To ensure the safe operation of batteries,accurately obtaining key internal state parameters is essential.However,traditional parameter measurement methods either require opening the battery or long-term measurements,...To ensure the safe operation of batteries,accurately obtaining key internal state parameters is essential.However,traditional parameter measurement methods either require opening the battery or long-term measurements,which are impractical.Therefore,the fixed values are commonly used for these parameters in electrochemical models and have significant limitations.To overcome these limitations,this paper proposes a deep neural network(DNN)based data-driven evaluation method to determine model parameters.By coupling an improved one-dimensional isothermal pseudo-twodimensional(P2D)model with DNN,this study identified concentration-dependent parameters through detailed discharge curve analysis.The results show that the data-driven method can effectively obtain the change trend of concentration-dependent parameters through the charge and discharge curve,and the method can be extended to different battery systems in different discharge rates and aging applications.This work is expected to provide new parameter selection insights for data-driven battery prediction and monitoring models.展开更多
Study on soil phosphorus（P） fraction is an important aspect in probing the mechanisms of soil P accumulation in farmland and mitigating its losing risk to the environment. We used a sequential extraction method to e...Study on soil phosphorus（P） fraction is an important aspect in probing the mechanisms of soil P accumulation in farmland and mitigating its losing risk to the environment. We used a sequential extraction method to evaluate the impacts of long-term fertilization and straw incorporation on inorganic, organic, and residual P（Pi, Po, and Pre） fractions in the plow layer（0–20 cm） of acidic paddy soil in southern China. The experiment comprised of six treatments：（i） no fertilizer control（CK）;（ii） straw incorporation and green manure（SG）;（iii） nitrogen and P fertilizer（NP）;（iv） NP＋SG;（v） NP＋K fertilizer（NPK）; and（vi） NPK＋SG. The results showed that, compared to the initial total soil P content（TSP, 600 mg kg^–1 in 1990）, long-term（20 years） combined continuous P fertilizer and SG significantly increased P accumulation（by 13–20%） while single fertilization（39.3 kg P ha^–1 yr^–1） could maintain soil P status at the most. The average soil P fractions comprised of extractable Pi, Po, and Pre by 51.7, 33.4, and 14.9% in total soil P, respectively. With comparison of no fertilizer addition（CK）, long-term single fertilization significantly（P〈0.05） increased the accumulation of Na HCO3^–, Na OH^–, and HCl^– extractable Pi fractions accounting for two- to three-fold, while SG increased the accumulation of Na HCO3^– and Na OH^– extractable Piand Po accounting for 12–60%. Though the mobilization of Pre fractions was not significant（P〉0.05）, our data indicate that SG may partially substitute for fertilizer P input and minimizing soil P accumulation and subsequent environmental risk in the subtropical paddy soil.展开更多
The Mn-Ce-Nb-O_x/P84 catalytic filter for removal of particulates and NO simultaneous was prepared by a novel method(foam coating method). The process parameters including the concentrations of PTFE emulsion, particle...The Mn-Ce-Nb-O_x/P84 catalytic filter for removal of particulates and NO simultaneous was prepared by a novel method(foam coating method). The process parameters including the concentrations of PTFE emulsion, particle size of catalyst and calcination temperature for preparation of catalytic filters were analyzed. In addition, the physical properties and performance for removal of NO(NH_3-SCR) and particulates of Mn-Ce-Nb-O_x/P84 catalytic filter prepared under the optimized parameters, were also systematic studied. Results show that the process parameters had significant influences on stability and performance of catalytic filter, The Mn-Ce-Nb-O_x/P84 catalytic filter prepared by foam coating method under the optimized parameters, has satisfactory physical properties and catalytic performance for removal of NO and particulates at 140-220 ℃. The NO removal efficiency of catalytic filter can reach95.3% at 200 ℃ as the catalyst loading amount is 450 g/m^2, Moreover,the dust removal efficiency of MnGe-Nb-O_x/P84 catalytic filter reaches as high as 99.98%, and the PM2.5 removal efficiency also reaches99.98%. The anti-sulfur performance of Mn-Ce-Nb-O_x catalytic filter is also attractive, after injecting150 ppm SO_2, the NO removal efficiency still retains up to 85%. It is indicated that the foam coating method can not only make a bond of high strength between catalyst and filter, but also make the catalytic filter possessing an excellent and stable performance for removal of NO and particulates.展开更多
