Evidence map›Paper›PMID 39585791›Full record

ArticleLangmuir : the ACS journal of surfaces and colloids2025

Durable Antimicrobial Microstructure Surface (DAMS) Enabled by 3D-Printing and ZnO Nanoflowers.

Fnu Yuqing, Shuhuan Zhang, Ruonan Peng, Justin Silva, Olivia Ernst, Blanca H Lapizco-Encinas, Rui Liu, Ke Du

Abstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Langmuir : the ACS journal of surfaces and colloids, 2025. 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

5 · Who and what money

Authors and funding

8 authors.

Fnu YuqingDepartment of Chemical and Environmental Engineering, University of California, Riverside, California 92521, United States.
Shuhuan ZhangDepartment of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.
Ruonan PengDepartment of Chemical and Environmental Engineering, University of California, Riverside, California 92521, United States.
Justin SilvaDepartment of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.
Olivia ErnstDepartment of Biomedical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.
Blanca H Lapizco-EncinasDepartment of Biomedical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.ORCID 0000-0001-6283-8210
Rui LiuDepartment of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.
Ke DuDepartment of Chemical and Environmental Engineering, University of California, Riverside, California 92521, United States.ORCID 0000-0002-6837-0927

Funding

Understand and Detect Sepsis: Pathogen Isolation, Biochemistry Assay, and Optofluidic SensingR35GM142763 · NIGMS · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI DU, KE · 2021 to 2025
$2.0M
NIGMS NIH HHS R35 GM142763
6 · The paper itself

Abstract

Numerous studies have been trying to create nanomaterial-based antimicrobial surfaces to prevent infections due to bacterial growth. One major challenge in real-world applications of these surfaces is their mechanical durability. In this study, we introduce durable antimicrobial microstructure surface (DAMS), which integrates DLP 3D-printed microstructures with zinc oxide (ZnO) nanoflowers. The microstructures function as protection armor for the nanoflowers during abrasion. The antimicrobial ability was evaluated by immersing in 2E8 CFU/mL

Indexed as

Infection ControlNanostructuresPrinting, Three-DimensionalZinc OxideMicrobial Sensitivity TestsZinc Oxide

Identifiers

PMID39585791
PMCPMC12249718

What OpenQuestion holds

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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.