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Record W4386757531 · doi:10.1021/acs.accounts.3c00364

Multiscale Process Intensification of Waste Valorization Reactions

2023· article· en· W4386757531 on OpenAlexafffund
Rafael M. Santos, Ning Zhang, Reza Bakhshoodeh

Bibliographic record

VenueAccounts of Chemical Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Guelph
FundersNatural Resources CanadaOntario Agri-Food Innovation AllianceNatural Sciences and Engineering Research Council of CanadaEngineering and Physical Sciences Research CouncilMitacsOntario Ministry of Research, Innovation and ScienceResearch Corporation for Science Advancement
KeywordsCarbonationProcess (computing)Process engineeringWork (physics)Environmental scienceBiochemical engineeringComputer scienceEngineeringMechanical engineeringChemical engineering

Abstract

fetched live from OpenAlex

Conspectus The central theme of this Account is the development of intensified and sustainable chemical processes for the sequestration of CO 2 in synergism with the utilization of wastes of industrial, urban, and agricultural origins. A challenge when working with solid waste–fluid reactions is that mass transfer limitations across solid–liquid, solid–gas, and gas–liquid interfaces and unfavorable thermodynamics lead to slow reaction rates, incomplete reaction conversions, high energy expenditure and processing costs, and inadequate product properties. The traditional macroscale approaches to overcoming slurry reaction limitations can be effective; however, they come at a cost to the environment. In the treatment or valorization of low-grade and waste resources, such conventional approaches are often unfeasible on an industrial scale. Sustainable solutions are thus needed. In the last six years, we have been exploring and developing approaches to overcoming reaction rate limitations of slurry reactions of environmental relevance by concurrently applying process intensification strategies and multiscale engineering approaches. The scientific approach has relied on laboratory-scale experiments to test and refine the devised multiscale process intensification strategies, with thermodynamic and computational modeling work supporting the experimental work and with advanced characterization techniques being used to elucidate reaction and transport mechanisms and aid the development of nanoscale reaction models and micro- and macroscale process models. The research streams, associated with the four key references, discussed next are (a) brine carbonation; (b) mineral carbonation and enhanced weathering; (c) process intensification and integration; and (d) characterization techniques. Within the four research streams, a number of mineral carbonation processes have been investigated and can be classified as (i) ambient weathering and carbonation; (ii) gas-(wet) solid accelerated carbonation; (iii) aqueous accelerated carbonation; (iv) supercritical accelerated carbonation; and (v) CO 2 mineralization from brine. In some cases, the research was aimed at producing valuable products with reduced environmental risk or a reduced carbon footprint, such as an organomineral fertilizer and zeolites. In other cases, the aim was to assess the reactivity of minerals to match the right feedstock with the right carbonation process, in view of maximizing net carbon sequestration. There were also cases where the carbonation process was reimagined by the use of innovative reaction conditions, reactors, and reagents. The experience with accelerated weathering and carbonation in engineered processes has been translated into the field of enhanced rock weathering (ERW) in agriculture, where the multidisciplinary approach used has served to advance ERW science and technology in ways that have had a resounding effect on recent commercial deployment. The completed research serves to encourage the adoption of process intensification technologies in place of conventional processes, in industry and among the research community, and to catalyze the development of the types of sustainable processes required by the chemical, metallurgical, and minerals industries (which are critical to the green transition) to reduce their environmental impact and carbon emissions. Moreover, the multiscale process intensification approaches developed may also be extended to other industrial, urban, and agricultural processes where the reduction of energy intensity, carbon intensity, and environmental footprint could be achieved.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.089
GPT teacher head0.418
Teacher spread0.328 · 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.

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

Citations14
Published2023
Admission routes2
Has abstractyes

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