Laser-sensitive primary explosives(LSPEs)have long been a focus of attention as the material foundation for safer and more efficient laser-initiation technology.However,LSPEs often have poor safety due to their struct...Laser-sensitive primary explosives(LSPEs)have long been a focus of attention as the material foundation for safer and more efficient laser-initiation technology.However,LSPEs often have poor safety due to their structural characteristics,which greatly limits the development and application of laser initiating technology.In this work,we introduced the concept of multidentate chelates into LSPEs and innovatively propose the concept of energetic quadridentate chelates.To achieve this highly creative idea,we synthesized an energetic flexible chelating ligand,namely,1,2-bis(3-nitroamino-1,2,4-triazol-5-yl)ethane(BNATE),and prepared a novel metal quadridentate chelate,namely,[Cu(BNATE)·2H_(2)O](1),by chelating it with Cu^(2+).Through a series of tests,including X-ray single-crystal diffraction analysis,thermogravimetric analysis,and differential scanning calorimetry(TG-DSC),and evaluation of the safety and detonation performance,it was proven that this compound adhered to the high stability characteristics of the chelate,and its safety and detonation performance were superior to previous LSPEs.Moreover,through laserinitiation experiments,it was determined that the compound had excellent photosensitivity and a lower laser-initiation threshold.To explain the reason why the chelate structure is specifically sensitive to a laser,diffuse reflection ultraviolet and TD-DFT simulations were conducted,which not only demonstrated experimentally that chelation had a good enhancement effect on the laser photosensitivity but also confirmed the mode of electron transfer in the quadridentate chelate structure.展开更多
Laser-sensitive primary explosives(LSPEs)are crucial material bases of advanced laser initiation technology.Copper azide(CA),a primary explosive with excellent detonation properties,is limited in preparation and appli...Laser-sensitive primary explosives(LSPEs)are crucial material bases of advanced laser initiation technology.Copper azide(CA),a primary explosive with excellent detonation properties,is limited in preparation and application owing to its extremely high sensitivity.Thus,incorporating CA into LSPEs relies on precise desensitisation strategies.This study successfully implemented a strategy involving sensitive-unit molecular-scale encapsulation.A 2D energetic metal–organic framework(EMOF)[Cu(ATRZ)(N_(3))_(2)]_(n)(CA-ATRZ)(ATRZ=4,4′-azo-1,2,4-triazole)was designed and synthesized via a safe and facile single-crystal-to-single-crystal(SCSC)transformation from a 3D EMOF[Cu(ATRZ)_(3)(NO_(3))_(2)]_(n).Leveraging its distinctive structural attributes of encapsulated confinement,CA-ATRZ is substantially improved in terms of safety compared to CA,while maintaining its superior detonation performance.Furthermore,CA-ATRZ obtained by combining MOFs with CA has outstanding ultrafast direct laser initiation characteristics,is free of toxic metals and perchlorate,has high initiating ability,and has decent thermal stability.This strategy could pave the way for developing advanced high-energy LSPEs.展开更多
Residential heating, ventilation and air conditioning(HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that a...Residential heating, ventilation and air conditioning(HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that adapt to realtime electricity price signals formulated by demand response program and ambient temperature can significantly reduce electricity costs while ensuring occupants' comfort. However, since the pricing process and weather conditions are affected by many factors, conventional model-based method is difficult to meet the scheduling requirements in complex environments. To solve this problem, we propose an adaptive optimal scheduling strategy for residential HVAC based on deep reinforcement learning(DRL) method. The scheduling problem can be regarded as a Markov decision process(MDP). The proposed method can adaptively learn the state transition probability to make economical decision under the tolerance violations. Specifically, the residential thermal parameters obtained by the leastsquares parameter estimation(LSPE) can provide a basis for the state transition probability of MDP. Daily simulations are verified under the electricity prices and temperature data sets, and numerous experimental results demonstrate the effectiveness of the proposed method.展开更多
基金financial support from the National Natural Science Foundation of China(21975232).
文摘Laser-sensitive primary explosives(LSPEs)have long been a focus of attention as the material foundation for safer and more efficient laser-initiation technology.However,LSPEs often have poor safety due to their structural characteristics,which greatly limits the development and application of laser initiating technology.In this work,we introduced the concept of multidentate chelates into LSPEs and innovatively propose the concept of energetic quadridentate chelates.To achieve this highly creative idea,we synthesized an energetic flexible chelating ligand,namely,1,2-bis(3-nitroamino-1,2,4-triazol-5-yl)ethane(BNATE),and prepared a novel metal quadridentate chelate,namely,[Cu(BNATE)·2H_(2)O](1),by chelating it with Cu^(2+).Through a series of tests,including X-ray single-crystal diffraction analysis,thermogravimetric analysis,and differential scanning calorimetry(TG-DSC),and evaluation of the safety and detonation performance,it was proven that this compound adhered to the high stability characteristics of the chelate,and its safety and detonation performance were superior to previous LSPEs.Moreover,through laserinitiation experiments,it was determined that the compound had excellent photosensitivity and a lower laser-initiation threshold.To explain the reason why the chelate structure is specifically sensitive to a laser,diffuse reflection ultraviolet and TD-DFT simulations were conducted,which not only demonstrated experimentally that chelation had a good enhancement effect on the laser photosensitivity but also confirmed the mode of electron transfer in the quadridentate chelate structure.
基金support by the National Natural Science Foundation of China 21975232 is acknowledged(Q.Z.).
文摘Laser-sensitive primary explosives(LSPEs)are crucial material bases of advanced laser initiation technology.Copper azide(CA),a primary explosive with excellent detonation properties,is limited in preparation and application owing to its extremely high sensitivity.Thus,incorporating CA into LSPEs relies on precise desensitisation strategies.This study successfully implemented a strategy involving sensitive-unit molecular-scale encapsulation.A 2D energetic metal–organic framework(EMOF)[Cu(ATRZ)(N_(3))_(2)]_(n)(CA-ATRZ)(ATRZ=4,4′-azo-1,2,4-triazole)was designed and synthesized via a safe and facile single-crystal-to-single-crystal(SCSC)transformation from a 3D EMOF[Cu(ATRZ)_(3)(NO_(3))_(2)]_(n).Leveraging its distinctive structural attributes of encapsulated confinement,CA-ATRZ is substantially improved in terms of safety compared to CA,while maintaining its superior detonation performance.Furthermore,CA-ATRZ obtained by combining MOFs with CA has outstanding ultrafast direct laser initiation characteristics,is free of toxic metals and perchlorate,has high initiating ability,and has decent thermal stability.This strategy could pave the way for developing advanced high-energy LSPEs.
基金supported in part by the Fundamental Research Funds for the Central Universities (No. 2018JBZ004)the National Natural Science Foundation of China (No. 52007004)。
文摘Residential heating, ventilation and air conditioning(HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that adapt to realtime electricity price signals formulated by demand response program and ambient temperature can significantly reduce electricity costs while ensuring occupants' comfort. However, since the pricing process and weather conditions are affected by many factors, conventional model-based method is difficult to meet the scheduling requirements in complex environments. To solve this problem, we propose an adaptive optimal scheduling strategy for residential HVAC based on deep reinforcement learning(DRL) method. The scheduling problem can be regarded as a Markov decision process(MDP). The proposed method can adaptively learn the state transition probability to make economical decision under the tolerance violations. Specifically, the residential thermal parameters obtained by the leastsquares parameter estimation(LSPE) can provide a basis for the state transition probability of MDP. Daily simulations are verified under the electricity prices and temperature data sets, and numerous experimental results demonstrate the effectiveness of the proposed method.
