The risk of flammability is an unavoidable issue for gel polymer electrolytes(GPEs).Usually,flameretardant solvents are necessary to be used,but most of them would react with anode/cathode easily and cause serious int...The risk of flammability is an unavoidable issue for gel polymer electrolytes(GPEs).Usually,flameretardant solvents are necessary to be used,but most of them would react with anode/cathode easily and cause serious interfacial instability,which is a big challenge for design and application of nonflammable GPEs.Here,a nonflammable GPE(SGPE)is developed by in situ polymerizing trifluoroethyl methacrylate(TFMA)monomers with flame-retardant triethyl phosphate(TEP)solvents and LiTFSI–LiDFOB dual lithium salts.TEP is strongly anchored to PTFMA matrix via polarity interaction between-P=O and-CH_(2)CF_(3).It reduces free TEP molecules,which obviously mitigates interfacial reactions,and enhances flame-retardant performance of TEP surprisingly.Anchored TEP molecules are also inhibited in solvation of Li^(+),leading to anion-dominated solvation sheath,which creates inorganic-rich solid electrolyte interface/cathode electrolyte interface layers.Such coordination structure changes Li^(+)transport from sluggish vehicular to fast structural transport,raising ionic conductivity to 1.03 mS cm^(-1) and transfer number to 0.41 at 30℃.The Li|SGPE|Li cell presents highly reversible Li stripping/plating performance for over 1000 h at 0.1 mA cm^(−2),and 4.2 V LiCoO_(2)|SGPE|Li battery delivers high average specific capacity>120 mAh g^(−1) over 200 cycles.This study paves a new way to make nonflammable GPE that is compatible with Li metal anode.展开更多
Osteoarthritis(OA)has emerged as a significant health concern among the elderly population,with increasing attention paid to ferroptosis-induced OA in recent years.However,the prolonged use of nonsteroidal anti-inflam...Osteoarthritis(OA)has emerged as a significant health concern among the elderly population,with increasing attention paid to ferroptosis-induced OA in recent years.However,the prolonged use of nonsteroidal anti-inflammatory drugs or corticosteroids can lead to a series of side effects and limited therapeutic efficacy.This study aimed to employ the Mannich condensation reaction between epigallocatechin-3-gallate(EGCG)and selenomethionine(SeMet)to efficiently synthesize polyphenol-based nanodrugs in aqueous media for treating OA.Molecular biology experiments demonstrated that EGCG-based nanodrugs(ES NDs)could effectively reduce glutathione peroxidase 4(GPX4)inactivation,abnormal Fe2+accumulation,and lipid peroxidation induced by oxidative stress,which ameliorated the metabolic disorder of chondrocytes and other multiple pathological processes triggered by ferroptosis.Moreover,imaging and histopathological analysis of the destabilization of the medial meniscus model in mice confirmed that ES NDs exhibiting significant therapeutic effects in relieving OA.The intra-articular delivery of ES NDs represents a promising approach for treating OA and other joint inflammatory diseases.展开更多
Fourier neural operator(FNO)model is developed for large eddy simulation(LES)of three-dimensional(3D)turbulence.Velocity fields of isotropic turbulence generated by direct numerical simulation(DNS)are used for trainin...Fourier neural operator(FNO)model is developed for large eddy simulation(LES)of three-dimensional(3D)turbulence.Velocity fields of isotropic turbulence generated by direct numerical simulation(DNS)are used for training the FNO model to predict the filtered velocity field at a given time.The input of the FNO model is the filtered velocity fields at the previous several time-nodes with large time lag.In the a posteriori study of LES,the FNO model performs better than the dynamic Smagorinsky model(DSM)and the dynamic mixed model(DMM)in the prediction of the velocity spectrum,probability density functions(PDFs)of vorticity and velocity increments,and the instantaneous flow structures.Moreover,the proposed model can significantly reduce the computational cost,and can be well generalized to LES of turbulence at higher Taylor-Reynolds numbers.展开更多
