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A novel approach is presented by integrating images-driven deep learning (DL) with high entropy oxides (HEOs) analysis. A fully convolutional neural network (FCN) is used to interpret experimental scanning transmission electron microscopy (STEM) images of HEO of various sizes. The FCN model is designed to predict column heights (CHs) and elemental distributions from single, experimentally acquired STEM images of complex (Mn, Fe, Ni, Cu, Zn)3O4 HEO nanoparticles (NPs) at atomic resolution. The model's ability to predict elemental distributions was tested across various crystallographic zones. It was found that the model could effectively adapt to different atomic configurations and operational conditions. One of the significant outcomes was the identification of substantial elemental inhomogeneities in all experimental NPs, which highlighted the random and complex nature of element distribution within HEOs. The developed FCN DL method can be applied to assist experimental HEO and beyond NP analysis in various operating conditions. [ABSTRACT FROM AUTHOR]

The nucleation and growth of nanoparticles are critical processes determining the size, shape, and properties of resulting nanoparticles. However, understanding the complex mechanisms guiding the formation and growth of colloidal multielement alloy nanoparticles remains incomplete due to the involvement of multiple elements with different properties. This study investigates in situ colloidal synthesis of multielement alloys using transmission electron microscopy (TEM) in a liquid cell. Two different pathways for nanoparticle formation in a solution containing Au, Pt, Ir, Cu, and Ni elements, resulting in two distinct sets of particles are observed. One set exhibits high Au and Cu content, ranging from 10 to 30 nm, while the other set is multi‐elemental, with Pt, Cu, Ir, and Ni, all less than 4 nm. The findings suggest that, besides element miscibility, metal ion characteristics, particularly reduction rates, and valence numbers, significantly impact particle composition during early formation stages. Density functional theory (DFT) simulations confirm differences in nanoparticle composition and surface properties collectively influence the unique growth behaviors in each nanoparticle set. This study illuminates mechanisms underlying the formation and growth of multielement nanoparticles by emphasizing factors responsible for chemical separation and effects of interplay between composition, surface energies, and element miscibility on final nanoparticles size and structure. [ABSTRACT FROM AUTHOR]

Understanding the thermal decomposition of metal salt precursors on carbon structures is essential for the controlled synthesis of metal‐decorated carbon nanomaterials. Here, the thermolysis of a Ni precursor salt, NiCl2·6H2O, on amorphous carbon (a‐C) and graphene oxide (GO) substrates is explored using in situ transmission electron microscopy. Thermal decomposition of NiCl2·6H2O on GO occurs at higher temperatures and slower kinetics than on a‐C substrate. This is correlated to a higher activation barrier for Cl2 removal calculated by the density functional theory, strong Ni‐GO interaction, high‐density oxygen functional groups, defects, and weak van der Waals using GO substrate. The thermolysis of NiCl2·6H2O proceeds via multistep decomposition stages into the formation of Ni nanoparticles with significant differences in their size and distribution depending on the substrate. Using GO substrates leads to nanoparticles with 500% smaller average sizes and higher thermal stability than a‐C substrate. Ni nanoparticles showcase the fcc crystal structure, and no size effect on the stability of the crystal structure is observed. These findings demonstrate the significant role of carbon substrate on nanoparticle formation and growth during the thermolysis of carbon–metal heterostructures. This opens new venues to engineer stable, supported catalysts and new carbon‐based sensors and filtering devices. [ABSTRACT FROM AUTHOR]

Tunnel‐structured MnO2 represents open‐framed electrode materials for reversible energy storage. Its wide application is limited by its poor cycling stability, whose structural origin is unclear. We tracked the structure evolution of β‐MnO2 upon Li+ ion insertion/extraction by combining advanced in situ diagnostic tools at both electrode level (synchrotron X‐ray scattering) and single‐particle level (transmission electron microscopy). The instability is found to originate from a partially reversible phase transition between β‐MnO2 and orthorhombic LiMnO2 upon lithiation, causing cycling capacity decay. Moreover, the MnO2/LiMnO2 interface exhibits multiple arrow‐headed disordered regions, which severely chop into the host and undermine its structural integrity. Our findings could account for the cycling instability of tunnel‐structured materials, based on which future strategies should focus on tuning the charge transport kinetics toward performance enhancement. [ABSTRACT FROM AUTHOR]

