The overall photocatalytic CO_(2) reduction reaction(OPCRR)that can directly convert CO_(2) and H_(2)O into fuels represents a promising renewable energy conversion technology.As a typical redox reaction,the OPCRR inv...The overall photocatalytic CO_(2) reduction reaction(OPCRR)that can directly convert CO_(2) and H_(2)O into fuels represents a promising renewable energy conversion technology.As a typical redox reaction,the OPCRR involves two half-reactions:the CO_(2) reduction half-reaction(CRHR)and the water oxidation half-reaction(WOHR).Generally,both half-reactions can be promoted by adjusting the wettability of catalysts.However,there is a contradiction in wettability requirements for the two half-reactions.Specifically,CRHR prefers a hydrophobic surface that can accumulate more CO_(2) molecules on the active sites,ensuring the appropriate ratio of gas-phase(CO_(2))to liquid-phase(H_(2)O)reactants.Conversely,the WOHR prefers a hydrophilic surface that can promote the departure of the gaseous product(O_(2))from the catalyst surface,preventing isolation between active sites and the reactant(H_(2)O).Here,we successfully reconciled the contradictory wettability requirements for the CRHR and WOHR by creating an alternately hydrophobic catalyst.This was achieved through a selectively hydrophobic modification method and a charge-transfer-control strategy.Consequently,the collaboratively promoted CRHR and WOHR led to a significantly enhanced OPCRR with a solar-to-fuel conversion efficiency of 0.186%.Notably,in ethanol production,the catalyst exhibited a 10.64-fold increase in generation rate(271.44μmol g^(-1)h~(-1))and a 4-fold increase in selectivity(55.77%)compared to the benchmark catalyst.This innovative approach holds great potential for application in universal overall reactions involving gas participation.展开更多
Industrial CO_(2)electroreduction has received tremendous attentions for resolution of the current energy and environmental crisis,but its performance is greatly limited by mass transport at high current density.In th...Industrial CO_(2)electroreduction has received tremendous attentions for resolution of the current energy and environmental crisis,but its performance is greatly limited by mass transport at high current density.In this work,an ion‐polymer‐modified gas‐diffusion electrode is used to tackle this proton limit.It is found that gas diffusion electrode‐Nafion shows an impressive performance of 75.2%Faradaic efficiency in multicarbon products at an industrial current density of 1.16 A/cm^(2).Significantly,in‐depth electrochemical characterizations combined with in situ Raman have been used to determine the full workflow of protons,and it is found that HCO_(3)^(−)acts as a proton pool near the reaction environment,and HCO_(3)^(−)and H_(3)O^(+)are local proton donors that interact with the proton shuttle−SO_(3)^(−)from Nafion.With rich proton hopping sites that decrease the activation energy,a“Grotthuss”mechanism for proton transport in the above system has been identified rather than the“Vehicle”mechanism with a higher energy barrier.Therefore,this work could be very useful in terms of the achievement of industrial CO_(2)reduction fundamentally and practically.展开更多
To reduce CO_(2) emissions in response to global climate change,shale reservoirs could be ideal candidates for long-term carbon geo-sequestration involving multi-scale transport processes.However,most current CO_(2) s...To reduce CO_(2) emissions in response to global climate change,shale reservoirs could be ideal candidates for long-term carbon geo-sequestration involving multi-scale transport processes.However,most current CO_(2) sequestration models do not adequately consider multiple transport mechanisms.Moreover,the evaluation of CO_(2) storage processes usually involves laborious and time-consuming numerical simulations unsuitable for practical prediction and decision-making.In this paper,an integrated model involving gas diffusion,adsorption,dissolution,slip flow,and Darcy flow is proposed to accurately characterize CO_(2) storage in depleted shale reservoirs,supporting the establishment of a training database.On this basis,a hybrid physics-informed data-driven neural network(HPDNN)is developed as a deep learning surrogate for prediction and inversion.By incorporating multiple sources of scientific knowledge,the HPDNN can be configured with limited simulation resources,significantly accelerating the forward and inversion processes.Furthermore,the HPDNN can more intelligently predict injection performance,precisely perform reservoir parameter inversion,and reasonably evaluate the CO_(2) storage capacity under complicated scenarios.The validation and test results demonstrate that the HPDNN can ensure high accuracy and strong robustness across an extensive applicability range when dealing with field data with multiple noise sources.This study has tremendous potential to replace traditional modeling tools for predicting and making decisions about CO_(2) storage projects in depleted shale reservoirs.展开更多