We establish a deconvolutional artificial-neural-network(D-ANN)approach in large-eddy simulation(LES)of compressible turbulent flow.Filtered variables in the neighboring locations are taken as the inputs of D-ANN to r...We establish a deconvolutional artificial-neural-network(D-ANN)approach in large-eddy simulation(LES)of compressible turbulent flow.Filtered variables in the neighboring locations are taken as the inputs of D-ANN to recover original(unfiltered)variables,including density,momentum and pressure.The scale-similarity form is adopted to reconstruct subfilter-scale(SFS)terms.The proposed D-ANN models can give better a priori predictions of the sub-filter stress and heat flux than the classical approximate-deconvolution method(ADM)and the velocity-gradient model(VGM).The predicted SFS terms with the D-ANN models have correlation coefficients larger than 98.4%and relative errors smaller than 18%.In the a posteriori analysis,the D-ANN model compares against the implicit LES(ILES),the dynamic-Smagorinsky model(DSM),and the dynamic-mixed model(DMM).The D-ANN model predicts better than these classical models for velocity spectra,statistical properties of SFS kinetic energy flux and velocity increments.The turbulence statistics and transient velocity divergence are also accurately reconstructed.The type of explicit filter and the impact of compressibility do not significantly affect a posteriori accuracy of the D-ANN model.Results showthat the proposed D-ANN approach has a great potential in developing highly accurate SFS models for large-eddy simulation of complex compressible turbulent flow.展开更多
Construction of two Ru^(Ⅲ)cations and six lacunary Keggin fragments resulted in a novel Ru_(2)W_(12)-cluster{(RuO_(6))_(2)(WO_(3))_(12)(H_(2)O)_(12)}bridged polyoxometalate,NaH_(11)[(RuO_(6))(AsW_(9)O_(33))_(3){(W_(6...Construction of two Ru^(Ⅲ)cations and six lacunary Keggin fragments resulted in a novel Ru_(2)W_(12)-cluster{(RuO_(6))_(2)(WO_(3))_(12)(H_(2)O)_(12)}bridged polyoxometalate,NaH_(11)[(RuO_(6))(AsW_(9)O_(33))_(3){(W_(6)O_(3))(H_(2)O)_(6)}]_(2)53H_(2)O(NaH_(11)·1·53H_(2)O),which represent the largest cluster in all the Ru-containing polyoxometalates.The most interesting characteristic is that the symmetry-related Ru_(2)W_(12)-cluster-based hexamers contain two windmill-shaped[(RuO_(6))(AsW_(9)O_(33))_(3){(W_(6)O_(3))(H_(2)O)_(6)}]trimers or the Ru_(2)W_(12) cluster was tightly wrapped by six segments of B-β-AsW_(9)O_(33).The other remarkable feature is that there have one intriguing cubane structure:which is composed of the Ru(1,2)and W(1,28,50,51,52,53)atoms.The oxygenation reactions of anilines to azoxybenzenes was evaluated when NaH_(11)·1·53H_(2)O served as effective catalyst by probing various reaction.The inherent redox property of oxygen-rich polyoxometalate surfaces and high photocatalytic activity of the Ru-containing metal cluster imbedded in NaH_(11)·1·53H_(2)O provide sufficient driving force for the photocatalytic transformation from anilines to azoxybenzenes.The oxidation of anilines can be realized with higher selectivity to afford various azoxybenzene compounds.The durability test shows that Ru-doping catalyst displays excellent chemical stability during the photocatalytic process.展开更多
A dynamic nonlinear algebraic model with scale-similarity dynamic procedure(DNAM-SSD)is proposed for subgrid-scale(SGS)stress in large-eddy simulation of turbulence.The model coefficients of the DNAM-SSD model are ada...A dynamic nonlinear algebraic model with scale-similarity dynamic procedure(DNAM-SSD)is proposed for subgrid-scale(SGS)stress in large-eddy simulation of turbulence.The model coefficients of the DNAM-SSD model are adaptively calculated through the scale-similarity relation,which greatly simplifies the conventional Germano-identity based dynamic procedure(GID).The a priori study shows that the DNAM-SSD model predicts the SGS stress considerably better than the conventional velocity gradient model(VGM),dynamic Smagorinsky model(DSM),dynamic mixed model(DMM)and DNAM-GID model at a variety of filter widths ranging from inertial to viscous ranges.The correlation coefficients of the SGS stress predicted by the DNAM-SSD model can be larger than 95%with the relative errors lower than 30%.In the a posteriori testings of LES,the DNAM-SSD model outperforms the implicit LES(ILES),DSM,DMM and DNAM-GID models without increasing computational costs,which only takes up half the time of the DNAM-GID model.The DNAM-SSD model accurately predicts plenty of turbulent statistics and instantaneous spatial structures in reasonable agreement with the filtered DNS data.These results indicate that the current DNAM-SSD model is attractive for the development of highly accurate SGS models for LES of turbulence.展开更多
基金supported by the National Natural Science Foundation of China(Nos.52172214,52272221,52171182)the Postdoctoral Innovation Project of Shandong Province(No.202102003)+2 种基金The Key Research and Development Program of Shandong Province(2021ZLGX01)the Qilu Young Scholar ProgramHPC Cloud Platform of Shandong University are also thanked.
