The global shift toward next-generation energy systems is propelled by the urgent need to combat climate change and the dwindling supply of fossil fuels.This review explores the intricate challenges and opportunities ...The global shift toward next-generation energy systems is propelled by the urgent need to combat climate change and the dwindling supply of fossil fuels.This review explores the intricate challenges and opportunities for transitioning to sustainable renewable energy sources such as solar,wind,and hydrogen.This transition economically challenges traditional energy sectors while fostering new industries,promoting job growth,and sustainable economic development.The transition to renewable energy demands social equity,ensuring universal access to affordable energy,and considering community impact.The environmental benefits include a significant reduction in greenhouse gas emissions and a lesser ecological footprint.This study highlights the rapid growth of the global wind power market,which is projected to increase from$112.23 billion in 2022 to$278.43 billion by 2030,with a compound annual growth rate of 13.67%.In addition,the demand for hydrogen is expected to increase,significantly impacting the market with potential cost reductions and making it a critical renewable energy source owing to its affordability and zero emissions.By 2028,renewables are predicted to account for 42%of global electricity generation,with significant contributions from wind and solar photovoltaic(PV)technology,particularly in China,the European Union,the United States,and India.These developments signify a global commitment to diversifying energy sources,reducing emissions,and moving toward cleaner and more sustainable energy solutions.This review offers stakeholders the insights required to smoothly transition to sustainable energy,setting the stage for a resilient future.展开更多
Reliable calculations of nuclear binding energies are crucial for advancing the research of nuclear physics. Machine learning provides an innovative approach to exploring complex physical problems. In this study, the ...Reliable calculations of nuclear binding energies are crucial for advancing the research of nuclear physics. Machine learning provides an innovative approach to exploring complex physical problems. In this study, the nuclear binding energies are modeled directly using a machine-learning method called the Gaussian process. First, the binding energies for 2238 nuclei with Z > 20 and N > 20 are calculated using the Gaussian process in a physically motivated feature space, yielding an average deviation of 0.046 MeV and a standard deviation of 0.066 MeV. The results show the good learning ability of the Gaussian process in the studies of binding energies. Then, the predictive power of the Gaussian process is studied by calculating the binding energies for 108 nuclei newly included in AME2020. The theoretical results are in good agreement with the experimental data, reflecting the good predictive power of the Gaussian process. Moreover, the α-decay energies for 1169 nuclei with 50 ≤ Z ≤ 110 are derived from the theoretical binding energies calculated using the Gaussian process. The average deviation and the standard deviation are, respectively, 0.047 MeV and 0.070 MeV. Noticeably, the calculated α-decay energies for the two new isotopes ^ (204 )Ac(Huang et al. Phys Lett B 834, 137484(2022)) and ^ (207) Th(Yang et al. Phys Rev C 105, L051302(2022)) agree well with the latest experimental data. These results demonstrate that the Gaussian process is reliable for the calculations of nuclear binding energies. Finally, the α-decay properties of some unknown actinide nuclei are predicted using the Gaussian process. The predicted results can be useful guides for future research on binding energies and α-decay properties.展开更多
Machine learning combined with density functional theory(DFT)enables rapid exploration of catalyst descriptors space such as adsorption energy,facilitating rapid and effective catalyst screening.However,there is still...Machine learning combined with density functional theory(DFT)enables rapid exploration of catalyst descriptors space such as adsorption energy,facilitating rapid and effective catalyst screening.However,there is still a lack of models for predicting adsorption energies on oxides,due to the complexity of elemental species and the ambiguous coordination environment.This work proposes an active learning workflow(LeNN)founded on local electronic transfer features(e)and the principle of coordinate rotation invariance.By accurately characterizing the electron transfer to adsorption site atoms and their surrounding geometric structures,LeNN mitigates abrupt feature changes due to different element types and clarifies coordination environments.As a result,it enables the prediction of^(*)H adsorption energy on binary oxide surfaces with a mean absolute error(MAE)below 0.18 eV.Moreover,we incorporate local coverage(θ_(l))and leverage neutral network ensemble to establish an active learning workflow,attaining a prediction MAE below 0.2 eV for 5419 multi-^(*)H adsorption structures.These findings validate the universality and capability of the proposed features in predicting^(*)H adsorption energy on binary oxide surfaces.展开更多
