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Graphene plasmons (GPs) are of great importance in photonics and optoelectronics due to ultrahigh near-field confinement and enhancement. However, the large momentum mismatch between GPs and incident light hinders the efficient excitation of GPs. Conventional excitation schemes, such as prism coupling, grating coupling, and resonant metal antennae, go against the tunability and multifunction of the GP device. Here, we numerically demonstrate the efficient excitation and active control of propagating GPs in a resonant graphene nanoantenna (GNA)-based GP launcher. The resonant GNA provides high-momentum near-field components to match the wavevector of GPs, and the excitation efficiency is significantly enhanced by the quarter-wavelength condition in a reflective configuration. Furthermore, the propagating behavior of GPs is gate-tunable with a GNA. Using spatially engineered GNAs, a tunable directional GP launcher with an extinction ratio of larger than 1000 is achieved. Moreover, we design a vertically crossed GNA-based propagating GP launcher that can serve as the incident polarization information recording. Finally, some graphene plasmonic circuits at the nanoscale, such as a GP waveguide, splitter, and prism, are realized using spatial conductivity patterns in graphene. The efficient excitation and flexible control of propagating GPs with engineered GNAs associated with the spatial conductivity patterns in graphene provide a gate-tunable and multifunctional platform for nanoscale graphene plasmonic devices.

The application of machine learning (ML) to corrosion research has become an important trend in corrosion science in recent years. In this paper, the feature extraction method for corrosion data and the ML algorithms commonly used (including artificial neural networks, support vector machines, ensemble learning and other widely used algorithms) in corrosion field is introduced. Then, the characteristics of different algorithms and their application scenarios in the corrosion prediction are summarized. Finally, the development trend of ML in material corrosion field is prospected.

• 0.02 wt.% Li makes Zn–4Cu reach the benchmark mechanical properties. • Li affects the phase composition of corrosion products and changes corrosion rate. • Trace Li enhances the inhibition effect on S. aureus for Zn–4Cu alloy. In this work, trace Li was introduced to strengthen Zn–4Cu alloys. The results indicated that trace amounts of Li contributed to a significant increase in strength, resulting in an acceptable loss of elongation at fracture. Additionally, Li in the form of LiZn 4 led to more intensive galvanic corrosion, which accelerated the early corrosion rate. The release of a large amount of Zn2+, caused by the addition of Li, affected the phase composition of the main Zn-containing corrosion products. Moreover, the inhibition effect of the alloy on Staphylococcus aureus (S. aureus) was enhanced by the addition of 0.02 wt.% Li. [Display omitted] [ABSTRACT FROM AUTHOR]

Broadband near-infrared (NIR) phosphors are the critical component of phosphor converted NIR light-emitting diode (LED) light sources. However, there are still a lack of NIR phosphors with excellent external quantum efficiency (EQE) and thermal stability. Here, we report a highly efficient broadband NIR phosphor Y3Ga3MgSiO12: Cr3+. The optimized phosphor yields an internal quantum efficiency (IQE) and an EQE of 79.9 and 33.7%, respectively. The integrated emission intensity still remains at 84.4% of that at room temperature when heated to 423 K. A broadband NIR LED lamp was made by combining as-prepared phosphor and a blue InGaN LED chip, which shows an output power of 89.8 mW with a photoelectric conversion efficiency of 17.1% driven at 525 mW input power. Our research provides a promising NIR phosphor with high efficiency broadband for the NIR light source.

For efficient solid-state refrigeration technologies based on electrocaloric effect (ECE), it is a great challenge of simultaneously obtaining a large adiabatic temperature change (ΔT) within a wide temperature span (Tspan) in lead-free ferroelectric ceramics. Here, we studied the electrocaloric effect (ECE) in (1-x)(Na0.5Bi0.5)TiO3-xCaTiO3((1-x)NBT-xCT) and explored the combining effect of morphotropic phase boundary (MPB) and relaxor feature. The addition of CT not only constructs a MPB region with the coexistence of rhombohedral and orthorhombic phases, but also enhances the relaxor feature. The ECE peak appears around the freezing temperature (Tf), and shifts toward to lower temperature with the increasing CT amount. The directly measured ECE result shows that the ceramic of x =0.10, which is in the MPB region, has an optimal ECE property of ΔTmax = 1.28 K @ 60 °C under 60 kV/cm with a wide Tspanof 65 °C. The enhanced ECE originates from the electric-field-induced transition between more types of polar nanoregions and long-range ferroelectric macrodomains. For the composition with more relaxor feature in the MPB region, such as x = 0.12, the ECE is relatively weak under low electric fields but it exhibits a sharp increment under a sufficiently high electric field. This work provides a guideline to develop the solid–state cooling devices for electronic components.

