ArticleScientific reports2026
Waste to energy through sustainable bioenergy and biohydrogen production from lignocellulosic waste using microbial fuel cell and microbial electrolysis cell.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The accumulation of agricultural lignocellulosic waste, specifically rice straw, and the environmental impact of fossil fuel combustion necessitate the development of sustainable waste-to-energy technologies. Bioelectrochemical systems enable a simultaneous recovery of energy and the treatment of organic waste utilizing a mixed culture of bacteria. This study investigates for the first time the performance of rice straw-derived substrates with different levels of complexity, i.e. rice straw, rice straw hydrolysate, and xylan, to simultaneously produce bioelectricity and biohydrogen, with the objective of clarifying the influence of substrate characteristics on system efficiency. Microbial fuel cells (MFC) result indicated that xylan exhibited the highest performance, achieving a maximum cell potential of 852 ± 27 mV and a power density of 8.88 ± 0.27 W/m², representing a 2.4-fold increase over the control. This was supported by a high Chemical Oxygen Demand (COD) removal efficiency of 97.88 ± 1.32%. The higher values of power density are attributed to the employment of a mixed bacterial culture (sludge) that has already adapted to the degradation of lignocellulosic biomass, hence boosting its utilization and conversion to electrons, resulting in higher electricity generation. Electrochemical analysis indicated efficient electron transfer, reflected by increased current responses at higher scan rates and low charge transfer resistance values. Electrochemical characterization via cyclic voltammetry and electrochemical impedance spectroscopy (EIS) revealed that rice straw-powered cell exhibited the lowest charge transfer resistance (3.37 Ω), correlating with the highest recorded electrical current (9.23 ± 0.25 mA). Conversely, the microbial electrolysis cell (MEC) results showed that rice straw hydrolysate was the optimal substrate for biohydrogen production, yielding a maximum rate of 9.26 ± 0.08 mmol/day.L and a COD removal of 94.92 ± 0.88%, significantly outperforming xylan-based systems and the control cells. These findings indicate that while simpler carbohydrate structures like xylan favor electricity generation in MFCs, the bioavailable nutrients in alkaline-pretreated hydrolysates are more effective for electrohydrogenesis in microbial electrolysis cells. This research provides a critical comparative framework for selecting biomass fractions and system configurations to maximize the efficiency of agricultural waste-to-energy conversion strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.