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Record W4410568234 · doi:10.1016/j.surfin.2025.106771

Fabrication of copper- and silver-coated triply periodic minimal surface structures through 3D printing, electroplating and electroless processes

2025· article· en· W4410568234 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSurfaces and Interfaces · 2025
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Guelph
FundersOntario Agri-Food Innovation AllianceFundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco
KeywordsMaterials scienceElectroplatingFabricationCopperMetallurgy3D printingNanotechnologyLayer (electronics)

Abstract

fetched live from OpenAlex

This research presents an innovative approach that offers an accessible method for directly coating metallic layers onto 3D-printed parts for point-of-use (POU) water treatment applications. This provides more control over the final geometry while concentrating the disinfecting agent on the surface—rather than using a massive piece—ensuring effective treatment while reducing material costs and minimizing waste of expensive metallic resources. TPMS (Triply Periodic Minimal Surface) infill meshes were generated via a Schwarz P function coded in Python and then fabricated with a commercial-grade PLA-based composite filament with conductive properties. This made the electrochemical deposition of copper ions onto the printed infill surfaces possible via a DC-powered electroplating process. Initially, four different approaches were tested under four different electrolyte bath concentrations—sixteen experiments (four under static conditions and twelve under agitation)—with the outcomes evaluated through visual inspection, digital microscopy, and scanning electron microscopy (SEM), which was also used as a tool for quantifying the fraction of the surface area with metal deposition. Energy-dispersive spectroscopy (EDS) and ImageJ-based surface quantification were employed to validate coating composition and coverage. The optimal electroplating conditions were then refined by incorporating a postprint annealing treatment and reconfiguring the disposition of the components to enhance coating uniformity. The deposition process was monitored by measuring the electric current, allowing for the quantification of copper mass deposited through Faraday’s law of electrolysis. Finally, a silver-over-copper (Ag@Cu) deposition was successfully performed, with the resulting silver mass assessed via inductively coupled plasma‒mass spectrometry (ICP‒MS). Application tests demonstrated >99% disinfection efficiency against E. coli within a calculated exposure of minutes, with statistical analysis confirming the significance of bacterial reduction, and ICP-MS assessing minimal metal leaching, supporting the safety and durability of the system. The results confirm that the proposed methodology not only achieves a homogeneous metallic coating on complex TPMS structures but also provides a durable, scalable and reproducible solution for developing effective water treatment devices tailored for local farmers and isolated areas.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.231
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it