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Record W2002034927 · doi:10.2495/esus110101

Biomass char production at low severity conditions under CO<sub>2</sub>and N<sub>2</sub>environments

2011· article· en· W2002034927 on OpenAlexafffundabout
Guillaume Pilon, Jean‐Michel Lavoie

Bibliographic record

VenueWIT transactions on ecology and the environment · 2011
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversité de Sherbrooke
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesUniversité de Sherbrooke
KeywordsBiomass (ecology)CharHeat of combustionCrop residuePulp and paper industryBiorefineryEnvironmental sciencePyrolysisPanicum virgatumBiocharRaw materialBioenergyChemistryWaste managementBiofuelAgronomyCombustionOrganic chemistryAgriculture

Abstract

fetched live from OpenAlex

In a perspective of biomass value addition, biomass char, a thermochemical product, long time considered as a residue, is now getting attention and may represent a vector in the sustainability of the whole biomass sector. Some char types were shown to have great potential as a solid fuel or precursor for further transformations as well as having attributes for storage and transportation. Other types showed potential as a soil carbon sequestration technique and soil amendment enhancing biomass yields. Depending on several factors, but mostly on biomass and production conditions, biomass char physico-chemical characteristics may vary tremendously. Therefore, in order to be used in accordance for specific utilizations, its characteristics must be carefully understood and controlled. In this study, chars with varying properties were produced in a custom-made lab-scale fixed bed reactor. Along these experiments, various biomass chars were produced under CO 2 and N 2 for temperatures of 300 and 500 C. Char was produced from switchgrass (Panicum virgatum L.) an energy crop grown in Canada. It was then characterized for ultimate and proximate analysis as well as for calorific value. In addition, specific surface was characterized by Brunauer-Emmett-Teller (BET) technique. Char organic content composition was verified by Soxhlet extractions using dichloromethane and extracts were analysed by GC-MS.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.169
Teacher spread0.161 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2011
Admission routes3
Has abstractyes

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