Precise Extraction of Charge Carrier Mobility for Organic Transistors

Unreliable mobility values, and particularly greatly overestimated values and severely distorted temperature dependences, have recently hampered the development of the organic transistor field. Given that organic field‐effect transistors (OFETs) have been routinely used to evaluate mobility, precise parameter extraction using the electrical properties of OFETs is thus of primary importance. This review examines the origins of the various mobilities that must be determined for OFET applications, the relevant extraction methods, and the data selection limitations, which help in avoiding conceptual errors during mobility extraction. For increased precision, the review also discusses device fabrication considerations, calibration of both the specific gate‐dielectric capacitance and the threshold voltage, the contact effects, and the bias and temperature dependences, which must actually be handled with great care but have mostly been overlooked to date. This review serves as a systematic overview of the OFET mobility extraction process to ensure high precision and will also aid in improving future research.     

Flotation Behavior,Collector Adsorption Mechanism of Quartz and Feldspar-Quartz Systems Using PEA as a Novel Green Collector

Silicon - A novel green cationic surfactant Poly (propylene glycol) bis (2-aminopropyl ether) (PEA) with multiple amine groups was utilized as a collector for flotation separation of quartz from...     

Preparation and characterization of calcium phosphate cement with enhanced tissue adhesion for bone defect repair

Anti-washout and tissue adhesion properties are essential for the clinical application of injectable bone materials. In this study, we prepared calcium phosphate cement (CPC) with anti-washout and tissue adhesion properties and attempted to build covalent bonds between CPC and the amino groups in bone tissue under a self-regulating pH system in the CPC (acidic to basic). The results of push-out tests demonstrated that a significant enhancement (from 6.42 ± 0.76 N to 61.5 ± 4.09 N) in tissue adhesion was obtained with the addition of 6% (w/w) oxidized sodium alginate (OSA) in CPC. The FTIR, XRD, anti-washout test, XPS, pH test, and SEM results suggested that the synergistic effect of OSA-citric acid (CA) led to the formation of a three-dimensional gel network structure in the CPC, and the Schiff base reaction between aldehyde and amino groups induced adhesion between CPC and the bone tissue. Further, the addition of less OSA had no significant negative effect on the hydration properties of CPC. Our work aims to promote the development of injectable bone material in clinical applications.     

An effectiveness analysis of altmetrics indices for different levels of artificial intelligence publications

Scientometrics - Altmetrics indices are increasingly applied to measure scholarly influence in recent years because they can reflect the influence of research outputs more timely comparing with...     

A spatio-temporal fusion method for remote sensing data Using a linear injection model and local neighbourhood information

This paper presents a spatio-temporal fusion method for remote sensing images by using a linear injection model and local neighbourhood information. In this method, the linear injection model is first introduced to generate an initial fused image, the spatial details are extracted from the fine-resolution image at the base date, and are weighted by a proper injection gains. Then, the spatial details and the relative spectral information from the coarse-resolution images are blended to generate the fusion result. To further enhance its robustness to the noise, the local neighbourhood information, derived from the fine-resolution image and the fused result simultaneously, is introduced to refine the initial fused image to obtain a more accurate prediction result. The algorithm can effectively capture phenology change or land-cover-type change with minimum input data. Simulated data and two types of real satellite images with seasonal changes and land-cover-type changes are employed to test the performance of the proposed method. Compared with a spatial and temporal adaptive reflectance fusion model (STARFM) and a flexible spatio-temporal fusion algorithm (FSDAF), results show that the proposed approach improves the accuracy of fused images in phenology change area and effectively captures land-cover-type reflectance changes.