Solvation Structure and Dynamics of Mg(TFSI)_(2) Aqueous Electrolyte

Using ab initio molecular dynamics(AIMD)simulations,classical molecular dynamics(CMD)simulations,small-angle X-ray scattering(SAXS),and pulsed-field gradient nuclear magnetic resonance(PFG-NMR),the solvation structure and ion dynamics of magnesium bis(trifluoromethanesulfonyl)imide(Mg(TFSI)_(2))aqueous electrolyte at 1,2,and 3 m concentrations are investigated.From AIMD and CMD simulations,the first solvation shell of an Mg;ion is found to be composed of six water molecules in an octahedral configuration and the solvation shell is rather rigid.The TFSI^(-)ions prefer to stay in the second solvation shell and beyond.Meanwhile,the comparable diffusion coefficients of positive and negative ions in Mg(TFSI)_(2)aqueous electrolytes have been observed,which is mainly due to the formation of the stable[Mg(H_(2)O_(6))_(2)]^(+)complex,and,as a result,the increased effective Mg ion size.Finally,the calculated correlated transference numbers are lower than the uncorrelated ones even at the low concentration of 2 and 3 m,suggesting the enhanced correlations between ions in the multivalent electrolytes.This work provides a molecular-level understanding of how the solvation structure and multivalency of the ion affect the dynamics and transport properties of the multivalent electrolyte,providing insight for rational designs of electrolytes for improved ion transport properties.

Hydrogen energy carriers

The versatility of hydrogen will provide opportunities in large scale,long duration energy storage,and the decarbonization of industry.Hydrogen energy carriers are molecules and materials that store hydrogen at higher volumetric density than possible using gas phase hydrogen.

LiCoO_(2) Epitaxial Film Enabling Precise Analysis of Interfacial Degradations

Interfacial structure evolution and degradation are critical to the electrochemical performance of LiCoO_(2)(LCO),the most widely studied and used cathode material in lithium ion batteries.To understand such processes requires precise and quantitative measurements.Herein,we use well-defined epitaxial LCO thin films to reveal the interfacial degradation mechanisms.Through our systematical investigations,we find that surface corrosion is significant after forming the surface phase transition layer,and the cathode electrolyte interphase(CEI)has a double layer structure,an inorganic inner layer containing CoO,LiF,LiOH/Li_(2)O and Li_(x)PF_(y)O_(2),and an outmost layer containing Li2CO_(3) and organic carbonaceous components.Furthermore,surface cracks are found to be pronounced due to mechanical failures and chemical etching.This work demonstrates a model material to realize the precise measurements of LCO interfacial degradations,which deepens our understanding on the interfacial degradation mechanisms.

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems.However,the present paradigm involves time-intensive manual analysis that is inherently biased,error-prone,and unable to accommodate the large volumes of data produced by modern instrumentation.While more automated approaches have been proposed,many are not robust to a high variety of data,and do not generalize well to diverse microstructural features and material systems.Here,we present a flexible,semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems:(1)epitaxial heterostructures of SrTiO_(3)/Ge,(2)La_(0.8)Sr_(0.2)FeO_(3) thin films,and(3)MoO_(3) nanoparticles.We demonstrate that the few-shot learning method is more robust against noise,more reconfigurable,and requires less data than conventional image analysis methods.This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

Predicting defect behavior in B2 intermetallics by merging ab initio modeling and machine learning

