Activity

We explore extensively topological quantum phase transitions (TQPTs) of the breathing kagomé lattice model in the presence of staggered fluxes. We obtain rich topological phases, including the Chern insulator (CI) and the second-order topological insulator (SOTI) phases, by tuning the dimerized hopping parametert1′ and the staggered-flux parameterϕ. The CI phases can be identified on the basis of the chiral edge states and the non-zero Chern numbers. However, in sharp contrast to the CI phases, the SOTI phases are characterized by the robust corner states and the quantized polarizations. selleckchem In addition, we explore the TQPTs considering the next-nearest-neighbor hopping parametert2. We demonstrate the existence of two-dimensional SOTIs with broken time-reversal symmetry and reveal the TQPTs between the CIs and the SOTIs.Charge density wave (CDW) is an intriguing physical phenomenon especially found in two-dimensional (2D) layered systems such as transition-metal dichalcogenides (TMDs). The study of CDW is vital for understanding lattice modification, strongly correlated electronic behaviors, and other related physical properties. This paper gives a review of the recent studies on CDW emerging in 2D TMDs. First, a brief introduction and the main mechanisms of CDW are given. Second, the interplay between CDW patterns and the related unique electronic phenomena (superconductivity, spin, and Mottness) is elucidated. Then various manipulation methods such as doping, applying strain, local voltage pulse to induce the CDW change are discussed. Finally, examples of the potential application of devices based on CDW materials are given. We also discuss the current challenge and opportunities at the frontier in this research field.The stability and the electronic properties of two dimensional (2D) GaAs/MoSSe Janus interfaces were investigated using first principles density functional theory calculations. The effect of different atomic terminations on the interface stability, electronic properties and charge transfer at the interfaces were analyzed. Metallic states are formed at the stable MoSSe/GaAs interface owing to the synergistic effect of the presence of 2D occupied antibonding states in MoSSe and the band alignment at the interface. The non-symmetric structure of MoSSe Janus material turns out to play a key role to control the electronic properties of the stable Janus interface, which will be crucial deciding factor for practical applications.Pineapple, as a world-famous tropical fruit, is also prone to produce by-products rich in cellulose. In this study, different sections of pineapple, including pineapple core (PC), pineapple pulp (PPu), pineapple leaf (PL) and pineapple peel (PPe) were used for production of pineapple cellulose nanocrystals (PCNCs) by sulfuric acid hydrolysis. The crystallinity of PCNCs from PC, PPu, PL and PPe were 57.81%, 55.68%, 59.19% and 53.58%, respectively, and the thermal stability of PCNCs in order was PC > PL > PPe > PPu. The prepared PCNCs from PC, PPu, PL and PPe were needle like structure at the average aspect ratios of 14.2, 5.6, 5.5, and 14.8, respectively. Additionally, the differences in the structure and properties of PCNCs affected the stability of the prepared Pickering emulsions, which ranked as PPu > PPe > PL > PC. The Pickering emulsions stabilized by PCNCs prepared from PPu could be stored stably for more than 50 d. These results show the differences of PCNCs from four sections of pineapple, and provide isolated raw material selection for the further application of PCNCs.Electrons can degrade pentachlorphenate sodium (PCPNa) directly or activate molecular oxygen to produce·O2-and ·OH for its degradation. However, less work has been performed to control such two kinds of reaction pathway by modifying BiOCl. Herein, we firstly regulated the reaction pathway between electrons and PCPNa by adjusting the amount of surface oxygen vacancies (OVs) and surface adsorbed hydroxyl groups in I-doped BiOCl exposed with different facets. OVs on (001) facets-exposed I-doped BiOCl enabled large amount of PCPNa to adsorb on its surface and facilitated the direct reaction between electrons and PCPNa. In contrary, more surface adsorbed hydroxyl groups and oxygen on (010) facets-exposed I-doped BiOCl can retard the direct reaction between electrons and PCPNa via lowering the adsorption of PCPNa and increasing the activation of molecular oxygen by electrons. Although more·O2-and ·OH generated in I-doped (010)-facets exposed BiOCl, I-doped (001)-facets exposed BiOCl exhibited better photocatalytic activity. We proposed that the direct reaction between electrons and PCPNa can enhance the utilization efficiency of photogenerated electrons and improve photocatalytic degradation efficiency of PCPNa.Fiber constructed yarns are the elementary building blocks for the generation of implantable biotextiles, and there are always needs for designing and developing new types of yarns to improve the properties of biotextile implants. In the present study, we aim to develop novel nanofiber yarns (NYs) by combining nanostructure that more closely mimic the extracellular matrix fibrils of native tissues with biodegradability, strong mechanical properties and great textile processibility. A novel electrospinning system which integrates yarn formation with hot drawing process was developed to fabricate poly(L-lactic acid) (PLLA) NYs. Compared to the PLLA NYs without hot drawing, the thermally drawn PLLA NYs presented superbly-orientated fibrous structure and notably enhanced crystallinity. Importantly, they possessed admirable mechanical performances, which matched and even exceeded the commercial PLLA microfiber yarns (MYs). The thermally drawn PLLA NYs were also demonstrated to notably