Evidence map›Paper›PMID 39686174›Full record

ArticleSensors (Basel, Switzerland)2024

Investigation of 3D Printed Self-Sensing UHPC Composites Using Graphite and Hybrid Carbon Microfibers.

Han Liu, Simon Laflamme, Bin Cai, Ping Lyu, Sri Sritharan, Kejin Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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 50011, USA.ORCID 0000-0003-3057-522X
Simon LaflammeDepartment of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA.ORCID 0000-0002-0601-9664
Bin CaiDepartment of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA.ORCID 0000-0003-1024-7835
Ping LyuDepartment of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA.
Sri SritharanDepartment of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA.ORCID 0000-0001-9941-8156
Kejin WangDepartment of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA.ORCID 0000-0002-7466-3451

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper explores the development of 3D-printed self-sensing Ultra-High Performance Concrete (UHPC) by incorporating graphite (G) powder, milled carbon microfiber (MCMF), and chopped carbon microfiber (CCMF) as additives into the UHPC matrix to enhance piezoresistive properties while maintaining workability for 3D printing. Percolation curves were established to identify optimal filler inclusion levels, and a series of compressive tests, including quasi-static cyclic, dynamic cyclic, and monotonic compressive loading, were conducted to evaluate the piezoresistive and mechanical performance of 29 different mix designs. It was found that incorporating G powder improved the conductivity of the UHPC but decreased compressive strength for both mold-cast and 3D-printed specimens. However, incorporating either MCMF or CCMF into the UHPC resulted in the maximum 9.8% and 19.2% increase in compressive strength and Young's modulus, respectively, compared to the plain UHPC. The hybrid combination of MCMF and CCMF showed particularly effective in enhancing sensing performance, achieving strain linearity over 600 με. The best-preforming specimens (3G250M250CCMF) were fabricated using 3 wt% of G, 0.25 wt% of MCMF, and 0.25 wt% of CCMF, yielding a maximum strain gauge factor of 540, a resolution of 68 με, and an accuracy of 4.5 με under axial compression. The 3D-printed version of the best-performing specimens exhibited slightly diminished piezoresistive and mechanical behaviors compared to their mold-cast counterparts, yielding a maximum strain gauge factor of 410, a resolution of 99 με, and an accuracy of 8.6 με.

Indexed as

3D printingadditive manufacturingcarbon microfibercementitiousself-sensingstrain sensingstructural health monitoringUHPC

Identifiers

PMID39686174
PMCPMC11645035

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.