• Combining physics knowledge with machine learning methods is an outstanding challenge in materials science. We introduced dimension-synchronous-computation symbolic regression method to efficiently establish expressions for band gap of NaCl-type compounds. It is embedding the dimension computation system to ensure the dimensional consistency. And descriptor binding mechanism is introduced to keep the knowledge in modeling. The pattern of 'knowledge-model-knowledge' provides a new scheme for multi-component material modeling and design, and believed to be used to inspire existing machine learning applications. There is growing interest in applying machine learning techniques in the field of materials science. However, the interpretation and knowledge extracted from machine learning models is a major concern, particularly as formulating an explicit model that provides insight into physics is the goal of learning. In the present study, we propose a framework that utilizes the filtering ability of feature engineering, in conjunction with symbolic regression to extract explicit, quantitative expressions for the band gap energy from materials data. We propose enhancements to genetic programming with dimensional consistency and artificial constraints to improve the search efficiency of symbolic regression. We show how two descriptors attributed to volumetric and electronic factors, from 32 possible candidates, explicitly express the band gap energy of NaCl-type compounds. Our approach provides a basis to capture underlying physical relationships between materials descriptors and target properties. The table of contents entry: One dimension-synchronous-computation symbolic regression method is introduced to efficiently establish expressions for band gap of NaCl-type compounds. It is embedding the dimension computation system to ensure the dimensional consistency of expression. And descriptor binding mechanism is introduced to keep the knowledge in modeling. The pattern of 'knowledge-modelknowledge' is believed to be used to inspire existing machine learning applications. [Display omitted]. [ABSTRACT FROM AUTHOR]

Ce-doped garnet phosphors play an important role in the white light-emitting diode (LED) family. In the past years, a lot of trial-and-error experiments guided by experience to discover phosphors suitable for white LEDs have been presented. The working temperature of phosphors may reach 200 °C in white LEDs, and so, the exploration of phosphors with excellent thermal stability at the desired wavelength continues to be a challenge. In the present study, to discover novel cyan–green garnet:Ce phosphors, wavelength and thermal stability machine learning models were built by constructing reasonable features. Among the 171,636 compounds with garnet structures predicted by our models, 25 samples were selected for preparation and characterization by multiobjective optimization based on active learning. Lu1.5Sr1.5Al3.5Si1.5O12:Ce performed the best with excellent thermal stability (≥60% emission intensity was retained at 640 K) and exhibited emission peaks of about 505 nm, and it is a very promising phosphor for future applications, especially in high-temperature operating environments.

Introducing polarization field of piezoelectric materials is an effective strategy to improve photocatalytic performance. In this study, a new type of BaTiO3/CuO heterostructure catalyst was designed and synthesized to achieve high piezo-photocatalytic activity through the synergy of heterojunction and piezoelectric effect. The BaTiO3/CuO heterostructure shows a significantly enhanced piezo-photocatalytic degradation efficiency of organic pollutants compared with the individual BaTiO3nanowires (NWs) and CuO nanoparticles (NPs). Under the co-excitation of ultrasonic vibration and ultraviolet radiation, the optimal degradation reaction rate constant kof polarized BaTiO3/CuO heterostructure on methyl orange (MO) dye can reach 0.05 min−1, which is 6.1 times of photocatalytic rate and 7 times of piezocatalytic rate. The BaTiO3/CuO heterostructure with remarkable piezo-photocatalytic behavior provides a promising strategy for the development of high-efficiency catalysts for wastewater purification, and it also helps understand the coupling mechanism between piezoelectric effect and photocatalysis.

