Lithium-ion batteries are essential for renewable energy storage,necessitating efficient battery management systems(BMS)for optimal performance and longevity.Accurate estimation of the state of health(SOH)is crucial f...Lithium-ion batteries are essential for renewable energy storage,necessitating efficient battery management systems(BMS)for optimal performance and longevity.Accurate estimation of the state of health(SOH)is crucial for BMS safety,yet current machine learning-based SOH estimation relying on global aging features often overlooks localized degradation patterns.In this study,we introduce a novel SOH estimation pipeline that integrates voltage-range-specific segmentation with a multi-stage,crossvalidation-driven localized feature-selection framework and a feature-augmented dual-stream fusion network.Our methodology partitions full-range voltage into localized intervals to construct a degradation-sensitive feature library,from which 4 optimal features are identified from a set of 336 candidates.These selected features are combined with raw voltage signals via a dual-stream architecture that employs a dynamic gating mechanism to recalibrate feature contributions during training.Crossvalidation-based evaluation on datasets encompassing different chemistries and charge/discharge protocols demonstrate that our approach can achieve lower average root-mean-square-error(Oxford dataset:0.7201%,Massachusetts Institute of Technology(MIT)dataset:0.7184%)compared to baseline models.An in-depth analysis of the physical significance of the screened features improves the interpretability of the features.This work underscores the significant potential of leveraging localized feature enhancement in SOH estimation by systematically integrating degradation-sensitive features,thereby offering precise estimation.展开更多
To achieve high-energy-density and safe lithium-metal batteries(LMBs),solid-state electrolytes(SSEs)that exhibit fast Li-ion conductivity and good stability against lithium metal are of great importance.This study pre...To achieve high-energy-density and safe lithium-metal batteries(LMBs),solid-state electrolytes(SSEs)that exhibit fast Li-ion conductivity and good stability against lithium metal are of great importance.This study presents a systematic exploration of selenide-based materials as potential SSE candidates.Initially,Li_(8)SeN_(2)and Li_(7)PSe_(6)were selected from 25 ternary selenides based on their ability to form stable interfaces with lithium metal.Subsequently,their favorable electronic insulation and mechanical properties were verified.Furthermore,extensive theoretical investigations were conducted to elucidate the fundamental mechanisms underlying Li-ion migration in Li_(8)SeN_(2),Li_(7)PSe_(6),and derived Li_(6)PSe_(5)X(X=Cl,Br,I).Notably,the highly favorable Li-ion conduction mechanism of vacancy diffusion was identified in Li6PSe5Cl and Li_(7)PSe_(6),which exhibited remarkably low activation energies of 0.21 and 0.23 eV,and conductivity values of 3.85×10^(-2)and 2.47×10^(-2)S cm^(-1)at 300 K,respectively.In contrast,Li-ion migration in Li_(8)SeN_(2)was found to occur via a substitution mechanism with a significant diffusion energy barrier,resulting in a high activation energy and low Li-ion conductivity of 0.54 eV and 3.6×10^(-6)S cm^(-1),respectively.Throughout this study,it was found that the ab initio molecular dynamics and nudged elastic band methods are complementary in revealing the Li-ion conduction mechanisms.Utilizing both methods proved to be efficient,as relying on only one of them would be insufficient.The discoveries made and methodology presented in this work lay a solid foundation and provide valuable insights for future research on SSEs for LMBs.展开更多
Grain size,characterized by a combination of grain length,width,and thickness,is one of the major determinants of yield in rice.The present study identified TATA-box binding protein-associated factor 2(TAF2)as an esse...Grain size,characterized by a combination of grain length,width,and thickness,is one of the major determinants of yield in rice.The present study identified TATA-box binding protein-associated factor 2(TAF2)as an essential component regulating transcription and determining grain size in rice.Map-based cloning showed that a G/T substitution in TAF2 resulted in a naturally occurring mutant called reduced grain size and plant height 1(rgh1).The mutants,with weak edited rgh1 alleles,exhibited a small grain phenotype with reduced grain length and width,while the severe knockout mutant(rgh1-2s)was dwarf and completely sterile.Allelic test performed between rgh1 and several edited alleles confirmed that the mutation in TAF2 caused the rgh1 phenotype.GUS staining showed that TAF2 was mainly expressed in the vascular bundles of roots,stems,leaves,and grains.The cytological analysis revealed that reduced cell division in the glumes resulted in the small grain phenotype of rgh1.Further RNA-sequencing detected altered expression of genes involved in the basic biological processes in rgh1 mutant.These findings provide novel insights into the TAF2-mediated genetic mechanism regulating grain size in rice.展开更多
