Project of a Time-of-Flight Multi-Reflection Mass Spectrometer for the Flerov Laboratory of Nuclear Reactions in JINR
JOURNAL OF ANALYTICAL CHEMISTRY（2023）
Institute for Analytical Instrumentation RAS
Abstract
Project of a specialized mass spectrometer for precision mass measurement of superheavy elements at the Factory of Superheavy Elements at the Joint Institute for Nuclear Research (JINR) in Dubna is presented in the paper. The mass spectrometer is intended for achieving the mass accuracy of 10 –7 at a low statistics (~5 events). The key part of the mass spectrometer is a new generation multi-reflection time-of-flight mass analyzer. To prepare and separate the probe and calibrant, a set of new ion-optical elements is implemented in the spectrometer, such as a radio-frequency selector of the state of charge, quadrupole mass filters operating in the beat node coincidence mode, a collision dissociation cell with beam focusing in the gap of a vacuum valve, and a source of calibration ions with electron ionization of fullerene soot.
MoreTranslated text
Key words
superheavy elements,multi-reflection time-of-flight mass analyzer,mass accuracy,ion mirror,fullerene soot
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