The ultrahigh electrostrain and piezoelectric constant (d33) in relaxor piezoelectric PMN–30PT single crystals are closely related to the coexistence and transition of multiple phases at the morphotropic phase boundary (MPB). However, the key mechanisms underlying the stability of the phases and their transitions are yet to be fully understood. In this work, we undertake a systematic study of the influences of phase transitions on the electrostrictive and piezoelectric behaviors in ⟨001⟩-, ⟨011⟩-, and ⟨111⟩-oriented PMN–30PT single crystals. We first classify the various phase transitions within the quasi-MPB in electric field–temperature phase diagrams as either dominated by the electric field or by temperature. We find that the electrostrain reaches a maximum at each phase transition, especially in the electric-field-dominated transitions, whereas d33only peaks at specific phase transitions. In particular, the electrostrain in the ⟨001⟩ crystal reaches a maximum of S= 0.52% at 55 °C under an external electric field with E= 15 kV/cm, primarily due to a joint contribution of the electric field-dominated rhombohedral–monoclinic and monoclinic–tetragonal phase transitions at the quasi-MPB. An ultrahigh d33(∼2460 pC/N) only occurs at the rhombohedral–monoclinic phase transition in the ⟨001⟩ crystal and at the rhombohedral–orthorhombic transition in the ⟨011⟩ crystal (d33∼ 1500 pC/N) due to the lower energy barriers. The temperature-dominated phase transitions also contribute toward minor peaks in electrostrain and/or d33. This work provides a deeper and quantitative understanding of the microscopic mechanisms underlying electrostrictive and piezoelectric behaviors relevant for the design of high-performance materials.

Designing refractory high-entropy alloys (RHEAs) for high-temperature (HT) applications is an outstanding challenge given the vast possible composition space, which contains billions of candidates, and the need to optimize across multiple objectives. Here, we present an approach that accelerates the discovery of RHEA compositions with superior strength and ductility by integrating machine learning (ML), genetic search, cluster analysis, and experimental design. We iteratively synthesize and characterize 24 predicted compositions after six feedback loops. Four compositions show outstanding combinations of HT yield strength and room-temperature (RT) ductility spanning the ranges of 714–1061 MPa and 17.2%–50.0% fracture strain, respectively. We identify an attractive alloy system, ZrNbMoHfTa, particularly the composition Zr0.13Nb0.27Mo0.26Hf0.13Ta0.21, which demonstrates a yield approaching 940 MPa at 1200 °C and favorable RT ductility with 17.2% fracture strain. The high yield strength at 1200 °C exceeds that reported for RHEAs, with 1200 °C exceeding the service temperature limit for Ni-based superalloys. Our ML-based approach makes it possible to rapidly optimize multiple properties for materials design, thus overcoming the common problems of limited data and a vast composition space in complex materials systems while satisfying multiple objectives.

The atomic force microscope (AFM) provides a facilitating tool to investigate the atomic-scale friction properties of surfaces through the sliding of the scanning tip; therefore, the interaction between the tip and the surface should play an important role to determine the frictional behaviors. In this study, density functional theory (DFT) calculations have been carried out to perform the pushing down processes of a tip (10 atom Ir or Au tip) on the top, hollow, and bridge sites of the graphene/Ni(111) substrate. The calculation results indicate that the interactions between the tips and the graphene/Ni(111) substrate influence the adsorption energy remarkably, leading to the sequence of bridge < top < hollow for Ir and Au tips, which is totally different from the adsorption energy of an inert Ar atom, following the sequence of hollow < bridge < top. The strong interactions between the (Ir or Au) tip and the graphene/Ni(111) substrate will introduce novel frictional properties into the system, and an anomalous negative friction coefficient could be obtained. Further investigations show that these interactions arise from the hybridizations between the 2pzorbitals of C atoms and the 5dz2orbitals of the tip apex atom.

Piezocatalytic H2O2production is a promising alternative to the traditional anthraquinone method and direct synthesis, for obtaining desired products in a clean and safe way. In this work, we studied the piezocatalytic behavior of narrow band gap material BiFeO3and achieved a superior H2O2generation performance by defect engineering enabled dual-channel reaction. The concentration of oxygen vacancies (OVs) is adjusted by the hydrothermal process parameters, so that the valence band shifts to a more positive position with more OVs. As the water oxidation reaction is selectively enhanced as its energy barrier is lowered, while the oxygen reduction reaction is basically maintained, i.e. a dual-channel for H2O2production. Meanwhile, OVs act as the electron capture center to facilitate charge separation, which further improves the reaction activity. Accordingly, the H2O2yield of BiFeO3catalyst with suitable OVs concentration reaches 110.07 μmol/g/h in pure water and 342.36 μmol/g/h under sacrificial agent system. This work provides a promising strategy for the development of narrow band gap catalysts for H2O2production.

