNS， while enhanced the safety and photostability， providing new ideas for the development of high-performance laser ignition agents and photosensitizers.

Abstract:To enable comprehensive prediction of typical fuze cook-off processes and address the challenge of quantifying output pressure， an advanced strain-gage pressure bar sensor was utilized for dynamic pressure acquisition during experimental investigations. A comprehensive coupled numerical framework was developed， integrating heat transfer models， Arrhenius reaction kinetics， and ignition response mechanisms， to systematically analyze the cook-off behavior and generate detailed pressure profiles of booster explosives. The kinetic parameters， such as activation energy and pre-exponential factors， were inversely determined through the application of a Back Propagation （BP） neural network. Meanwhile， the state parameters that govern the ignition reaction equation were optimized using a multi-island genetic algorithm. Coupled simulations utilizing ANSYS Fluent and LS-DYNA within the Workbench platform were performed to numerically investigate the cook-off response under different heating rates. This approach enables comprehensive full-process characterization from thermal reaction to ignition. The results indicate that slower heating rates shift the ignition zone toward the central region of the charge， thereby intensifying the severity of the reaction.

Abstract:In this study， to gain deeper insight into the combustion characteristics of single-base propellant， a multi-parameter measurement system based on laser diffuse reflection spectroscopy was developed. This system was employed to measure the combustion parameters of both single-base and double-base propellants. As a result， the combustion spectra and burning rates of both propellant types were successfully obtained. The experimental results revealed that within the 250-500 nm wavelengh range， emission peaks of OH*（313.9 nm）， CO₂*（462.3 nm）， and CHO*（421.7 nm） were observed， attributed to the active intermediates generated during single-base propellant combustion. Meanwhile， in the 500-780 nm range， distinct emission peaks of Na*（588.7 nm）， K*（766.8 nm）， and Ca*（554.6 nm） were detected， analyzed to originate from residual lignin in nitrocellulose. Compared with the burning velocity measurement results from the image and target line methods， the laser diffuse reflection spectroscopy method showed consistent results， with maximum relative errors of 4.17% and 9.97%. Furthermore， the results from double-base propellant combustion parameter measurements indicated that this method is also applicable for the simultaneous measurement of combustion velocity and spectra of double-base propellants. The developed method possesses feasibility and versatility， enabling non-contact and non-destructive measurement of propellant burning velocity.

Abstract:A comprehensive analysis platform of ReaxMDDB-EMs was developed for investigation of thermolysis reaction mechanisms across varied energetic compounds. An automatic data import program was implemented with a combined strategy of preprocessing and batch-import to solve the problem of unacceptable long time for dealing with massive data. Performance testing of the automatic data import program shows a 18-fold speed-up， which dramatically reduces the time to 26.8 hours for importing large volume reaction data set over one million species or reactions. The hierarchical functions developed for reaction analysis enable the unified retrieval， statistical analysis， and visualization of the massive reaction data collected in ReaxMDDB-EMs. The application of ReaxMDDB-EMs unravels the similarities and differences among the thermolysis of four nitramine energetic compounds， which indicates that the ReaxMDDB-EMs as a convenient tool allows for a comprehensive analysis of reaction mechanism within vast chemical space of thermolysis for energetic materials. This work provides an efficient tool for the new research paradigm of data-driven design of energetic materials on-demand in the big-data era.

Abstract:To enhance the understanding of safety of multi-chamber mixing processes， a multiphase flow CFD numerical model based on the Eulerian method was established for the continuous mixing of multi-component materials in a multi-chamber kneader， taking a cast polymer bonded explosive （PBX） as the object. Experimental verification was conducted to confirm the reliability of the model. Based on the model， the influence laws of key process and structural parameters including blade rotation speed， kneading clearance and blade profile on the mixing safety stimulus were studied. The results show that the pressure level gradually decreased from the feeding chamber to the discharging chamber. Increasing the blade rotation speed was beneficial for reducing the pressure in the chambers， but the shear stimulus significantly increased. As the blade rotation speed increased from 15 r·min^-1 to 75 r·min^-1， the peak pressure in the kneader decreased from 402966 Pa to 258107 Pa， and the peak shear stress increased from 6268.5 Pa to 16607.9 Pa. Increasing the kneading clearance significantly reduced the pressure and shear stress in the chambers. As the kneading clearance increased from 1 mm to 5 mm， the peak pressure in the kneader decreased from 391094 Pa to 284478 Pa， and the peak shear stress decreases from 8320.5 Pa to 3982.6 Pa. Compared with the two-wing-two-wing blades， four-wing-two-wing blades produced stronger shear stimulus due to more kneading sites， but the blade profile had a smaller impact on the kneading pressure. When the four-wing-two-wing blades and two-wing-two-wing blades were used in chambers 1-7， the peak shear stresses in the kneader were 7481.3 Pa and 4518.1 Pa， respectively.

