Thermodynamic equilibrium theory-guided design and synthesis of Mg-doped LiFe_(0.4)Mn_(0.6)PO_(4)/C cathode for lithium-ion batteries

Mn-rich LiFe_(1-x)Mn_(x)PO_(4)(x>0.5),which combines the high operation voltage of LiMnPO_(4)with excellent rate performa nce of LiFePO4,is hindered by its sluggish kinetic properties.Herein,thermodynamic equilibrium analysis of Mn^(2+)-Fe^(2+)-Mg^(2+)-C_(2)O_(4)^(2-)-H_(2)O system is used to guide the design and preparation of insitu Mg-doped(Fe_(0.4)Mn_(0.6))_(1-x)Mg_(x)C_(2)O_(4)intermediate,which is then employed as an innovative precursor to synthesize high-performance Mg-doped LiFe_(0.4)Mn_(0.6)PO_(4).It indicates that the metal ions with a high precipitation efficiency and the stoichiometric precursors with uniform element distribution can be achieved under the optimized thermodynamic conditions.Meanwhile,accelerated Li+diffusivity and reduced charge transfer resistance originating from Mg doping are verified by various kinetic characterizations.Benefiting from the contributions of inherited homogeneous element distribution,small particle size,uniform carbon layer coating,enhanced Li+migration ability and structural stability induced by Mg doping,the Li(Fe_(0.4)Mn_(0.6))_(0.97)Mg_(0.03)PO_(4)/C exhibits splendid electrochemical performance.

ASSIMILATION OF OBSERVED SURFACE WIND WITH GRAPES

With the advances of numerical weather simulation and reduced data assimilation updating cycle, surface observation data assimilation becomes more and more important in data assimilation systems It is widely accepted that a better data assimilation system should contain the restriction of thermod^amic processes in the surface layer. Therefore, in this paper, a new surface wind observation operator is utilized in Global and Regional Assimilation PrEdiction System_3D-Variance （GRAPES_3D-Var）, with the restriction of thermodynamic process in the planetary boundary layer （PBL）. In order to research the ability of this new surface wind observation operator in assimilation and forecasting, a series of experiments are operated by using the GRAPES model. The main results indicate that this new method of surface wind observation operator has positive impact on the forecast with the GRAPES model.