Electrocaloric effect (ECE) in ferroelectric (FE)/antiferroelectric (AFE) materials offers a promising high-efficient and zero-emission solid-state cooling technology, whose materials design is usually focused on the morphotropic phase boundary (MPB) between two FE phases. This work constructs an MPB between an orthorhombic AFE and a rhombohedral FE phase in Pb0.97–xBaxLa0.02Zr0.95Ti0.05O3(PBLZT100x, x= 0–0.08) ceramics and achieves a superior ECE performance. An unprecedented high electrocaloric strength of 1.52 K·mm/kV and an ultrahigh refrigeration efficiency (coefficient of performance = 16) are obtained in PBLZT4, in the MPB near AFE end. Moreover, a large negative ECE, with the highest strength up to −0.41 K·mm/kV, is also realized due to the electric field-induced AFE–FE transition. The coexistence of giant positive and negative ECEs at adjacent temperatures can further improve the cooling capacity (∼17%) of solid-state refrigeration in a well-designed cooling cycle. This work provides a brand new materials design strategy to achieve giant positive and negative ECEs simultaneously and a novel cooling cycle to efficiently utilize the two effects.

The release of debris and ions from metallic artificial joints during bio-tribocorrosion posed a severe threat to patient health. In this work, the lifecycle of a CoCrMo alloy was presented by investigating the subsurface microstructure transformation in-vitro. The results showed that the originally coarse grains changed to nano-grains (NGs) on the top region of the alloy, and nanoparticles (NPs) were torn off the surface, which were then blocked by the tribo-film. The agglomerated alloy NPs contained in the tribo-film transformed into debris after being removed from the alloy surface. The majority of the torn-off NPs were corroded and released ions into solution due to their high chemical activities. [ABSTRACT FROM AUTHOR]

A generalized size-dependent thermodynamic model was derived to describe the electrochemical properties of nanoparticles, which takes into account the effects of size-dependent stress distributions in the surface shell and core of nanoparticles, based on the thermodynamic equilibrium theory. This model can be used to simultaneously analyze the nanoparticle size, stresses, electrochemical properties, and their coupling behaviors in thermodynamic equilibrium nanoparticles. Combined with the molecular dynamics simulations, the spherical nanoparticles of pure metals (Au, Pt, Ni, Cu, and Fe) were modeled as a core–shell structure. The thermodynamic analysis showed that the anodic current density decreased with decreasing nanoparticle radius, implying that the stability of nanoparticles was enhanced, which is qualitatively consistent with some experimental observations.

Low rate performance and poor cyclic performance are vital factors undermining the practical application of Li-rich layered oxides as the cathode material for advanced Li-ion batteries. Herein, we demonstrate a significant enhancement in rate capability and cyclic performance of Li1.2Mn0.54Ni0.13Co0.13O2 via an L-ascorbic acid-based treatment. The discharge capacity ratio at different current rates (0.5C/0.05C) increases from 70.4% to 79.9% after L-ascorbic acid-based modification. Furthermore, the remaning energy for the modified sample after the 100th cycle is 628.6 Wh Kg[?]1, which is 35.6% higher than the energy density of pristine sample (463.5 Wh Kg[?]1). The enhancement in electrochemical performance of the L-ascorbic acid treated Li1.2Mn0.54Ni0.13Co0.13O2 is attributed to the co-contribution of chemical activation of Li2MnO3 phase, exposure of high proportion of Li-conducting-favorable faces at the particle surface, increase in specific surface area and in-situ formation of minor spinel phase under the surface.

