Evidence map›Paper›PMID 42096448›Full record

ArticlePloS one2026

Microbial fuel cells for wastewater treatment and electricity production: A multi-platform simulation workflow.

Muhammad Ali

Abstract read
In one paragraph

Article in PloS one, 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

1 author.

Muhammad AliDepartment of Chemical Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.ORCID https://orcid.org/0009-0009-9120-2065

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The need for sustainable energy generation and efficient wastewater treatment continues to motivate technologies that integrate energy recovery with environmental remediation. Here, a microbial fuel cell (MFC) system is designed and evaluated, leveraging electrogenic microorganisms to produce electricity during wastewater treatment, with a focus on material selection and design configuration. The proposed design integrates key elements including a proton exchange membrane, anodic and cathodic chambers, and an external circuit to support conversion of organic waste to electrical output through an anode-cathode redox cycle. Four software platforms were used to evaluate complementary aspects of the MFC system under stated modeling assumptions. MATLAB was used to model bacterial growth kinetics and anode performance using Butler-Volmer and Monod based relations. DWSIM was used for thermodynamic screening and mass and energy balance calculations to assess feasibility and stream behavior. COMSOL Multiphysics was used to interpret spatial concentration gradients and biofilm related distributions within the anode compartment. MINITAB was used for a design of experiments style statistical screening (ANOVA and Fisher post hoc testing) of five anode materials using a constructed voltage dataset guided by exploratory prototype observations, and electrode material showed a strong effect on voltage output (F = 21779.35, p < 0.001, R² = 99.83%), with platinum producing the highest mean voltage. Post hoc Fisher testing further indicated that the platinum electrode was statistically different from the other materials. Overall, the study establishes a reproducible simulation workflow that supports comparative screening of anode materials and design configurations for MFC based wastewater treatment with energy recovery.

Indexed as

Bioelectric Energy SourcesElectricityWastewaterWater PurificationBiofilmsComputer SimulationElectrodesWorkflowWastewater

Identifiers

PMID42096448
PMCPMC13152150

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.