Local Gradient Research Articles

Anisotropic Hollow Structure with Chemotaxis Enabling Intratumoral Autonomic Therapy.

Effective intratumoral drug penetration is pivotal for successful cancer treatment. However, due to the disrupted capillary networks and poor perfusion in solid tumors, there exist challenges to realize autonomous directional drug penetration and controlled drug release within the tumor. Considering the specificity of glucose within tumor tissue, we draw inspiration from nature and engineer asymmetrical hollow structures exhibiting chemotaxis towards high glucose levels. By incorporating multiple shells into these structures, we enhance the local chemical concentration gradients, thereby improving cellular uptake and precise targeting. The advantages of anisotropic hollow multishell structure (a-HoMS) can be reflected from the diffusion coefficient and directivity, which increase by 73.4% and 265% respectively compared to conventional isotropic hollow spheres, achieving the most linear movement while ensuring the speed of movement. Furthermore, the multi-level porosity and temporal-spatial order of a-HoMS enable sequential drug delivery that inhibits angiogenesis with inducing cell apoptosis. After the eradication of localized tumor cells, the a-HoMS can automatically migrate to the alive tumor cells under the glucose gradient, inducing another cycle of drug delivery and chemotaxis, resulting in excellent antitumor efficacy. These anisotropic HoMS demonstrate intelligence, adaptability, and precision in tumor therapy, providing valuable insights for programmable treatment within tissues.

Anisotropic Hollow Structure with Chemotaxis Enabling Intratumoral Autonomic Therapy

Effective intratumoral drug penetration is pivotal for successful cancer treatment. However, due to the disrupted capillary networks and poor perfusion in solid tumors, there exist challenges to realize autonomous directional drug penetration and controlled drug release within the tumor. Considering the specificity of glucose within tumor tissue, we draw inspiration from nature and engineer asymmetrical hollow structures exhibiting chemotaxis towards high glucose levels. By incorporating multiple shells into these structures, we enhance the local chemical concentration gradients, thereby improving cellular uptake and precise targeting. The advantages of anisotropic hollow multishell structure (a‐HoMS) can be reflected from the diffusion coefficient and directivity, which increase by 73.4% and 265% respectively compared to conventional isotropic hollow spheres, achieving the most linear movement while ensuring the speed of movement. Furthermore, the multi‐level porosity and temporal‐spatial order of a‐HoMS enable sequential drug delivery that inhibits angiogenesis with inducing cell apoptosis. After the eradication of localized tumor cells, the a‐HoMS can automatically migrate to the alive tumor cells under the glucose gradient, inducing another cycle of drug delivery and chemotaxis, resulting in excellent antitumor efficacy. These anisotropic HoMS demonstrate intelligence, adaptability, and precision in tumor therapy, providing valuable insights for programmable treatment within tissues.

Molecular Dynamics Analysis of Hydrogen Diffusion Behavior in Alpha-Fe Bi-Crystal Under Bending Deformation

The hydrogen embrittlement (HE) phenomenon occurring in drawn pearlitic steel wires sometimes results in dangerous delayed fracture and has been an important issue for a long time. HE is very sensitive to the amount of plastic deformation applied in the drawing process. Hydrogen (H) atom diffusion is affected by ambient thermal and mechanical conditions such as stress, pressure, and temperature. In addition, the influence of stress gradient (SG) on atomic diffusion is supposed to be crucial but is still unclear. Metallic materials undergoing plastic deformation naturally have SG, such as residual stresses, especially in inhomogeneous regions (e.g., surface or grain boundary). In this study, we performed molecular dynamics (MD) simulation using EAM potentials for Fe and H atoms and investigated the behavior of H atoms diffusing in pure iron (α-Fe) with the SG condition. Two types of SG conditions were investigated: an overall gradient established by a bending deformation of the specimen and an atomic-scale local gradient caused by the grain boundary (GB) structure. A bi-crystal model with H atoms and a GB structure was subjected to bending deformation. For a moderate flexure, bending stress is distributed linearly along the thickness of the specimen. The diffusion coefficient of H atoms in the bulk region increased with an increase in the SG value. In addition, it was clearly observed that the direction of diffusion was affected by the existence of the SG. It was found that diffusivity of the H atom is promoted by the reduction in its cohesive energy. From these MD results, we recognize an exponential relationship between the amount of H atom diffusion and the intensity of the SG in nano-sized bending deformation.

