Reactive transport equations in porous media are critical in various scientific and engineering disciplines,but solving these equations can be computationally expensive when exploring different scenarios,such as varyi...Reactive transport equations in porous media are critical in various scientific and engineering disciplines,but solving these equations can be computationally expensive when exploring different scenarios,such as varying porous structures and initial or boundary conditions.The deep operator network(DeepONet)has emerged as a popular deep learning framework for solving parametric partial differential equations.However,applying the DeepONet to porous media presents significant challenges due to its limited capability to extract representative features from intricate structures.To address this issue,we propose the Porous-DeepONet,a simple yet highly effective extension of the DeepONet framework that leverages convolutional neural networks(CNNs)to learn the solution operators of parametric reactive transport equations in porous media.By incorporating CNNs,we can effectively capture the intricate features of porous media,enabling accurate and efficient learning of the solution operators.We demonstrate the effectiveness of the Porous-DeepONet in accurately and rapidly learning the solution operators of parametric reactive transport equations with various boundary conditions,multiple phases,and multiphysical fields through five examples.This approach offers significant computational savings,potentially reducing the computation time by 50–1000 times compared with the finite-element method.Our work may provide a robust alternative for solving parametric reactive transport equations in porous media,paving the way for exploring complex phenomena in porous media.展开更多
Aqueous zinc-ion capacitors (ZICs) are considered as potential candidates for next generation electrochemical energy storage devices due to their high safety and low cost.However,the existing aqueous ZICs usually have...Aqueous zinc-ion capacitors (ZICs) are considered as potential candidates for next generation electrochemical energy storage devices due to their high safety and low cost.However,the existing aqueous ZICs usually have the problems of zinc dendrite growth and unsatisfactory performance at low temperature.Herein,an erythritol (Eryt) additive with inhibition of zinc dendrites and anti-freezing capability was introduced into the ZnSO4electrolyte.The experimental characterization and theoretical calculation confirm that the Eryt adsorbed on the surface of zinc anodes regulates the deposition orientation of Zn^(2+) and inhibits the formation of dendrites.It also reconstructs the solvation structure in the electrolyte to reduce water activity,enabling the electrolyte to have a lower freezing point for operation at low temperature.With the assistance of Eryt,the Zn||Zn symmetric cell exhibits a long cycle life of 2000 h,while the ZIC assembled with activated carbon (AC) cathode and zinc anode (Zn||AC) maintains a capacity retention of 98.2% after 30,000 cycles at a current density of 10 A g^(-1)(even after 10,000 cycles at-20°C,the capacity retention rate reached 94.8%.).This work provides a highly scalable,low-cost and effective strategy for the protection of the anodes of low-temperature aqueous ZICs.展开更多
Bipolar membranes(BPMs)exhibit the unique capability to regulate the operating environment of electrochemical system through the water dissociation-combination processes.However,the industrial utilization of BPMs is l...Bipolar membranes(BPMs)exhibit the unique capability to regulate the operating environment of electrochemical system through the water dissociation-combination processes.However,the industrial utilization of BPMs is limited by instability and serious energy consumption.The current-induced membrane discharge(CIMD)at high-current conditions has a negative influence on the performance of anion-exchange membranes,but the underlying ion transport mechanisms in the BPMs remain unclear.Here,the CIMD-coupled Poisson-Nernst-Planck(PNP)equations are used to explore the ion transport mechanisms in the BPMs for both reverse bias and forward bias at neutral and acid-base conditions.It is demonstrated that the CIMD effect in the reverse-bias mode can be suppressed by enhancing the diffusive transport of salt counter-ions(Na^(+)and Cl^(−))into the BPMs,and that in the forward-bias mode with acid-base electrolytes can be suppressed by matching the transport rate of water counter-ions(H_(3)O^(+)and OH^(−)).Suppressing the CIMD can promote the water dissociation in the reverse-bias mode,as well as overcome the plateau of limiting current density and reduce the interfacial blockage of salt co-ions(Cl^(−))in the anion-exchange layer in the forward-bias mode with acid-base electrolytes.Our work highlights the importance of regulating ion crossover transport on improving the performance of BPMs.展开更多
When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain ada...When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are welllabeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation:distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.展开更多
