REVIEW 1 cited by
Statistical screening model for moderately coupled and dense plasmas
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
For atoms embedded in dense plasma, the plasma screening effects will greatly alter their structure and dynamics, and then determine the radiation transport properties of the plasma. In the present work, a new statistical model is proposed for treating electron screening effects on atoms in moderately/strongly coupled and dense plasmas, in which the three-body processes are found to significantly influence the plasma-electron density distributions and leads to a dependence of the distribution on the specific bound state of the targeted atom. As a critical check, the model is applied to simulate the emission spectra of He-like Aluminum and Chlorine in hot dense plasmas, and much better agreements of the line shifts are obtained with the experiments of Stillman et al. in 2017 and Beiersdorfer et al. in 2019 than previous calculation results. Compared with the classical molecular dynamic simulations of electron distributions in moderately coupled plasmas, the present model can better describe the low-energy electron distribution than other models and the multi-body effects are well considered. The present model provides a promising tool to reasonably treat the electron screening effect of non-equilibrium dense plasma on atoms with specific bound states, which is urgently needed in high-precision simulations of the atomic processes, plasma spectra and radiation transport properties etc.
Forward citations
Cited by 1 Pith paper
-
Neurosymbolic Learning for Predicting Cell Fate Decisions from Longitudinal Single Cell Transcriptomics in Paediatric Acute Myeloid Leukemia
A computational ranking of candidate 'plasticity marker' genes in pediatric AML from longitudinal scRNA-seq, using LSTM, Transformer, and BDM perturbation, without reported predictive performance.
Discussion (0). Continue with ORCID to comment.