Evidence map›Paper›PMID 41847213›Full record

ArticleResearch (Washington, D.C.)2026

An Intelligent Floor Drain System for Self-Powered Disinfection via Low-Velocity Wastewater Energy Harvesting.

Zhijie Huang, Yu Wang, Yuanhao Wang, Chris Rhys Bowen, Hong-Joon Yoon, Ya Yang

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2026. 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

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

6 authors.

Zhijie HuangCenter on Nanoenergy Research, institute of Science and Technology for Carbon Peak & Neutrality, School of Physical Science & Technology, Guangxi University, Nanning 530004, P. R. China.
Yu WangCenter on Nanoenergy Research, institute of Science and Technology for Carbon Peak & Neutrality, School of Physical Science & Technology, Guangxi University, Nanning 530004, P. R. China.
Yuanhao WangResearch Institute of Urbanization and Urban Safety, College of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, P. R. China.
Chris Rhys BowenDepartment of Mechanical Engineering, University of Bath, Bath BA2 7AK, UK.
Hong-Joon YoonDepartment of Electronic Engineering, Gachon University, Seongnam 13120, Republic of Korea.
Ya YangCenter on Nanoenergy Research, institute of Science and Technology for Carbon Peak & Neutrality, School of Physical Science & Technology, Guangxi University, Nanning 530004, P. R. China.ORCID https://orcid.org/0000-0003-0168-2974

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid urbanization intensifies hygiene and sustainability challenges in drainage systems, where conventional floor drains suffer from odor backflow, bacterial growth, and pathogen transmission. Existing disinfection methods depend on external power or chemicals, increasing energy consumption and environmental pollution. Herein, we develop an intelligent floor drain system that enables self-powered disinfection by recovering wastewater energy. By synergistically integrating a turbine blade drain valve, a magnetic levitation module, a contactless drive module, and an electromagnetic power generation (EMG) module, the intelligent floor drain system recovers energy from wastewater for power generation while maintaining its traditional functionality. The EMG module is able to produce a peak power output of 0.8 mW at a drainage rate of 4.15 l/min. A voltage-multiplying circuit boosts energy output by 55%. The system was able to achieve 98.2% sterilization efficiency after 50 min of operation. This work contributes to the global goals of sustainability and energy efficiency.

Identifiers

PMID41847213
PMCPMC12989653

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.