Multi-Agent Reinforcement Learning for Smart Community Energy Management

This paper investigates a Local Strategy-Driven Multi-Agent Deep Deterministic Policy Gradient (LSD-MADDPG) method for demand-side energy management systems (EMS) in smart communities. LSD-MADDPG modifies the conventional MADDPG framework by limiting data sharing during centralized training to only discretized strategic information. During execution, it relies solely on local information, eliminating post-training data exchange. This approach addresses critical challenges commonly faced by EMS solutions serving dynamic, increasing-scale communities, such as communication delays, single-point failures, scalability, and nonstationary environments. By leveraging and sharing only strategic information among agents, LSD-MADDPG optimizes decision-making while enhancing training efficiency and safeguarding data privacy—a critical concern in the community EMS. The proposed LSD-MADDPG has proven to be capable of reducing energy costs and flattening the community demand curve by coordinating indoor temperature control and electric vehicle charging schedules across multiple buildings. Comparative case studies reveal that LSD-MADDPG excels in both cooperative and competitive settings by ensuring fair alignment between individual buildings’ energy management actions and community-wide goals, highlighting its potential for advancing future smart community energy management.

Multi-Year Hurricane Impacts Across an Urban-to-Industrial Forest Use Gradient

Coastal forests in the eastern United States are increasingly threatened by hurricanes; however, monitoring their initial impacts and subsequent recovery is challenging across scales. Understanding disturbance impacts and responses is essential for sustainable forest management, biodiversity conservation, and climate change adaptation. Using Sentinel-2 imagery, we calculated the annual Normalized Difference Vegetation Index change (∆NDVI) of forests before and after Hurricane Michael (HM) in Florida to determine how different forest use types were impacted, including the initial wind damage in 2018 and subsequent recovery or reactive management for two focal areas located near and far from the coast. We used detailed parcel data to define forest use types and characterized multi-year impacts using sampling and k-means clustering. We analyzed five years of timberland logging activity up to the fall of 2023 to identify changes in logging rates that may be attributable to post-hurricane salvage efforts. We found uniform impacts across forest use types near the coast, where winds were the most intense but differences inland. Forest use types showed a wide range of multi-year responses. Urban forests had the fastest 3-year recovery, and the timberland response was delayed, apparently due to salvage logging that increased post-hurricane, peaked in 2021–2022, and returned to the pre-hurricane rate by 2023. The initial and secondary consequences of HM on forests were complex, as they varied across local and landscape gradients. These insights reveal the importance of considering forest use types to understand the resilience of coastal forests in the face of potentially increasing hurricane activity.

Unconventional mechanical responses and mechanisms of Ti-6Al-4V sheet subjected to electrically-assisted cyclic loading-unloading: Thermal and athermal effects