文摘The risk of flammability is an unavoidable issue for gel polymer electrolytes(GPEs).Usually,flameretardant solvents are necessary to be used,but most of them would react with anode/cathode easily and cause serious interfacial instability,which is a big challenge for design and application of nonflammable GPEs.Here,a nonflammable GPE(SGPE)is developed by in situ polymerizing trifluoroethyl methacrylate(TFMA)monomers with flame-retardant triethyl phosphate(TEP)solvents and LiTFSI–LiDFOB dual lithium salts.TEP is strongly anchored to PTFMA matrix via polarity interaction between-P=O and-CH_(2)CF_(3).It reduces free TEP molecules,which obviously mitigates interfacial reactions,and enhances flame-retardant performance of TEP surprisingly.Anchored TEP molecules are also inhibited in solvation of Li^(+),leading to anion-dominated solvation sheath,which creates inorganic-rich solid electrolyte interface/cathode electrolyte interface layers.Such coordination structure changes Li^(+)transport from sluggish vehicular to fast structural transport,raising ionic conductivity to 1.03 mS cm^(-1) and transfer number to 0.41 at 30℃.The Li|SGPE|Li cell presents highly reversible Li stripping/plating performance for over 1000 h at 0.1 mA cm^(−2),and 4.2 V LiCoO_(2)|SGPE|Li battery delivers high average specific capacity>120 mAh g^(−1) over 200 cycles.This study paves a new way to make nonflammable GPE that is compatible with Li metal anode.
基金supported by the National Natural Science Foundation of China(Grant No.81972128 to Xuesong Zhang)National Natural Science Foundation of China(Grant No.82072478 to Yunpeng Zhao)the Application of Clinical Features of Capital City of Science and Technology Commission China BEIJING Special Subject(Z181100001718180 to Xuesong Zhang).
文摘Osteoarthritis(OA)has emerged as a significant health concern among the elderly population,with increasing attention paid to ferroptosis-induced OA in recent years.However,the prolonged use of nonsteroidal anti-inflammatory drugs or corticosteroids can lead to a series of side effects and limited therapeutic efficacy.This study aimed to employ the Mannich condensation reaction between epigallocatechin-3-gallate(EGCG)and selenomethionine(SeMet)to efficiently synthesize polyphenol-based nanodrugs in aqueous media for treating OA.Molecular biology experiments demonstrated that EGCG-based nanodrugs(ES NDs)could effectively reduce glutathione peroxidase 4(GPX4)inactivation,abnormal Fe2+accumulation,and lipid peroxidation induced by oxidative stress,which ameliorated the metabolic disorder of chondrocytes and other multiple pathological processes triggered by ferroptosis.Moreover,imaging and histopathological analysis of the destabilization of the medial meniscus model in mice confirmed that ES NDs exhibiting significant therapeutic effects in relieving OA.The intra-articular delivery of ES NDs represents a promising approach for treating OA and other joint inflammatory diseases.
基金supported by the National Natural Science Foundation of China(Nos.91952104,92052301,12172161,and 12161141017)National Numerical Windtunnel Project(No.NNW2019ZT1-A04)+4 种基金Shenzhen Science and Technology Program(No.KQTD20180411143441009)Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(No.GML2019ZD0103)CAAI-Huawei Mind Spore open Fundand by Department of Science and Technology of Guangdong Province(No.2019B21203001)supported by Center for Computational Science and Engineering of Southern University of Science and Technology。
文摘Fourier neural operator(FNO)model is developed for large eddy simulation(LES)of three-dimensional(3D)turbulence.Velocity fields of isotropic turbulence generated by direct numerical simulation(DNS)are used for training the FNO model to predict the filtered velocity field at a given time.The input of the FNO model is the filtered velocity fields at the previous several time-nodes with large time lag.In the a posteriori study of LES,the FNO model performs better than the dynamic Smagorinsky model(DSM)and the dynamic mixed model(DMM)in the prediction of the velocity spectrum,probability density functions(PDFs)of vorticity and velocity increments,and the instantaneous flow structures.Moreover,the proposed model can significantly reduce the computational cost,and can be well generalized to LES of turbulence at higher Taylor-Reynolds numbers.
基金This research was supported by the National Nat542 ural Science Foundation of China(Grants 91952104,92052301 and 91752201).
