Improvement in the stability and bioavailability of pumpkin lutein using ß-cyclodextrin microcapsules.

Growing concerns about food nutrition and food supplies have encouraged the development of effective constituents. Lutein is an important nutrient element, and its health benefits are gradually being recognized. Lutein, as a carotenoid antioxidant, can protect cells and organs from damage caused by free radicals. However, in processing, storage, and usage, lutein is unstable and often undergoes isomerization and oxidative decomposition, which limits its wide range of applications. ß-Cyclodextrin is an ideal substrate to prepare microcapsule structures, which are highly biocompatible and nontoxic. During the lutein encapsulation process, ideal ß-cyclodextrin microcapsules were used to form inclusion compounds. The results reveal that the encapsulation efficiency of the microcapsules reached 53%. Moreover, using ultrasonic-assisted extraction can easily and efficiently purify lutein. In addition, the capability of the ß-cyclodextrin composite shell can enhance the bioactive molecules' activity and stability.

SISSO-assisted prediction and design of mechanical properties of porous graphene with a uniform nanopore array.

Mechanical properties of porous graphene can be effectively tuned by tailoring the nanopore arrangement. Knowledge of the relationship between the porous structure and overall mechanical properties is thus essential for the wide potential applications, and the existing challenge is to efficiently predict and design the mechanical properties of porous graphene due to the diverse nanopore arrangements. In this work, we report on how the SISSO (Sure Independence Screening and Sparsifying Operator) algorithm can be applied to build a bridge between the mechanical properties of porous graphene and the uniform nanopore array. We first construct a database using the strength and work of fracture calculated by large-scale molecular dynamics simulations. Then the SISSO algorithm is adopted to train a predictive model and automatically derive the optimal fitting formulae which explicitly describe the nonlinear structure-property relationships. These expressions not only enable the direct and accurate prediction of targeted properties, but also serve as a convenient and portable tool for inverse design of the porous structure. Compared with other forecasting methods including several popular machine learning algorithms, the SISSO algorithm shows its advantages in both accuracy and convenience.

Structure-dependent mechanical properties of self-folded two-dimensional nanomaterials.

The design of self-folded two-dimensional nanomaterials (SF-2DNMs) has been proposed to greatly enhance the ductility of two-dimensional material assemblies. However, the dependences of the mechanical properties of SF-2DNMs on the folded geometries have not been fully clarified. In this paper, we develop a theoretical model to describe the mechanical properties of SF-2DNMs based on the shear-lag analysis. With this model, the load transfer behaviors in SF-2DNMs are demonstrated. The Young's modulus and tensile strength of SF-2DNMs are found to increase and then converge with the fold length, which agree well with the results of molecular dynamics simulations. Moreover, the phase diagrams of failure modes are obtained for SF-2DNMs and their stacked assemblies, providing design criteria for the geometries of SF-2DNMs. The structure-property relationship revealed in our study will provide useful guidelines for the structure design and property optimization of SF-2DNMs.

2D-Topology-Seeded Graphitization for Highly Thermally Conductive Carbon Fibers.

Highly thermally conductive carbon fibers (CFs) have become an important material to meet the increasing demand for efficient heat dissipation. To date, high thermal conductivity has been only achieved in specific pitch-based CFs with high crystallinity. However, obtaining high graphitic crystallinity and high thermal conductivity beyond pitch-CFs remains a grand challenge. Here, a 2D-topology-seeded graphitization method is presented to mediate the topological incompatibility in graphitization by seeding 2D graphene oxide (GO) sheets into the polyacrylonitrile (PAN) precursor. Strong mechanical strength and high thermal conductivity up to 850 W m- 1 K-1 are simultaneously realized, which are one order of magnitude higher in conductivity than commercial PAN-based CFs. The self-oxidation and seeded graphitization effect generate large crystallite size and high orientation to far exceed those of conventional CFs. Topologically seeded graphitization, verified in experiments and simulations, allows conversion of the non-graphitizable into graphitizable materials by incorporating 2D seeds. This method extends the preparation of highly thermally conductive CFs, which has great potential for lightweight thermal-management materials.

Manipulating Uniform Nucleation to Achieve Dendrite-Free Zn Anodes for Aqueous Zn-Ion Batteries.

