Evidence map›Paper›PMID 41514506›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Ionic Highways under Multivariate-Coupled Strategies: Ultrahigh Power Generation from Industrial Waste Liquors Using Robust COF Membranes.

Hongyan Qi, Weibo Sun, Jundong Zhong, Zhen Xing, Tingting Xu, Shuang Zhao, Haoyang Tan, Ziyi Hu, Hujun Qian, Yuchen Wu and 4 more

Abstract read
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In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

14 authors.

Hongyan QiNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Weibo SunNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Jundong ZhongNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Zhen XingNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Tingting XuNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Shuang ZhaoNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Haoyang TanNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Ziyi HuNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Hujun QianState Key Laboratory of Supramolecular Structure and Materials, Institute of Theoretical Chemistry, College of Chemistry, Jilin University, Changchun, China.
Yuchen WuInternational Center of Future Science, College of Chemistry, Jilin University, Changchun, China.
Haibo ZhangNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Jianxin MuNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.
Xuanbo ZhuNational and Local Joint Engineering Laboratory for Synthetic Technology of High-Performance Polymer, College of Chemistry, Jilin University, Changchun, China.ORCID https://orcid.org/0000-0003-0001-566X
Lei JiangCAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0000-0003-4579-728X

Funding

Excellent Young Scientific and Technological Talents of Jilin Province Project 20240602013RCFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China 22341301National Natural Science Foundation of China 22373042National Natural Science Foundation of China 22522302
6 · The paper itself

Abstract

Efficiently harvesting the intrinsic energy from low-grade heat, acidity, and high salinity of desulfurization waste liquors is crucial for sustainable management, yet remains challenging due to the instability of conventional membranes under such extreme multi-physics conditions. Herein, we report a high-performance osmotic energy conversion device engineered via a multivariate coupling strategy. The core of this device is a robust membrane based on β-ketoenamine-linked covalent organic frameworks (COFs), featuring nanochannels functionalized with tailored stimuli-responsive groups to dynamically regulate surface charge density. The β-ketoenamine linkage endows exceptional membrane stability, enabling durable operation under coupled thermal, chemical, and electrochemical stresses. Experimental and computational studies demonstrate that the remarkable power enhancement stems not only from acid-induced protonation that boosts charge density, but also from the utilization of low-grade heat to accelerate ion transport. By simulating the multi-physical field coupling in real waste liquors, the device achieves an ultrahigh power output of 258.81 W m

Indexed as

covalent organic framework membranemultivariate‐coupledosmotic energy harvestingsmart response device

Identifiers

PMID41514506
PMCPMC13042868

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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.