We present a combination of machine learning and high throughput calculations to predict the points defects behavior in binary intermetallic(A–B)compounds,using as an example systems with the cubic B2 crystal structure(with equiatomic AB stoichiometry).To the best of our knowledge,this work is the first application of machine learning-models for point defect properties.High throughput first principles density functional calculations have been employed to compute intrinsic point defect energies in 100 B2 intermetallic compounds.The systems are classified into two groups:(i)those for which the intrinsic defects are antisites for both A and B rich compositions,and(ii)those for which vacancies are the dominant defect for either or both composition ranges.The data was analyzed by machine learning-techniques using decision tree,and full and reduced multiple additive regression tree(MART)models.Among these three schemes,a reduced MART(r-MART)model using six descriptors(formation energy,minimum and difference of electron densities at the Wigner–Seitz cell boundary,atomic radius difference,maximal atomic number and maximal electronegativity)presents the highest fit(98%)and predictive(75%)accuracy.This model is used to predict the defect behavior of other B2 compounds,and it is found that 45%of the compounds considered feature vacancies as dominant defects for either A or B rich compositions(or both).The ability to predict dominant defect types is important for the modeling of thermodynamic and kinetic properties of intermetallic compounds,and the present results illustrate how this information can be derived using modern tools combining high throughput calculations and data analytics.

Mass transport in a highly immiscible alloy on extended shear deformation

Forced mixing to a single-phase or supersaturated solid solution(SSS)and its prerequisite microstructure evolution in immiscible systems has been a focus of research for fundamental science and practical applications.Controlling the formation of SSS by shear deformation could enable a material design beyond conventional equilibrium microstructure in immiscible systems.Here,a highly immiscible Cu-50 at.%Cr binary alloy(mixing enthalpy of∼20 kJ mol^(−1))was employed to investigate the microstructure evolution and localized tendencies of SSS during severe shear deformation.Our results demonstrate the dislocation mediated microstructural refinement process in each phase of the binary alloy and the mechanisms associated with localized solute supersaturation as a function of shear strain.Pronounced grain refinement in the softer Cu phase occurs owing to the strain localization driving the preferential dynamic recrystallization.The grain refinement of the Cr phase,however,is enabled by the progressive evolution of grain lamination,splitting,and fragmentation as a function of shear strain.The solute supersaturation is found to be strongly dependent on the local environments that affect the dislocation activity,including the level of microstructure refinement,the interfacial orientation relationship,the mechanical incompatibility,and the localized preferential phase oxidation.Ab initio simulations confirm that it is more favorable to oxidize Cr than Cu at incoherent Cu/Cr interfaces,limiting the mass transport on an incoherent boundary.Our results unveil the mechanism underpinning the non-equilibrium mass transport in immiscible systems upon severe deformation that can be applied to produce immiscible alloys with superior mechanical properties.

Ultrafast metal oxide reduction at Pd/PdO_(2) interface enables onesecond hydrogen gas detection under ambient conditions

Here,we report a Pd/PdO_(x) sensing material that achieves 1-s detection of 4% H_(2) gas(i.e.,the lower explosive limit concentration for H_(2))at room temperature in air.The Pd/PdO_(x) material is a network of interconnected nanoscopic domains of Pd,PdO,and PdO_(2).Upon exposure to 4% H_(2),PdO and PdO_(2) in the Pd/PdO_(x) are immediately reduced to metallic Pd,generating over a>90% drop in electrical resistance.The mechanistic study reveals that the Pd/PdO_(2) interface in Pd/PdOx is responsible for the ultrafast PdO_(x) reduction.Metallic Pd at the Pd/PdO_(2) interface enables fast H_(2) dissociation to adsorbed H atoms,significantly lowering the PdO2 reduction barrier.In addition,control experiments suggest that the interconnectivity of Pd,PdO,and PdO2 in our Pd/PdO_(x) sensing material further facilitates the reduction of PdO,which would otherwise not occur.The 1-s response time of Pd/PdO_(x) under ambient conditions makes it an excellent alarm for the timely detection of hydrogen gas leaks.

Electron energy levels determining cathode electrolyte interphase formation

Cathode electrolyte interphase(CEI)has a significant impact on the performance of rechargeable batteries and is gaining increasing attention.Understanding the fundamental and detailed CEI formation mechanism is of critical importance for battery chemistry.Herein,a diverse of characterization tools are utilized to comprehensively analyze the composition of the CEI layer as well as its formation mechanism by LiCoO_(2)(LCO)cathode.We reveal that CEI is mainly composed of the reduction products of electrolyte and it only parasitizes the degraded LCO surface which has transformed into a disordered spinel structure due to oxygen loss and lithium depletion.Based on the energy diagram and the chemical potential analysis,the CEI formation process has been well explained,and the proposed CEI formation mechanism is further experimentally validated.This work highlights that the CEI formation process is nearly identical to that of the anode-electrolyte-interphase,both of which are generated due to the electrolyte directly in contact with the low chemical potential electrode material.This work can deepen and refresh our understanding of CEI.

