Evidence map›Paper›PMID 33902675›Full record

ArticleBiotechnology for biofuels2021

Investigating the effects of substrate morphology and experimental conditions on the enzymatic hydrolysis of lignocellulosic biomass through modeling.

Jessica C Rohrbach, Jeremy S Luterbacher

Abstract read
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Article in Biotechnology for biofuels, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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  5. From Low-CostPolymers · 2025
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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

2 authors.

Jessica C RohrbachLaboratory of Sustainable and Catalytic Processing, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland.
Jeremy S LuterbacherLaboratory of Sustainable and Catalytic Processing, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland. jeremy.luterbacher@epfl.ch.ORCID https://orcid.org/0000-0002-0967-0583

Funding

Innosuisse - Schweizerische Agentur für Innovationsförderung KTI.2014.0116
6 · The paper itself

Abstract

backgroundUnderstanding how the digestibility of lignocellulosic biomass is affected by its morphology is essential to design efficient processes for biomass deconstruction. In this study, we used a model based on a set of partial differential equations describing the evolution of the substrate morphology to investigate the interplay between experimental conditions and the physical characteristics of biomass particles as the reaction proceeds. Our model carefully considers the overall quantity of cellulase present in the hydrolysis mixture and explores its interplay with the available accessible cellulose surface.

resultsExploring the effect of various experimental and structural parameters highlighted the significant role of internal mass transfer as the substrate size increases and/or the enzyme loading decreases. In such cases, diffusion of cellulases to the available cellulose surface limits the rate of glucose release. We notably see that increasing biomass loading, while keeping enzyme loading constant should be favored for both small- (R < 300 [Formula: see text]) and middle-ranged (300 < R < 1000 [Formula: see text]) substrates to enhance enzyme diffusion while minimizing the use of enzymes. In such cases, working at enzyme loadings exceeding the full coverage of the cellulose surface (i.e. e

conclusionsBased on the developed model, we are able to propose several design criteria for deconstruction process. Importantly, we highlight the crucial role of adjusting the enzyme and biomass loading to the wood particle size and accessible cellulose surface to maintain a strong concentration gradient, while avoiding unnecessary excess in cellulase loading. Theory-based approaches that explicitly consider the entire lignocellulose particle structure can be used to clearly identify the relative importance of bottlenecks during the biomass deconstruction process, and serve as a framework to build on more detailed cellulase mechanisms.

Indexed as

CellulaseHydrolysisLignocellulosic biomassMass transferModelingPorosity

Identifiers

PMID33902675
PMCPMC8073973

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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.