Background Anorexia nervosa(AN)has been characterised as a psychiatric disorder associated with increased control.Currently,it remains difficult to predict treatment response in patients with AN.Their cognitive abilit...Background Anorexia nervosa(AN)has been characterised as a psychiatric disorder associated with increased control.Currently,it remains difficult to predict treatment response in patients with AN.Their cognitive abilities are known to be resistant to treatment.It has been established that the frontoparietal control network(FPCN)is the direct counterpart of the executive control network.Therefore,the resting-state brain activity of the FPCN may serve as a biomarker to predict treatment response in AN.Aims The study aimed to investigate the association between resting-state functional connectivity(RSFC)of the FPCN,clinical symptoms and treatment response in patients with AN.Methods In this case-control study,79 female patients with AN and no prior treatment from the Shanghai Mental Health Center and 40 matched healthy controls(HCs)were recruited from January 2015 to March 2022.All participants completed the Questionnaire Versionof the Eating Disorder Examination(version 6.0)to assess the severity of their eating disorder symptoms.Additionally,RSFC data were obtained from all participants at baseline by functional magnetic resonance imaging.Patients with AN underwent routine outpatient treatment at the 4th and 12th week,during which time their clinical symptoms were evaluated using the same measures as at baseline.Results Among the 79 patients,40 completed the 4-week follow-up and 35 completed the 12-week follow-up.The RSFC from the right posterior parietal cortex(PPC)and dorsolateral prefrontal cortex(diPFC)increased in 79 patients with AN vs 40 HCs after controlling for depression and anxiety symptoms.By multiple linear regression,the RSFC of the PPC to the inferior frontal gyrus was found to be a significant factor for self-reported eating disorder symptoms at baseline and the treatment response to cognitive preoccupations about eating and body image,after controlling for age,age of onset and body mass index.The RSFC in the dIPFC to the middle temporal gyrus and the superior frontal gyrus may be significant factors in the treatment response to binge eating and loss of control/overeating in patients with AN.Conclusions Alterations in RSFC in the FPCN appear to affect self-reported eating disorder symptoms and treatment response in patients with AN.Our findings offer new insight into the pathogenesis of AN and could promote early prevention and treatment.展开更多
The hydrogen evolution reaction performance of semiconducting 2H-phase molybdenum disulfide(2H-MoS_(2))presents a significant hurdle in realizing its full potential applications.Here,we utilize theoretical calculation...The hydrogen evolution reaction performance of semiconducting 2H-phase molybdenum disulfide(2H-MoS_(2))presents a significant hurdle in realizing its full potential applications.Here,we utilize theoretical calculations to predict possible functionalized graphene quantum dots(GQDs),which can enhance HER activity of bulk MoS_(2).Subsequently,we design a functionalized GQD-induced in-situ bottom-up strategy to fabricate near atom-layer 2H-MoS_(2) nanosheets mediated with GQDs(ALQD)by modulating the concentration of electron withdrawing/donating functional groups.Experimental results reveal that the introduction of a series of functionalized GQDs during the synthesis of ALQD plays a crucial role.Notably,the higher the concentration and strength of electron-withdrawing functional groups on GQDs,the thinner and more active the resulting ALQD are.Remarkably,the synthesized near atom-layer ALQD-SO_(3)demonstrate significantly improved HER performance.Our GQD-induced strategy provides a simple and efficient approach for expanding the catalytic application of MoS_(2).Furthermore,it holds substantial potential for developing nanosheets in other transition-metal dichalcogenide materials.展开更多
Concentration distribution of the deterrent in single-base propellant during the process of firing plays an important role in the ballistic properties of gun propellant in weapons. However, the diffusion coefficient c...Concentration distribution of the deterrent in single-base propellant during the process of firing plays an important role in the ballistic properties of gun propellant in weapons. However, the diffusion coefficient calculated by molecular dynamics(MD) simulation is 6 orders of magnitude larger than the experimental values. Meanwhile, few simple and comprehensive theoretical models can explain the phenomenon and accurately predict the concentration distribution of the propellant. Herein, an onion model combining with MD simulation and finite element method of diffusion in propellants is introduced to bridge the gap between the experiments and simulations, and correctly predict the concentration distribution of deterrent. Furthermore, a new time scale is found to characterize the diffusion process. Finally, the time-and position-depended concentration distributions of dibutyl phthalate in nitrocellulose are measured by Raman spectroscopy to verify the correctness of the onion model. This work not only provides guidance for the design of the deterrent, but could be also extended to the diffusion of small molecules in polymer with different crystallinity.展开更多