For the sake of unveiling the macro-micro behaviors and underlying control mechanisms of electroplastic effect (EPE) of sheet metals during recent thriving electrically-assisted incremental forming (EAIF) processes, electrically-assisted cyclic loading-unloading tension (EACT) experiments were carried out at a current density of 14～20A/mm2 followed by forced and unforced cooling. The electro-thermo-mechanical responses and the evolution rules of dislocation configurations, fracture modes, phase composition and local orientation distribution were characterized by IR imaging, SEM, quantitative EBSD and TEM tests. Moreover, the thermal and athermal components of the electrically-induced stress drop throughout the EACT processes were decoupled and systematically analyzed via temperature control tests and isothermal correction. The results show that thermal effect of electric current possesses a great proportion of 75 % in the overall stress drop and plays a key role in elastic modulus degradation and ductility enhancement by activating pyramidal {101‾1}⟨12‾10⟩ slip systems, weakening (0001) texture and promoting dynamic recrystallization (DRX) and α→β→α′ phase transformation. While the athermal effect only operates after reaching both threshold current density and plastic strain, it increases monotonically with current density, brings about “hot spots” effect, local charge imbalance and weakened atomic bonding, and further causes intensified local strain gradient, substructure formation and DRX nucleation. The ratio of athermal stress drop first decreases and then increases significantly with loading cycle at the later stage of EACT under the combined effect of local Joule heating effect and flow localization. Additionally, the athermal effect only activates short-range solute diffusion and localized diffusional α→β phase transformation, while the combined thermal and athermal effects promote long-range solute diffusion and an increasing rate in β content of 261.8 %. The present work provides theoretical basis for optimizing the EAIF forming process and realizing extreme manufacture of light-weight thin-walled complex components.

Natural and anthropogenic factors influence flowering synchrony and reproduction of a dominant plant in an inter-Andean scrub.

Agriculture expansion, livestock, and global change have transformed biological communities and altered, through aerosols and direct deposition, N:P balance in soils of inter-Andean valleys, potentially affecting flowering phenology of many species and thereby flowering synchrony and plant reproduction. We evaluated the influence of variation in temperature and moisture along the local elevational gradient and treatments with the addition of N and P and grazing on flowering synchrony and reproduction of Croton, a dominant shrub of the inter-Andean dry scrub. Along the elevational gradient (300 m difference between the lowest and highest site), we set up plots with and without grazing nested with four nutrient treatments: control and addition of N or P alone or combined N + P. We recorded the number of female and male flowers in bloom monthly from September 2017 to August 2019 to calculate flowering synchrony. We assessed fruiting, seed mass, and pre-dispersal seed predation. Higher growing-season soil temperatures, which were negatively associated with local elevation and higher nitrogen availability promoted flowering synchrony of Croton, particularly among larger plants. Greater flowering synchrony, high soil temperatures, and addition of N + P resulted in production of more fruits of Croton, but also intensified pre-dispersal seed predation. Temperature, availability of moisture throughout the elevational gradient, and nutrient manipulation affected flowering synchrony, which subsequently affected production of fruits in Croton. These results emphasize the critical role of current anthropogenic changes in climate and nutrient availability on flowering synchrony and reproduction of Croton, a dominant plant of the inter-Andean scrub.

A Straightforward Model for Quantifying Local pH Gradients Governing the Oxygen Evolution Reaction.

The production and consumption of protons by an electrocatalyst will, under certain conditions, generate localized microenvironments with properties distinct from those of the bulk solution. These local properties are particularly impactful for reactions involving proton-coupled electron transfer, where the generation of locally basic or acidic environments may significantly influence the energy efficiency and reaction selectivity of the electrocatalyst. Whereas local pH environments have been observed and characterized in reductive half-reactions, including the CO2 reduction and hydrogen evolution reactions, the incompatibility of conventional techniques and materials has limited studies in oxidative half-reactions, including the oxygen evolution reaction (OER), which provides the reducing equivalents for solar-to-fuels electrolysis. With the straightforward parameters bulk pH, buffer composition and pKa, and mass transport, we develop a model for describing local pH as a function of current density regardless of the microscopic details of the mechanism. Using an acid-stable PbOx OER catalyst, we observe the formation and dissipation of pH gradients during the OER and validate the model with voltammetric and potentiometric studies. The model predicts how local acidic environments can develop over a narrow OER current density window, thus providing further motivation for the development of OER catalysts that are stable to acid, even when operating in basic aqueous conditions. More generally, the model is not restricted to the OER and is useful for determining the onset of local pH gradients for other electrocatalytic reactions that involve the consumption or generation of protons in energy conversion reactions.

