ArticleEnvironmental science and pollution research international2022
Implementation of graphitic carbon nitride nanomaterials and laser irradiation for increasing bioethanol production from potato processing wastes.
Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed, 21 citations in OpenAlex.
- Nanoparticle-microbe interactions in biofuel fermentation: current understanding and prospective applications.Nanoscale advances · 2026Review
- Biostimulation of green microalgae Chlorella sorokiniana using nanoparticles of MgO, CaScientific reports · 2023Article
- Effects of AlScientific reports · 2023Article
- Perspectives on Nanomaterials and Nanotechnology for Sustainable Bioenergy Generation.Materials (Basel, Switzerland) · 2022Review
- Biotechnological advances in biomass pretreatment for bio-renewable production through nanotechnological intervention.Biomass conversion and biorefinery · 2022Review
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
Agricultural and agro-industrial wastes (e.g., potato peel waste) are causing severe environmental problems. The processes of pretreatment, saccharification, and fermentation are the major obstacles in bioethanol production from wastes and must be overcome by efficient novel techniques. The effect of exposing the fungi (yeast) Saccharomyces cerevisiae to laser source with the addition of graphitic carbon nitride nanosheets (g-C
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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.