Table_1_Research progress and hotspot of the artificial intelligence application in the ultrasound during 2011–2021: A bibliometric analysis.DOCX

Ultrasound, as a common clinical examination tool, inevitably has human errors due to the limitations of manual operation. Artificial intelligence is an advanced computer program that can solve this problem. Therefore, the relevant literature on the application of artificial intelligence in the ultrasonic field from 2011 to 2021 was screened by authors from the Web of Science Core Collection, which aims to summarize the trend of artificial intelligence application in the field of ultrasound, meanwhile, visualize and predict research hotspots. A total of 908 publications were included in the study. Overall, the number of global publications is on the rise, and studies on the application of artificial intelligence in the field of ultrasound continue to increase. China has made the largest contribution in this field. In terms of institutions, Fudan University has the most number of publications. Recently, IEEE Access is the most published journal. Suri J. S. published most of the articles and had the highest number of citations in this field (29 articles). It's worth noting that, convolutional neural networks (CNN), as a kind of deep learning algorithm, was considered to bring better image analysis and processing ability in recent most-cited articles. According to the analysis of keywords, the latest keyword is “COVID-19” (2020.8). The co-occurrence analysis of keywords by VOSviewer visually presented four clusters which consisted of “deep learning,” “machine learning,” “application in the field of visceral organs,” and “application in the field of cardiovascular”. The latest hot words of these clusters were “COVID-19; neural-network; hepatocellular carcinoma; atherosclerotic plaques”. This study reveals the importance of multi-institutional and multi-field collaboration in promoting research progress.</p

Tunable Broadband Nanocarbon Transparent Conductor by Electrochemical Intercalation

Optical transparent and electrical conducting materials with broadband transmission are important for many applications in optoelectronic, telecommunications, and military devices. However, studies of broadband transparent conductors and their controlled modulation are scarce. In this study, we report that reversible transmittance modulation has been achieved with sandwiched nanocarbon thin films (containing carbon nanotubes (CNTs) and reduced graphene oxide (rGO)) <i>via</i> electrochemical alkali-ion intercalation/deintercalation. The transmittance modulation covers a broad range from the visible (450 nm) to the infrared (5 μm), which can be achieved only by rGO rather than pristine graphene films. The large broadband transmittance modulation is understood with DFT calculations, which suggest a decrease in interband transitions in the visible range as well as a reduced reflection in the IR range upon intercalation. We find that a larger interlayer distance in few-layer rGO results in a significant increase in transparency in the infrared region of the spectrum, in agreement with experimental results. Furthermore, a reduced plasma frequency in rGO compared to few-layer graphene is also important to understand the experimental results for broadband transparency in rGO. The broadband transmittance modulation of the CNT/rGO/CNT systems can potentially lead to electrochromic and thermal camouflage applications