Adversarial sample attack method based on loss smoothing

Deep neural networks (DNNs) are vulnerable to adversarial examples.Although the existing momentum-based adversarial example generation method can achieve a close 100%white-box attack success rate, it is still not ideal when attacking other models, and the black- box attack success rate is low. To address this, an adversarial example attack method based on loss smoothing is proposed to improve the transferability of adversarial examples. In the iterative process of calculating the gradient at each step, the current gradient is not used directly, but the local average gradient is used to accumulate momentum, so as to suppress the local oscillation phenomenon on the loss function surface, thereby stabilizing the update direction and escaping the local extreme point. A large number of experimental results on the ImageNet dataset show that compared with the existing momentum-based method, the average black-box attack success rate of the proposed method in single model attack experiments is improved by 38.07%and 27.77%, and the average black-box attack success rate in integrated model attack experiments is improved by and.Rising32.50%and28.63%

Blade Designs For Improved Multi-Phase Performance In sCO2 Compressors; Part II - Optical Diagnostics In sCO2 And Experimental Evaluation With Particle Image Velocimetry

Abstract This paper presents the second part of a study in which the leading-edge and suction surface of a compressor blade was modified to delay onset of phase change for sCO2 compressors operating near the critical point. Using a first-of-its-kind apparatus for the measurement of sCO2 flow fields, Particle Image Velocimetry (PIV) is used for local flow field measurements of two compressor blade geometries: the modified “biased-wedge,” and a conventional constant thickness blade. Utilizing the developed hardware, the feasibility of a simple, laser-based diagnostic for qualitatively measuring liquid phase regions, is also presented. The design of the optical diagnostics rig, a discussion of numerous challenges, and necessary considerations involved in performing optical-based measurements like PIV, in sCO2, are discussed. Velocity field measurements for the modified compressor profile show a much lower suction peak compared to a conventional blade. These results validate numerical results at the tested conditions, where the suction side profile of the biased wedge works to minimize the local pressure gradient.

A zero-knowledge proof federated learning on DLT for healthcare data

With the increasingly widespread adoption of Healthcare 4.0 practices, new challenges have arisen for the utilization of collected sensitive data. On the one hand, these data have immense potential to unlock valuable insights for personalized medicine, early disease detection, and predictive analysis thanks to the use of Artificial Intelligence. On the other hand, ensuring the protection of patient privacy is of paramount importance to maintain trust and uphold ethical practices within the healthcare system. Classical centralized learning approaches do not fit well with the privacy and security requirements imposed by the law and the sensitivity of treated data, which is why decentralized learning approaches are gaining ground. Among these, Federated Learning (FL) stands out as a viable alternative, providing greater security and performance comparable to classic centralized learning approaches. However, there are still various attacks targeting the local parameters or gradients updated by the participants. Therefore, we present our architecture based on the conjunction of Zero-Knowledge Proof, FL, and blockchain that implements also the decentralized identifier standard. The adoption of this architecture can grant the execution, management, supervision, and updating of the FL process, guaranteeing the resilience of the system and the reliability and traceability of exchanged data. In order to test the performance, robustness, and implementation costs of the proposed architecture, we develop a case study on the prediction of blood glucose levels in people with Type-1-diabetes. The results of our analysis show an improved system in terms of balance between performance privacy and security, guaranteeing high levels of verifiability, therefore proving the proposed architecture suitable for most of the FL processes needed in the healthcare field.

Magnetic-chemotactic hybrid microrobots with precise remote targeting capability.