Abstract:As an emerging data-driven technology， machine learning provide a promising pathway for the intelligent research and development of energetic materials. However， data scarcity and heterogeneity have become the core bottleneck that restricts modeling accuracy and practical application. Focusing on the acquisition path and the existing of energetic material data， this review evaluates the mainstream data optimization strategies from two perspectives： quantity expansion and quality improvement. For data quantity expansion， recent advances in SMILES enumeration， generative adversarial networks， and transfer learning are introduced for enhancing model generalization ability. For data quality improvement， the roles of outlier detection， standardized preprocessing， and feature engineering in improving model robustness and interpretability are discussed. It is shown that effective data optimization can not only alleviate data limitations but also significantly enhance prediction stability and structural extrapolation capabilities under small-sample and structurally complex conditions. Finally， future directions are proposed， including the development of high-throughput experimental platforms， unification of data standards， and establishment of intelligent closed-loop systems. It is expected to provide a feasible roadmap and methodological reference for advancing the data ecosystem and intelligent design of energetic materials.

Abstract:In order to meet the dual constraint requirements of safety current and anti-electromagnetic radiation power of semiconductor bridge initiating explosive devices， based on GJB 344A-2020" General specification for insensitive electric initiators"： Non-fire test standard， the electro-magnetic-thermal multi-physical field coupling model was constructed on COMSOL Multiphysics platform by numerical simulation method. By integrating the parallel shunt mechanism of negative temperature coefficient （NTC） thermistor， the loop resistance was monitored in real time and the current input was dynamically compensated. The effects of thermal safety under three working conditions of constant current 1A， constant power 1 W and double constraints 1A1W were compared and analyzed. The results show that the power of 1 A constant current condition is only 0.78 W， which deviates from the standard by 22% because the loop resistance is reduced to 0.78 Ω. The initial current of 1W constant power condition is 0.91 A， which is lower than the safety threshold. The dynamic adjustment strategy realizes the coordinated stability of current and power through closed-loop control. The heat balance temperature of the bridge area is controlled at 449.06 K， and the shunt rate is increased from 29% to 41.26% compared with the 1A constant current condition， and the shunt rate is increased by 0.6% compared with the 1W constant power condition.

Abstract:The combustion process of energetic materials （EMs） is a complex multi-stage process. By studying their thermal decomposition and combustion reactions， establishing precise combustion reaction kinetics models enables effective prediction of the thermal behavior of EMs， which is of significant importance for their synthesis， production， transportation， storage， and practical application in modern weaponry and equipment. Compared to traditional EMs， third-generation EMs exhibit higher energy density， which imposes more stringent requirements on their thermal stability. This review summarizes recent advances in thermal properties and combustion research of third-generation EMs， including both ionic and covalent types. The current research status on thermal properties and combustion reactions of typical third-generation EMs is expounded from three perspectives： thermal decomposition profiles， decomposition pathways/mechanism， and combustion performance. It identifies the shortcomings of the current research and proposes the research direction of the thermal behavior of the third-generation energetic materials. It is proposed to construct a multi-scale coupled research system： high-precision measurement of combustion parameters via novel experimental apparatus， accurate diagnosis of combustion intermediates， and cross-scale modeling combining quantum chemistry-machine learning-fluid mechanics to achieve full-chain analysis from free-radical mechanisms to macroscopic flame propagation.

Abstract:Aiming at the reliability evaluation of the energy transfer interface of pyrotechnic sequence， a reliability evaluation method based on fiducial inference method was proposed. This method fully considered the randomness characteristics of the energy transfer interface data. By constructing the probability distribution model of the performance parameters， the prior knowledge was organically combined with the test data， and the accurate evaluation and randomness quantification of the interface reliability were realized. Firstly， the reliability model of the energy transfer interface of pyrotechnic sequence was established. On this basis， the reliability evaluation algorithm framework based on fiducial inference was designed. In order to verify the effectiveness of the proposed method， the evaluation results of the quantile correction method and the Monte Carlo method were compared and analyzed. The results show that when the sample size is 3 to 70， the deviation between the evaluation results based on the fiducial inference method and the true value is the smallest， demonstrating good convergence and stability. Especially when the sample size is less than or equal to 10， this method shows significant advantages， which effectively overcomes the dependence of traditional methods on sample amount， and provides a new method for the reliability evaluation of the energy transfer interface of pyrotechnic sequences.