The morphology and crystallinity of electrode materials have a major effect on their charge carrier storage properties when applied in rechargeable batteries. While nanosizing electrode particles (with larger surface area) and maintaining electrode integrity are both good for performance enhancement, they seem to contradict each other and are challenging to balanced. Herein, electrode particles consisting of numerous nanograins with uniform crystalline orientation are designed to guarantee both high surface area and high structural integrity, allowing the significant improvement of Li+ storage kinetics and performance. Applying this "mesocrystallizing" strategy to an NiCo2O4‐based anode, results in various degrees of pseudocapacitance response, the long‐term cyclability and rate performance of this material are also significantly enhanced. Impressively, the mesocrystalline NiCo2O4 electrode exhibits a high specific capacity of 1403 mAh g–1 after 200 cycles at 1.6 A g–1 (a rate of 1.8 C). The growth mechanism of mesocrystalline materials with different morphologies is identified to be a topotactic structural transition process featuring a gradual edge‐to‐core corrosion process. This work presents an important synthetic clue to balance the morphology and crystallinity of battery electrode materials for their performance optimization and is expected to inspire future structural design for battery materials beyond the one prototyped here. [ABSTRACT FROM AUTHOR]

Understanding the behavior of confined matter within Van der Waals (VdW) materials is complicated due to the interplay of various factors, including the VdW interaction between the interlayers, the layer interaction with the matter, and the bending strain energy of the layers to accommodate encapsulation. Herein, new insight on the magnitude of pressure and density of water entrapped within confined spaces in VdW materials is provided. This is accomplished by studying the plasmon excitation of water encapsulated between two sheets of graphene membranes in an aberration‐corrected scanning transmission electron microscope. The results indicate ≈12% maximum increase in the density of water under tight graphene encasement, where pressure as high as 400 MPa is expected. The pressure estimation from theoretical analysis considering the effect of VdW forces, Laplace pressure, and strain energy is in agreement with the experimental results. The findings of this work open new opportunities to explore the local physical state of not only water but also other liquid materials under high pressure with imaging and analytical resolutions never achieved before. [ABSTRACT FROM AUTHOR]

LiCoO2 is a prime example of widely used cathodes that suffer from the structural/thermal instability issues that lead to the release of their lattice oxygen under nonequilibrium conditions and safety concerns in Li‐ion batteries. Here, it is shown that an atomically thin layer of reduced graphene oxide can suppress oxygen release from LixCoO2 particles and improve their structural stability. Electrochemical cycling, differential electrochemical mass spectroscopy, differential scanning calorimetry, and in situ heating transmission electron microscopy are performed to characterize the effectiveness of the graphene‐coating on the abusive tolerance of LixCoO2. Electrochemical cycling mass spectroscopy results suggest that oxygen release is hindered at high cutoff voltage cycling when the cathode is coated with reduced graphene oxide. Thermal analysis, in situ heating transmission electron microscopy, and electron energy loss spectroscopy results show that the reduction of Co species from the graphene‐coated samples is delayed when compared with bare cathodes. Finally, density functional theory and ab initio molecular dynamics calculations show that the rGO layers could suppress O2 formation more effectively due to the strong COcathode bond formation at the interface of rGO/LCO where low coordination oxygens exist. This investigation uncovers a reliable approach for hindering the oxygen release reaction and improving the thermal stability of battery cathodes. [ABSTRACT FROM AUTHOR]

The article discusses the study of revealing nanoscale mineralization pathways of hydroxyapatite using in situ liquid cell transmission electron microscopy. Topics discussed include treat impairments in hard tissues or overcome pathological calcification in soft tissues, a detailed understanding of mineralization pathways of calcium phosphate materials is needed; and report a detailed mechanistic study of hydroxyapatite (HA) mineralization pathways in an artificial saliva solution.

