电控离子交换技术(electrochemically switched ion exchange,ESIX)是将电活性离子交换材料(EXIMs)沉积或涂覆在导电基底上,通过电化学控制导电基底上活性材料氧化还原状态实现目标离子置入与释放,从而实现离子的分离。该技术具有痕量...电控离子交换技术(electrochemically switched ion exchange,ESIX)是将电活性离子交换材料(EXIMs)沉积或涂覆在导电基底上,通过电化学控制导电基底上活性材料氧化还原状态实现目标离子置入与释放,从而实现离子的分离。该技术具有痕量提取、无二次污染、速率可控、高选择性等优点。通过共沉淀法制备Ni Fe Mn LDH,并将其与碳纳米管(CNTs)、聚偏二氟乙烯(PVDF)混合涂覆到石墨板上,制得NiFeMn LDH/CNTs/PVDF膜电极。NiFeMn LDH层板上具有丰富的羟基官能团,可与W(Ⅵ)发生羟基配位;层间的阴离子与W(Ⅵ)进行离子交换,可为W(Ⅵ)提供丰富的活性位点。在ESIX系统中,膜电极对W(Ⅵ)的吸附容量可达122.10 mg·g^(-1),且W(Ⅵ)与Mo(Ⅵ)、Cl^(-)、■分离因子(■)分别为1.25、19.60、35.80,实现了W(Ⅵ)选择性分离。此外,该膜电极具有优异的循环稳定性,为钨的高效分离提供了新的方向。展开更多
In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel...In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel cells(PEMFC).Firstly,the Shapley additive explanations(SHAP)value method is used to select external characteristic parameters with high contributions as inputs for the data-driven approach.Next,a novel swarm optimization algorithm,the enhanced search ant colony optimization,is proposed.This algorithm improves the ant colony optimization(ACO)algorithm based on a reinforcement factor to avoid premature convergence and accelerate the convergence speed.Comparative experiments are set up to compare the performance differences between particle swarm optimization(PSO),ACO,and ENSACO.Finally,a data-driven method based on ENSACO-LSTM is proposed to predict the power degradation trend of PEMFCs.And actual aging data is used to validate the method.The results show that,within a limited number of iterations,the optimization capability of ENSACO is significantly stronger than that of PSO and ACO.Additionally,the prediction accuracy of the ENSACO-LSTM method is greatly improved,with an average increase of approximately 50.58%compared to LSTM,PSO-LSTM,and ACO-LSTM.展开更多
文摘电控离子交换技术(electrochemically switched ion exchange,ESIX)是将电活性离子交换材料(EXIMs)沉积或涂覆在导电基底上,通过电化学控制导电基底上活性材料氧化还原状态实现目标离子置入与释放,从而实现离子的分离。该技术具有痕量提取、无二次污染、速率可控、高选择性等优点。通过共沉淀法制备Ni Fe Mn LDH,并将其与碳纳米管(CNTs)、聚偏二氟乙烯(PVDF)混合涂覆到石墨板上,制得NiFeMn LDH/CNTs/PVDF膜电极。NiFeMn LDH层板上具有丰富的羟基官能团,可与W(Ⅵ)发生羟基配位;层间的阴离子与W(Ⅵ)进行离子交换,可为W(Ⅵ)提供丰富的活性位点。在ESIX系统中,膜电极对W(Ⅵ)的吸附容量可达122.10 mg·g^(-1),且W(Ⅵ)与Mo(Ⅵ)、Cl^(-)、■分离因子(■)分别为1.25、19.60、35.80,实现了W(Ⅵ)选择性分离。此外,该膜电极具有优异的循环稳定性,为钨的高效分离提供了新的方向。
基金Supported by the Major Science and Technology Project of Jilin Province(20220301010GX)the International Scientific and Technological Cooperation(20240402071GH).
文摘In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel cells(PEMFC).Firstly,the Shapley additive explanations(SHAP)value method is used to select external characteristic parameters with high contributions as inputs for the data-driven approach.Next,a novel swarm optimization algorithm,the enhanced search ant colony optimization,is proposed.This algorithm improves the ant colony optimization(ACO)algorithm based on a reinforcement factor to avoid premature convergence and accelerate the convergence speed.Comparative experiments are set up to compare the performance differences between particle swarm optimization(PSO),ACO,and ENSACO.Finally,a data-driven method based on ENSACO-LSTM is proposed to predict the power degradation trend of PEMFCs.And actual aging data is used to validate the method.The results show that,within a limited number of iterations,the optimization capability of ENSACO is significantly stronger than that of PSO and ACO.Additionally,the prediction accuracy of the ENSACO-LSTM method is greatly improved,with an average increase of approximately 50.58%compared to LSTM,PSO-LSTM,and ACO-LSTM.