基金financially supported by the National Natural Science Foundation of China(22378204,22008121,51790492)the National Outstanding Youth Science Fund Project of National Natural Science Foundation of China(T2125004)+1 种基金the Funding of NJUST(No.TSXK2022D002)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_0454)。
文摘The overall photocatalytic CO_(2) reduction reaction(OPCRR)that can directly convert CO_(2) and H_(2)O into fuels represents a promising renewable energy conversion technology.As a typical redox reaction,the OPCRR involves two half-reactions:the CO_(2) reduction half-reaction(CRHR)and the water oxidation half-reaction(WOHR).Generally,both half-reactions can be promoted by adjusting the wettability of catalysts.However,there is a contradiction in wettability requirements for the two half-reactions.Specifically,CRHR prefers a hydrophobic surface that can accumulate more CO_(2) molecules on the active sites,ensuring the appropriate ratio of gas-phase(CO_(2))to liquid-phase(H_(2)O)reactants.Conversely,the WOHR prefers a hydrophilic surface that can promote the departure of the gaseous product(O_(2))from the catalyst surface,preventing isolation between active sites and the reactant(H_(2)O).Here,we successfully reconciled the contradictory wettability requirements for the CRHR and WOHR by creating an alternately hydrophobic catalyst.This was achieved through a selectively hydrophobic modification method and a charge-transfer-control strategy.Consequently,the collaboratively promoted CRHR and WOHR led to a significantly enhanced OPCRR with a solar-to-fuel conversion efficiency of 0.186%.Notably,in ethanol production,the catalyst exhibited a 10.64-fold increase in generation rate(271.44μmol g^(-1)h~(-1))and a 4-fold increase in selectivity(55.77%)compared to the benchmark catalyst.This innovative approach holds great potential for application in universal overall reactions involving gas participation.
基金National Key R&D Program of China,Grant/Award Number:2021YFF0500700Fundamental Research Funds for the Central Universities,Grant/Award Numbers:30921013103,30920041113+1 种基金Jiangsu Natural Science Foundation,Grant/Award Number:BK20190460National Natural Science Foundation of China,Grant/Award Numbers:51888103,52006105,92163124。
文摘Industrial CO_(2)electroreduction has received tremendous attentions for resolution of the current energy and environmental crisis,but its performance is greatly limited by mass transport at high current density.In this work,an ion‐polymer‐modified gas‐diffusion electrode is used to tackle this proton limit.It is found that gas diffusion electrode‐Nafion shows an impressive performance of 75.2%Faradaic efficiency in multicarbon products at an industrial current density of 1.16 A/cm^(2).Significantly,in‐depth electrochemical characterizations combined with in situ Raman have been used to determine the full workflow of protons,and it is found that HCO_(3)^(−)acts as a proton pool near the reaction environment,and HCO_(3)^(−)and H_(3)O^(+)are local proton donors that interact with the proton shuttle−SO_(3)^(−)from Nafion.With rich proton hopping sites that decrease the activation energy,a“Grotthuss”mechanism for proton transport in the above system has been identified rather than the“Vehicle”mechanism with a higher energy barrier.Therefore,this work could be very useful in terms of the achievement of industrial CO_(2)reduction fundamentally and practically.
基金This work is funded by National Natural Science Foundation of China(Nos.42202292,42141011)the Program for Jilin University(JLU)Science and Technology Innovative Research Team(No.2019TD-35).The authors would also like to thank the reviewers and editors whose critical comments are very helpful in preparing this article.
文摘To reduce CO_(2) emissions in response to global climate change,shale reservoirs could be ideal candidates for long-term carbon geo-sequestration involving multi-scale transport processes.However,most current CO_(2) sequestration models do not adequately consider multiple transport mechanisms.Moreover,the evaluation of CO_(2) storage processes usually involves laborious and time-consuming numerical simulations unsuitable for practical prediction and decision-making.In this paper,an integrated model involving gas diffusion,adsorption,dissolution,slip flow,and Darcy flow is proposed to accurately characterize CO_(2) storage in depleted shale reservoirs,supporting the establishment of a training database.On this basis,a hybrid physics-informed data-driven neural network(HPDNN)is developed as a deep learning surrogate for prediction and inversion.By incorporating multiple sources of scientific knowledge,the HPDNN can be configured with limited simulation resources,significantly accelerating the forward and inversion processes.Furthermore,the HPDNN can more intelligently predict injection performance,precisely perform reservoir parameter inversion,and reasonably evaluate the CO_(2) storage capacity under complicated scenarios.The validation and test results demonstrate that the HPDNN can ensure high accuracy and strong robustness across an extensive applicability range when dealing with field data with multiple noise sources.This study has tremendous potential to replace traditional modeling tools for predicting and making decisions about CO_(2) storage projects in depleted shale reservoirs.
