Approaching Ultimate Synthesis Reaction Rate of Ni-Rich Layered Cathodes for Lithium-Ion Batteries

Nickel-rich layered oxide LiNi_(x)Co_(y)MnzO_(2)(NCM,x+y+z=1)is the most promising cathode material for high-energy lithium-ion batteries.However,conventional synthesis methods are limited by the slow heating rate,sluggish reaction dynamics,high energy consumption,and long reaction time.To overcome these chal-lenges,we first employed a high-temperature shock(HTS)strategy for fast synthesis of the NCM,and the approaching ultimate reaction rate of solid phase transition is deeply investigated for the first time.In the HTS process,ultrafast average reaction rate of phase transition from Ni_(0.6)Co_(0.2)Mn_(0.2)(OH)_(2) to Li-containing oxides is 66.7(%s^(-1)),that is,taking only 1.5 s.An ultrahigh heating rate leads to fast reaction kinetics,which induces the rapid phase transition of NCM cathodes.The HTS-synthesized nickel-rich layered oxides perform good cycling performances(94%for NCM523,94%for NCM622,and 80%for NCM811 after 200 cycles at 4.3 V).These findings might also assist to pave the way for preparing effectively Ni-rich layered oxides for lithium-ion batteries.

Microstructure and Properties of Fe-Based Coating on Column Surface Formed by High Frequency Induction Cladding

The Fe-based coating was produced on the surface of the column substrate with a Al2O3 cylindrical sleeve by high frequency induction cladding, microstructure of the coating was investigated with scanning electron microscope (SEM), the crystal structure was characterized by X-ray diffractometer (XRD), the microhardness and wear resisitance of the coating were evaluated. The results show that a metallurgical bond between coating and substrate was obtained during the rapid solidification, the phases of the coating were composed of austenite and the eutectic of γ-Fe + (Cr, Fe)7(C, B)3. Compared with the substrate, the microhardness and wear resistance of the coating improved apparently, solid-solution strengthening and second-phase particle hardening led to these results.

Thermal transport in phosphorene and phosphorene-based materials:A review on numerical studies

The recently discovered two-dimensional(2D)layered material phosphorene has attracted considerable interest as a promising p-type semiconducting material.In this article,we review the recent advances in numerical studies of the ther-mal properties of monolayer phosphorene and phosphorene-based heterostructures.We first briefly review the commonly used first-principles and molecular dynamics(MD)approaches to evaluate the thermal conductivity and interfacial thermal resistance of 2D phosphorene.Principles of different steady-state and transient MD techniques have been elaborated on in detail.Next,we discuss the anisotropic thermal transport of phosphorene in zigzag and armchair chiral directions.Subse-quently,the in-plane and cross-plane thermal transport in phosphorene-based heterostructures such as phosphorene/silicon and phosphorene/graphene is summarized.Finally,the numerical research in the field of thermal transport in 2D phospho-rene is highlighted along with our perspective of potentials and opportunities of 2D phosphorenes in electronic applications such as photodetectors,field-effect transistors,lithium ion batteries,sodium ion batteries,and thermoelectric devices.

Boosting cycling stability by regulating surface oxygen vacancies of LNMO by rapid calcination

Spinel LiNi_(0.5-x)Mn_(1.5+x)O_(4)(LNMO)has attracted intensive interest for lithium-ion battery due to its high voltage and high energy density.However,severe capacity fade attributed to unstable surface structure has hampered its commercialization.Oxygen vacancies(OVs)tend to occur in the surface of the material and lead to surface structure reconstruction,which deteriorates the battery performance during electrochemical cycling.Here,we utilize high-temperature-shock(HTS)method to synthesize LNMO materials with fewer surface OVs.Rapid calcination drives lower surface OVs concentration,reducing the content of Mn^(3+)and surface reconstruction layers,which is beneficial to obtain a stable crystal structure.The LNMO material synthesized by HTS method delivers an initial capacity of 127 mAh·g^(-1) at 0.1 C and capacity retention of 81.6%after 300 cycles at 1 C,and exhibits excellent performance at low temperature.

