AI summary

70% confidence

Extracted 1 performance metrics using pattern matching.

Generated by MESSAI extraction pipeline · review against source PDF

Generic MECRepresentative model
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Representative MEC — matched on the paper’s system type only, not its reactor or geometry.

Extraction

Reported parameters

121 extracted values

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What they did

System
MEC
Substrate
pure compound

What worked

No outcome metrics extracted yet.

Abstract

Hydrogen production from renewable resources via microbial electrolysis cells (MECs) is a promising approach for sustainable energy production. Yet high hydrogen yield from real feedstocks has not been demonstrated in up-scaled MECs. In this study, a 10-L single chamber MEC with a high electrode surface area to volume ratio (66 m²/m³) was constructed and electroactive cathodic biofilms were enriched for hydrogen evolution reaction. A high hydrogen yield of 91% was achieved using lignocellulosic hydrolysate with a hydrogen production rate of 0.71 L/L/D at an organic loading rate of 0.4 g/D. The anodic and cathodic microbial communities, with Enterococcus spp. as the known electroactive bacteria, were capable of achieving current densities of 13.7 A/m² and 16.5 A/m², respectively. A machine learning algorithm was used to investigate the correlation between community data and electrochemical performance, and the critical genera on determining current density were identified.

Keywords

Microbial electrolysis cellHydrogen productionHydrolysateElectrolysisElectrochemistryHydrogen

Identifiers

PubMed
33147527
Journal
Bioresource technology
Year
2020