Evidence map›Paper›PMID 40979289›Full record

ReviewInnovation (Cambridge (Mass.))2025

Liquid metals power advanced nuclear energy systems.

Lin Zhang, Chang Deng, Xu Ji, Xiaojing Liu

Abstract readReview
In one paragraph

Review in Innovation (Cambridge (Mass.)), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Permeation behaviour of hydrogen isotopes in molten FLiBe (2LiF-BeFInternational journal of hydrogen energy · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lin ZhangSchool of Nuclear Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Chang DengSchool of Nuclear Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Xu JiSchool of Nuclear Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Xiaojing LiuSchool of Nuclear Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of advanced nuclear energy systems, known for their cleanliness and sustainability, is a key strategy for achieving a low-carbon energy transition. Liquid metal (LM)-powered advanced nuclear energy systems demonstrate sustainability and environmental friendliness, as well as being irreplaceable in specific areas. This paper charts a comprehensive scene of applications, challenges, and prospects of LMs in advanced nuclear energy (fusion and fission). First, next-generation fission reactors that use LM coolants, such as sodium or lead, are currently under design and construction. However, the coupling mechanisms of multiphase and multiphysics interactions remain unresolved due to various challenges, including corrosion and lead-water interactions. Second, the exploration of new LM-cooled reactors should emphasize sustainable development while ensuring basic performance. Lastly, the unique properties of LMs, including efficient energy transport and tritium breeding, position them as crucial materials in fusion system design. However, surface characteristics and the magnetohydrodynamic (MHD) effect remain major technical challenges. LMs have already left their mark in nuclear energy and are expected to be an effective solution to overcoming the energy crisis.

Indexed as

advanced nuclear energy systemsclean energy and sustainable developmentenergy conversion and utilizationliquid metalslow carbon

Identifiers

PMID40979289
PMCPMC12447655

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.