Spinel transition metal oxides are important electrode materials for lithium-ion batteries, whose lithiation undergoes a two-step reaction, whereby intercalation and conversion occur in a sequential manner. These two reactions are known to have distinct reaction dynamics, but it is unclear how their kinetics affects the overall electrochemical response. Here we explore the lithiation of nanosized magnetite by employing a strain-sensitive, bright-field scanning transmission electron microscopy approach. This method allows direct, real-time, high-resolution visualization of how lithiation proceeds along specific reaction pathways. We find that the initial intercalation process follows a two-phase reaction sequence, whereas further lithiation leads to the coexistence of three distinct phases within single nanoparticles, which has not been previously reported to the best of our knowledge. We use phase-field theory to model and describe these non-equilibrium reaction pathways, and to directly correlate the observed phase evolution with the battery's discharge performance.

Colloidal particles with controlled shape and internal structure have attracted great attention due to their novel morphologies and various potential applications. Among the diverse synthetic strategies toward anisotropically shaped polymer particles, facile and accurate engineering of such structures remains challenging. This review highlights the synthetic approaches to manipulate the shape of polymer particles driven by phase separation in emulsions upon solvent evaporation. And, special attention is given to the thermodynamic and kinetic principles of particle shape control, followed by detailed experimental examples and their applications. Major synthetic strategies for the preparation of nonspherical block copolymer (BCP) particles by evaporation of solvent from BCP‐containing emulsions are discussed as follows: engineering of i) interfacial properties of the confining emulsion droplets, ii) particle (or droplet) size, iii) segregation behavior of BCPs within the droplet, and iv) solvent‐induced BCP self‐assembly kinetics (i.e., solvent evaporation rate). Next, functionalized BCP particles produced by careful design of the chemical structures of polymer or by incorporation of functional additives into the polymer matrix are introduced. Finally, this review article aims to present the challenging issues associated with current methods and future directions for research in this field.

Shape and morphology of polymeric particles are of great importance in controlling their optical properties or self-assembly into unusual superstructures. Confinement of block copolymers (BCPs) in evaporative emulsions affords particles with diverse structures, including prolate ellipsoids, onion-like spheres, oblate ellipsoids, and others. Herein, we report that the evaporation rate of solvent from emulsions encapsulating symmetric polystyrene-b-polybutadiene (PS-b-PB) determines the shape and internal nanostructure of micron-sized BCP particles. A distinct morphological transition from the ellipsoids with striped lamellae to the onion-like spheres was observed with decreasing evaporation rate. Experiments and dissipative particle dynamics (DPD) simulations showed that the evaporation rate affected the organization of BCPs at the particle surface, which determined the final shape and internal nanostructure of the particles. Differences in the solvent diffusion rates in PS and PB at rapid evaporation rates induced alignment of both domains perpendicular to the particle surface, resulting in ellipsoids with axial lamellar stripes. Slower evaporation rates provided sufficient time for BCP organization into onion-like structures with PB as the outermost layer, owing to the preferential interaction of PB with the surroundings. BCP molecular weight was found to influence the critical evaporation rate corresponding to the morphological transition from ellipsoid to onion-like particles, as well as the ellipsoid aspect ratio. DPD simulations produced morphologies similar to those obtained from experiments and thus elucidated the mechanism and driving forces responsible for the evaporation-induced assembly of BCPs into particles with well-defined shapes and morphologies.

Carbon-supported, Pt and PtCo nanocrystals (NCs) with controlled size and composition were synthesized and examined for hydrodeoxygenation (HDO) of 5-hydroxymethylfurfural (HMF). Experiments in a continuous flow reactor with 1-propanol solvent, at 120 to 160 °C and 33 bar H2, demonstrated that reaction is sequential on both Pt and PtCo alloys, with 2,5-dimethylfuran (DMF) formed as an intermediate product. However, the reaction of DMF is greatly suppressed on the alloys, such that a Pt3Co2 catalyst achieved DMF yields as high as 98%. XRD and XAS data indicate that the Pt3Co2 catalyst consists of a Pt-rich core and a Co oxide surface monolayer whose structure differs substantially from that of bulk Co oxide. Density functional theory (DFT) calculations reveal that the oxide monolayer interacts weakly with the furan ring to prevent side reactions, including overhydrogenation and ring opening, while providing sites for effective HDO to the desired product, DMF. We demonstrate that control over metal nanoparticle size and composition, along with operating conditions, is crucial to achieving good performance and stability. Implications of this mechanism for other reactions and catalysts are discussed

To understand the metabolic characteristics of Clostridium acetobutylicum and to examine the potential for enhanced butanol production, we reconstructed the genome-scale metabolic network from its annotated genomic sequence and analyzed strategies to improve its butanol production. The generated reconstructed network consists of 502 reactions and 479 metabolites and was used as the basis for an in silico model that could compute metabolic and growth performance for comparison with fermentation data. The in silico model successfully predicted metabolic fluxes during the acidogenic phase using classical flux balance analysis. Nonlinear programming was used to predict metabolic fluxes during the solventogenic phase. In addition, essential genes were predicted via single gene deletion studies. This genome-scale in silico metabolic model of C. acetobutylicum should be useful for genome-wide metabolic analysis as well as strain development for improving production of biochemicals, including butanol.

