Silicon-based materials have demonstrated remarkable potential in high-energy-density batteries owing to their high theoretical capacity.However,the significant volume expansion of silicon seriously hinders its utiliz...Silicon-based materials have demonstrated remarkable potential in high-energy-density batteries owing to their high theoretical capacity.However,the significant volume expansion of silicon seriously hinders its utilization as a lithium-ion anode.Herein,a functionalized high-toughness polyimide(PDMI) is synthesized by copolymerizing the 4,4'-Oxydiphthalic anhydride(ODPA) with 4,4'-oxydianiline(ODA),2,3-diaminobenzoic acid(DABA),and 1,3-bis(3-aminopropyl)-tetramethyl disiloxane(DMS).The combination of rigid benzene rings and flexible oxygen groups(-O-) in the PDMI molecular chain via a rigidness/softness coupling mechanism contributes to high toughness.The plentiful polar carboxyl(-COOH) groups establish robust bonding strength.Rapid ionic transport is achieved by incorporating the flexible siloxane segment(Si-O-Si),which imparts high molecular chain motility and augments free volume holes to facilitate lithium-ion transport(9.8 × 10^(-10) cm^(2) s^(-1) vs.16 × 10^(-10) cm^(2) s~(-1)).As expected,the SiO_x@PDMI-1.5 electrode delivers brilliant long-term cycle performance with a remarkable capacity retention of 85% over 500 cycles at 1.3 A g^(-1).The well-designed functionalized polyimide also significantly enhances the electrochemical properties of Si nanoparticles electrode.Meanwhile,the assembled SiO_x@PDMI-1.5/NCM811 full cell delivers a high retention of 80% after 100 cycles.The perspective of the binder design strategy based on polyimide modification delivers a novel path toward high-capacity electrodes for high-energy-density batteries.展开更多
A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as mea...A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.展开更多
To increase airspace capacity, alleviate flight delay,and improve network robustness, an optimization method of multi-layer air transportation networks is put forward based on Laplacian energy maximization. The effect...To increase airspace capacity, alleviate flight delay,and improve network robustness, an optimization method of multi-layer air transportation networks is put forward based on Laplacian energy maximization. The effectiveness of taking Laplacian energy as a measure of network robustness is validated through numerical experiments. The flight routes addition optimization model is proposed with the principle of maximizing Laplacian energy. Three methods including the depth-first search( DFS) algorithm, greedy algorithm and Monte-Carlo tree search( MCTS) algorithm are applied to solve the proposed problem. The trade-off between system performance and computational efficiency is compared through simulation experiments. Finally, a case study on Chinese airport network( CAN) is conducted using the proposed model. Through encapsulating it into multi-layer infrastructure via k-core decomposition algorithm, Laplacian energy maximization for the sub-networks is discussed which can provide a useful tool for the decision-makers to optimize the robustness of the air transportation network on different scales.展开更多
基金supported by the National Natural Science Foundation of China (51673017)the National Natural Science Foundation of China (21404005)+1 种基金the Fundamental Research Funds for the Central Universities (XK1802-2)the Natural Science Foundation of Jiangsu Province (BK20150273)。
文摘Silicon-based materials have demonstrated remarkable potential in high-energy-density batteries owing to their high theoretical capacity.However,the significant volume expansion of silicon seriously hinders its utilization as a lithium-ion anode.Herein,a functionalized high-toughness polyimide(PDMI) is synthesized by copolymerizing the 4,4'-Oxydiphthalic anhydride(ODPA) with 4,4'-oxydianiline(ODA),2,3-diaminobenzoic acid(DABA),and 1,3-bis(3-aminopropyl)-tetramethyl disiloxane(DMS).The combination of rigid benzene rings and flexible oxygen groups(-O-) in the PDMI molecular chain via a rigidness/softness coupling mechanism contributes to high toughness.The plentiful polar carboxyl(-COOH) groups establish robust bonding strength.Rapid ionic transport is achieved by incorporating the flexible siloxane segment(Si-O-Si),which imparts high molecular chain motility and augments free volume holes to facilitate lithium-ion transport(9.8 × 10^(-10) cm^(2) s^(-1) vs.16 × 10^(-10) cm^(2) s~(-1)).As expected,the SiO_x@PDMI-1.5 electrode delivers brilliant long-term cycle performance with a remarkable capacity retention of 85% over 500 cycles at 1.3 A g^(-1).The well-designed functionalized polyimide also significantly enhances the electrochemical properties of Si nanoparticles electrode.Meanwhile,the assembled SiO_x@PDMI-1.5/NCM811 full cell delivers a high retention of 80% after 100 cycles.The perspective of the binder design strategy based on polyimide modification delivers a novel path toward high-capacity electrodes for high-energy-density batteries.
基金Project(71001079)supported by the National Natural Science Foundation of China
文摘A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.
基金The National Natural Science Foundation of China(No.61573098,71401072)the Natural Science Foundation of Jiangsu Province(No.BK20130814)
文摘To increase airspace capacity, alleviate flight delay,and improve network robustness, an optimization method of multi-layer air transportation networks is put forward based on Laplacian energy maximization. The effectiveness of taking Laplacian energy as a measure of network robustness is validated through numerical experiments. The flight routes addition optimization model is proposed with the principle of maximizing Laplacian energy. Three methods including the depth-first search( DFS) algorithm, greedy algorithm and Monte-Carlo tree search( MCTS) algorithm are applied to solve the proposed problem. The trade-off between system performance and computational efficiency is compared through simulation experiments. Finally, a case study on Chinese airport network( CAN) is conducted using the proposed model. Through encapsulating it into multi-layer infrastructure via k-core decomposition algorithm, Laplacian energy maximization for the sub-networks is discussed which can provide a useful tool for the decision-makers to optimize the robustness of the air transportation network on different scales.