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Enregistrement W3011211420 · doi:10.2172/1603765

Biomass Electrochemical Reactor for Upgrading Biorefinery Waste to Industrial Chemicals and Hydrogen

2019· report· en· W3011211420 sur OpenAlexfundno aff
John A. Staser

Notice bibliographique

Revuenon disponible
Typereport
Langueen
DomaineEngineering
ThématiqueLignin and Wood Chemistry
Établissements canadiensnon disponible
Organismes subventionnairesOffice of Energy EfficiencyOffice of Energy Efficiency and Renewable EnergyLakehead UniversityU.S. Department of Energy
Mots-clésBiorefineryLigninDepolymerizationBiomass (ecology)Environmental scienceProcess engineeringWaste managementChemistryBiofuelEngineeringOrganic chemistry

Résumé

récupéré en direct d'OpenAlex

The goal of this project was to develop an electrochemical process for depolymerization of biorefinery lignin to industrial chemicals, most notably as replacements in resins. The project team consisted of Ohio University (lead organization), Hexion, Inc. and Lakehead University. There were six distinct project tasks, consisting of Initial Validation, Development of TiO2 Nanowire-supported Ni-Co Electrocatalysts, Electrochemical Characterization of TiO2 Nanowire-supported Ni-Co Electrocatalysts, Development of Electrochemical Flow Reactor for Production of Industrial Chemicals and Hydrogen, Product Formulations and Integrated Biorefinery Analysis. The project was divided into two budget periods. After intermediate validation near the end of Budget Period 1, the project was discontinued. This final report is intended to highlight major project objectives and results. Technical metrics were developed between the project team and the DOE validation team during the initial validation period. Critical technical metrics included conversion of lignin to products and product selectivity. Desired products were low molecular weight aromatic compounds in the 150-300 MW range. We targeted this class of compounds because of their potential to replace petroleum derivatives in resin formulations. Electrochemical oxidation of biorefinery lignin can lead to significant lignin depolymerization and conversion, with >40% of the lignin reacted. However, product stream analysis is extremely difficult. We were not able to adequately quantify the concentration of the primary oxidation products, or to determine with any degree of certainty what the product selectivity was. The project team initially proposed analytical techniques such as GC-MS to identify product distributions. However, due to 1) difficulty in extracting products into an organic phase suitable for GC analysis and 2) the wide range of product compounds with similar structures, GC-MS analysis was difficult to perform. The project team did have some success with NMR spectroscopic analysis, but not enough so to adequately identify product selectivity. By UV-vis spectroscopy and statistical analysis, we were able to confirm achieving the technical milestone for lignin conversion, and achieved at least 40% conversion by the electrochemical oxidation technique. However, we were not able to confirm product selectivity using GC-MS analysis, as originally postulated. Despite these difficulties, we were able to incorporate the product stream into a resin, and observed better resin synthesis behavior using the oxidized lignin versus the unoxidized lignin. However, no resin synthesized with oxidized biorefinery lignin met the commercial standards for resin quality. One potential problem with electrochemical oxidation of biomass is the competing oxygen evolution reaction (OER) at the reactor anode. We observed that, especially at higher anode potentials, the OER can consume up to 50% of the energy input to the system, meaning that much of the energy goes toward generation of an essentially worthless product (O2). However, we also observed that the OER can be avoided almost entirely at lower potentials. These uncertainties made assigning a value to the electrochemical reactor product stream difficult. Any product generated electrochemically would have to be valuable enough to offset the additional cost of electricity incurred, including electricity to run the electrochemical reactor and the additional electricity that must be purchased because some of the lignin (which is currently burned in biorefineries to recover energy) is diverted to the electrochemical reactor. It is not clear at this time whether the product stream has sufficient economic value to offset these additional electricity costs. The two most promising areas for this project in terms of demonstrating economic feasibility are product stream analysis and resin synthesis. In particular, product stream analysis has proven to be difficult. With additional time, we would refine analytical techniques to better understand key product stream characteristics, such as aromatic compound content. Evaluating the product streams in resin synthesis would likely provide more information on the economic value of the product stream. If we could determine that value, then we would be able to better evaluate whether the electrochemical conversion approach is feasible. The details of this work are presented in the following final report. The report is organized into individual tasks for clarity, although all tasks were integrated and many occurred simultaneously.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,034
Tête enseignante GPT0,252
Écart entre enseignants0,219 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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