The sulfide-based solid-state electrolytes(SEs)reactivity toward moisture and Li-metal are huge barriers that impede their large-scale manufactu ring and applications in all-solid-state lithium batteries(ASSLBs).Herei...The sulfide-based solid-state electrolytes(SEs)reactivity toward moisture and Li-metal are huge barriers that impede their large-scale manufactu ring and applications in all-solid-state lithium batteries(ASSLBs).Herein,we proposed an Al and O dual-doped strategy for Li_(3)PS_(4)SE to regulate the chemical/electrochemical stability of anionic PS_(4)^(3-)tetrahedra to mitigate structural hydrolysis and parasitic reactions at the SE/Li interface.The optimized Li_(3.08)A_(10.04)P_(0.96)S_(3.92)O_(0.08)SE presents the highestσLi+of 3.27 mS cm^(-1),which is~6.8 times higher than the pristine Li_(3)PS_(4)and excellently inhibits the structural hydrolysis for~25 min@25%humidity at RT.DFT calculations confirmed that the enhanced chemical stability was revealed to the intrinsically stable entities,e.g.,POS33-units.Moreover,Li_(3.08)Al_(0.04)P_(0.96)S_(3.92)O_(0.08)SE cycled stably in Li//Li symmetric cell over 1000 h@0.1 mA cm^(-2)/0.1 mA h cm^(-2),could be revealed to Li-Al alloy and Li_(2)Oat SE/Li interface impeding the growth of Li-dendrites during cycling.Resultantly,LNO@LCO/Li_(3.08)Al_(0.04)P_(0.96)S_(3.92)O_(0.08)/Li-In cell delivered initial discharge capacities of 129.8 mA h g^(-1)and 83.74%capacity retention over 300 cycles@0.2 C at RT.Moreover,the Li_(3.08)Al_(0.04)P_(0.96)S_(3.92)O_(0.08)SE presented>90%capacity retention over 200 and 300 cycles when the cell was tested with LiNi_(0.8)Co_(0.15)Al_(0.05)O_(2)(NCA)cathode material vs.5 and 10 mg cm^(-2)@RT.展开更多
Solid polymer electrolytes have been considered as the promising candidates to improve the safety and stability of high-energy lithium metal batteries.However,the practical applications of solid polymer electrolytes a...Solid polymer electrolytes have been considered as the promising candidates to improve the safety and stability of high-energy lithium metal batteries.However,the practical applications of solid polymer electrolytes are still limited by the low ionic conductivity,poor interfacial contact with electrodes,narrow electrochemical window and weak mechanical strength.Here,a series of novel block copolymer electrolytes with three-dimensional networks are designed by cross-linked copolymerization of the polyethylene glycol soft segments and hexamethylene diisocyanate trimer hard segments.Their ionic migration performances and interface compatibilities with Li metal anode have been optimized delicately by tailoring the ratio of these functional units.The optimized block copolymer electrolyte has shown an amorphous crystalline structure,a high ionic conductivity of ~5.7×10^(-4)S cm^(-1),high lithium ion transference number(~0.49),wide electrochemical window up to ~4.65 V(vs.Li+/Li) and favorable mechanical strength at 55℃.Furthermore,the enhanced interface compatibility can well support the normal operations of lithium metal batteries using both LiFePO4 and LiNi0.8Co0.15Al0.05O2 cathodes.This study not only paves a new way to develop solid polymer electrolyte with optimizing functional units,but also provides a polymer electrolyte design strategy for the application demand of lithium metal battery.展开更多
The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the t...The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the traditional PID control has been proven not sufficient and capable for this particular petro-chemical process.In this work,an incremental multivariable predictive functional control(IMPFC) algorithm was proposed with less online computation,great precision and fast response.An incremental transfer function matrix model was set up through the step-response data,and predictive outputs were deduced with the theory of single-value optimization.The results show that the method can optimize the incremental control variable and reject the constraint of the incremental control variable with the positional predictive functional control algorithm,and thereby making the control variable smoother.The predictive output error and future set-point were approximated by a polynomial,which can overcome the problem under the model mismatch and make the predictive outputs track the reference trajectory.Then,the design of incremental multivariable predictive functional control was studied.Simulation and application results show that the proposed control strategy is effective and feasible to improve control performance and robustness of process.展开更多
In this paper we obtained the asymptotic formula of the orthogonal rational function on the unit circle with respect to the weight function μ(z) with preasigned poles, which are in the exterior of the unit disk.