Defect-engineered carbon materials have been emerged as promising electrocatalysts for oxygen reduction reaction(ORR)in metal-air batteries.Developing a facile strategy for the preparation of highly active nanocarbon ...Defect-engineered carbon materials have been emerged as promising electrocatalysts for oxygen reduction reaction(ORR)in metal-air batteries.Developing a facile strategy for the preparation of highly active nanocarbon electrocatalysts remains challenging.Herein,a low-cost and simple route is developed to synthesize defective graphene by pyrolyzing the mixture of glucose and carbon nitride.Molecular dynamics simulations reveal that the graphene formation is ascribed to two-dimensional layered feature of carbon nitride,and high compatibility of carbon nitride/glucose systems.Structural measurements suggest that the graphene possesses rich edge and topological defects.The graphene catalyst exhibits higher power density than commercial Pt/C catalyst in a primary Zn-air battery.Combining experimental results and theoretical thermodynamic analysis,it is identified that graphitic nitrogen-modified topological defects at carbon framework edges are responsible for the decent ORR performance.The strategy presented in this work can be can be scaled up readily to fabricate defective carbon materials.展开更多
基金supported by the National Key Research and Development Program of China(2022YFA1503501)the National Natural Science Foundation of China(22378112,22278127,and 22078088)+1 种基金the Fundamental Research Funds for the Central Universities(2022ZFJH004)the Shanghai Rising-Star Program(21QA1401900).
文摘Reactive transport equations in porous media are critical in various scientific and engineering disciplines,but solving these equations can be computationally expensive when exploring different scenarios,such as varying porous structures and initial or boundary conditions.The deep operator network(DeepONet)has emerged as a popular deep learning framework for solving parametric partial differential equations.However,applying the DeepONet to porous media presents significant challenges due to its limited capability to extract representative features from intricate structures.To address this issue,we propose the Porous-DeepONet,a simple yet highly effective extension of the DeepONet framework that leverages convolutional neural networks(CNNs)to learn the solution operators of parametric reactive transport equations in porous media.By incorporating CNNs,we can effectively capture the intricate features of porous media,enabling accurate and efficient learning of the solution operators.We demonstrate the effectiveness of the Porous-DeepONet in accurately and rapidly learning the solution operators of parametric reactive transport equations with various boundary conditions,multiple phases,and multiphysical fields through five examples.This approach offers significant computational savings,potentially reducing the computation time by 50–1000 times compared with the finite-element method.Our work may provide a robust alternative for solving parametric reactive transport equations in porous media,paving the way for exploring complex phenomena in porous media.
基金the financial supports of the National Natural Science Foundation of China(22109045,21875065)the China Postdoctoral Science Foundation Funded Project(2021M701191).
文摘Aqueous zinc-ion capacitors (ZICs) are considered as potential candidates for next generation electrochemical energy storage devices due to their high safety and low cost.However,the existing aqueous ZICs usually have the problems of zinc dendrite growth and unsatisfactory performance at low temperature.Herein,an erythritol (Eryt) additive with inhibition of zinc dendrites and anti-freezing capability was introduced into the ZnSO4electrolyte.The experimental characterization and theoretical calculation confirm that the Eryt adsorbed on the surface of zinc anodes regulates the deposition orientation of Zn^(2+) and inhibits the formation of dendrites.It also reconstructs the solvation structure in the electrolyte to reduce water activity,enabling the electrolyte to have a lower freezing point for operation at low temperature.With the assistance of Eryt,the Zn||Zn symmetric cell exhibits a long cycle life of 2000 h,while the ZIC assembled with activated carbon (AC) cathode and zinc anode (Zn||AC) maintains a capacity retention of 98.2% after 30,000 cycles at a current density of 10 A g^(-1)(even after 10,000 cycles at-20°C,the capacity retention rate reached 94.8%.).This work provides a highly scalable,low-cost and effective strategy for the protection of the anodes of low-temperature aqueous ZICs.
