Evidence map›Paper›PMID 35424244›Full record

ArticleRSC advances2021

Numerical study on the effect of discrete catalytic layer arrangement on methane steam reforming performance.

Han Wang, Guogang Yang, Shian Li, Qiuwan Shen, Zheng Li, Biaojie Chen

Abstract read
In one paragraph

Article in RSC advances, 2021. 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

6 authors.

Han WangMarine Engineering College, Dalian Maritime University China wang.han@dlmu.edu.cn yanggg@dlmu.edu.cn lishian@dlmu.edu.cn.ORCID https://orcid.org/0000-0002-3140-4214
Guogang YangMarine Engineering College, Dalian Maritime University China wang.han@dlmu.edu.cn yanggg@dlmu.edu.cn lishian@dlmu.edu.cn.
Shian LiMarine Engineering College, Dalian Maritime University China wang.han@dlmu.edu.cn yanggg@dlmu.edu.cn lishian@dlmu.edu.cn.
Qiuwan ShenMarine Engineering College, Dalian Maritime University China wang.han@dlmu.edu.cn yanggg@dlmu.edu.cn lishian@dlmu.edu.cn.ORCID https://orcid.org/0000-0001-6983-0414
Zheng LiMarine Engineering College, Dalian Maritime University China wang.han@dlmu.edu.cn yanggg@dlmu.edu.cn lishian@dlmu.edu.cn.
Biaojie ChenMarine Engineering College, Dalian Maritime University China wang.han@dlmu.edu.cn yanggg@dlmu.edu.cn lishian@dlmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The arrangement of catalytic layers inside the reactor is an important factor that affects the efficiency of methane steam reforming to produce hydrogen, and the traditional continuous catalytic layer structure is limited by the heat and mass transfer, resulting in unbalanced heat distribution inside the reactor and poor reaction performance. In order to improve the performance of methane reforming and balance the internal temperature of the reactor, different catalytic layers were designed based on 2D numerical simulation, and different numbers of discrete catalytic layers were modeled to compare the heat and mass transfer, methane conversion rate and hydrogen yield between the walls and inside the reactor. The results show that the increase in the number of catalyst gaps improves the temperature gradient inside the reactor, reduces the average cold point temperature difference inside the reactor by up to 7.2%, maintains a better thermal balance inside the reactor, improves the reaction rate inside the reactor, and the methane conversion rate and hydrogen yield after the reaction have been improved by 28.46% and 12.7% respectively.

Identifiers

PMID35424244
PMCPMC8693868

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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.