Micro/nanorobots (MNRs) hold great promise for various applications due to their capability to execute complex tasks in hard-to-reach micro/nano cavities. However, the developed magnetic MNRs, as marionettes of external magnetic fields, lack built-in intelligence for self-targeting, while chemotactic MNRs suffer from limited self-targeting range. Here, we demonstrate magnetic-chemotactic ZnO/Fe-Ag Janus microrobots (JMRs) capable of rapid, remote self-targeting for bacterial elimination. The JMRs utilize the magnetic Fe engine for coarse navigation from a distance, allowing for external control to swiftly guide them to the vicinity of a hidden/uncharted target that establishes a local chemical gradient ([CO2] or [H+] gradient). Once in proximity, the inherent chemotaxis of the JMRs takes over, the chemotactic engine enables them to autonomously accumulate at the target site along the chemical gradient in high precision. Upon reaching the target, the ZnO/Fe-Ag JMRs can release Zn2+ and Ag+ to eliminate bacteria residing there. The proposed strategy of integrating on-board chemotaxis with external magnetic field-driven propulsion paves the way for efficient precise therapies using MNRs, especially in targeted drug/energy delivery involving remote hidden or uncharted targets.

Comparative study of microstructural evolution and mechanical properties in friction stir processed, reinforced friction stir processed, and heat-treated reinforced friction stir processed Al composites

The development of friction stir welding (FSW) created the basic foundation for friction stir processing (FSP). This process entails refining the local microstructure and achieving the localised plastic deformation due to the stirring effect of the tool, which may involve adding additional filler material as required. The rotating tool involved in the process has a shoulder and pin responsible for heat generation for plastic deformation and localised mixing. The rotating tool is inserted and traversed on the desired surface, tailoring the material properties. The tool’s exposure to the surface causes localised plastic deformation and thermal gradient, and microstructural changes occur locally. The present investigation uses Friction Stir Processing (FSP) to fabricate an aluminium metal matrix composite. Recently, the use of aluminium alloy has been replaced by composites because of their increased mechanical and physical properties (specific properties). The experiment leads to manufacturing an aluminium metal matrix composite using aluminium oxide, boron carbide and commercially pure copper dust. Later, the effect of heat treatment on the respective metal matrix composite is studied. A comparative study among three different types of FSP techniques viz. FSP, Reinforced FSP, and Heat-treated Reinforced FSP have been performed. The tool revolution speed (RPM) and tool traverse speed of 400 RPM and 10 mm/min had been implemented, respectively. The T4 Heat-Treatment cycle was used during the current investigation. This investigative study was performed to analyse the changes in grain sizes and hardness values at the stir zone (SZ), thermo-mechanically affected zone (TMAZ), heat affected zone (HAZ) and on the base materials (BM) of the samples. The reinforced FSP metal matrix composite (MMC) showed an 81.26% increase in the micro-hardness value (HV) compared to the base metal. Further on analysing the microstructures, the reinforced FSP composite showed a 65.20% reduction in grain size. Moreover, the Heat-Treated sample showed an increase in the micro-hardness value by 99.8%.

Microplastics in marine sponges (Porifera) along a highly urbanized estuarine gradient in Santos, Brazil

Microplastics (MPs) are ubiquitously found in environmental matrices, particularly affecting aquatic systems. While several marine species have been widely used to assess MP contamination, sponges (Porifera) are less used. The MPs contamination was assessed in the sun sponge (Hymeniacidon heliophila) along a gradient at the Santos Estuarine System (Brazil). A 14-fold difference between concentrations (particles g−1) was verified between the most (1.40 ± 0.81) and least (0.10 ± 0.12) contaminated sites, confirming the local contamination gradient. The MPs found were primarily polypropylene, small (1.2–1000 μm), fibrous, and colored. Considering total concentrations, sizes and shapes these spatial patterns were similar those previously detected in molluscs obtained in the same sites. On the other hand, they differed in polymeric composition and color categories. Such findings give important initial insights into the potential role of marine sponges as putative sentinels of MPs contamination.

