Evidence map›Paper›PMID 35921416›Full record

ArticleScience advances2022

A scalable solid-state nanoporous network with atomic-level interaction design for carbon dioxide capture.

Haiyan Mao, Jing Tang, Gregory S Day, Yucan Peng, Haoze Wang, Xin Xiao, Yufei Yang, Yuanwen Jiang, Shuo Chen, David M Halat and 9 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.6field-weighted citation impact, top 6% of its field
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

13 citing papers in PubMed, 54 citations in OpenAlex.

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  12. Porous organic polymers for COChemical Society reviews · 2022
    Review
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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

19 authors at 5 institutions in 1 country.

Haiyan MaoDepartment of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0003-0591-1236
Jing TangDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-6351-993X
Gregory S DayDepartment of Chemistry, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0002-8064-8071
Yucan PengDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0001-7852-1541
Haoze WangDepartment of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0002-6961-6554
Xin XiaoDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0003-1098-9484
Yufei YangDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-3480-095X
Yuanwen JiangDepartment of Chemical Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-2056-2639
Shuo ChenDepartment of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0003-3581-0997
David M HalatDepartment of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0002-0919-1689
Alicia LundDepartment of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0001-7520-9544
Xudong LvDepartment of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA.
Wenbo ZhangDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.
Chongqing YangThe Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
Zhou LinDepartment of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0003-3271-5345
Hong-Cai ZhouDepartment of Chemistry, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0002-9029-3788
Alexander PinesDepartment of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0002-5113-7715
Yi CuiDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-6103-6352
Jeffrey A ReimerDepartment of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0002-4191-3725
University of California, Berkeley · USStanford University · USLawrence Berkeley National Laboratory · USSLAC National Accelerator Laboratory · USTexas A&M University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbon capture and sequestration reduces carbon dioxide emissions and is critical in accomplishing carbon neutrality targets. Here, we demonstrate new sustainable, solid-state, polyamine-appended, cyanuric acid-stabilized melamine nanoporous networks (MNNs) via dynamic combinatorial chemistry (DCC) at the kilogram scale toward effective and high-capacity carbon dioxide capture. Polyamine-appended MNNs reaction mechanisms with carbon dioxide were elucidated with double-level DCC where two-dimensional heteronuclear chemical shift correlation nuclear magnetic resonance spectroscopy was performed to demonstrate the interatomic interactions. We distinguished ammonium carbamate pairs and a mix of ammonium carbamate and carbamic acid during carbon dioxide chemisorption. The coordination of polyamine and cyanuric acid modification endows MNNs with high adsorption capacity (1.82 millimoles per gram at 1 bar), fast adsorption time (less than 1 minute), low price, and extraordinary stability to cycling by flue gas. This work creates a general industrialization method toward carbon dioxide capture via DCC atomic-level design strategies.

Identifiers

PMID35921416
PMCPMC9348791
OpenAlexW4289653513

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.