promote the adhesion, alignment, proliferation, and tenogenic differentiation of human adipose derived mesenchymal stem cells (hADMSCs) compared to the PLLA NYs without hot drawing. The thermally drawn PLLA NYs were further processed into various nanofibrous tissue scaffolds with defined structures and adjustable mechanical and biological properties using textile braiding and weaving technologies, demonstrating the feasibility and versatility of thermally drawn PLLA NYs for textile-forming utilization. The hADMSCs cultured on PLLA NY-based textiles presented enhanced attachment and proliferation capacities than those cultured on PLLA MY-based textiles. link2 This work presents a facile technique to manufacture high performance PLLA NYs, which opens up opportunities to generate advanced nanostructured biotextiles for surgical implant applications.Finlets have a unique overhanging structure at the posterior, similar to a flag. They are located between the dorsal/anal fin and the caudal fin on the dorsal and ventral sides of the body. Until now, the sensing ability of the finlets is less understood. In this paper, we design and manufacture a biomimetic soft robotic finlet (48.5mm in length, 30mm in height) with mechanosensation based on printed stretchable liquid metal sensors. The robotic finlet’s posterior fin ray can achieve side-to-side movement orthogonal to the anterior fin ray. A flow sensor encapsulating with a liquid metal sensor network enables the biomimetic finlets to sense the direction and flow intensity. The stretchable liquid metal sensors mounted on the micro-actuators are utilized to perceive the swing motion of the fin ray. We found that the finlet prototype can sense the fin ray’s flapping amplitudes and flapping frequency, and the membrane between the two orthogonal fin rays can amplify the sensor output. Our results indicate that the over-hanging structure endows the biomimetic finlet with the ability to sense external stimuli from stream-wise, lateral, and vertical directions. We further demonstrate that the finlet can detect a Karman Vortex Street through DPIV experiments. This study lays a foundation for exploring the environmental perception of biological fish fins and provides a new approach for future underwater robots to perceive complex flow environments. Key words finlet, liquid metal printing, proprioception, environment perception, flow sensing.This study aimed to prepare chitosan-coated silver nanotriangles (AgNTs) and assess their computed tomography (CT) contrast property byin vitroandin vivoexperiments. AgNTs with a range of sizes were synthesized by a seed-based growth method, and subsequently characterized by transmission electron microscopy (TEM), ultraviolet-visible absorption spectroscopy and dynamic light scattering. The x-ray attenuation capability of all prepared AgNTs was evaluated using micro CT. The CT contrast effect of AgNTs with the highest x-ray attenuation coefficient was investigated in MDA-MB-231 breast cancer cells and a mouse model of breast cancer. The TEM results displayed that all synthesized AgNTs were triangular in shape and their mean edge lengths ranged from 60 to 149 nm. All AgNTs tested exhibited stronger x-ray attenuation capability than iohexol at the same mass concentration of the active elements, and the larger the AgNTs size, the higher the x-ray attenuation coefficient. AgNTs with the largest size were selected for further research, due to their strongest x-ray attenuation capability and best biocompatibility. The attenuation coefficient of breast cancer cells treated with AgNTs increased in a particle concentration-dependent manner.In vivoCT imaging showed that the contrast of the tumor injected with AgNTs was significantly enhanced. These findings indicated that AgNTs could be a promising candidate for highly efficient tumor CT contrast agents.To investigate the impact of training sample size on the performance of deep learning-based organ auto-segmentation for head-and-neck cancer patients, a total of 1160 patients with head-and-neck cancer who received radiotherapy were enrolled in this study. Patient planning CT images and regions of interest (ROIs) delineation, including the brainstem, spinal cord, eyes, lenses, optic nerves, temporal lobes, parotids, larynx and body, were collected. An evaluation dataset with 200 patients were randomly selected and combined with Dice similarity index to evaluate the model performances. Eleven training datasets with different sample sizes were randomly selected from the remaining 960 patients to form auto-segmentation models. All models used the same data augmentation methods, network structures and training hyperparameters. A performance estimation model of the training sample size based on the inverse power law function was established. link3 Different performance change patterns were found for different organs. Six organs had the best performance with 800 training samples and others achieved their best performance with 600 training samples or 400 samples. The benefit of increasing the size of the training dataset gradually decreased. Compared to the best performance, optic nerves and lenses reached 95% of their best effect at 200, and the other organs reached 95% of their best effect at 40. For the fitting effect of the inverse power law function, the fitted root mean square errors of all ROIs were less than 0.03 (left eye 0.024, others less then 0.01), and theRsquare of all ROIs except for the body was greater than 0.5. The sample size has a significant impact on the performance of deep learning-based auto-segmentation. The relationship between sample size and performance depends on the inherent characteristics of the organ. In some cases, relatively small samples can achieve satisfactory performance.