Evidence map›Paper›PMID 41917110›Full record

ArticleScientific reports2026

Thermodynamic calculation of metallic Fe yield and CO

Xin Jiang, Xiaoling Deng, Xinyue Fan, Yulu Zhou, Lanjie Li, Haiyan Zheng, Qiangjian Gao, Fengman Shen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Xin JiangKey Laboratory for Ecological Metallurgy of Multimetallic Mineral (Ministry of Education), Northeastern University, Shenyang, 110819, China. jiangx@smm.neu.edu.cn.
Xiaoling DengCISDI Group Co., Ltd, Chongqing, 401122, China.
Xinyue FanSchool of Metallurgy, Northeastern University, Shenyang, 110819, Liaoning, China.
Yulu ZhouSchool of Metallurgy, Northeastern University, Shenyang, 110819, Liaoning, China.
Lanjie LiHBIS Group, HBIS Materials Technology Research Institute, Shijiazhuang, 050023, Hebei, China. lilanjie@hbisco.com.
Haiyan ZhengKey Laboratory for Ecological Metallurgy of Multimetallic Mineral (Ministry of Education), Northeastern University, Shenyang, 110819, China.
Qiangjian GaoKey Laboratory for Ecological Metallurgy of Multimetallic Mineral (Ministry of Education), Northeastern University, Shenyang, 110819, China.
Fengman ShenKey Laboratory for Ecological Metallurgy of Multimetallic Mineral (Ministry of Education), Northeastern University, Shenyang, 110819, China.

Funding

Baowu Low Carbon Metallurgy Innovation Foundation BWLCF 202303Innovative Research Group Project of the National Natural Science Foundation of China NSFC 52074072Innovative Research Group Project of the National Natural Science Foundation of China NSFC 52074074Innovative Research Group Project of the National Natural Science Foundation of China NSFC 52074086Innovative Research Group Project of the National Natural Science Foundation of China NSFC 52274322Key Technologies Research and Development Program No.2021YFC2902401
6 · The paper itself

Abstract

Under the "dual-carbon" goals background, the Chinese iron and steel industry urgently needs to undergo a low-carbon transformation. Currently, promoting the substitution of coke oven gas (COG) for natural gas to develop shaft furnaces is a crucial initiative for implementing sustainable development. Through thermodynamic calculations, the iron yield and CO

Indexed as

Carbon emissionsCoke oven gas (COG)Gas-based shaft furnace direct reduction processIron yieldThermodynamic calculation

Identifiers

PMID41917110
PMCPMC13181022

What OpenQuestion holds

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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.