Evidence map›Paper›PMID 41094828›Full record

ArticleSensors (Basel, Switzerland)2025

Embedment of 3D Printed Self-Sensing Composites for Smart Cementitious Components.

Han Liu, Israel Sousa, Simon Laflamme, Shelby E Doyle, Antonella D'Alessandro, Filippo Ubertini

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

6 authors.

Han LiuDepartment of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50010, USA.ORCID 0000-0003-3057-522X
Israel SousaDepartment of Civil and Environmental Engineering, University of Perugia, Via G. Duranti, 93, 06125 Perugia, Italy.
Simon LaflammeDepartment of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50010, USA.ORCID 0000-0002-0601-9664
Shelby E DoyleDepartment of Architecture, Iowa State University, Ames, IA 50010, USA.ORCID 0000-0001-5742-9076
Antonella D'AlessandroDepartment of Civil and Environmental Engineering, University of Perugia, Via G. Duranti, 93, 06125 Perugia, Italy.ORCID 0000-0003-2928-1961
Filippo UbertiniDepartment of Civil and Environmental Engineering, University of Perugia, Via G. Duranti, 93, 06125 Perugia, Italy.ORCID 0000-0002-5044-8482

Funding

European Union - NextGenerationEU, under the Italian Ministry of 591 University and Research (MUR) National Innovation Ecosystem ECS00000041 - VITALITYItalian Ministry of University and Research (MUR) via the 589 FIS2021 Advanced Grant FIS00001797U.S. National Science Foundation No. 2349792 and 2431765
6 · The paper itself

Abstract

The automation of concrete constructions through 3D printing (3DP) has been increasingly developed and adopted in civil engineering due to its promising advantages over traditional construction methods. However, widespread implementation is hindered by uncertainties in quality control, homogeneity, and interlayer bonding, as well as the uniqueness of each printed component. Building upon our prior work in developing 3D-printable self-sensing cementitious materials by incorporating graphite powder and carbon microfibers into a cementitious matrix to enhance its piezoresistive properties, this study aims at enabling condition assessment of cementitious 3DP by integrating the self-sensing materials as sensing nodes within conventional components. Three different 3D-printed strip patterns, consisting of one, two, and three strip lines that mimic the pattern used in fabricating foil strain gauges were investigated as conductive electrode designs to impart strain sensing capabilities, and characterized from a series of quasi-static and dynamic tests. Results demonstrate that the three-strip design yielded the highest sensitivity (λstat of 669, λdyn of 630), whereas the two-strip design produced the highest signal quality (SNR

Indexed as

3D printingcarbon microfibercementitious compositesnon-destructive evaluationresistorself-sensingstrain sensingstructural health monitoring

Identifiers

PMID41094828
PMCPMC12526622

What OpenQuestion 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 OpenQuestion graph.