Chrome Extension
WeChat Mini Program
Use on ChatGLM

Colliding Heavy Nuclei Take Multiple Identities on the Path to Fusion

NATURE COMMUNICATIONS(2023)

Department of Nuclear Physics and Accelerator Applications | Istituto Nazionale di Fisica Nucleare | Ruđer Bošković Institute | Dipartimento di Fisica e Astronomia

Cited 7|Views31
Abstract
The properties of superheavy elements probe extremes of physics and chemistry. They are synthesised at accelerator laboratories using nuclear fusion, where two atomic nuclei collide, stick together (capture), then with low probability evolve to a compact superheavy nucleus. The fundamental microscopic mechanisms controlling fusion are not fully understood, limiting predictive capability. Even capture, considered to be the simplest stage of fusion, is not matched by models. Here we show that collisions of 40Ca with 208Pb, experience an 'explosion' of mass and charge transfers between the nuclei before capture, with unexpectedly high probability and complexity. Ninety different partitions of the protons and neutrons between the projectile-like and target-like nuclei are observed. Since each is expected to have a different probability of fusion, the early stages of collisions may be crucial in superheavy element synthesis. Our interpretation challenges the current view of fusion, explains both the successes and failures of current capture models, and provides a framework for improved models.
More
Translated text
Key words
Nuclear Structure
PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers

Formation of 258rf in Drift Plus Diffusion Dynamics

INTERNATIONAL CONFERENCE ON HEAVY-ION COLLISIONS AT NEAR-BARRIER ENERGIES, FUSION 2023 2024

被引用0

Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper

要点】:该论文揭示了在超重元素合成过程中,重核碰撞融合的多个身份及其极端的物理和化学特性,挑战了现有的核聚变观点,提供了改进模型的框架。

方法】:研究者通过加速器实验室使用核聚变方法,将40Ca与208Pb的原子核进行碰撞,观察其质量和电荷转移。

实验】:实验观察到40Ca与208Pb碰撞前 capture 阶段存在高概率和复杂性的质量和电荷转移,90种不同的质子和中子分配情况,这可能对超重元素合成过程中的早期阶段至关重要,其结果挑战了现有的核聚变模型。