Molecular dynamics (MD) simulations of displacement cascades in Fe-3 at.% Cu alloy were carried out with various primary knocked-on atom (PKA) energies at different temperature. The results showed that if PKA energy was lower than 20 keV, no stable clusters of Cu was found. However, when energy equaled to 20 keV, Cu cluster containing seven Cu atoms was found and Cu cluster could be stabilized after 5 ps. MD simulations and first principles calculations showed that irradiation-induced vacancies played a key role in the formation of the Cu cluster, and Cu atoms congregation decreased the energy of systems. [ABSTRACT FROM AUTHOR]

The effects of Ca on the properties of PrBa1-xCaxCo2O5+d (x = 0.0, 0.3, and 0.5) as a cathode material for intermediate temperature solid oxide fuel cells were studied. Higher Ca content in PrBa1-xCaxCo2O5+d led to a gradual change in phase symmetry from A-site cation ordered double perovskite (x = 0.0) to mixed A-site cation ordered-disordered perovskite (x = 0.3) to A-site cation disordered simple perovskite (x = 0.5). It also led to a decreased oxygen content. Comparing the electrochemical performance of the samples with x = 0.0 and x = 0.5, PrBa0.7Ca0.3Co2O5+d exhibited the best catalytic activity for the oxygen reduction reaction and maximum power density. This was ascribed to the synergistic effect of the A-site cation ordered-disordered structure, which combined the advantages of a fast oxygen diffusion rate and a relatively short oxygen diffusion distance from the oxygen reduction site to the cathode/electrolyte interface. The maximum power density, which was as high as 2.16 W cm[?]2, was achieved for the PrBa0.7Ca0.3Co2O5+d-based single cell with a commercial anode-supported half cell at 800degC. PrBa0.7Ca0.3Co2O5+d was shown to be a potential cathode material for IT-SOFCs.

Why are the transition temperatures (Tc) of superconducting materials so different? The answer to this question is not only of great significance in revealing the mechanism of high-Tcsuperconductivity but also can be used as a guide for the design of new superconductors. However, so far, it is still challenging to identify the governing factors affecting the Tc. In this work, with the aid of machine learning and first-principles calculations, we found a close relevance between the upper limit of the Tcand the energy-level distribution of valence electrons. It implies that some additional inter-orbital electron-electron interaction should be considered in the interpretation of high-Tcsuperconductivity.

Size-dependent thermodynamic model is presented to simultaneously analyze stress and vacancy concentration, along with their coupling behavior in spherical metal nanoparticles. A nanoparticle is treated as a composite with a core lattice and a surface shell, which both have their corresponding thermodynamic properties. Thermodynamic analysis of Ni, Cu, Au, and Pt particles shows that the vacancy concentration in the core and the surface shell could be significantly decreased for smaller particles. The apparent vacancy concentration in the whole nanoparticle reaches the maximum at the critical particle size of about 100 nm and is lower for larger or smaller particles. This result provides comprehensive understanding of the vacancy concentration in nanomaterials, which had been represented by two opposite views in the past decades.

Experimental and theoretical studies of water-molecule adsorption on BaTiO3single-crystal surfaces are presented in this paper. The Fourier transform infrared spectrum shows that there are three types of energy-nonequivalent active modes for water-molecule adsorption on the in-plane-polarized BaTiO3(100) surface. The X-ray photoelectron spectroscopic results illustrate hydroxyl group on the surface, thereby indicating that the adsorbed water molecules are dissociated. The first-principles calculations of the 1/4-, 1/2-, and 1-monolayer water coverage demonstrate that H bonds are formed between the hydrogen of water and the surface oxygen of BaTiO3and between the hydrogen of hydroxyl and the surface oxygen of BaTiO3, and the difference in the water adsorption behavior on the BaO- and TiO2-terminated surfaces. The calculation results are in good agreement with the experimental observations.

High-efficiency long-wavelength emission near-infrared (NIR) phosphors are the key to next-generation LED light sources. However, high-efficiency phosphors usually exhibit narrow-band emission at shorter wavelengths due to the crystal field intensity. In this paper, we utilize multi-objective optimization to discover the NIR phosphor Gd3Mg0.5Al1.5Ga2.5Ge0.5O12:0.04Cr3+. It exhibits a broadband NIR emission from 650 to 1100 nm peaking at 763 nm, with a full width at half maximum (FWHM) of 150 nm, an internal quantum efficiency (IQE)/external quantum efficiency (EQE) of 90%/53.1%, and good thermal stability (85.3% @ 150 °C). The packaging results show that ∼53.2 mW of output power is achieved at 915 mW input power, which suggests promising applications for NIR pc-LED. Our approach is based on the data of emission wavelength (WL) and IQE for garnet:Cr NIR phosphors to construct machine learning models. An active learning strategy is used to make tradeoffs between WL and IQE, and we are able to find the targeted phosphor after only four iterations of synthesis and characterization.

