Twist angle-dependent work functions in CVD-grown twisted bilayer graphene probed by Kelvin probe force microscopy.

Tailoring the interlayer twist angle of bilayer graphene (BLG) significantly affects its electronic properties, including its superconductivity, topological transitions, ferromagnetic states, and correlated insulating states. These exotic electronic properties are sensitive to the work functions of BLG samples. In this study, the twist angle-dependent work functions of chemical vapour deposition-grown twisted bilayer graphene (tBLG) were investigated in detail using Kelvin probe force microscopy (KPFM) in combination with Raman spectroscopy. The thickness-dependent surface potentials of Bernal-stacked multilayer graphene were measured. It is found that with the increase in the number of layers, the work function decreases and tends to saturate. Bernal-stacked BLG and tBLG were determined via KPFM due to their twist angle-specific surface potentials. The detailed relationship between the twist angle and surface potential was determined via in situ KPFM and Raman spectral measurements. With the increase in the twist angle, the work function of tBLG will increase rapidly and then increase slowly when it is greater than 5°. The thermal stability of tBLG was investigated through a controlled annealing process. tBLG will become Bernal-stacked BLG after annealing at 350 °C. Our work provides the twist angle-dependent surface potentials of tBLG and provides the relevant conditions for the stability of the twist angle, which lays the foundation for further exploration of its twist angle-dependent electronic properties.

Detection of sarcopenia using deep learning-based artificial intelligence body part measure system (AIBMS).

Background: Sarcopenia is an aging syndrome that increases the risks of various adverse outcomes, including falls, fractures, physical disability, and death. Sarcopenia can be diagnosed through medical images-based body part analysis, which requires laborious and time-consuming outlining of irregular contours of abdominal body parts. Therefore, it is critical to develop an efficient computational method for automatically segmenting body parts and predicting diseases. Methods: In this study, we designed an Artificial Intelligence Body Part Measure System (AIBMS) based on deep learning to automate body parts segmentation from abdominal CT scans and quantification of body part areas and volumes. The system was developed using three network models, including SEG-NET, U-NET, and Attention U-NET, and trained on abdominal CT plain scan data. Results: This segmentation model was evaluated using multi-device developmental and independent test datasets and demonstrated a high level of accuracy with over 0.9 DSC score in segment body parts. Based on the characteristics of the three network models, we gave recommendations for the appropriate model selection in various clinical scenarios. We constructed a sarcopenia classification model based on cutoff values (Auto SMI model), which demonstrated high accuracy in predicting sarcopenia with an AUC of 0.874. We used Youden index to optimize the Auto SMI model and found a better threshold of 40.69. Conclusion: We developed an AI system to segment body parts in abdominal CT images and constructed a model based on cutoff value to achieve the prediction of sarcopenia with high accuracy.

Size-dependent strain-engineered nanostructures in MoS2monolayer investigated by atomic force microscopy.

The strain has been employed for controlled modification of electronical and mechanical properties of two-dimensional (2D) materials. However, the thermal strain-engineered behaviors of the CVD-grown MoS2have not been systematically explored. Here, we investigated the strain-induced structure and properties of CVD-grown triangular MoS2flakes by several advanced atomic force microscopy. Two different kinds of flakes with sharp-corner or vein-like nanostructures are experimentally discovered due to the size-dependent strain behaviors. The critical size of these two kinds of flakes can be roughly estimated at âˆ¼17µm. Within the small flakes, the sharp-corner regions show specific strain-modified properties due to the suffering of large tensile strain. While in the large MoS2flakes, the complicated vein-like nanoripple structures were formed due to the interface slipping process under the larger tensile strain. Our work not only demonstrates the size-specific strain behaviors of MoS2flakes but also sheds light on the artificial design and preparation of strain-engineered nanostructures for the devices based on the 2D materials.

Iron-Oxide Nanocluster Labeling of Clostridium novyi-NT Spores for MR Imaging-Monitored Locoregional Delivery to Liver Tumors in Rat and Rabbit Models.

PURPOSE: To label Clostridium novyi-NT spores (C. novyi-NT) with iron oxide nanoclusters and track distribution of bacteria during magnetic resonance (MR) imaging-monitored locoregional delivery to liver tumors using intratumoral injection or intra-arterial transcatheter infusion. MATERIALS AND METHODS: Vegetative state C. novyi-NT were labeled with iron oxide particles followed by induction of sporulation. Labeling was confirmed with fluorescence microscopy and transmission electron microscopy (TEM). T2 and T2* relaxation times for magnetic clusters and magnetic microspheres were determined using 7T and 1.5T MR imaging scanners. In vitro assays compared labeled bacteria viability and oncolytic potential to unlabeled controls. Labeled spores were either directly injected into N1-S1 rodent liver tumors (n = 24) or selectively infused via the hepatic artery in rabbits with VX2 liver tumors (n = 3). Hematoxylin-eosin, Prussian blue, and gram staining were performed. Statistical comparison methods included paired t-test and ANOVA. RESULTS: Both fluorescence microscopy and TEM studies confirmed presence of iron oxide labels within the bacterial spores. Phantom studies demonstrated that the synthesized nanoclusters produce R2 relaxivities comparable to clinical agents. Labeling had no significant impact on overall growth or oncolytic properties (P >.05). Tumor signal-to-noise ratio (SNR) decreased significantly following intratumoral injection and intra-arterial infusion of labeled spores (P <.05). Prussian blue and gram staining confirmed spore delivery. CONCLUSIONS: C. novyi-NT spores can be internally labeled with iron oxide nanoparticles to visualize distribution with MR imaging during locoregional bacteriolytic therapy involving direct injection or intra-arterial transcatheter infusion.

Mechanochromic behavior of aryl-substituted buta-1,3-diene derivatives with aggregation enhanced emission.

Three tetra-aryl substituted 1,3-butadiene derivatives with aggregation enhanced emission (AEE) and mechanochromic fluorescence behavior have been rationally designed and synthesized. The results suggest an effective design strategy for developing diverse materials with aggregation induced emission (AIE) and significant mechanochromic performance by employing D-π-A structures with large dipole moments.