Platinum(Pt)-based noble metal catalysts(PGMs)are the most widely used commercial catalysts,but they have the problems of high cost,low reserves,and susceptibility to small-molecule toxicity.Transition metal oxides(TM...Platinum(Pt)-based noble metal catalysts(PGMs)are the most widely used commercial catalysts,but they have the problems of high cost,low reserves,and susceptibility to small-molecule toxicity.Transition metal oxides(TMOs)are regarded as potential substitutes for PGMs because of their stability in oxidizing environments and excellent catalytic performance.In this study,comprehensive investigation into the influence of elastic strains on the adsorption energies of carbon(C),hydrogen(H)and oxygen(O)on TMOs was conducted.Based on density functional theory(DFT)calculations,these effects in both tetragonal structures(PtO_(2),PdO_(2))and hexagonal structures(ZnO,CdO),along with their respective transition metals were systematically explored.It was identified that the optimal adsorption sites on metal oxides pinpointed the top of oxygen or the top of metal atom,while face-centered cubic(FCC)and hexagonal close-packed(HCP)holes were preferred for the transition metals.Furthermore,under the influence of elastic strains,the results demonstrated significant disparities in the adsorption energies of H and O between oxides and transition metals.Despite these differences,the effect of elastic strains on the adsorption energies of C,H and O on TMOs mirrored those on transition metals:adsorption energies increased under compressive strains,indicating weaker adsorption,and decreased under tension strains,indicating stronger adsorption.This behavior was rationalized based on the d-band model for adsorption atop a metallic atom or the p-band model for adsorption atop an oxygen atom.Consequently,elastic strains present a promising avenue for tailoring the catalytic properties of TMOs.展开更多
The experimental research programs of 1950s, to understand the adsorption of CO on W surfaces, changed to ab initio studies in 2000s. The goals were to seek improved practical applications. Most of the studies were ba...The experimental research programs of 1950s, to understand the adsorption of CO on W surfaces, changed to ab initio studies in 2000s. The goals were to seek improved practical applications. Most of the studies were based on density functional theory. Many studies also used programs, such as VASP (Vienna Abinitio simulation package) and CPMD. The computational procedures used plane wave approximations. This needed studies with selection of K points and cutoff energy selection to assure convergence in energy calculations. Observations and analysis of papers published from 2006 to 2022 indicate that the cutoff energies were selected arbitrarily without any needed convergence studies. By selecting a published 2006 paper, this paper has clearly showed that an arbitrary selection of cutoff energy, such as 460 eV, is not in the range of, cutoff energies that assure convergence of energy calculations, with ab initio methods and have indicated correction procedures. .展开更多
Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate energies.Researchers urgently need solutions to the...Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate energies.Researchers urgently need solutions to the dilemma of traditional particle identification methods.This study explores the possibility of applying intelligent learning algorithms to the particle identification of heavy-ion collisions at low and intermediate energies.Multiple intelligent algorithms,including XgBoost and TabNet,were selected to test datasets from the neutron ion multi-detector for reaction-oriented dynamics(NIMROD-ISiS)and Geant4 simulation.Tree-based machine learning algorithms and deep learning algorithms e.g.TabNet show excellent performance and generalization ability.Adding additional data features besides energy deposition can improve the algorithm’s performance when the data distribution is nonuniform.Intelligent learning algorithms can be applied to solve the particle identification problem in heavy-ion collisions at low and intermediate energies.展开更多