A reduced-order model for fast predicting ionized flows of hypersonic vehicles along flight trajectory

An improved Reduced-Order Model(ROM)is proposed based on a flow-solution preprocessing operation and a fast sampling strategy to efficiently and accurately predict ionized hypersonic flows.This ROM is generated in low-dimensional space by performing the Proper Orthogonal Decomposition(POD)on snapshots and is coupled with the Radial Basis Function(RBF)to achieve fast prediction speed.However,due to the disparate scales in the ionized flow field,the conventional ROM usually generates spurious negative errors.Here,this issue is addressed by performing flow-solution preprocessing in logarithmic space to improve the conventional ROM.Then,extra orthogonal polynomials are introduced in the RBF interpolation to achieve additional improvement of the prediction accuracy.In addition,to construct high-efficiency snapshots,a trajectory-constrained adaptive sampling strategy based on convex hull optimization is developed.To evaluate the performance of the proposed fast prediction method,two hypersonic vehicles with classic configurations,i.e.a wave-rider and a reentry capsule,are used to validate the proposed method.Both two cases show that the proposed fast prediction method has high accuracy near the vehicle surface and the free-stream region where the flow field is smooth.Compared with the conventional ROM prediction,the prediction results are significantly improved by the proposed method around the discontinuities,e.g.the shock wave and the ionized layer.As a result,the proposed fast prediction method reduces the error of the conventional ROM by at least 45%,with a speedup of approximately 2.0×105compared to the Computational Fluid Dynamic(CFD)simulations.These test cases demonstrate that the method developed here is efficient and accurate for predicting ionized hypersonic flows.

Recycle spent graphite to defect-engineered,high-power graphite anode

Graphite is a dominant anode material for lithium-ion batteries(LIBs)due to its outstanding electrochemical performance.However,slow lithium ion(Li+)kinetics of graphite anode restricts its further application.Herein,we report that high-temperature shock(HTS)can drive spent graphite(SG)into defect-rich recycled graphite(DRG)which is ideal for high-rate anode.The DRG exhibits the charging specific capacity of 323 mAh/g at a high current density of 2 C,which outperforms commercial graphite(CG,120 mAh/g).The eminent electrochemical performance of DRG can be attributed to the recovery of layered structure and partial remaining defects of SG during ultrafast heating and cooling process,which can effectively reduce total strain energy,accelerate the phase transition in thermodynamics and improve the Li+diffusion.This study provides a facile strategy to guide the re-graphitization of SG and design high performance battery electrode materials by defect engineering from the atomic level.

Cryo-EM for nanomaterials:Progress and perspective

Cryogenic electron microscopy(cryo-EM)has extensively boosted structural biology research since the“resolution revolution”in the year of 2013 which was soon awarded the Nobel Prize in Chemistry in 2017.The advances in camera techniques and software algorithms enabled cryoEM to routinely characterize the three-dimensional structures of biomolecules at near-atomic resolution.Biomolecules are basically sensitive to electron irradiation damage,which can be minimized at cryo-temperature.This principle has inspired material scientists to characterize electron beam-or air-sensitive materials by cryo-EM,such as the electrodes in the lithium-ion battery,metal-organic frameworks(MOFs),covalent-organic frameworks(COFs)and zeolites.In addition,the reaction systems can be fast-frozen at vitreous ice in cryoEM,which correspondingly preserves the materials at the close-to-native state.Herein,we summarized the development and applications of both the cryo-EM technique and other emerging cryo-techniques in materials science,and energy storage and conversion.Cryo-EM techniques,capable of the direct observation of sensitive materials and electrochemical reaction processes,will greatly renew our understanding of materials science and related mechanisms.

Predicting Total Dwell Time of IPSA Plan Based on Machine Learning and Dose Calculation Models

Objective To establish two models based on machine learning and dose calculation algorithm that can be used for the prediction of the total dwell time and rapid quality control of brachytherapy plans.Methods A total of 1042 cases of treated gynecologic oncology patients were selected,of which 512 were used as training data to establish the model and the rest were used as test data.Each treatment plan optimized by inverse planning simulated annealing with all three catheters of the Fletcher applicator.The source strength Sk,prescription dose D,source dwell time t,and tumor volume V were recorded for each case.RV was defined as Sk·t/D.In accordance with the prescription dosage calculation formula in the planning system and machine learning method,the following equations were established:RV=kV2/3 and RV=a+b · V+c·V2.The R2 correlation coefficient represents the accuracy of the results.Result The dose calculation algorithm-based model is RV=1272×V2/3,R2=0.959,whereas the machine learning-based model is RV=258.8× V-0.359× V2+5110,R2=0.961.The treatment time prediction of the two models,each having 13 and 15 cases,respectively,has an error rate of more than10%,and the dose calculation algorithm-based method is more accurate.Conclusion The treatment time can be quickly predicted according to the planning target volume,and the two prediction models can be used as a way of quality control.