基金sponsored by the National Key R&D Program of China(2022YFB4602101)the Fundamental Research Funds for the Central Universities(2022ZFJH004 and 2024SMECP05)+2 种基金the National Natural Science Foundation of China(22278127 and 22378112)the Shanghai Pilot Program for Basic Research(22T01400100-18)the Postdoctoral Fellowship Program of CPSF(GZC20230801)。
文摘Bipolar membranes(BPMs)exhibit the unique capability to regulate the operating environment of electrochemical system through the water dissociation-combination processes.However,the industrial utilization of BPMs is limited by instability and serious energy consumption.The current-induced membrane discharge(CIMD)at high-current conditions has a negative influence on the performance of anion-exchange membranes,but the underlying ion transport mechanisms in the BPMs remain unclear.Here,the CIMD-coupled Poisson-Nernst-Planck(PNP)equations are used to explore the ion transport mechanisms in the BPMs for both reverse bias and forward bias at neutral and acid-base conditions.It is demonstrated that the CIMD effect in the reverse-bias mode can be suppressed by enhancing the diffusive transport of salt counter-ions(Na^(+)and Cl^(−))into the BPMs,and that in the forward-bias mode with acid-base electrolytes can be suppressed by matching the transport rate of water counter-ions(H_(3)O^(+)and OH^(−)).Suppressing the CIMD can promote the water dissociation in the reverse-bias mode,as well as overcome the plateau of limiting current density and reduce the interfacial blockage of salt co-ions(Cl^(−))in the anion-exchange layer in the forward-bias mode with acid-base electrolytes.Our work highlights the importance of regulating ion crossover transport on improving the performance of BPMs.
基金supported by the National Natural Science Foundation of China (62206204,62176193)the Natural Science Foundation of Hubei Province,China (2023AFB705)the Natural Science Foundation of Chongqing,China (CSTB2023NSCQ-MSX0932)。
文摘When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are welllabeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation:distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.
基金supported by grants from Shanghai Jiao Tong University(YG2022ZD026)National Natural Science Foundation of China(81771461,82071545),Science and Technology Commission of Shanghai Municipality(20Y11906500)+2 种基金Shanghai Clinical Medical Research Center for Psychiatric and Psychological Disorders(19MC1911100)hospital-level research projects of Shanghai Mental Health Center(2020-YJ09,2020-QH-04)Youth Project of Shanghai Health Commission(20224Y0267).
文摘Background Anorexia nervosa(AN)has been characterised as a psychiatric disorder associated with increased control.Currently,it remains difficult to predict treatment response in patients with AN.Their cognitive abilities are known to be resistant to treatment.It has been established that the frontoparietal control network(FPCN)is the direct counterpart of the executive control network.Therefore,the resting-state brain activity of the FPCN may serve as a biomarker to predict treatment response in AN.Aims The study aimed to investigate the association between resting-state functional connectivity(RSFC)of the FPCN,clinical symptoms and treatment response in patients with AN.Methods In this case-control study,79 female patients with AN and no prior treatment from the Shanghai Mental Health Center and 40 matched healthy controls(HCs)were recruited from January 2015 to March 2022.All participants completed the Questionnaire Versionof the Eating Disorder Examination(version 6.0)to assess the severity of their eating disorder symptoms.Additionally,RSFC data were obtained from all participants at baseline by functional magnetic resonance imaging.Patients with AN underwent routine outpatient treatment at the 4th and 12th week,during which time their clinical symptoms were evaluated using the same measures as at baseline.Results Among the 79 patients,40 completed the 4-week follow-up and 35 completed the 12-week follow-up.The RSFC from the right posterior parietal cortex(PPC)and dorsolateral prefrontal cortex(diPFC)increased in 79 patients with AN vs 40 HCs after controlling for depression and anxiety symptoms.By multiple linear regression,the RSFC of the PPC to the inferior frontal gyrus was found to be a significant factor for self-reported eating disorder symptoms at baseline and the treatment response to cognitive preoccupations about eating and body image,after controlling for age,age of onset and body mass index.The RSFC in the dIPFC to the middle temporal gyrus and the superior frontal gyrus may be significant factors in the treatment response to binge eating and loss of control/overeating in patients with AN.Conclusions Alterations in RSFC in the FPCN appear to affect self-reported eating disorder symptoms and treatment response in patients with AN.Our findings offer new insight into the pathogenesis of AN and could promote early prevention and treatment.