The 28 nm process has a high cost-performance ratio and has gradually become the standard for the field of radiation-hardened devices.However,owing to the minimum physical gate length of only 35 nm,the physical area o...The 28 nm process has a high cost-performance ratio and has gradually become the standard for the field of radiation-hardened devices.However,owing to the minimum physical gate length of only 35 nm,the physical area of a standard 6T SRAM unit is approximately 0.16μm^(2),resulting in a significant enhancement of multi-cell charge-sharing effects.Multiple-cell upsets(MCUs)have become the primary physical mechanism behind single-event upsets(SEUs)in advanced nanometer node devices.The range of ionization track effects increases with higher ion energies,and spacecraft in orbit primarily experience SEUs caused by high-energy ions.However,ground accelerator experiments have mainly obtained low-energy ion irradiation data.Therefore,the impact of ion energy on the SEU cross section,charge collection mechanisms,and MCU patterns and quantities in advanced nanometer devices remains unclear.In this study,based on the experimental platform of the Heavy Ion Research Facility in Lanzhou,low-and high-energy heavy-ion beams were used to study the SEUs of 28 nm SRAM devices.The influence of ion energy on the charge collection processes of small-sensitive-volume devices,MCU patterns,and upset cross sections was obtained,and the applicable range of the inverse cosine law was clarified.The findings of this study are an important guide for the accurate evaluation of SEUs in advanced nanometer devices and for the development of radiation-hardening techniques.展开更多
Surface energies of five different surfaces of scheelite crystal were calculated using density functional theory （DFT）. Based on the calculation results, the predominantly exposed surfaces in the morphologies of sch...Surface energies of five different surfaces of scheelite crystal were calculated using density functional theory （DFT）. Based on the calculation results, the predominantly exposed surfaces in the morphologies of scheelite crystals were predicted. {112} and {001} cleavage surfaces and {112} crystal surface are the commonly exposed surfaces, which are consistent with both previous literatures and the present experimental observations based on the XRD. Cleavage generates more easily along {112} surfaces than along {001} surfaces due to their different interlayer spacings. The surface roughness and appearance of different predominantly exposed surfaces were then investigated using AFM. The roughness of smooth {112} cleavage surface is the lowest among these three surfaces. On {001} cleavage surface, terraces are flat and separated by steps of about 10 nm in height. Subsequently, contact angle measurements were adopted to evaluate the wettability and surface energies of these surfaces. The surface energies evaluated directly correspond to the trend calculated with DFT.展开更多
Based on the significance of renewable resources in relieving energy crisis,application of renewable resources for reducing energy consumption of rural housings and carbon emission of traditional energies are believed...Based on the significance of renewable resources in relieving energy crisis,application of renewable resources for reducing energy consumption of rural housings and carbon emission of traditional energies are believed as an inevitable choice for the construction of a conservation-minded society.Taking easily-acquired and low-cost solar energy,biomass energy and rainwater for example,strategies of applying renewable resources in rural housings are discussed.And the research focuses on the application of solar energy PV Power System and solar energy photo-thermal power system in rural residence,significance of power system such as methane and waste reusing for the integrated utilization of biomass energy and residence,and also recycling and cooling effects of intermediate water.展开更多
A structure relaxation model based on the empirical electron theory of solids and molecules is developed to compute the diffusion active energies of C, N in γFe. First, adding a restriction, the lattice maintains rig...A structure relaxation model based on the empirical electron theory of solids and molecules is developed to compute the diffusion active energies of C, N in γFe. First, adding a restriction, the lattice maintains rigidity when solute atom migrates to the saddle point. In this step, the hybridization classes of every atom do not change. Then, the restriction is loosed and the atoms are relaxed under the coulomb repulsive forces. It is supposed that the energy needed in the first step would be compensated partly by the second step. In this way, the diffusion active energies of C, N in γFe are computed. Compared with the experiment data, the relative errors are less than 5%, which are good results in the computation of activation energy of diffusion.展开更多
