Evidence map›Paper›PMID 40539830›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Predictable Self-Assembly as an Unexplored Key Factor Influencing Membrane Separation: Insights from Monophenols.

Qiuyu Han, Lu Yin, Tingting Mi, Qi Chen, Wanlin Ouyang, Liping Fan, Qinshi Wang, Yue Zhang, Zhishu Tang, Huaxu Zhu and 1 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Qiuyu HanJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Lu YinJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Tingting MiJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Qi ChenJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Wanlin OuyangJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Liping FanJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Qinshi WangJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Yue ZhangJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Zhishu TangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Huaxu ZhuJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Bo LiJiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing, 210023, China.ORCID https://orcid.org/0000-0001-8532-2508

Funding

Jiangsu Province Leading Talents Cultivation Project for Traditional Chinese Medicine SLJ0304National Key R&D Program of China 2022YFB3805000National Natural Science Foundation of China 82274222Open Project of Chinese Materia Medica First-Class Discipline of Nanjing University of Chinese Medicine ZYXYL2024-013
6 · The paper itself

Abstract

While nanofiltration (NF) holds promise for separating small molecules, effectively separating structurally similar compounds like monophenols remains challenging. This study unveils a novel NF separation strategy based on the often-overlooked phenomenon of solute self-assembly. Using a combination of experimental and computational approaches, a direct link between monophenol self-assembly and rejection behavior during NF is established. The self-assembly of monophenols, primarily driven by π-π stacking interactions, is shown to significantly influence their rejection rates, with larger, more numerous self-assemblies experiencing higher rejection. Furthermore, a clear relationship between monophenol structures and self-assembly strength is established, revealing that the number and Hydrogen (H)-bonding capacity of substituents on the aromatic ring dictate the propensity for self-assembly. This insight enables the development of a predictive model for monophenol self-assembly, which is validated through NF experiments using binary mixtures, confirming that predictable differences in self-assembly behavior can be leveraged for selective separation. This study establishes solute self-assembly as a tunable parameter for enhancing NF separation of similarly sized molecules.

Indexed as

monophenolsnanofiltrationself‐assemblyseparationπ‐π stacking interaction

Identifiers

PMID40539830
PMCPMC12442694

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.