How to achieve synergistic improvement of permittivity(ε_(r))and breakdown strength(E_(b))is a huge challenge for polymer dielectrics.Here,for the first time,theπ-conjugated comonomer(MHT)can simultaneously promote ...How to achieve synergistic improvement of permittivity(ε_(r))and breakdown strength(E_(b))is a huge challenge for polymer dielectrics.Here,for the first time,theπ-conjugated comonomer(MHT)can simultaneously promote theε_(r)and E_(b)of linear poly(methyl methacrylate)(PMMA)copolymers.The PMMA-based random copolymer films(P(MMA-co-MHT)),block copolymer films(PMMA-b-PMHT),and PMMA-based blend films were prepared to investigate the effects of sequential structure,phase separation structure,and modification method on dielectric and energy storage properties of PMMA-based dielectric films.As a result,the random copolymer P(MMA-coMHT)can achieve a maximumε_(r)of 5.8 at 1 kHz owing to the enhanced orientation polarization and electron polarization.Because electron injection and charge transfer are limited by the strong electrostatic attraction ofπ-conjugated benzophenanthrene group analyzed by the density functional theory(DFT),the discharge energy density value of P(MMA-co-PMHT)containing 1 mol%MHT units with the efficiency of 80%reaches15.00 J cm^(-3)at 872 MV m^(-1),which is 165%higher than that of pure PMMA.This study provides a simple and effective way to fabricate the high performance of polymer dielectrics via copolymerization with the monomer of P-type semi-conductive polymer.展开更多
High resolution satellite images are becoming increasingly available for urban multi-temporal semantic understanding.However,few datasets can be used for land-use/land-cover(LULC)classification,binary change detection...High resolution satellite images are becoming increasingly available for urban multi-temporal semantic understanding.However,few datasets can be used for land-use/land-cover(LULC)classification,binary change detection(BCD)and semantic change detection(SCD)simultaneously because classification datasets always have one time phase and BCD datasets focus only on the changed location,ignoring the changed classes.Public SCD datasets are rare but much needed.To solve the above problems,a tri-temporal SCD dataset made up of Gaofen-2(GF-2)remote sensing imagery(with 11 LULC classes and 60 change directions)was built in this study,namely,the Wuhan Urban Semantic Understanding(WUSU)dataset.Popular deep learning based methods for LULC classification,BCD and SCD are tested to verify the reliability of WUSU.A Siamese-based multi-task joint framework with a multi-task joint loss(MJ loss)named ChangeMJ is proposed to restore the object boundaries and obtains the best results in LULC classification,BCD and SCD,compared to the state-of-the-art(SOTA)methods.Finally,a large spatial-scale mapping for Wuhan central urban area is carried out to verify that the WUsU dataset and the ChangeMJ framework have good application values.展开更多
基金the funding of National Key R&D Program of China(No.2020YFA0711700)Hunan National Natural Science Foundation(2021JJ30652)+3 种基金National Natural Science Foundation of China(52002404)Natural Science Foundation of Guangdong Province(2020A1515011198)Characteristic Innovation Projects of Colleges and Universities in Guangdong Province(2020KT SCX081)State Key Laboratory of Powder Metallurgy,Central South University,Changsha,China
文摘How to achieve synergistic improvement of permittivity(ε_(r))and breakdown strength(E_(b))is a huge challenge for polymer dielectrics.Here,for the first time,theπ-conjugated comonomer(MHT)can simultaneously promote theε_(r)and E_(b)of linear poly(methyl methacrylate)(PMMA)copolymers.The PMMA-based random copolymer films(P(MMA-co-MHT)),block copolymer films(PMMA-b-PMHT),and PMMA-based blend films were prepared to investigate the effects of sequential structure,phase separation structure,and modification method on dielectric and energy storage properties of PMMA-based dielectric films.As a result,the random copolymer P(MMA-coMHT)can achieve a maximumε_(r)of 5.8 at 1 kHz owing to the enhanced orientation polarization and electron polarization.Because electron injection and charge transfer are limited by the strong electrostatic attraction ofπ-conjugated benzophenanthrene group analyzed by the density functional theory(DFT),the discharge energy density value of P(MMA-co-PMHT)containing 1 mol%MHT units with the efficiency of 80%reaches15.00 J cm^(-3)at 872 MV m^(-1),which is 165%higher than that of pure PMMA.This study provides a simple and effective way to fabricate the high performance of polymer dielectrics via copolymerization with the monomer of P-type semi-conductive polymer.
基金supported by National Key Research and Development Program of China under grant number 2022YFB3903404National Natural Science Foundation of China under grant number 42325105,42071350LIESMARS Special Research Funding.
文摘High resolution satellite images are becoming increasingly available for urban multi-temporal semantic understanding.However,few datasets can be used for land-use/land-cover(LULC)classification,binary change detection(BCD)and semantic change detection(SCD)simultaneously because classification datasets always have one time phase and BCD datasets focus only on the changed location,ignoring the changed classes.Public SCD datasets are rare but much needed.To solve the above problems,a tri-temporal SCD dataset made up of Gaofen-2(GF-2)remote sensing imagery(with 11 LULC classes and 60 change directions)was built in this study,namely,the Wuhan Urban Semantic Understanding(WUSU)dataset.Popular deep learning based methods for LULC classification,BCD and SCD are tested to verify the reliability of WUSU.A Siamese-based multi-task joint framework with a multi-task joint loss(MJ loss)named ChangeMJ is proposed to restore the object boundaries and obtains the best results in LULC classification,BCD and SCD,compared to the state-of-the-art(SOTA)methods.Finally,a large spatial-scale mapping for Wuhan central urban area is carried out to verify that the WUsU dataset and the ChangeMJ framework have good application values.