Characterizing and predicting the partial slip subjected to variable gradients of velocity and pressure in eccentric micro-scale Taylor–Couette flows

In the context of eccentric micro-scale Taylor–Couette flow, variations in localized flow scales result in a non-uniform fluid–solid interface slip state, distinct from the typically studied uniform slip velocity distribution. This study introduces a boundary condition definition method aimed at characterizing partial slip states, complemented by a coupled iterative analysis system tailored to address this complexity. Key contributions include the development of a method for calculating the limiting shear stress, which considers local velocity gradients and pressures. Validation demonstrates that the locally derived slip state aligns more closely with Knudsen number distributions of local flow scales compared to traditional uniform slip models, and exhibits greater consistency with experimentally measured pressure distributions. Additionally, the study reveals that eccentric Taylor–Couette flow, characterized by significant variations in local flow scales and strong self-induced pressure effects, leads to complex distributions of local pressure, velocity gradients, and differences in local slip velocities. Specifically, the non-uniform distribution of local pressure gradients due to eccentricity results in partial slip occurring predominantly on the rotor in regions with positive pressure gradients, and on the stator in regions with negative pressure gradients. Furthermore, the variation in gap height exerts a greater influence on local slip compared to rotational speed and eccentricity ratio. Under certain conditions influenced by pressure gradients, the slip velocity on the rotor may exceed its tangential speed.

On the isotropy of temperature fluctuations in passive scalar turbulence

We use direct numerical simulation to investigate the scalar gradient skewness downstream of a square grid element. The passive scalar is generated by applying a constant heat flux on the grid element. We primarily focus on the far-downstream grid-element centerline, where the scalar turbulence is homogeneous, and there are no mean velocity or scalar gradients. In this region, some discrepancy exists in the literature concerning the isotropy of the scalar. To the best of our knowledge, this is the first study that measures scalar gradients in all three directions. We detect nonzero skewness for the lateral scalar gradients, while in the streamwise direction, the skewness is zero. We show, through statistical analysis, that the nonzero values are solely due to steep gradients called cliffs. The cliffs originate from the bars of the grid-element that generate sharp mean scalar gradients along the lateral directions in the near wake. These mean gradients decay as the flow develops downstream, but the convected cliffs remember the generating upstream conditions and, in particular, the direction of the mean scalar gradient. Due to this memory effect, the cliffs align preferentially along a specific direction despite the absence of a local mean scalar gradient, thus making the homogeneous scalar field anisotropic. We also report some hitherto undocumented properties of cliffs and ramps through conditional statistical analysis. Finally, we corroborate our conclusions with two additional simulations, one involving grid-element turbulence in the presence of a transverse mean scalar gradient and the other scalar turbulence due to a heated cylinder.

Mechanical and microstructural profiling of additively manufactured cobalt–nickel functional gradient structure

In this study, a functional gradient material (FGM) structure composed of a nickel alloy (IN718), and a cobalt alloy (CoCrMo) was additively manufactured using a co-axial powder-fed laser-directed energy deposition (L-DED) system. The high manufacturing flexibility of L-DED enabled the seamless deposition of IN718-CoCrMo FGM structure through interfacial bonding driven by thermal gradient and cool-down mechanisms. Microscopic analysis confirmed the absence of cracks or delamination in the CoCrMo-IN718 interfacial bonding region. The SEM-EBSD microstructural analysis and micro-hardness testing were performed on the as-printed CoCrMo-IN718 FGM primarily to correlate the hardness properties-microstructural grain phase morphology between the parent alloys and their interfacial bonding region. It was observed that the average hardness of the CoCrMo-IN718 interface zone (322.83 HV1) fell between IN718 (268.67 HV1) and CoCrMo (359.75 HV1) regions. The EBSD analysis reports indicated that along the build direction of CoCrMo-IN718 FGM, the preferential grain orientation aligned in [100] with grain structure transitioning from equiaxed → columnar → elongated columnar dendrites → equiaxed grain, predominantly comprised of face-centered cubic (FCC)-gamma (γ) phase crystal structures. Relatively, coarser grain structures were observed in the interface bonding region, attributed to the analogous crystallography space groups, and prolonged localized thermal gradients.