High-entropy materials represent a new category of high-performance materials,first proposed in 2004 and extensively investigated by researchers over the past two decades.The definition of high-entropy materials has c...High-entropy materials represent a new category of high-performance materials,first proposed in 2004 and extensively investigated by researchers over the past two decades.The definition of high-entropy materials has continuously evolved.In the last ten years,the discovery of an increasing number of high-entropy materials has led to significant advancements in their utilization in energy storage,electrocatalysis,and related domains,accompanied by a rise in techniques for fabricating high-entropy electrode materials.Recently,the research emphasis has shifted from solely improving the performance of high-entropy materials toward exploring their reaction mechanisms and adopting cleaner preparation approaches.However,the current definition of high-entropy materials remains relatively vague,and the preparation method of high-entropy materials is based on the preparation method of single metal/low-or medium-entropy materials.It should be noted that not all methods applicable to single metal/low-or medium-entropy materials can be directly applied to high-entropy materials.In this review,the definition and development of high-entropy materials are briefly reviewed.Subsequently,the classification of high-entropy electrode materials is presented,followed by a discussion of their applications in energy storage and catalysis from the perspective of synthesis methods.Finally,an evaluation of the advantages and disadvantages of various synthesis methods in the production process of different high-entropy materials is provided,along with a proposal for potential future development directions for high-entropy materials.展开更多
The conformers of allyl alcohol and allyl mercaptan were studied with B3LYP/aug-cc-pVTZ method. Their relative energies were calculated at MP3, MP4（SDQ）, and CCSD（T） levels. The most stable conformers for these tw...The conformers of allyl alcohol and allyl mercaptan were studied with B3LYP/aug-cc-pVTZ method. Their relative energies were calculated at MP3, MP4（SDQ）, and CCSD（T） levels. The most stable conformers for these two molecules are Gauche-gauche＇ （Gg＇）. The theo-retical photoelectron spectra simulated with the calculated ionization energies demonstrate that there are at least four conformers in allyl alcohol and four conformers in allyl mercaptan in the gas-phase experiments. The Dyson orbitals of the highest occupied molecular orbital （HOMO） and the next HOMO （HOMO-1） of allyl mercaptan Ggt conformer show strongly mixing ns and πc=c characteristics, which may be due to the resonance and inductive effects between πc=c and ns in HOMO-1 and HOMO.展开更多
Cells undergo metabolic reprogramming to adapt to changes in nutrient availability, cellular activity, and transitions in cell states. The balance between glycolysis and mitochondrial respiration is crucial for energy...Cells undergo metabolic reprogramming to adapt to changes in nutrient availability, cellular activity, and transitions in cell states. The balance between glycolysis and mitochondrial respiration is crucial for energy production, and metabolic reprogramming stipulates a shift in such balance to optimize both bioenergetic efficiency and anabolic requirements. Failure in switching bioenergetic dependence can lead to maladaptation and pathogenesis. While cellular degradation is known to recycle precursor molecules for anabolism, its potential role in regulating energy production remains less explored. The bioenergetic switch between glycolysis and mitochondrial respiration involves transcription factors and organelle homeostasis, which are both regulated by the cellular degradation pathways. A growing body of studies has demonstrated that both stem cells and differentiated cells exhibit bioenergetic switch upon perturbations of autophagic activity or endolysosomal processes. Here, we highlighted the current understanding of the interplay between degradation processes, specifically autophagy and endolysosomes, transcription factors, endolysosomal signaling, and mitochondrial homeostasis in shaping cellular bioenergetics. This review aims to summarize the relationship between degradation processes and bioenergetics, providing a foundation for future research to unveil deeper mechanistic insights into bioenergetic regulation.展开更多
Fourteen conformers of 3-amino-1-propanol as the minima on the potential energy surface are examined at the MP2/6-311＋＋G＊＊ level. Their relative energies calculated at B3LYP, MP3 and MP4 levels of theory indicated...Fourteen conformers of 3-amino-1-propanol as the minima on the potential energy surface are examined at the MP2/6-311＋＋G＊＊ level. Their relative energies calculated at B3LYP, MP3 and MP4 levels of theory indicated that two most stable conformers display the intramolecular OH - N hydrogen bonds. The vertical ionization energies of these conformers calculated with ab initio electron propagator theory in the P3/aug-cc-pVTZ approximation are in agreement with experimental data from photoelectron spectroscopy. Natural bond orbital analyses were used to explain the differences of IEs of the highest occupied molecular ortibal of conformers. Combined with statistical mechanics principles, conformational distributions at various temperatures are obtained and the temperature dependence of photoelectron spectra is interpreted.展开更多