The essence of Zn dendrite formation is ultimately derived from Zn nucleation and growth during the repeated Zn plating/stripping process. Here, the nucleation process of Zn has been analyzed using ex situ scanning electron microscopy to explore the formation of the initial Zn dendrite, demonstrating that the formation of tiny protrusions (the initial state of Zn dendrites) is caused by the inhomogeneity of Zn nucleation. Based on this, the uniform Zn nucleation is promoted by the Ni5Zn21 alloy coating (ZnNi) on the surface of Zn foil by electrodeposition, and the mechanism of ZnNi-promoted even nucleation is further analyzed with the assistance of density functional theory (DFT). The DFT results indicate that the ZnNi displays a stronger binding ability to Zn compared to the bare Zn, suggesting that Zn nuclei will preferentially form around ZnNi instead of continuing to grow on the surface of the initial Zn nuclei. Therefore, the designed Zn metal anode (Zn@ZnNi) can be ultra-stable for over 2200 h at a current density of 2 mA cm-2 in the symmetric cell. Even at a much higher current density of 20 mA cm-2, the extra-long life of over 2200 cycles (over 530 h) can be achieved. Moreover, the full cell with the Zn@ZnNi anode exhibits extra-long cycling performance for 500 cycles with a capacity of 207.7 mA h g-1 and 1100 cycles (148.5 mA h g-1) at a current density of 0.5 and 1 A g-1, respectively.

Driving the Interfacial Ion-Transfer Kinetics by Mesoporous TiO2 Spheres for High-Performance Aqueous Zn-Ion Batteries.

The aqueous zinc-ion batteries (ZIBs) have been considered as a promising energy storage device. However, the ion transfer at the Zn metal anode-electrolyte interface is limited by the sluggish kinetics resulting in high interface resistance. Herein, mesoporous TiO2 (m-TiO2) is coated on the Zn foil (Zn-TiO2) driving the ion's faster transfer to reduce interface resistance (70.1 Ω vs 799.3 Ω of bare Zn). The lower interface resistance is ascribed to shortening the ion transfer path provided by the mesoporous structure and the smaller Zn2+ absorption energy barrier of the surface of the Zn-TiO2 anode as well as the unobstructed ion transfer path at the crystal planes (100) of TiO2, which have been supported by the density functional theory (DFT) calculation and experiments. Therefore, the Zn-TiO2 anodes in the symmetrical cells display a low voltage hysteresis (36.5 mV) and long-term cycling stability (500 h at 4.4 mA cm-2). Especially, the Zn-TiO2/MnO2 full cells show superior cycling performance with a high capacity of 269.8 mAh g-1 after 50 cycles at 0.2 A g-1 and 210.9 mAh g-1 after 1000 cycles at 0.5 A g-1. The analysis of ion-transfer kinetics at the interface provides deep enlightenment and reference for the study of the metal anodes.

Unveiling the mechanism of structure-dependent thermal transport behavior in self-folded graphene film: a multiscale study.

Understanding the relationship between the microstructures and overall properties is one of the basic concerns for material design and applications. As a ubiquitous structural configuration in nature, the folded morphology is also widely observed in graphene-based nanomaterials, namely grafold. Recently, a self-folded graphene film (SF-GF) material has been successfully fabricated by the assembly of grafolds and exhibits promising applications in thermal management. However, the dependence of thermal properties of SF-GF on the structural features of grafold has remained unclear. We here develop a theoretical model to describe the thermal transport behavior in SF-GF. Our model demonstrates the relationship between the fold length of grafolds and thermal properties of SF-GF. It serves as an efficient and portable tool to predict the temperature profile and thermal conductivity of SF-GF with good validations by large-scale molecular dynamics simulations. Using this model, we further study the evolution of thermal conductivity of SF-GF with the unfolding deformation during the stretch. Moreover, the effect of geometrical irregularity of grafolds is uncovered. The model developed in this work not only provides practical guidelines for the manipulation and design of thermal properties of SF-GF, but also benefits the understanding of thermal transport behaviors in other two-dimensional nanomaterials with folded structures.

Asymmetric elastoplasticity of stacked graphene assembly actualizes programmable untethered soft robotics.

There is ever-increasing interest yet grand challenge in developing programmable untethered soft robotics. Here we address this challenge by applying the asymmetric elastoplasticity of stacked graphene assembly (SGA) under tension and compression. We transfer the SGA onto a polyethylene (PE) film, the resulting SGA/PE bilayer exhibits swift morphing behavior in response to the variation of the surrounding temperature. With the applications of patterned SGA and/or localized tempering pretreatment, the initial configurations of such thermal-induced morphing systems can also be programmed as needed, resulting in diverse actuation systems with sophisticated three-dimensional structures. More importantly, unlike the normal bilayer actuators, our SGA/PE bilayer, after a constrained tempering process, will spontaneously curl into a roll, which can achieve rolling locomotion under infrared lighting, yielding an untethered light-driven motor. The asymmetric elastoplasticity of SGA endows the SGA-based bi-materials with great application promise in developing untethered soft robotics with high configurational programmability.

Multilayer Graphene-Based Thermal Rectifier with Interlayer Gradient Functionalization.