Here, we report the shape-controlled synthesis of tripodal and triangular gadolinium oxide (Gd2O3) nanoplates. In the presence of lithium ions, the shape of the nanocrystals is readily controlled by tailoring reaction parameters such as temperature and time. We observe that the morphology transforms from an initial tripodal shape to a triangular shape with increasing reaction time or elevated temperatures. Highly uniform Gd2O3 nanoplates are self-assembled into nanofibril-like liquid-crystalline superlattices with long-range orientational and positional order. In addition, shape-directed self-assemblies are investigated by tailoring the aspect ratio of the arms of the Gd2O3 nanoplates. Due to a strong paramagnetic response, Gd2O3 nanocrystals are excellent candidates for MRI contrast agents and also can be doped with rare-earth ions to form nanophosphors, pointing to their potential in multimodal imaging. In this work, we investigate the MR relaxometry at high magnetic fields (9.4 and 14.1 T) and the optical properties including near-IR to visible upconversion luminescence and X-ray excited optical luminescence of doped Gd2O3 nanoplates. The complex shape of Gd2O3 nanoplates, coupled with their magnetic properties and their ability to phosphoresce under NIR or X-ray excitation which penetrate deep into tissue, makes these nanoplates a promising platform for multimodal imaging in biomedical applications.

BackgroundThere have been several methods developed for the prediction of synthetic metabolic pathways leading to the production of desired chemicals. In these approaches, novel pathways were predicted based on chemical structure changes, enzymatic information, and/or reaction mechanisms, but the approaches generating a huge number of predicted results are difficult to be applied to real experiments. Also, some of these methods focus on specific pathways, and thus are limited to expansion to the whole metabolism.ResultsIn the present study, we propose a system framework employing a retrosynthesis model with a prioritization scoring algorithm. This new strategy allows deducing the novel promising pathways for the synthesis of a desired chemical together with information on enzymes involved based on structural changes and reaction mechanisms present in the system database. The prioritization scoring algorithm employing Tanimoto coefficient and group contribution method allows examination of structurally qualified pathways to recognize which pathway is more appropriate. In addition, new concepts of binding site covalence, estimation of pathway distance and organism specificity were taken into account to identify the best synthetic pathway. Parameters of these factors can be evolutionarily optimized when a newly proven synthetic pathway is registered. As the proofs of concept, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-CoA were predicted. The prediction shows a high reliability, in which experimentally verified synthetic pathways were listed within the top 0.089% of the identified pathway candidates.ConclusionsIt is expected that the system framework developed in this study would be useful for the in silico design of novel metabolic pathways to be employed for the efficient production of chemicals, fuels and materials.

We examined the packing structure of polystyrene-coated gold nanoparticles (Au@PS) as a function of grafting density. A series of Au@PS nanoparticles with grafting densities in the range of 0.51−1.94 chains nm −2 were prepared by a ligand exchange process using thiol-terminated PS and then selfassembled at a liquid−air interface. We observed a transition from disordered to bodycentered cubic (bcc) to face-centered cubic (fcc) arrangements with increasing grafting density, even though the ligand length-to-core radius ratio (λ) was as high as 3.0, a condition that typically favors nonclose-packed bcc symmetry in the self-assembly of hard nanoparticles. To explain this phenomenon, we define λ eff to include the concentrated polymer brush regime as part of the "hard core", which predicts that the softness of Au@PS nanoparticles is reduced from 1.53 to 0.14 in a theta solvent as the grafting density increases from 0.51 to 1.94 chains nm −2 . This new definition of λ can also predict the effective radii of nanoparticles using the established optimal packing model. The experimental findings are supported by a combination of coarse-grained molecular dynamics simulation and adaptive common neighbor analysis, which show that changes in grafting density can drive the observed transitions in nanoparticle packing. These studies provide new insights for controlling the selfassembled symmetries of polymer-coated nanocrystals using a simple ligand exchange process to tune particle softness.