文摘The global shift toward next-generation energy systems is propelled by the urgent need to combat climate change and the dwindling supply of fossil fuels.This review explores the intricate challenges and opportunities for transitioning to sustainable renewable energy sources such as solar,wind,and hydrogen.This transition economically challenges traditional energy sectors while fostering new industries,promoting job growth,and sustainable economic development.The transition to renewable energy demands social equity,ensuring universal access to affordable energy,and considering community impact.The environmental benefits include a significant reduction in greenhouse gas emissions and a lesser ecological footprint.This study highlights the rapid growth of the global wind power market,which is projected to increase from$112.23 billion in 2022 to$278.43 billion by 2030,with a compound annual growth rate of 13.67%.In addition,the demand for hydrogen is expected to increase,significantly impacting the market with potential cost reductions and making it a critical renewable energy source owing to its affordability and zero emissions.By 2028,renewables are predicted to account for 42%of global electricity generation,with significant contributions from wind and solar photovoltaic(PV)technology,particularly in China,the European Union,the United States,and India.These developments signify a global commitment to diversifying energy sources,reducing emissions,and moving toward cleaner and more sustainable energy solutions.This review offers stakeholders the insights required to smoothly transition to sustainable energy,setting the stage for a resilient future.
基金the National Key R&D Program of China(No.2023YFA1606503)the National Natural Science Foundation of China(Nos.12035011,11975167,11947211,11905103,11881240623,and 11961141003).
文摘Reliable calculations of nuclear binding energies are crucial for advancing the research of nuclear physics. Machine learning provides an innovative approach to exploring complex physical problems. In this study, the nuclear binding energies are modeled directly using a machine-learning method called the Gaussian process. First, the binding energies for 2238 nuclei with Z > 20 and N > 20 are calculated using the Gaussian process in a physically motivated feature space, yielding an average deviation of 0.046 MeV and a standard deviation of 0.066 MeV. The results show the good learning ability of the Gaussian process in the studies of binding energies. Then, the predictive power of the Gaussian process is studied by calculating the binding energies for 108 nuclei newly included in AME2020. The theoretical results are in good agreement with the experimental data, reflecting the good predictive power of the Gaussian process. Moreover, the α-decay energies for 1169 nuclei with 50 ≤ Z ≤ 110 are derived from the theoretical binding energies calculated using the Gaussian process. The average deviation and the standard deviation are, respectively, 0.047 MeV and 0.070 MeV. Noticeably, the calculated α-decay energies for the two new isotopes ^ (204 )Ac(Huang et al. Phys Lett B 834, 137484(2022)) and ^ (207) Th(Yang et al. Phys Rev C 105, L051302(2022)) agree well with the latest experimental data. These results demonstrate that the Gaussian process is reliable for the calculations of nuclear binding energies. Finally, the α-decay properties of some unknown actinide nuclei are predicted using the Gaussian process. The predicted results can be useful guides for future research on binding energies and α-decay properties.
基金supported by the National Natural Science Foundation of China(No.52488201)the Natural Science Basic Research Program of Shaanxi(No.2024JC-YBMS-284)+1 种基金the Key Research and Development Program of Shaanxi(No.2024GHYBXM-02)the Fundamental Research Funds for the Central Universities.
文摘Machine learning combined with density functional theory(DFT)enables rapid exploration of catalyst descriptors space such as adsorption energy,facilitating rapid and effective catalyst screening.However,there is still a lack of models for predicting adsorption energies on oxides,due to the complexity of elemental species and the ambiguous coordination environment.This work proposes an active learning workflow(LeNN)founded on local electronic transfer features(e)and the principle of coordinate rotation invariance.By accurately characterizing the electron transfer to adsorption site atoms and their surrounding geometric structures,LeNN mitigates abrupt feature changes due to different element types and clarifies coordination environments.As a result,it enables the prediction of^(*)H adsorption energy on binary oxide surfaces with a mean absolute error(MAE)below 0.18 eV.Moreover,we incorporate local coverage(θ_(l))and leverage neutral network ensemble to establish an active learning workflow,attaining a prediction MAE below 0.2 eV for 5419 multi-^(*)H adsorption structures.These findings validate the universality and capability of the proposed features in predicting^(*)H adsorption energy on binary oxide surfaces.