In this paper, discussed are the problems about uniqueness of algebroidal functions in the unit disc with share-values in a sector domain instead of the whole disk. Results are obtained extending some uniqueness theor...In this paper, discussed are the problems about uniqueness of algebroidal functions in the unit disc with share-values in a sector domain instead of the whole disk. Results are obtained extending some uniqueness theorems of meromorphic functions.展开更多
We establish a precise Schwarz lemma for real-valued and bounded harmonic functions in the real unit ball of dimension n. This extends Chen's Schwarz-Pick lemma for real-valued and bounded planar harmonic mapping.
This paper presents a new approach via composite cost function to solve the unit commitment problem. The unit com-mitment problem involves determining the start-up and shut-down schedules for generating units to meet ...This paper presents a new approach via composite cost function to solve the unit commitment problem. The unit com-mitment problem involves determining the start-up and shut-down schedules for generating units to meet the fore-casted demand at the minimum cost. The commitment schedule must satisfy the other constraints such as the generating limits, spinning reserve, minimum up and down time, ramp level and individual units. The proposed algorithm gives the committed units and economic load dispatch for each specific hour of operation. Numerical simulations were carried out using three cases: four-generator, seven-generator, and ten-generator thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as Dynamic programming, Branch and bound, Ant colony system, and traditional Tabu search. The result demonstrated the accuracy of the proposed method.展开更多
This paper deals with a Unit Commitment (UC) problem of a power plant aimed to find the optimal scheduling of the generating units involving cubic cost functions. The problem has non convex generator characteristics, ...This paper deals with a Unit Commitment (UC) problem of a power plant aimed to find the optimal scheduling of the generating units involving cubic cost functions. The problem has non convex generator characteristics, which makes it very hard to handle the corresponding mathematical models. However, Teaching Learning Based Optimization (TLBO) has reached a high efficiency, in terms of solution accuracy and computing time for such non convex problems. Hence, TLBO is applied for scheduling of generators with higher order cost characteristics, and turns out to be computationally solvable. In particular, we represent a model that takes into account the accurate higher order generator cost functions along with ramp limits, and turns to be more general and efficient than those available in the literature. The behavior of the model is analyzed through proposed technique on modified IEEE-24 bus system.展开更多
The development of accurate prediction models continues to be highly beneficial in myriad disciplines. Deep learning models have performed well in stock price prediction and give high accuracy. However, these models a...The development of accurate prediction models continues to be highly beneficial in myriad disciplines. Deep learning models have performed well in stock price prediction and give high accuracy. However, these models are largely affected by the vanishing gradient problem escalated by some activation functions. This study proposes the use of the Vanishing Gradient Resilient Optimized Gated Recurrent Unit (OGRU) model with a scaled mean Approximation Coefficient (AC) time lag which should counter slow convergence, vanishing gradient and large error metrics. This study employed the Rectified Linear Unit (ReLU), Hyperbolic Tangent (Tanh), Sigmoid and Exponential Linear Unit (ELU) activation functions. Real-life datasets including the daily Apple and 5-minute Netflix closing stock prices were used, and they were decomposed using the Stationary Wavelet Transform (SWT). The decomposed series formed a decomposed data model which was compared to an undecomposed data model with similar hyperparameters and different default lags. The Apple daily dataset performed well with a Default_1 lag, using an undecomposed data model and the ReLU, attaining 0.01312, 0.00854 and 3.67 minutes for RMSE, MAE and runtime. The Netflix data performed best with the MeanAC_42 lag, using decomposed data model and the ELU achieving 0.00620, 0.00487 and 3.01 minutes for the same metrics.展开更多
