Evidence map›Paper›PMID 42356906›Full record

ArticleSensors (Basel, Switzerland)2026

Design of a Multi-Ion Detection System Based on IoT Technology and Its Application in Cement-Based Materials.

Yudong Sun, Zijing Zhang, Yixuan Li, Shaoyang Ding, Hanbo Chen, Zhengeng Xu, Yuejing Li, Xincheng Li, Dafu Wang, Jun Ren

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (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

10 authors.

Yudong SunSchool of Architecture and Planning, Yunnan University, Kunming 650091, China.
Zijing ZhangSchool of Architecture and Planning, Yunnan University, Kunming 650091, China.
Yixuan LiSchool of Architecture and Planning, Yunnan University, Kunming 650091, China.ORCID 0009-0003-5146-8076
Shaoyang DingSchool of Architecture and Planning, Yunnan University, Kunming 650091, China.
Hanbo ChenSchool of Architecture and Planning, Yunnan University, Kunming 650091, China.
Zhengeng XuSchool of Architecture and Planning, Yunnan University, Kunming 650091, China.
Yuejing LiSchool of Architecture and Planning, Yunnan University, Kunming 650091, China.
Xincheng LiYunnan Institute of Building Research, Kunming 650223, China.
Dafu WangSchool of Architecture and Planning, Yunnan University, Kunming 650091, China.
Jun RenSchool of Architecture and Planning, Yunnan University, Kunming 650091, China.ORCID 0000-0002-9605-4542

Funding

National Natural Science Foundation of China 52408299Yunnan Province Science and Technology Department 202501AT070774Yunnan Provincial Department of Education 2026Y0232
6 · The paper itself

Abstract

Simultaneous multi-ion detection is important for interpreting leaching, corrosion, hydration, and solidification processes in cement-based materials, because these processes are controlled by coupled ion migration, binding, and precipitation-dissolution reactions. Conventional methods such as pore-solution extraction, ion chromatography, inductively coupled plasma optical emission spectroscopy, and single-ion potentiometric measurements provide useful chemical information, but they generally rely on discrete sampling or isolated ion channels and therefore have limited ability to capture time-aligned multi-ion evolution. In this study, an IoT-based in situ multi-ion detection system was developed by integrating ion-selective electrodes for Cl

Indexed as

cement-based materialsion-selective electrodesIoT sensingleaching kineticsmulti-ion in situ detection

Identifiers

PMID42356906
PMCPMC13306688

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.