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Permanent record · RIR–2025

Optimizing Nanofiltration Membrane Performance for the Removal of Emerging Organic Micro-contaminants in Wastewater

Nanofiltration is a promising technology for water purification, yet its efficiency in removing specific organic micro-contaminants requires further optimization. This research evaluates the impact of membrane surface modifications on the rejection rates of persistent organic pollutants.

Open to researchQualified 85/100P4 provenance
Primary research question

How do specific membrane surface modifications influence the rejection efficiency of emerging organic micro-contaminants during nanofiltration processes?

Knowledge gap

What remains worth asking

It remains useful to test the long-term stability and selectivity of modified nanofiltration membranes under varying water quality conditions.

Potential contribution

Why it may matter

Advancing membrane technology is critical for ensuring safe water reuse and environmental protection.

Academic placement

OECD fields and topic tags

Chemical EngineeringEnvironmental EngineeringWater Resource Management

Scope: Nanofiltration systems in municipal or industrial wastewater treatment plants. · Method signals: Laboratory experiments, Spectroscopic analysis, Performance modeling

Possible study pathways

One question, different levels

Research master’s

Advanced water treatment technologies.

Doctoral

Membrane science and environmental remediation.

originalityModerate
methodologyAdvanced
Data accessAccessible
ethicsAccessible

Qualification signal

85/100

  • Focuses on improving water treatment efficiency.
  • Open-access scholarly source and DOI metadata verified

Provenance

Research Idea Registry curation

  • DOI and bibliographic metadata independently resolved
  • Open-access status verified
  • The research direction is transparently marked as AI-inferred
The public contributor code contains no name or account email.

APA 7 source

Piekutin, J. (2020). Organic micro-contaminants removed from water in the nanofiltration process – preliminary research results. Desalination and Water Treatment, 199, 220-226. https://doi.org/10.5004/dwt.2020.26243

Paper abstract and discussion context; AI-inferred direction

Open source ↗