基金Science and Technology Commission of Shanghai Municipality(21ZR1472900,22ZR1471600)。
文摘Platinum(Pt)-based noble metal catalysts(PGMs)are the most widely used commercial catalysts,but they have the problems of high cost,low reserves,and susceptibility to small-molecule toxicity.Transition metal oxides(TMOs)are regarded as potential substitutes for PGMs because of their stability in oxidizing environments and excellent catalytic performance.In this study,comprehensive investigation into the influence of elastic strains on the adsorption energies of carbon(C),hydrogen(H)and oxygen(O)on TMOs was conducted.Based on density functional theory(DFT)calculations,these effects in both tetragonal structures(PtO_(2),PdO_(2))and hexagonal structures(ZnO,CdO),along with their respective transition metals were systematically explored.It was identified that the optimal adsorption sites on metal oxides pinpointed the top of oxygen or the top of metal atom,while face-centered cubic(FCC)and hexagonal close-packed(HCP)holes were preferred for the transition metals.Furthermore,under the influence of elastic strains,the results demonstrated significant disparities in the adsorption energies of H and O between oxides and transition metals.Despite these differences,the effect of elastic strains on the adsorption energies of C,H and O on TMOs mirrored those on transition metals:adsorption energies increased under compressive strains,indicating weaker adsorption,and decreased under tension strains,indicating stronger adsorption.This behavior was rationalized based on the d-band model for adsorption atop a metallic atom or the p-band model for adsorption atop an oxygen atom.Consequently,elastic strains present a promising avenue for tailoring the catalytic properties of TMOs.
文摘The experimental research programs of 1950s, to understand the adsorption of CO on W surfaces, changed to ab initio studies in 2000s. The goals were to seek improved practical applications. Most of the studies were based on density functional theory. Many studies also used programs, such as VASP (Vienna Abinitio simulation package) and CPMD. The computational procedures used plane wave approximations. This needed studies with selection of K points and cutoff energy selection to assure convergence in energy calculations. Observations and analysis of papers published from 2006 to 2022 indicate that the cutoff energies were selected arbitrarily without any needed convergence studies. By selecting a published 2006 paper, this paper has clearly showed that an arbitrary selection of cutoff energy, such as 460 eV, is not in the range of, cutoff energies that assure convergence of energy calculations, with ab initio methods and have indicated correction procedures. .
基金This work was supported by the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDB34030000)the National Key Research and Development Program of China(No.2022YFA1602404)+1 种基金the National Natural Science Foundation(No.U1832129)the Youth Innovation Promotion Association CAS(No.2017309).
文摘Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate energies.Researchers urgently need solutions to the dilemma of traditional particle identification methods.This study explores the possibility of applying intelligent learning algorithms to the particle identification of heavy-ion collisions at low and intermediate energies.Multiple intelligent algorithms,including XgBoost and TabNet,were selected to test datasets from the neutron ion multi-detector for reaction-oriented dynamics(NIMROD-ISiS)and Geant4 simulation.Tree-based machine learning algorithms and deep learning algorithms e.g.TabNet show excellent performance and generalization ability.Adding additional data features besides energy deposition can improve the algorithm’s performance when the data distribution is nonuniform.Intelligent learning algorithms can be applied to solve the particle identification problem in heavy-ion collisions at low and intermediate energies.
基金supported by the National Natural Science Foundation of China(Nos.12105341 and 12035019)the opening fund of Key Laboratory of Silicon Device and Technology,Chinese Academy of Sciences(No.KLSDTJJ2022-3).