基金supported by the National Natural Science Foundation of China(Nos.21203008,21975025,12274025)the Hainan Province Science and Technology Special Fund(Nos.ZDYF2021SHFZ232,ZDYF2023GXJS022)the Hainan Province Postdoctoral Science Foundation(No.300333)。
文摘The sulfide-based solid-state electrolytes(SEs)reactivity toward moisture and Li-metal are huge barriers that impede their large-scale manufactu ring and applications in all-solid-state lithium batteries(ASSLBs).Herein,we proposed an Al and O dual-doped strategy for Li_(3)PS_(4)SE to regulate the chemical/electrochemical stability of anionic PS_(4)^(3-)tetrahedra to mitigate structural hydrolysis and parasitic reactions at the SE/Li interface.The optimized Li_(3.08)A_(10.04)P_(0.96)S_(3.92)O_(0.08)SE presents the highestσLi+of 3.27 mS cm^(-1),which is~6.8 times higher than the pristine Li_(3)PS_(4)and excellently inhibits the structural hydrolysis for~25 min@25%humidity at RT.DFT calculations confirmed that the enhanced chemical stability was revealed to the intrinsically stable entities,e.g.,POS33-units.Moreover,Li_(3.08)Al_(0.04)P_(0.96)S_(3.92)O_(0.08)SE cycled stably in Li//Li symmetric cell over 1000 h@0.1 mA cm^(-2)/0.1 mA h cm^(-2),could be revealed to Li-Al alloy and Li_(2)Oat SE/Li interface impeding the growth of Li-dendrites during cycling.Resultantly,LNO@LCO/Li_(3.08)Al_(0.04)P_(0.96)S_(3.92)O_(0.08)/Li-In cell delivered initial discharge capacities of 129.8 mA h g^(-1)and 83.74%capacity retention over 300 cycles@0.2 C at RT.Moreover,the Li_(3.08)Al_(0.04)P_(0.96)S_(3.92)O_(0.08)SE presented>90%capacity retention over 200 and 300 cycles when the cell was tested with LiNi_(0.8)Co_(0.15)Al_(0.05)O_(2)(NCA)cathode material vs.5 and 10 mg cm^(-2)@RT.
基金supported financially by the National Key R&D Program of China (Grant No. 2018YFB0104300)Beijing Natural Science Foundation (JQ19003, KZ201910005002 and L182009)+1 种基金National Natural Science Foundation of China (Grants 21875007, 51622202, and 21974007)the Project of Youth Talent Plan of Beijing Municipal Education Commission (CIT&TCD201804013)。
文摘Solid polymer electrolytes have been considered as the promising candidates to improve the safety and stability of high-energy lithium metal batteries.However,the practical applications of solid polymer electrolytes are still limited by the low ionic conductivity,poor interfacial contact with electrodes,narrow electrochemical window and weak mechanical strength.Here,a series of novel block copolymer electrolytes with three-dimensional networks are designed by cross-linked copolymerization of the polyethylene glycol soft segments and hexamethylene diisocyanate trimer hard segments.Their ionic migration performances and interface compatibilities with Li metal anode have been optimized delicately by tailoring the ratio of these functional units.The optimized block copolymer electrolyte has shown an amorphous crystalline structure,a high ionic conductivity of ~5.7×10^(-4)S cm^(-1),high lithium ion transference number(~0.49),wide electrochemical window up to ~4.65 V(vs.Li+/Li) and favorable mechanical strength at 55℃.Furthermore,the enhanced interface compatibility can well support the normal operations of lithium metal batteries using both LiFePO4 and LiNi0.8Co0.15Al0.05O2 cathodes.This study not only paves a new way to develop solid polymer electrolyte with optimizing functional units,but also provides a polymer electrolyte design strategy for the application demand of lithium metal battery.
