Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of ...Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.展开更多
The internal mechanisms of nucleation and growth of L1_(2)-AI_(3)RE(RE=Sc,Y,La-Lu) second phases in Al alloys were investigated by combining first-principles calculations with quasi-harmonic approximation(QHA).The cal...The internal mechanisms of nucleation and growth of L1_(2)-AI_(3)RE(RE=Sc,Y,La-Lu) second phases in Al alloys were investigated by combining first-principles calculations with quasi-harmonic approximation(QHA).The calculated results show that the diffusion rate D_s and chemical potential AG_V increase with the increase of temperature.With the increase of atomic number,the D_s and the strain energy ΔE_(CS)increase firstly from Sc to La,and then decreases,while the calculated interface energy γ_(α/β) and ΔG_V show opposite tendency.Based on above calculated results,the critical nucleation radius R*and coarsening rate K_(LSW) are obtained from the classical nucleation theory(CNT) and LSW model of the Ostwald ripening of particles,respectively.With the increase of atomic number,the R*increases firstly,and then decreases for all planes at finite temperatures.Whereas the K_(LSW) shows opposite variation to the R^(*).From this point of view,it is reasonably speculated that Y and later RE elements can replace the expensive Sc for heat-resistance Al alloys.The solubility c_(∞) of particles is usually very small at low temperature,and there is obvious solubility only when the temperature reaches 600 K.The surface energies E_(sur) of AI_(3)RE compounds and Al solid solution are respectively larger and smaller than that of pure Al,respectively,except for the surface(001) and(110) of Al_(3)La.For all planes,with the increase of atomic number of RE,E_(sur) decreases firstly from Sc to La,and then increases linearly to Lu.These results are helpful for designing high performance heat-resistance Al alloys.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42141019 and 42261144687)and STEP(Grant No.2019QZKK0102)supported by the Korea Environmental Industry&Technology Institute(KEITI)through the“Project for developing an observation-based GHG emissions geospatial information map”,funded by the Korea Ministry of Environment(MOE)(Grant No.RS-2023-00232066).
文摘Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.
基金Project supported by the R&D plan for Key Areas in Guangdong Province (2020B010186001)the National Natural Science Foundation of China (52171115,52071299)。
文摘The internal mechanisms of nucleation and growth of L1_(2)-AI_(3)RE(RE=Sc,Y,La-Lu) second phases in Al alloys were investigated by combining first-principles calculations with quasi-harmonic approximation(QHA).The calculated results show that the diffusion rate D_s and chemical potential AG_V increase with the increase of temperature.With the increase of atomic number,the D_s and the strain energy ΔE_(CS)increase firstly from Sc to La,and then decreases,while the calculated interface energy γ_(α/β) and ΔG_V show opposite tendency.Based on above calculated results,the critical nucleation radius R*and coarsening rate K_(LSW) are obtained from the classical nucleation theory(CNT) and LSW model of the Ostwald ripening of particles,respectively.With the increase of atomic number,the R*increases firstly,and then decreases for all planes at finite temperatures.Whereas the K_(LSW) shows opposite variation to the R^(*).From this point of view,it is reasonably speculated that Y and later RE elements can replace the expensive Sc for heat-resistance Al alloys.The solubility c_(∞) of particles is usually very small at low temperature,and there is obvious solubility only when the temperature reaches 600 K.The surface energies E_(sur) of AI_(3)RE compounds and Al solid solution are respectively larger and smaller than that of pure Al,respectively,except for the surface(001) and(110) of Al_(3)La.For all planes,with the increase of atomic number of RE,E_(sur) decreases firstly from Sc to La,and then increases linearly to Lu.These results are helpful for designing high performance heat-resistance Al alloys.