As a counterpart of electrical and optical diodes with asymmetric transmission properties, the nanoscale thermal rectifier has attracted huge attention. Graphene has been expected as the most promising candidate for the design and fabrication of high-performance thermal rectifiers. However, most reported graphene-based thermal rectification has been achieved only within the plane of the graphene layer, and the efficiency is heavily limited by the lateral size, restricting the potential applications. In this paper, we propose a design of multilayer graphene-based thermal rectifier (MGTR) with interlayer gradient functionalization. A unique thermal rectification along the vertical direction without lateral size limitation is demonstrated by molecular dynamics simulations. The heat flux prefers to transport from a fully hydrogenated graphene layer to a pristine graphene layer. The analysis of phonon density of states reveals that the mismatch between dominant frequency domains plays a crucial role in the vertical thermal rectification phenomenon. The impacts of temperature and strain on the rectification efficiency are systematically investigated, and we verify the interlayer welding process as an effective approach to eliminate the degradation induced by out-of-plane compression. In addition, compared with uniform hydrogenation at average H-coverage, an anomalous enhancement of in-plane thermal conductivity of multilayer graphene with interlayer gradient hydrogenation is observed. The proposed MGTR has great potential in designing devices for heat management and logic control.

Correction: Mechanical and thermal properties of grain boundary in a planar heterostructure of graphene and hexagonal boron nitride.

Correction for 'Mechanical and thermal properties of grain boundary in a planar heterostructure of graphene and hexagonal boron nitride' by Yinfeng Li, et al., Nanoscale, 2018, DOI: 10.1039/c7nr07306b.

Mechanical and thermal properties of grain boundary in a planar heterostructure of graphene and hexagonal boron nitride.

In this study, the mechanical properties of grain boundaries (GBs) in planar heterostructures of graphene and hexagonal boron nitride (h-BN) were studied using the molecular dynamics method in combination with the density functional theory and classical disclination theory. The hybrid interface between graphene and h-BN grains was optimally matched by a non-bisector GB composed of pentagon-heptagon defects arranged in a periodic manner. GB was found to be a vulnerable spot to initiate failure under uniaxial tension; moreover, the tensile strength was found to anomalously increase with an increase in the mismatch angle between graphene and h-BN grains, i.e., the density of pentagon-heptagon defects along the GBs. The disclination theory was successfully adopted to predict the stress field caused by lattice mismatch at the GB. Comparison between stress contours of GBs with different mismatch angles demonstrates that the arrangement of 5-7 disclinations along the GB is crucial to the strength, and the stress concentration at the GB decreases with an increase in disclination density; this results in an anomalous increase of strength with an increase in the mismatch angle of grains. Moreover, the thermal transfer efficiency of the hybrid GB was revealed to be dependent not only on the mismatch angle of grains but also on the direction of the thermal flux. Thermal transfer efficiency from graphene to h-BN is higher than that from h-BN to graphene. Detailed analyses for the phonon density of states (PDOS) of GB atoms were carried out for the mismatch angle-dependence of interfacial conductance. Our results provide useful insights for the application of two-dimensional polycrystalline heterostructures in next-generation electronic nanodevices.

Expression of insulin-like growth factors (IGFs) and IGF signaling: molecular complexity in uterine leiomyomas.

OBJECTIVE: To study whether dysregulation of insulin-like growth factors (IGFs) and IGF signaling are common molecular changes in symptomatic leiomyomas (fibroids) and whether IGFs are associated with large fibroids. DESIGN: Examination of IGFs and IGF pathway genes in a large cohort of fibroids at transcriptional and translational levels. Mechanisms leading to alterations of IGFs and related genes were also analyzed. SETTING: University clinical research laboratory. PATIENT(S): Hysterectomies for symptomatic fibroids were collected: 180 cases from paraffin-embedded tissues and 50 cases from fresh-frozen tissues. INTERVENTION(S): Tissue microarray and immunohistochemistry, DNA methylation analysis, reverse-transcriptase polymerase chain reaction, and Western blot. MAIN OUTCOME MEASUREMENT(S): Transcription and translation analyses of IGF-1/2, p-AKT, p-S6K, and TSC1/2 in fibroids and matched myometrium. RESULT(S): Insulin-like growth factors and downstream effectors were dysregulated in approximately one third of fibroids. All except for IGF-2 seemed to be abnormally regulated at translation levels. Up-regulation of IGF-2 messenger RNAs was contributed by all four alternating slicing promoters. There was a positive correlation of IGF-1 and p-AKT over-expression with fibroid size. Insulin-like growth factor 1 but not IGF-2 levels directly correlated with activation of p-AKT and p-S6K. CONCLUSION(S): Altered expressions of IGFs and their related downstream proteins were found in one third of fibroids. Large fibroids show high levels of IGF-1 and p-AKT activity compared with small ones.