基于类肽等级自组装结构仿生纳米材料:合成,表征和应用

类肽(或N-取代甘氨酸)具有合成效率高、化学稳定性强、抗酶水解及生物相容性好等优点,是一类潜在的可自定义序列的生物仿生聚合物.通过调节类肽的侧链化学,可以精确地控制类肽序列并实现侧链的多样性.基于以上类肽分子独特的优势,在过去的几年里,研究者设计和合成了大量的双亲性类肽作为基本的结构单元,通过自下而上的分子自组装作用构建了结构可控和具有特定功能的仿生纳米材料.本文从以下三个方面综述了我们在类肽自组装领域取得的一些成果.首先,概述了以云母和硅片为无机基底辅助类肽自组装.将原子力显微镜原位成像技术和单分子力谱技术相结合,可实时观察类肽分子在表面的组装过程并直接测定类肽分子与基底间的相互作用,揭示基底表面对类肽自组装的影响.其次,介绍了类肽分子在溶液中自组装成纳米管和具有自修复功能的纳米薄膜.最后,综述了基于类肽自组装纳米材料的应用,包括以类肽自组装纳米材料为催化模板构建纳米仿生催化剂和作为细胞内输送物质的载体等.

In situ preparation of visible-light-driven carbon quantum dots/NaBiO3 hybrid materials for the photoreduction of Cr(Ⅵ)

In this study,different carbon quantum dots(CQDs)/NaBiO3 hybrid materials were synthesized as photocatalysts to effectively utilize visible light for the photocatalytic degradation of contaminants effectively.These hybrid materials exhibit an enhanced photocatalytic reduction of hexavalent chromium(Cr(Ⅵ))in the aqueous medium.Zero-dimensional nanoparticles of CQDs were embedded within the two-dimensional NaBiO3 nanosheets by the hydrothermal process.Compared with that of the pure NaBiO3 nanosheets,the photocatalytic performance of the hybrid catalysts was significantly high and 6 wt.%CQDs/NaBiO3 catalyst exhibited better photocatalytic performance.We performed the first-principles density functional theory calculations to study the interfacial properties of pure NaBiO3 nanosheets and hybrid photocatalysts,and confirmed the CQDs played an important role in the CQDs/NaBiO3 composites.The experimental results indicated that the enhanced reduction of Cr(Ⅵ)was probably due to the high loading of CQDs(electron acceptor)on NaBiO3,which made NaBiO3 nanomaterials to respond in visible light and significantly improved their electron-hole separation efficiency.

Modulation of the electronic states of perovskite SrCrO3 thin films through protonation via low-energy hydrogen plasma implantation approaches

Hydrogenation of transition metal oxides offers a powerful platform to tailor physical functionalities as well as for potential applications in modern electronic technologies.An ideal nondestructive and efficient hydrogen incorporation approach is important for the realistic technological applications.We demonstrate the proton injection on SrCro3 thin films via an efficient low-energy hydrogen plasma implantation experiments,without destroying the original lattice framework.Hydrogen ions accumu-late largely at the interfacial regions with amorphous character which extend about one-third of the total thickness.The Hx.SrCro3(HSCO)thin films appear like exfoliated layers which however retain the fully strained state with distorted perovskite structure.Proton doping induces the change of Cr oxidation state from Cr^4+to Cr^3+in HSCO thin films and a transition from metallic to insulat-ing phase.Our investigations suggest an attractive platform in manipulating the electronic phases in proton-based approaches and may offer a potential peeling off strategy for nanoscale devices through low-energy hydrogen plasma implantation approaches.