文摘The 28 nm process has a high cost-performance ratio and has gradually become the standard for the field of radiation-hardened devices.However,owing to the minimum physical gate length of only 35 nm,the physical area of a standard 6T SRAM unit is approximately 0.16μm^(2),resulting in a significant enhancement of multi-cell charge-sharing effects.Multiple-cell upsets(MCUs)have become the primary physical mechanism behind single-event upsets(SEUs)in advanced nanometer node devices.The range of ionization track effects increases with higher ion energies,and spacecraft in orbit primarily experience SEUs caused by high-energy ions.However,ground accelerator experiments have mainly obtained low-energy ion irradiation data.Therefore,the impact of ion energy on the SEU cross section,charge collection mechanisms,and MCU patterns and quantities in advanced nanometer devices remains unclear.In this study,based on the experimental platform of the Heavy Ion Research Facility in Lanzhou,low-and high-energy heavy-ion beams were used to study the SEUs of 28 nm SRAM devices.The influence of ion energy on the charge collection processes of small-sensitive-volume devices,MCU patterns,and upset cross sections was obtained,and the applicable range of the inverse cosine law was clarified.The findings of this study are an important guide for the accurate evaluation of SEUs in advanced nanometer devices and for the development of radiation-hardening techniques.
基金Project(50831006)supported by the National Natural Science Foundation of ChinaProject(CX2011B122)supported by Hunan Provincial Innovation Foundation for Postgraduate,ChinaProject(2012BAB10B05)supported by the National Key Technologies R&D Program of China
文摘Surface energies of five different surfaces of scheelite crystal were calculated using density functional theory （DFT）. Based on the calculation results, the predominantly exposed surfaces in the morphologies of scheelite crystals were predicted. {112} and {001} cleavage surfaces and {112} crystal surface are the commonly exposed surfaces, which are consistent with both previous literatures and the present experimental observations based on the XRD. Cleavage generates more easily along {112} surfaces than along {001} surfaces due to their different interlayer spacings. The surface roughness and appearance of different predominantly exposed surfaces were then investigated using AFM. The roughness of smooth {112} cleavage surface is the lowest among these three surfaces. On {001} cleavage surface, terraces are flat and separated by steps of about 10 nm in height. Subsequently, contact angle measurements were adopted to evaluate the wettability and surface energies of these surfaces. The surface energies evaluated directly correspond to the trend calculated with DFT.
文摘Based on the significance of renewable resources in relieving energy crisis,application of renewable resources for reducing energy consumption of rural housings and carbon emission of traditional energies are believed as an inevitable choice for the construction of a conservation-minded society.Taking easily-acquired and low-cost solar energy,biomass energy and rainwater for example,strategies of applying renewable resources in rural housings are discussed.And the research focuses on the application of solar energy PV Power System and solar energy photo-thermal power system in rural residence,significance of power system such as methane and waste reusing for the integrated utilization of biomass energy and residence,and also recycling and cooling effects of intermediate water.
文摘A structure relaxation model based on the empirical electron theory of solids and molecules is developed to compute the diffusion active energies of C, N in γFe. First, adding a restriction, the lattice maintains rigidity when solute atom migrates to the saddle point. In this step, the hybridization classes of every atom do not change. Then, the restriction is loosed and the atoms are relaxed under the coulomb repulsive forces. It is supposed that the energy needed in the first step would be compensated partly by the second step. In this way, the diffusion active energies of C, N in γFe are computed. Compared with the experiment data, the relative errors are less than 5%, which are good results in the computation of activation energy of diffusion.
基金supported by the National Natural Science Foundation of China(22378431,52004338,51622406,21673298)Hunan Provincial Natural Science Foundation(2023JJ40210,2022JJ20075)+3 种基金the Science and Technology Innovation Program of Hunan Province(2023RC3259)the Key R&D plan of Hunan Province(2024JK2096)Scientifc Research Fund of Hunan Provincial Education Department(23B0699)Central South University Innovation-Driven Research Programme(2023CXQD008).