文摘We establish a deconvolutional artificial-neural-network(D-ANN)approach in large-eddy simulation(LES)of compressible turbulent flow.Filtered variables in the neighboring locations are taken as the inputs of D-ANN to recover original(unfiltered)variables,including density,momentum and pressure.The scale-similarity form is adopted to reconstruct subfilter-scale(SFS)terms.The proposed D-ANN models can give better a priori predictions of the sub-filter stress and heat flux than the classical approximate-deconvolution method(ADM)and the velocity-gradient model(VGM).The predicted SFS terms with the D-ANN models have correlation coefficients larger than 98.4%and relative errors smaller than 18%.In the a posteriori analysis,the D-ANN model compares against the implicit LES(ILES),the dynamic-Smagorinsky model(DSM),and the dynamic-mixed model(DMM).The D-ANN model predicts better than these classical models for velocity spectra,statistical properties of SFS kinetic energy flux and velocity increments.The turbulence statistics and transient velocity divergence are also accurately reconstructed.The type of explicit filter and the impact of compressibility do not significantly affect a posteriori accuracy of the D-ANN model.Results showthat the proposed D-ANN approach has a great potential in developing highly accurate SFS models for large-eddy simulation of complex compressible turbulent flow.
基金supported bythe National Natural Science Foundationof China(Nos.22171071,22071044,21771054,21571050)。
文摘Construction of two Ru^(Ⅲ)cations and six lacunary Keggin fragments resulted in a novel Ru_(2)W_(12)-cluster{(RuO_(6))_(2)(WO_(3))_(12)(H_(2)O)_(12)}bridged polyoxometalate,NaH_(11)[(RuO_(6))(AsW_(9)O_(33))_(3){(W_(6)O_(3))(H_(2)O)_(6)}]_(2)53H_(2)O(NaH_(11)·1·53H_(2)O),which represent the largest cluster in all the Ru-containing polyoxometalates.The most interesting characteristic is that the symmetry-related Ru_(2)W_(12)-cluster-based hexamers contain two windmill-shaped[(RuO_(6))(AsW_(9)O_(33))_(3){(W_(6)O_(3))(H_(2)O)_(6)}]trimers or the Ru_(2)W_(12) cluster was tightly wrapped by six segments of B-β-AsW_(9)O_(33).The other remarkable feature is that there have one intriguing cubane structure:which is composed of the Ru(1,2)and W(1,28,50,51,52,53)atoms.The oxygenation reactions of anilines to azoxybenzenes was evaluated when NaH_(11)·1·53H_(2)O served as effective catalyst by probing various reaction.The inherent redox property of oxygen-rich polyoxometalate surfaces and high photocatalytic activity of the Ru-containing metal cluster imbedded in NaH_(11)·1·53H_(2)O provide sufficient driving force for the photocatalytic transformation from anilines to azoxybenzenes.The oxidation of anilines can be realized with higher selectivity to afford various azoxybenzene compounds.The durability test shows that Ru-doping catalyst displays excellent chemical stability during the photocatalytic process.
基金National Numerical Windtunnel Project(No.NNW2019ZT1-A04)National Natural Science Foundation of China(NSFC Grants No.12172161,No.91952104,No.92052301,and No.91752201)+2 种基金Shenzhen Science and Technology Program(Grants No.KQTD20180411143441009)Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(Grant No.GML2019ZD0103)Department of Science and Technology of Guangdong Province(No.2020B1212030001).
文摘A dynamic nonlinear algebraic model with scale-similarity dynamic procedure(DNAM-SSD)is proposed for subgrid-scale(SGS)stress in large-eddy simulation of turbulence.The model coefficients of the DNAM-SSD model are adaptively calculated through the scale-similarity relation,which greatly simplifies the conventional Germano-identity based dynamic procedure(GID).The a priori study shows that the DNAM-SSD model predicts the SGS stress considerably better than the conventional velocity gradient model(VGM),dynamic Smagorinsky model(DSM),dynamic mixed model(DMM)and DNAM-GID model at a variety of filter widths ranging from inertial to viscous ranges.The correlation coefficients of the SGS stress predicted by the DNAM-SSD model can be larger than 95%with the relative errors lower than 30%.In the a posteriori testings of LES,the DNAM-SSD model outperforms the implicit LES(ILES),DSM,DMM and DNAM-GID models without increasing computational costs,which only takes up half the time of the DNAM-GID model.The DNAM-SSD model accurately predicts plenty of turbulent statistics and instantaneous spatial structures in reasonable agreement with the filtered DNS data.These results indicate that the current DNAM-SSD model is attractive for the development of highly accurate SGS models for LES of turbulence.
