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Record W7065400309

Development of membraneless mixed-reactant microfluidic fuel cells: electrocatalysis and evolution through numerical simulation.

2020· dissertation· fr· W7065400309 on OpenAlexfundno aff

Bibliographic record

VenueEspaceINRS Institutional Digital Repository (Institut National de la Recherche Scientifique) · 2020
Typedissertation
Languagefr
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCentre québécois sur les matériaux fonctionnels
KeywordsFuel cellsFuel supplyMembrane emulsification
DOInot available

Abstract

fetched live from OpenAlex

La demande croissante d'énergie et la détérioration de l'environnement ont motivé la recherche pour développer de nouveaux dispositifs de conversion et de stockage d'énergie alternative et verte à haute efficacité. Cela vaut également pour les produits de consommation tels que les appareils électroniques portables, qui sont des outils essentiels dans la vie moderne. L'introduction de smartphones, d'ordinateurs portables et de gadgets de nouvelle génération, est limitée par l'autonomie, qui est le problème fondamental des batteries Li-ion utilisées comme alimentation sur pratiquement tous les appareils électroniques portables commerciaux. Il est désormais bien connu que la demande d'énergie dépasse les développements de la technologie de batterie conventionnelle. Dans la quête d'une source d'énergie alternative capable de surmonter cette situation, les micro-piles à combustible apparaissent comme une solution intéressante car elles peuvent offrir la mobilité et la liberté recherchées par le consommateur en offrant une vitesse de recharge plus rapide et une durée de vie plus longue. De plus, cette technologie présente des avantages environnementaux importants car les carburants peuvent être obtenus à partir de sources organiques durables. Le méthanol est considéré comme un combustible potentiel pour les piles à combustible miniaturisées en raison de sa densité énergétique élevée et de son utilisation relativement sûre. Les piles à combustible microfluidiques à réactifs mixtes sans membrane alimentées au méthanol (MR-µDMFC) ont récemment été proposées comme technologie capable de répondre aux exigences énergétiques des appareils électroniques portables. Afin d'améliorer leurs performances, cette thèse se concentre sur le développement d'un matériau de cathode très efficace pour les MR-µDMFC, ajouté à une compréhension précise d'un fonctionnement à cellule unique. Ceci est prévu à être réalisé en utilisant des simulations numériques et en mettant en œuvre des améliorations de cellules de pile établies sur ces résultats de simulation. Par conséquent, une cathode sélective a été synthétisée dans ce travail et ensuite utilisée dans une pile MR-µDMFC à 4 cellules développée dans cette thèse. La pile a été testée dans des conditions passives produisant 1,1 mW de puissance de crête en connexion série, une puissance jugée suffisante pour les micro-appareils. La preuve de concept est démontrée en utilisant la pile pour alimenter une LED verte pendant 4 h avec une seule charge de 234 μL. Rising energy demands and the environmental deterioration have motivated the research for developing new, alternative and green energy conversion and storage devices with high efficiency. This also applies for consumer products such as portable electronic devices, which are essential tools in modern life. The introduction of next-generation smartphones, portable computers and a variety of gadgets is severely restricted by the autonomy, which is the fundamental issue of Li-ion batteries employed as power supply on practically all commercial portable electronic devices. It is now well known that power demand is outpacing developments in conventional battery technology. In the quest for an alternative power source capable of overcoming this situation, micro fuel cells appear as an attractive solution as they can offer the mobility and freedom sought by the consumer by offering faster recharging speed and longer service life. In addition, this technology has important environmental benefits because the fuels can be obtained from sustainable organic sources. Methanol is considered to be a potential fuel for miniaturized fuel cells due to its high energy density and relatively safe use. As a promising power source of such, methanol-fed membraneless mixed-reactants microfluidic fuel cells (MRµDMFCs) fabricated on polymeric substrate have recently been proposed as a technology capable of fulfill the energetic requirements for electronic portable devices. In order to improve their performance, this thesis centers on the development of a highly efficient cathode material for MR-µDMFCs, added to an accurate understanding of a single cell operation. This is intended to be achieved by employing numerical simulations and implementing stack cell improvements established on these simulation results. Consequently, a selective cathode was synthesized in this work and subsequently used in a 4-cell MR-µDMFC stack developed in this thesis. The stack was tested in passive conditions producing 1.1 mW of peak power in series connection, a power considered sufficient for micro-devices. The proof of concept is demonstrated by using the stack for powering a green LED during 4 h with a single charge of 234 μL.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.298
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2020
Admission routes1
Has abstractyes

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