It has been long believed that colloidal nickel hydroxide nanoparticles are produced by the reaction of nickel salts, glycerol and potassium hydroxide known as the Tower method. In the present work, we challenge this belief and reveal the reasons for error in identification of nickel products produced by the Tower method. We propose that Ni-based precursor complexes are the primary products of the Tower method reaction, and these precursors undergo transition to layered Ni-glycerolate derivatives upon thermal treatment. We demonstrated the presence of Ni2+ coordinated to different types of O-donor ligands (glycerol, glycerolate ion, acetate ion and/or OH−) forming Ni-complex precursors. Using in-situ transmission electron microscopy, we showed that Ni-based precursor complexes can be converted to nickel nanoparticles upon exposure to electron beam, but no evidence of nickel hydroxide nanoparticle formation was found. The nickel hydroxide nanoparticles are only formed upon further reaction of Ni-glycerolate precursors with an aqueous alkaline solution. Those new findings shed light on the nature of the metal derivatives obtained by the reaction of Ni2+ and glycerol in the Tower method and provide more solid foundation to design electrode materials for batteries, supercapacitors, electrocatalysts and electrochemical sensors. • Ni-based materials were carefully prepared and analyzed by different electrochemical characterization techniques. • Ni-glycerolates are the most probable products of Tower's method after thermal processing. • Nickel nanoparticles are obtained by irradiation with electron beam during electron microscopy assays. • Nickel hydroxide nanoparticles are only formed upon further reaction with an aqueous alkaline solution. [ABSTRACT FROM AUTHOR]

Sodium-ion batteries (SIBs) have attracted a great deal of attention recently as an economic alternative to Li-ion batteries. Cost-efficient reduced graphene oxide (rGO) has been intensively studied as both an active material and a functional additive in SIBs. However, the sodiation-desodiation process in rGO is not fully understood. In this study, we investigate the interaction of the Na ion with rGO by in situ transmission electron microscopy (TEM). For the first time, we observe reversible Na metal cluster (with a diameter of >10 nm) deposition on a rGO surface, which we evidence with an atom-resolved high-resolution TEM image of Na metal. This discovery leads to a porous reduced graphene oxide SIB anode with record high reversible specific capacity around 450 mAh/g at 25 mA/g, a high rate performance of 200 mAh/g at 250 mA/g, and stable cycling performance up to 750 cycles. In addition, direct observation of irreversible formation of Na2O on rGO unveils the origin of the commonly observed low first Columbic efficiency of rGO-containing electrodes. [ABSTRACT FROM AUTHOR]

With the increased need for high-rateLi-ion batteries, it has become apparent that new electrode materialswith enhanced Li-ion transport should be designed. Interfaces, suchas twin boundaries (TBs), offer new opportunities to navigate theionic transport within nanoscale materials. Here, we demonstrate theeffects of TBs on the Li-ion transport properties in single crystallineSnO2nanowires. It is shown that the TB-assisted lithiationpathways are remarkably different from the previously reported lithiationbehavior in SnO2nanowires without TBs. Our in situ transmissionelectron microscopy study combined with direct atomic-scale imagingof the initial lithiation stage of the TB-SnO2nanowiresprove that the lithium ions prefer to intercalate in the vicinityof the (101̅) TB, which acts as conduit for lithium-ion diffusioninside the nanowires. The density functional theory modeling showsthat it is energetically preferred for lithium ions to accumulatenear the TB compared to perfect neighboring lattice area. These findingsmay lead to the design of new electrode materials that incorporateTBs as efficient lithium pathways, and eventually, the developmentof next generation rechargeable batteries that surpass the rate performanceof the current commercial Li-ion batteries. [ABSTRACT FROM AUTHOR]