基金Project(61203021)supported by the National Natural Science Foundation of ChinaProject(2011216011)supported by the Scientific and Technological Program of Liaoning Province,China+2 种基金Project(2013020024)supported by the Natural Science Foundation of Liaoning Province,ChinaProject(2012BAF05B00)supported by the National Science and Technology Support Program,ChinaProject(LJQ2015061)supported by the Program for Liaoning Excellent Talents in Universities,China
文摘The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the traditional PID control has been proven not sufficient and capable for this particular petro-chemical process.In this work,an incremental multivariable predictive functional control(IMPFC) algorithm was proposed with less online computation,great precision and fast response.An incremental transfer function matrix model was set up through the step-response data,and predictive outputs were deduced with the theory of single-value optimization.The results show that the method can optimize the incremental control variable and reject the constraint of the incremental control variable with the positional predictive functional control algorithm,and thereby making the control variable smoother.The predictive output error and future set-point were approximated by a polynomial,which can overcome the problem under the model mismatch and make the predictive outputs track the reference trajectory.Then,the design of incremental multivariable predictive functional control was studied.Simulation and application results show that the proposed control strategy is effective and feasible to improve control performance and robustness of process.
文摘In this paper we obtained the asymptotic formula of the orthogonal rational function on the unit circle with respect to the weight function μ(z) with preasigned poles, which are in the exterior of the unit disk.
基金Supported by the NNSF of China(10471048)Supported by the Doctoral Foundation of the Education Committee of China(20050574002)
文摘In this paper, discussed are the problems about uniqueness of algebroidal functions in the unit disc with share-values in a sector domain instead of the whole disk. Results are obtained extending some uniqueness theorems of meromorphic functions.
基金Research supported by the National Natural Science Foundation of China(1120119911071083+1 种基金11671361)Jiangsu Overseas Visiting Scholar Program for University Prominent Young&Middle-aged Teachers and Presidents
文摘We establish a precise Schwarz lemma for real-valued and bounded harmonic functions in the real unit ball of dimension n. This extends Chen's Schwarz-Pick lemma for real-valued and bounded planar harmonic mapping.
文摘This paper presents a new approach via composite cost function to solve the unit commitment problem. The unit com-mitment problem involves determining the start-up and shut-down schedules for generating units to meet the fore-casted demand at the minimum cost. The commitment schedule must satisfy the other constraints such as the generating limits, spinning reserve, minimum up and down time, ramp level and individual units. The proposed algorithm gives the committed units and economic load dispatch for each specific hour of operation. Numerical simulations were carried out using three cases: four-generator, seven-generator, and ten-generator thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as Dynamic programming, Branch and bound, Ant colony system, and traditional Tabu search. The result demonstrated the accuracy of the proposed method.
文摘This paper deals with a Unit Commitment (UC) problem of a power plant aimed to find the optimal scheduling of the generating units involving cubic cost functions. The problem has non convex generator characteristics, which makes it very hard to handle the corresponding mathematical models. However, Teaching Learning Based Optimization (TLBO) has reached a high efficiency, in terms of solution accuracy and computing time for such non convex problems. Hence, TLBO is applied for scheduling of generators with higher order cost characteristics, and turns out to be computationally solvable. In particular, we represent a model that takes into account the accurate higher order generator cost functions along with ramp limits, and turns to be more general and efficient than those available in the literature. The behavior of the model is analyzed through proposed technique on modified IEEE-24 bus system.
文摘The development of accurate prediction models continues to be highly beneficial in myriad disciplines. Deep learning models have performed well in stock price prediction and give high accuracy. However, these models are largely affected by the vanishing gradient problem escalated by some activation functions. This study proposes the use of the Vanishing Gradient Resilient Optimized Gated Recurrent Unit (OGRU) model with a scaled mean Approximation Coefficient (AC) time lag which should counter slow convergence, vanishing gradient and large error metrics. This study employed the Rectified Linear Unit (ReLU), Hyperbolic Tangent (Tanh), Sigmoid and Exponential Linear Unit (ELU) activation functions. Real-life datasets including the daily Apple and 5-minute Netflix closing stock prices were used, and they were decomposed using the Stationary Wavelet Transform (SWT). The decomposed series formed a decomposed data model which was compared to an undecomposed data model with similar hyperparameters and different default lags. The Apple daily dataset performed well with a Default_1 lag, using an undecomposed data model and the ReLU, attaining 0.01312, 0.00854 and 3.67 minutes for RMSE, MAE and runtime. The Netflix data performed best with the MeanAC_42 lag, using decomposed data model and the ELU achieving 0.00620, 0.00487 and 3.01 minutes for the same metrics.