The study of piezocatalysis has become an important topic in piezoelectric research, especially for addressing environmental issues. However, the reliance on nanofabrication seriously hinders investigating materials with complex compositional design for higher performance and large-scale application. In this work, we use a machine learning strategy to efficiently sample the vast compositional space for ceramic powders with excellent piezoelectric response that we expect to impact piezocatalytic performance. The ceramics, synthesized by solid state reaction methods, belong to the multi-component system (Ba1−x−yCaxSry)(Ti1−u−v−wZruSnvHfw)O3with target property d33,the piezoelectric coefficient. The highest d33tends to occur within the phase boundary region with coexisting rhombohedral, orthorhombic and tetragonal phases, especially on the rhombohedral phase side. We select (Ba0.95Ca0.05)(Ti0.9Sn0.1)O3as it combines a relatively large d33with the fewest number of elements. Its sintered ceramic exhibits a high d33of 605±14 pC/N, consistent with the machine learning prediction 633±70 pC/N. The mechanically-ground ceramic powders have an excellent piezocatalytic activity with a degradation rate of (2.16±0.28)×10−2min−1for RhB dye solution, comparable to the performance of previously reported nanoparticles. Our work provides further insight into the nature of piezoelectricity in BaTiO3based ceramics, and affords an effective strategy for searching for superior piezocatalysts suitable for large-scale applications.

The electrochemical properties have different or reverse trend with decreasing radius dependent on the synthetic methods and thermodynamic states of nanoparticles. Here, a size-dependent thermodynamic model was derived to describe the thermodynamic equilibrium state of binary solid solution nanoparticles. This model combined the capillary equation with the Gibbs-Duhem equation and the Butler-Volmer equation, can simultaneously analyze nanoparticle size, stresses, solute segregation and electrochemical properties in solid solution nanoparticles. Then, spherical nanoparticles of CuZn binary solid solution were studied. With decreasing CuZn nanoparticle radius, the anodic current density decreased, whereas the equilibrium potential increased, meaning that the stability was enhanced. With increasing apparent Zn concentration, the anodic current density and the equilibrium potential difference between the CuZn nanoparticle components increased, implying that the selective corrosion of Zn atoms enhanced. These results were qualitatively consistent with some experimental observations.

Low rate performance and poor cyclic performance are vital factors undermining the practical application of Li-rich layered oxides as the cathode material for advanced Li-ion batteries. Herein, we demonstrate a significant enhancement in rate capability and cyclic performance of Li1.2Mn0.54Ni0.13Co0.13O2via an L-ascorbic acid-based treatment. The discharge capacity ratio at different current rates (0.5C/0.05C) increases from 70.4% to 79.9% after L-ascorbic acid-based modification. Furthermore, the remaning energy for the modified sample after the 100thcycle is 628.6 Wh Kg−1, which is 35.6% higher than the energy density of pristine sample (463.5 Wh Kg−1). The enhancement in electrochemical performance of the L-ascorbic acid treated Li1.2Mn0.54Ni0.13Co0.13O2is attributed to the co-contribution of chemical activation of Li2MnO3phase, exposure of high proportion of Li-conducting-favorable faces at the particle surface, increase in specific surface area and in-situ formation of minor spinel phase under the surface.

In this work, the effect of an L-ascorbic acid-based treatment on the physicochemical and electrochemical properties of a Li-rich oxide has been studied. Clear corrosion cavities with spinel coating layers were observed over the majority of the particle's surface, and these have been ascribed to the Li+-H+exchange and reduction of Mn4+to Mn2+, which is more soluble in the L-ascorbic acid solution. Furthermore, a special region without obvious traces of etching is observed over a small part of the surface of the L-ascorbic acid-treated sample, which arises from the enrichment of Ni2+at the rim of the particle. Compared to the pristine oxide, the modified samples exhibit significantly higher initial discharge capacity/Columbic efficiency, remarkably enhanced rate performance, and considerably retarded voltage decay. The specific energy density and energy retention after 100 cycles of usage, increases from 497.6 Wh kg−1and 63.4% for the pristine oxide to 640.8 Wh kg−1and 68.9% for the modified sample. This enhancement in the electrochemical performance of the modified samples can be attributed to the synchronous formation of the spinel coating layer and modification of the bulk microstructure of the Li-rich layered oxide.