Evidence map›Paper›PMID 41131109›Full record

ArticleScientific reports2025

Optimizing the effect of TiO

Bhupendra Prakash Sharma, Shyam Sunder Sharma, Ashu Yadav, Rahul Khatri, Surendra Kumar Yadav

Abstract read
In one paragraph

Article in Scientific reports, 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

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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

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

5 authors.

Bhupendra Prakash SharmaDepartment of Mechanical Engineering, Amity University, Noida, Uttar Pradesh, India.
Shyam Sunder SharmaDepartment of Mechanical Engineering, Manipal University Jaipur, Jaipur, India. shyamsunder.sharma@jaipur.manipal.edu.
Ashu YadavDepartment of Mechanical Engineering, Manipal University Jaipur, Jaipur, India.
Rahul KhatriDepartment of Mechanical Engineering, Manipal University Jaipur, Jaipur, India.
Surendra Kumar YadavDepartment of Mechanical Engineering, K. R. Mangalam University, Gurugram, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The incorporation of titanium dioxide (TiO2) nano powder in water-based paint formulations significantly enhances properties such as opacity, UV protection, and durability. However, the challenge lies in optimizing these improvements while managing costs and ensuring environmental and health safety. This study employs Response Surface Methodology (RSM) to systematically analyse and optimize the concentration and particle size distribution of TiO2 nano powder in water-based paints. The study is aimed to maximize opacity and durability while minimizing potential health hazards and environmental impacts. Experimental results were fitted to quadratic models, and the optimal conditions were determined by solving the regression equations and analysing the response surfaces. The optimized formulation achieved a significant improvement in opacity (24% increase) and UV resistance (30% enhancement) compared to conventional water-based paints. Furthermore, the optimized nano powder dispersion demonstrated a decrease in volatile organic compound (VOC) emissions during drying, contributing to better indoor air quality. This research not only underscores the effectiveness of RSM in fine-tuning the properties of nano-enhanced paints but also sets a precedence for the eco-friendly and safe application of nanotechnology in paint manufacturing. Future studies are recommended to scale up the production process and evaluate the long-term environmental impacts of nano TiO2-enriched water-based paints.

Indexed as

Environmental impactResponse surface methodologyTitanium dioxideVolatile organic compoundWater based paint

Identifiers

PMID41131109
PMCPMC12550099

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LicenceCC BY-NC-ND
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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.