Differential Cross-Section Measurements for the 9be(3he,3he0)9be Elastic Scattering and the 9be(3he,px)11b Reactions
NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS(2023)
Ruhr Univ Bochum
Abstract
The differential cross sections of 9Be(3He,3He0)9Be elastic scattering and of the 9Be(3He,p0,1,2,3,4+5,6,7)11B reactions have been determined in the energy range from 1.6 to 6 MeV at six backward angles from 120 degrees to 170 degrees, with a step of 10 degrees. The experiments were performed at the 4 MV Dynamitron Tandem Laboratory of the Central Unit for Ion Beams and Radionuclides of the Ruhr University Bochum in Germany. The obtained datasets have been validated through benchmarking experiments, at 8 beam energies, using a thick, high-purity, beryllium foil. The results of the present work are compared with existing ones from literature and any discrepancies observed are discussed.
MoreTranslated text
Key words
3He-NRA,3He-EBS,9Be,Differential cross sections
求助PDF
上传PDF
View via Publisher
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
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
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
Summary is being generated by the instructions you defined