文摘High-entropy materials represent a new category of high-performance materials,first proposed in 2004 and extensively investigated by researchers over the past two decades.The definition of high-entropy materials has continuously evolved.In the last ten years,the discovery of an increasing number of high-entropy materials has led to significant advancements in their utilization in energy storage,electrocatalysis,and related domains,accompanied by a rise in techniques for fabricating high-entropy electrode materials.Recently,the research emphasis has shifted from solely improving the performance of high-entropy materials toward exploring their reaction mechanisms and adopting cleaner preparation approaches.However,the current definition of high-entropy materials remains relatively vague,and the preparation method of high-entropy materials is based on the preparation method of single metal/low-or medium-entropy materials.It should be noted that not all methods applicable to single metal/low-or medium-entropy materials can be directly applied to high-entropy materials.In this review,the definition and development of high-entropy materials are briefly reviewed.Subsequently,the classification of high-entropy electrode materials is presented,followed by a discussion of their applications in energy storage and catalysis from the perspective of synthesis methods.Finally,an evaluation of the advantages and disadvantages of various synthesis methods in the production process of different high-entropy materials is provided,along with a proposal for potential future development directions for high-entropy materials.
文摘The conformers of allyl alcohol and allyl mercaptan were studied with B3LYP/aug-cc-pVTZ method. Their relative energies were calculated at MP3, MP4（SDQ）, and CCSD（T） levels. The most stable conformers for these two molecules are Gauche-gauche＇ （Gg＇）. The theo-retical photoelectron spectra simulated with the calculated ionization energies demonstrate that there are at least four conformers in allyl alcohol and four conformers in allyl mercaptan in the gas-phase experiments. The Dyson orbitals of the highest occupied molecular orbital （HOMO） and the next HOMO （HOMO-1） of allyl mercaptan Ggt conformer show strongly mixing ns and πc=c characteristics, which may be due to the resonance and inductive effects between πc=c and ns in HOMO-1 and HOMO.
文摘Cells undergo metabolic reprogramming to adapt to changes in nutrient availability, cellular activity, and transitions in cell states. The balance between glycolysis and mitochondrial respiration is crucial for energy production, and metabolic reprogramming stipulates a shift in such balance to optimize both bioenergetic efficiency and anabolic requirements. Failure in switching bioenergetic dependence can lead to maladaptation and pathogenesis. While cellular degradation is known to recycle precursor molecules for anabolism, its potential role in regulating energy production remains less explored. The bioenergetic switch between glycolysis and mitochondrial respiration involves transcription factors and organelle homeostasis, which are both regulated by the cellular degradation pathways. A growing body of studies has demonstrated that both stem cells and differentiated cells exhibit bioenergetic switch upon perturbations of autophagic activity or endolysosomal processes. Here, we highlighted the current understanding of the interplay between degradation processes, specifically autophagy and endolysosomes, transcription factors, endolysosomal signaling, and mitochondrial homeostasis in shaping cellular bioenergetics. This review aims to summarize the relationship between degradation processes and bioenergetics, providing a foundation for future research to unveil deeper mechanistic insights into bioenergetic regulation.
基金This work was supported by the Province Natural Science Foundation of Henan （No.082300410030）, the Foundation of Henan Educational Committee （No.2011A140015）, and the Doctoral Research Pund of Henan Normal University （No.525449）.
文摘Fourteen conformers of 3-amino-1-propanol as the minima on the potential energy surface are examined at the MP2/6-311＋＋G＊＊ level. Their relative energies calculated at B3LYP, MP3 and MP4 levels of theory indicated that two most stable conformers display the intramolecular OH - N hydrogen bonds. The vertical ionization energies of these conformers calculated with ab initio electron propagator theory in the P3/aug-cc-pVTZ approximation are in agreement with experimental data from photoelectron spectroscopy. Natural bond orbital analyses were used to explain the differences of IEs of the highest occupied molecular ortibal of conformers. Combined with statistical mechanics principles, conformational distributions at various temperatures are obtained and the temperature dependence of photoelectron spectra is interpreted.
