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Hybrid ML-driven simulation exploring the fate of environmentally relevant nanoplastics in complex aqueous matrices: Mechanistic insight into colloidal behavior via explainable AI

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Citation · APADOI ↗

Talib M. (2026). Hybrid ML-driven simulation exploring the fate of environmentally relevant nanoplastics in complex aqueous matrices: Mechanistic insight into colloidal behavior via explainable AI. Water research. https://doi.org/10.1016/j.watres.2026.126016

Article Signal

No abstract was available from the source feed.

Research Metadata

Source: ncbi
Published: 2026-01-01
Evidence score: 94
Confidence: 98%
Habitats: unknown
Taxa: Mechanistic insight, Water research
DOI: 10.1016/j.watres.2026.126016
PMID: 42107325

Managed Queue Status

Queue: paper-note-review
Status: queued
Managed: yes
Source: live-feed
Dedupe key: doi:10.1016/j.watres.2026.126016
Last seen: 2026-01-01T00:00:00.000Z
Reason: Auto-generated from a linked paper feed signal awaiting review.

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paper managed/paper-note agent/generated queue/paper-note-review status/queued source/ncbi habitat/unknown