Evidence map›Paper›PMID 42794387›Full record

ReviewGels (Basel, Switzerland)2026

Cellulose Ionogels: Unraveling Structure-Property Relationships Through Multiscale In-Situ Characterization and Theoretical Modeling.

Jia Wei, Ziyan He, Jingtao Ruan, Junjie Ou, Wen Zhang, Bin Tan, Xiaoheng He, Zhen Wang, Yufei Tang

Abstract readReview
In one paragraph

Review in Gels (Basel, Switzerland), 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

9 authors.

Jia WeiState Key Laboratory of Water Engineering Ecology and Environment in Arid Area, School of Eco-Environmental and Chemical Engineering, Xi'an University of Technology, Xi'an 710048, China.ORCID 0009-0001-1851-964X
Ziyan HeState Key Laboratory of Water Engineering Ecology and Environment in Arid Area, School of Eco-Environmental and Chemical Engineering, Xi'an University of Technology, Xi'an 710048, China.
Jingtao RuanState Key Laboratory of Water Engineering Ecology and Environment in Arid Area, School of Eco-Environmental and Chemical Engineering, Xi'an University of Technology, Xi'an 710048, China.
Junjie OuState Key Laboratory of Water Engineering Ecology and Environment in Arid Area, School of Eco-Environmental and Chemical Engineering, Xi'an University of Technology, Xi'an 710048, China.
Wen ZhangZhengzhou Institute of Emerging Industrial Technology, Zhengzhou 450000, China.
Bin TanSchool of Chemical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.
Xiaoheng HeState Key Laboratory of Water Engineering Ecology and Environment in Arid Area, School of Eco-Environmental and Chemical Engineering, Xi'an University of Technology, Xi'an 710048, China.
Zhen WangState Key Laboratory of Water Engineering Ecology and Environment in Arid Area, School of Eco-Environmental and Chemical Engineering, Xi'an University of Technology, Xi'an 710048, China.
Yufei TangState Key Laboratory of Water Engineering Ecology and Environment in Arid Area, School of Eco-Environmental and Chemical Engineering, Xi'an University of Technology, Xi'an 710048, China.

Funding

Education Department of Shaanxi Province 24JK0569National Natural Science Foundation of China 22403076National Natural Science Foundation of China 22608448National Natural Science Foundation of China 52572084Natural Science Basic Research Program of Shaanxi Province 2026JC-YBQN-0125Research Fund of the State Key Laboratory of Water Engineering Ecology and Environment in Arid Area SKL-ZZ03-2025-06Shaanxi Province Postdoctoral Science Foundation 2025BSHSDZZ289Xi'an University of Technology 109-256082405
6 · The paper itself

Abstract

Cellulose ionogels have emerged as promising functional soft materials for flexible electronics, energy storage, and biosensing owing to their inherent biocompatibility and unique ionic conductivity. However, establishing precise structure-property relationships remains a fundamental challenge due to the complex, non-equilibrium dynamic processes-such as transient solvation, competing hydrogen-bonding networks, and mesoscopic phase separation-that occur during dissolution and gelation. Traditional static and post-mortem characterizations fail to capture these spatiotemporally dynamic behaviors, creating a critical knowledge gap. To overcome this bottleneck, the integration of real-time in situ/operando characterization techniques with multiscale computational simulations has established a novel, synergistic paradigm. This review comprehensively synthesizes recent advances in decoding the multiscale architectures of cellulose ionogels. We systematically analyze how molecular-scale calculations and time-resolved vibrational/electronic spectroscopies reveal interfacial solvation mechanisms and dynamic bond cleavage/reconstruction. We further evaluate how mesoscopic scattering, nanomechanical mapping, and rheological tools resolve network topology and structural heterogeneity. By bridging these multiscale diagnostics with macroscopic transport and mechanics, the dynamic coupling/decoupling mechanisms governing ionic conductivity, mechanical toughness, and thermal stability are critically decoded. Finally, key technical bottlenecks and future trajectories-including physics-informed machine learning, operando multi-field coupling probes, and AI-driven inverse material design-are outlined, providing theoretical guidelines and technical blueprints for next-generation sustainable ionogels.

Indexed as

cellulose ionogelsin situ characterizationmultiscale dynamicsstructure–property relationshipstheoretical simulation

Identifiers

PMID42794387
PMCPMC13606184

What OpenQuestion holds

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Registered trials

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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.