基金supported by National Natural Science Foundation of China(22478239)Science and Technology Commission of Shanghai Municipality(19DZ2271100)National Natural Science Foundation of China(22208208)。
文摘To ensure the safe operation of batteries,accurately obtaining key internal state parameters is essential.However,traditional parameter measurement methods either require opening the battery or long-term measurements,which are impractical.Therefore,the fixed values are commonly used for these parameters in electrochemical models and have significant limitations.To overcome these limitations,this paper proposes a deep neural network(DNN)based data-driven evaluation method to determine model parameters.By coupling an improved one-dimensional isothermal pseudo-twodimensional(P2D)model with DNN,this study identified concentration-dependent parameters through detailed discharge curve analysis.The results show that the data-driven method can effectively obtain the change trend of concentration-dependent parameters through the charge and discharge curve,and the method can be extended to different battery systems in different discharge rates and aging applications.This work is expected to provide new parameter selection insights for data-driven battery prediction and monitoring models.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences(KZCX2-YW-T07)the National Natural Science Foundation of China (41171396)
文摘Study on soil phosphorus（P） fraction is an important aspect in probing the mechanisms of soil P accumulation in farmland and mitigating its losing risk to the environment. We used a sequential extraction method to evaluate the impacts of long-term fertilization and straw incorporation on inorganic, organic, and residual P（Pi, Po, and Pre） fractions in the plow layer（0–20 cm） of acidic paddy soil in southern China. The experiment comprised of six treatments：（i） no fertilizer control（CK）;（ii） straw incorporation and green manure（SG）;（iii） nitrogen and P fertilizer（NP）;（iv） NP＋SG;（v） NP＋K fertilizer（NPK）; and（vi） NPK＋SG. The results showed that, compared to the initial total soil P content（TSP, 600 mg kg^–1 in 1990）, long-term（20 years） combined continuous P fertilizer and SG significantly increased P accumulation（by 13–20%） while single fertilization（39.3 kg P ha^–1 yr^–1） could maintain soil P status at the most. The average soil P fractions comprised of extractable Pi, Po, and Pre by 51.7, 33.4, and 14.9% in total soil P, respectively. With comparison of no fertilizer addition（CK）, long-term single fertilization significantly（P〈0.05） increased the accumulation of Na HCO3^–, Na OH^–, and HCl^– extractable Pi fractions accounting for two- to three-fold, while SG increased the accumulation of Na HCO3^– and Na OH^– extractable Piand Po accounting for 12–60%. Though the mobilization of Pre fractions was not significant（P〉0.05）, our data indicate that SG may partially substitute for fertilizer P input and minimizing soil P accumulation and subsequent environmental risk in the subtropical paddy soil.
基金Project supported by the National Natural Science Foundation of China(21501097,21272118,21577065)the Natural Science Foundation of Jiangsu Province(BK20170954)+2 种基金the Startup Foundation for Introducing Talent of NUIST(2017r073)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China,China(18KJB430019)University Science Research Project of Jiangsu Province(18KJB430019)
文摘The Mn-Ce-Nb-O_x/P84 catalytic filter for removal of particulates and NO simultaneous was prepared by a novel method(foam coating method). The process parameters including the concentrations of PTFE emulsion, particle size of catalyst and calcination temperature for preparation of catalytic filters were analyzed. In addition, the physical properties and performance for removal of NO(NH_3-SCR) and particulates of Mn-Ce-Nb-O_x/P84 catalytic filter prepared under the optimized parameters, were also systematic studied. Results show that the process parameters had significant influences on stability and performance of catalytic filter, The Mn-Ce-Nb-O_x/P84 catalytic filter prepared by foam coating method under the optimized parameters, has satisfactory physical properties and catalytic performance for removal of NO and particulates at 140-220 ℃. The NO removal efficiency of catalytic filter can reach95.3% at 200 ℃ as the catalyst loading amount is 450 g/m^2, Moreover,the dust removal efficiency of MnGe-Nb-O_x/P84 catalytic filter reaches as high as 99.98%, and the PM2.5 removal efficiency also reaches99.98%. The anti-sulfur performance of Mn-Ce-Nb-O_x catalytic filter is also attractive, after injecting150 ppm SO_2, the NO removal efficiency still retains up to 85%. It is indicated that the foam coating method can not only make a bond of high strength between catalyst and filter, but also make the catalytic filter possessing an excellent and stable performance for removal of NO and particulates.