Growth characteristics of the mean shear layer in pipe bends with and without a guide vane

The growth characteristics of two identical pipe bends with and without a guide vane are investigated by means of large eddy simulation. The two pipe bends, with a radius of curvature slightly above the separation threshold, are subjected to two fully developed upstream flow conditions, with a corresponding Reynolds number of 11 700 and 24 000. A precursor computation method is employed to provide the fully developed turbulence inflow conditions for all cases. The growth of the mean shear layer in this work is characterized by the local momentum thickness, which measures the extent of momentum deficit confined under the mean shear layer. For both pipe bends, the initial growth of momentum thickness is observed in the first quarter of the bend. The onset location is almost independent of the Reynolds numbers. However, a clear Reynolds number dependence is observed in the onset magnitude, which strongly defines the growth rate thereafter. By examining the mean momentum balance in the bend section, the results show that rather than the adverse pressure gradient, the overall growth characteristics of the mean shear layer, which include the onset location and the growth rate, are better described by the balance between the centrifugal force and the radial pressure gradient. This balance manifests itself as a change in the swirling intensity of the secondary flow. The presence of guide vane significantly suppresses the swirling intensity in the bend section, leading to a noticeable reduction in the overall momentum thickness growth and the production of turbulence in the flow downstream of the bend. Further inspection also indicates that the initial mechanism leading to the suppression of separation at the inner bend is linked to the increasing dominance of the small vortices at the near-wall vicinity relative to the local adverse pressure gradient. Certain aspects pertaining to the turbulent statistics are also discussed.

A novel peak positioning method for nanometer displacement measurement by optical linear encoder

In the field of precision measurement, subdividing displacement within the grating period to achieve high precision and high resolution remains a significant challenge. For subdivision, traditional optical linear encoders need complex coding and complicated optical systems, which struggle to meet the demands of nanometer measurement. In this paper, based on the fundamental principles of grating displacement measurement, a high-precision peak positioning method from grating images is proposed for linear displacement measurements with nanometer resolution and submicron accuracy. By utilizing a local gradient interpolation algorithm to optimize curves, it could further improve the accuracy of displacement measurement. Experiments demonstrate that this method achieves a resolution of 2 nm and an accuracy of ± 0.1 μm in a range of 50 mm using a grating with a 20 μm period. This sets the groundwork for subdividing optical linear encoders further, the resolution and accuracy could be further improved by optimizing the subdivision method.

Achievable dual-strategy to stabilize Li-rich layered oxide interface by a one-step wet chemical reaction towards long oxygen redox reversibility

Oxygen release and electrolyte decomposition under high voltage endlessly exacerbate interfacial ramifications and structural degradation of high energy-density Li-rich layered oxide (LLO), leading to voltage and capacity fading. Herein, the dual-strategy of CrxB complex coating and local gradient doping is simultaneously achieved on LLO surface by a one-step wet chemical reaction at room temperature. Density functional theory (DFT) calculations prove that stable B–O and Cr–O bonds through the local gradient doping can significantly reduce the high-energy O 2p states of interfacial lattice O, which is also effective for the near-surface lattice O, thus greatly stabilizing the LLO surface. Besides, differential electrochemical mass spectrometry (DEMS) indicates that the CrxB complex coating can adequately inhibit oxygen release and prevents the migration or dissolution of transition metal ions, including allowing speedy Li+ migration. The voltage and capacity fading of the modified cathode (LLO-CrB) are adequately suppressed, which are benefited from the uniformly dense cathode electrolyte interface (CEI) composed of balanced organic/inorganic composition. Therefore, the specific capacity of LLO-CrB after 200 cycles at 1C is 209.3 mA h g–1 (with a retention rate of 95.1%). This dual-strategy through a one-step wet chemical reaction is expected to be applied in the design and development of other anionic redox cathode materials.