WeChat Mini Program
Old Version Features

Room Temperature Crystal Field Splitting of Curium Resolved by Circularly Polarized Luminescence Spectroscopy.

CHEMICAL SCIENCE(2025)

Lawrence Berkeley Natl Lab

Cited 0|Views2
Abstract
Coordination of Cm(iii) with a chiral decadentate ligand N,N,N',N'-tetrakis[(6-carboxypyridin-2-yl)methyl]-1,2-diaminocyclohexane (tpadac) generated complexes with strong luminescence allowing for the unprecedented measurement of well-resolved Cm(iii) circularly polarized luminescence spectra. Quantitative resolution of the electronic structure of the [Cm(tpadac)][K] complexes was achieved at room temperature, highlighting the strength of the combination of luminescence and circularly polarized luminescence spectroscopies to unravel the fundamental electronic structure of Cm(iii). These results are a clear demonstration that these spectroscopies are powerful yet simple tools for the fundamental understanding of electronic structure, which opens the door to future investigations of other Cm(iii) complexes in geometries relevant to nuclear applications, and even other 5f-elements.
More
Translated text
求助PDF
上传PDF
Bibtex
收藏
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