基金financially supported by the National Natural Science Foundation of China(22273096)the International Postdoctoral Exchange Fellowship Program between Helmholtz and OCPC(ZD2023019)+1 种基金the Young Scientists Fund of the National Natural Science Foundation of China(Grant No.22409139)the Sichuan Provincial Natural Science Foundation for Young Scientists(24NSFSC607)。
文摘Lithium-ion batteries are essential for renewable energy storage,necessitating efficient battery management systems(BMS)for optimal performance and longevity.Accurate estimation of the state of health(SOH)is crucial for BMS safety,yet current machine learning-based SOH estimation relying on global aging features often overlooks localized degradation patterns.In this study,we introduce a novel SOH estimation pipeline that integrates voltage-range-specific segmentation with a multi-stage,crossvalidation-driven localized feature-selection framework and a feature-augmented dual-stream fusion network.Our methodology partitions full-range voltage into localized intervals to construct a degradation-sensitive feature library,from which 4 optimal features are identified from a set of 336 candidates.These selected features are combined with raw voltage signals via a dual-stream architecture that employs a dynamic gating mechanism to recalibrate feature contributions during training.Crossvalidation-based evaluation on datasets encompassing different chemistries and charge/discharge protocols demonstrate that our approach can achieve lower average root-mean-square-error(Oxford dataset:0.7201%,Massachusetts Institute of Technology(MIT)dataset:0.7184%)compared to baseline models.An in-depth analysis of the physical significance of the screened features improves the interpretability of the features.This work underscores the significant potential of leveraging localized feature enhancement in SOH estimation by systematically integrating degradation-sensitive features,thereby offering precise estimation.
基金financially supported by the National Natural Science Foundation of China(Grant No.22273096)the Fundamental Research Funds for Central Universities(20826041G4185)
文摘To achieve high-energy-density and safe lithium-metal batteries(LMBs),solid-state electrolytes(SSEs)that exhibit fast Li-ion conductivity and good stability against lithium metal are of great importance.This study presents a systematic exploration of selenide-based materials as potential SSE candidates.Initially,Li_(8)SeN_(2)and Li_(7)PSe_(6)were selected from 25 ternary selenides based on their ability to form stable interfaces with lithium metal.Subsequently,their favorable electronic insulation and mechanical properties were verified.Furthermore,extensive theoretical investigations were conducted to elucidate the fundamental mechanisms underlying Li-ion migration in Li_(8)SeN_(2),Li_(7)PSe_(6),and derived Li_(6)PSe_(5)X(X=Cl,Br,I).Notably,the highly favorable Li-ion conduction mechanism of vacancy diffusion was identified in Li6PSe5Cl and Li_(7)PSe_(6),which exhibited remarkably low activation energies of 0.21 and 0.23 eV,and conductivity values of 3.85×10^(-2)and 2.47×10^(-2)S cm^(-1)at 300 K,respectively.In contrast,Li-ion migration in Li_(8)SeN_(2)was found to occur via a substitution mechanism with a significant diffusion energy barrier,resulting in a high activation energy and low Li-ion conductivity of 0.54 eV and 3.6×10^(-6)S cm^(-1),respectively.Throughout this study,it was found that the ab initio molecular dynamics and nudged elastic band methods are complementary in revealing the Li-ion conduction mechanisms.Utilizing both methods proved to be efficient,as relying on only one of them would be insufficient.The discoveries made and methodology presented in this work lay a solid foundation and provide valuable insights for future research on SSEs for LMBs.
基金supported by the National Natural Science Foundation of China(31971918 and 32070348)the Chinese Academy of Sciences Innovation Project(XDA24010402).
文摘Grain size,characterized by a combination of grain length,width,and thickness,is one of the major determinants of yield in rice.The present study identified TATA-box binding protein-associated factor 2(TAF2)as an essential component regulating transcription and determining grain size in rice.Map-based cloning showed that a G/T substitution in TAF2 resulted in a naturally occurring mutant called reduced grain size and plant height 1(rgh1).The mutants,with weak edited rgh1 alleles,exhibited a small grain phenotype with reduced grain length and width,while the severe knockout mutant(rgh1-2s)was dwarf and completely sterile.Allelic test performed between rgh1 and several edited alleles confirmed that the mutation in TAF2 caused the rgh1 phenotype.GUS staining showed that TAF2 was mainly expressed in the vascular bundles of roots,stems,leaves,and grains.The cytological analysis revealed that reduced cell division in the glumes resulted in the small grain phenotype of rgh1.Further RNA-sequencing detected altered expression of genes involved in the basic biological processes in rgh1 mutant.These findings provide novel insights into the TAF2-mediated genetic mechanism regulating grain size in rice.
