Production of p-rich nuclei with $$\boldsymbol{Z}\boldsymbol{=20-25}$$ based on radioactive ion beams

Li, Bing; Tang, Na; Zhang, Yuhai; Zhang, Feng-Shou

doi:10.1007/s41365-022-01048-4

Cited by 11 publications

(6 citation statements)

References 98 publications

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“…At KEK, the first productive experiment dedicated to the neutron-rich hypernucleus 10 Λ Li generated by the 10 B(π − , K + ) process was carried out [32], but statistical error prevented the determination of its binding energy. It was later discovered in other nuclei, including 6 He, 17,19 B, 15,19,22 C, and 29 F [33]. Regarding the most extreme case of the 6 Λ H hypernucleus, the FINUDA collaboration reported three candidate events from the 6 Li(K − , π + ) reaction [34], but the J-PARC E10 experiment [35] failed to obtain a signal for the 6 Li(π − , K + ) 6 Λ H reaction.…”

Section: Introductionmentioning

confidence: 99%

“…It was later discovered in other nuclei, including 6 He, 17,19 B, 15,19,22 C, and 29 F [33]. Regarding the most extreme case of the 6 Λ H hypernucleus, the FINUDA collaboration reported three candidate events from the 6 Li(K − , π + ) reaction [34], but the J-PARC E10 experiment [35] failed to obtain a signal for the 6 Li(π − , K + ) 6 Λ H reaction. In conclusion, there is still a dearth of experimental information about neutron-rich Λ hypernuclei at this time.…”

Section: Introductionmentioning

confidence: 99%

“…Proton-rich hypernuclei have so far attracted even less focus, although it is intriguing that proton-rich isotopes are lighter than neutron-rich ones and closer to the stability valley, and can thus form more easily. In emulsions, the hypernucleus 7 Λ Be with an unstable core 6 Be has been seen [31]. There are no current plans or particular experiments aimed at protonrich hypernuclei, because they cannot be created by the typical (K − , π + ), (π − , K + ), and (e, e ′ K) reactions.…”

Section: Introductionmentioning

confidence: 99%

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Geography of Technology Transfer in China

Liu

2023

East China Normal University Scientific Reports

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Graphs can model complex relationships between objects, enabling a myriad of Web applications such as online page/article classification and social recommendation. While graph neural networks (GNNs) have emerged as a powerful tool for graph representation learning, in an end-to-end supervised setting, their performance heavily relies on a large amount of task-specific supervision. To reduce labeling requirement, the "pre-train, fine-tune" and "pre-train, prompt" paradigms have become increasingly common. In particular, prompting is a popular alternative to fine-tuning in natural language processing, which is designed to narrow the gap between pre-training and downstream objectives in a task-specific manner. However, existing study of prompting on graphs is still limited, lacking a universal treatment to appeal to different downstream tasks. In this paper, we propose GraphPrompt, a novel pre-training and prompting framework on graphs. GraphPrompt not only unifies pre-training and downstream tasks into a common task template, but also employs a learnable prompt to assist a downstream task in locating the most relevant knowledge from the pre-trained model in a task-specific manner. Finally, we conduct extensive experiments on five public datasets to evaluate and analyze GraphPrompt. CCS CONCEPTS• Computing methodologies → Learning latent representations; • Information systems → Data mining.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Geography of Technology Transfer in China

Liu

2023

East China Normal University Scientific Reports

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“…As a 3D printing technology, DLW is a powerful tool to construct not only conventional biomaterials/scaffolds, but also functional microrobots. [ 8,140,141 ] DLW by 2PP or multiphoton polymerization allows for the construction of microgrippers with a resolution of sub‐100 nm. [ 66,142,143 ] Recently, an advanced 4D DLW was developed to fabricate reconfigurable micromachines in a one‐step mode (Figure 5C).…”

Section: Design and Fabrication Of Microgrippersmentioning

confidence: 99%

Untethered Microgrippers for Precision Medicine

Zhou,

Zhang,

Liu

et al. 2023

Small

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Microgrippers, a branch of micro/nanorobots, refer to motile miniaturized machines that are of a size in the range of several to hundreds of micrometers. Compared with tethered grippers or other microscopic diagnostic and surgical equipment, untethered microgrippers play an indispensable role in biomedical applications because of their characteristics such as miniaturized size, dexterous shape tranformation, and controllable motion, which enables the microgrippers to enter hard‐to‐reach regions to execute specific medical tasks for disease diagnosis and treatment. To date, numerous medical microgrippers are developed, and their potential in cell manipulation, targeted drug delivery, biopsy, and minimally invasive surgery are explored. To achieve controlled locomotion and efficient target‐oriented actions, the materials, size, microarchitecture, and morphology of microgrippers shall be deliberately designed. In this review, the authors summarizes the latest progress in untethered micrometer‐scale grippers. The working mechanisms of shape‐morphing and actuation methods for effective movement are first introduced. Then, the design principle and state‐of‐the‐art fabrication techniques of microgrippers are discussed. Finally, their applications in the precise medicine are highlighted, followed by offering future perspectives for the development of untethered medical microgrippers.

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“…In a nutshell, high planar slip tendency and high DSF promote the likelihood of fatigue cracking of TBs in low SFE and strong SRO effect alloys. [ 246 ]…”

Section: Differences Of Fatigue Mechanisms Between Amed and Conventio...mentioning

confidence: 99%

Review on Fatigue of Additive Manufactured Metallic Alloys: Microstructure, Performance, Enhancement, and Assessment Methods

Liu,

Yu,

Guo

et al. 2023

Advanced Materials

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Additive manufacturing (AM), which is a process of building objects in a layer‐upon‐layer fashion from designed models, has received unprecedented attention from research and industry because it offers outstanding merits of flexibility, customization, reduced buy‐to‐fly ratio, and cost‐effectiveness. However, the fatigue performance of safety‐critical industrial components fabricated by AM is still far below that obtained from conventional methods. This review discusses the microstructural heterogeneities, randomly dispersed defects, poor surface quality, and complex residual stress generated during the AM process that can negatively impact the fatigue performance of as‐printed parts. The difference in microstructural origin of fatigue failure between conventionally manufactured and printed metals is reviewed with particular attention to the effects of the trans‐scale microstructures on AM fatigue failure mechanisms. Various methods for mitigating the fatigue issue, including pre‐process, inter‐process and post‐process treatments, are illustrated. Empirical, semi‐empirical and microstructure‐sensitive models are presented to predict fatigue strength and lifetime. Summary and outlooks for future development of the fatigue performance of AM materials are provided.This article is protected by copyright. All rights reserved

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Production of p-rich nuclei with $$\boldsymbol{Z}\boldsymbol{=20-25}$$ based on radioactive ion beams

Cited by 11 publications

References 98 publications

Geography of Technology Transfer in China

Geography of Technology Transfer in China

Untethered Microgrippers for Precision Medicine

Review on Fatigue of Additive Manufactured Metallic Alloys: Microstructure, Performance, Enhancement, and Assessment Methods

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