ArticleScientific reports2024
Comprehensive studies for evaluating promising properties of Cu/graphene/fly ash nanocomposites.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Sustainable production of intermetallic nanocomposites from aluminum and iron scarp, with excellent tribo-mechanical and thermal properties for industrial applications.Scientific reports · 2025Article
- Synergistic impact of osseointegration and multifunctionality on functionally graded ceramic composites for bone healing applications.Scientific reports · 2025Article
- Development of Fe/SiBr/Si₃N₄/silica fume nanocomposites from recycled metal waste for industrial applications.Scientific reports · 2025Article
- Evaluation of tribo-mechanical measurements and thermal expansion of Cu-based nanocomposites reinforced by high strength hybrid ceramics.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Copper (Cu)'s electrical conductivity makes it attractive for industrial usage. Due to its inferior mechanical characteristics, thermal expansion, and wear resistance, its applications are limited. This manuscript solves these issues while retaining its major feature, excellent electrical conductivity. In this regard, different quantities of graphene (Gr) and fly ash (FA) nanoparticles were combined with Cu in a planetary ball mill at 440 rpm for 20 h using powder metallurgy (PM). The microstructure of the generated powders was characterized using X-ray diffraction technique and transmission electron microscopy. The powders underwent compression and were then subjected to firing at three distinct temperature levels, reaching a maximum of 850 °C. In addition, an analysis was conducted on the microstructure, mechanical properties, wear resistance, thermal expansion behaviour, and electrical conductivity of the sintered samples. Based on the findings, the inclusion of a hybrid of Gr and FA ceramics effectively led to a reduction in particle sizes. The bulk density slightly decreases with the addition of hybrid ceramic while increasing with the rise in sintering temperature. The hybrid composited Cu/0.8 vol.% Gr/8 vol.% FA recorded an increase in the microhardness, ultimate stress, and Young's modulus of 25, 20, and 50%, respectively, relative to the Cu matrix. Furthermore, the wear rate and coefficient of thermal expansion for the same sample decreased by 67 and 30%, respectively. Finally, increasing the sintering temperature showed a clear improvement in the mechanical, electrical, and corrosion properties. Based on the results obtained, it can be concluded that the prepared hybrid nanocomposites can be used in power generation, power transmission, electronic circuits, and other applications.
Identifiers
What OpenQuestion holds
Registered trials
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.