基金This research was supported by Shanghai Pujiang Program(21PJD022)National Natural Science Foundation of China(21901154).
文摘The hydrogen evolution reaction performance of semiconducting 2H-phase molybdenum disulfide(2H-MoS_(2))presents a significant hurdle in realizing its full potential applications.Here,we utilize theoretical calculations to predict possible functionalized graphene quantum dots(GQDs),which can enhance HER activity of bulk MoS_(2).Subsequently,we design a functionalized GQD-induced in-situ bottom-up strategy to fabricate near atom-layer 2H-MoS_(2) nanosheets mediated with GQDs(ALQD)by modulating the concentration of electron withdrawing/donating functional groups.Experimental results reveal that the introduction of a series of functionalized GQDs during the synthesis of ALQD plays a crucial role.Notably,the higher the concentration and strength of electron-withdrawing functional groups on GQDs,the thinner and more active the resulting ALQD are.Remarkably,the synthesized near atom-layer ALQD-SO_(3)demonstrate significantly improved HER performance.Our GQD-induced strategy provides a simple and efficient approach for expanding the catalytic application of MoS_(2).Furthermore,it holds substantial potential for developing nanosheets in other transition-metal dichalcogenide materials.
基金sponsored by the National Natural Science Foundation of China (91834301, 22078088, 22005143)the National Natural Science Foundation of China for Innovative Research Groups (51621002)。
文摘Concentration distribution of the deterrent in single-base propellant during the process of firing plays an important role in the ballistic properties of gun propellant in weapons. However, the diffusion coefficient calculated by molecular dynamics(MD) simulation is 6 orders of magnitude larger than the experimental values. Meanwhile, few simple and comprehensive theoretical models can explain the phenomenon and accurately predict the concentration distribution of the propellant. Herein, an onion model combining with MD simulation and finite element method of diffusion in propellants is introduced to bridge the gap between the experiments and simulations, and correctly predict the concentration distribution of deterrent. Furthermore, a new time scale is found to characterize the diffusion process. Finally, the time-and position-depended concentration distributions of dibutyl phthalate in nitrocellulose are measured by Raman spectroscopy to verify the correctness of the onion model. This work not only provides guidance for the design of the deterrent, but could be also extended to the diffusion of small molecules in polymer with different crystallinity.
基金supported by the National Natural Science Foundation of China(21838003,91834301 and 21978278)the Shanghai Scientific and Technological Innovation Project(18JC1410500 and 19JC1410400)the Fundamental Research Funds for the Central Universities(222201718002).
文摘Defect-engineered carbon materials have been emerged as promising electrocatalysts for oxygen reduction reaction(ORR)in metal-air batteries.Developing a facile strategy for the preparation of highly active nanocarbon electrocatalysts remains challenging.Herein,a low-cost and simple route is developed to synthesize defective graphene by pyrolyzing the mixture of glucose and carbon nitride.Molecular dynamics simulations reveal that the graphene formation is ascribed to two-dimensional layered feature of carbon nitride,and high compatibility of carbon nitride/glucose systems.Structural measurements suggest that the graphene possesses rich edge and topological defects.The graphene catalyst exhibits higher power density than commercial Pt/C catalyst in a primary Zn-air battery.Combining experimental results and theoretical thermodynamic analysis,it is identified that graphitic nitrogen-modified topological defects at carbon framework edges are responsible for the decent ORR performance.The strategy presented in this work can be can be scaled up readily to fabricate defective carbon materials.