In rechargeable lithium-ion batteries,understanding the atomic-scalemechanism of Li-induced structural evolution occurring at the hostelectrode materials provides essential knowledge for design of newhigh performance electrodes. Here, we report a new crystalline–crystallinephase transition mechanism in single-crystal Zn–Sb intermetallicnanowires upon lithiation. Using in situ transmission electron microscopy,we observed that stacks of atomic planes in an intermediate hexagonal(h-)LiZnSb phase are “shuffled” toaccommodate the geometrical confinement stress arising from lamellarnanodomains intercalated by lithium ions. Such atomic rearrangementarises from the anisotropic lithium diffusion and is accompanied byappearance of partial dislocations. This transient structure mediatesfurther phase transition from h-LiZnSb to cubic (c-)Li2ZnSb, which is associated with a nearly “zero-strain”coherent interface viewed along the [001]h/[111]cdirections. This study providesnew mechanistic insights into complex electrochemically driven crystalline–crystallinephase transitions in lithium-ion battery electrodes and representsa noble example of atomic-level structural and interfacial rearrangements. [ABSTRACT FROM AUTHOR]

The physico-chemical and mechanical properties of metallic (e.g., Au, Pt) nanoparticle complexes highly depend on the order and the distribution of their atomic structure. While transmission electron microscopy (TEM) provides the highest spatial resolution to an image of the nanoparticle's atomic structure, it is time consuming and cumbersome to estimate the atomic column height from the two-dimensional projected TEM images. With continued progress of in-situ or operando TEM techniques in discovery of nanoscale science, it is paramount to develop artificial intelligence approaches that can be integrated with real-time TEM imaging. In this work, we present a modeling framework based upon deep learning approach (i.e., convolutional neural network – CNN) for the detection of the atomic column heights in the experimental high-resolution transmission electron microscopy (HRTEM) images of gold nanoparticles of different sizes. For this purpose, we propose a method for the generation of the training dataset based on the Wulff construction, in order to bring a physically realistic treatment to the network's learning process. Moreover, we introduce a model based on the regression scheme, as a valid alternative to a classification approach reported in the prior literature. In addition to counting atoms in verity of columns and nanoparticles, the model also provides insights concerning the experimental conditions suitable for the appropriate identification of atomic column heights by the neural network. Thus, the developed modeling approach establishes a basis for accelerated or 'on-the-fly' analysis of nanoparticles as well as a framework for extending deep learning models to broad applications in nanoscience. [ABSTRACT FROM AUTHOR]

LiCoO2 is a prime example of widely used cathodes that suffer from the structural/thermal instability issues that lead to the release of their lattice oxygen under nonequilibrium conditions and safety concerns in Li‐ion batteries. Here, it is shown that an atomically thin layer of reduced graphene oxide can suppress oxygen release from LixCoO2 particles and improve their structural stability. Electrochemical cycling, differential electrochemical mass spectroscopy, differential scanning calorimetry, and in situ heating transmission electron microscopy are performed to characterize the effectiveness of the graphene‐coating on the abusive tolerance of LixCoO2. Electrochemical cycling mass spectroscopy results suggest that oxygen release is hindered at high cutoff voltage cycling when the cathode is coated with reduced graphene oxide. Thermal analysis, in situ heating transmission electron microscopy, and electron energy loss spectroscopy results show that the reduction of Co species from the graphene‐coated samples is delayed when compared with bare cathodes. Finally, density functional theory and ab initio molecular dynamics calculations show that the rGO layers could suppress O2 formation more effectively due to the strong COcathode bond formation at the interface of rGO/LCO where low coordination oxygens exist. This investigation uncovers a reliable approach for hindering the oxygen release reaction and improving the thermal stability of battery cathodes. [ABSTRACT FROM AUTHOR]