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Impact of Nonoxidized Sulfur Species on Elemental Mercury Removal by SO<sub>2</sub> Activated Petroleum Cokes

2020· article· en· W3089054283 on OpenAlexaff
Min She, Yufeng Duan, Chun Zhu, Charles Q. Jia

Bibliographic record

VenueEnergy & Fuels · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Toronto
FundersGovernment of Jiangsu ProvinceMinistry of Science and Technology of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsSulfurChemistrySulfideMercury (programming language)Flue gasActivated carbonAdsorptionPetroleum cokeThermogravimetric analysisDesorptionNitrogenCokeFlue-gas desulfurizationInorganic chemistryNuclear chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

High-sulfur petroleum coke is potentially one of the most promising materials for developing efficient and low-cost sorbents for Hg 0 removal from flue gas. In this study, three distinct SO 2 -activated high-sulfur petroleum cokes were prepared at 650–850 °C via different sulfurization protocols, including SO 2 -impregnated petroleum coke (PC-S), SO 2 -impregnated coke produced with an additional reductive heat-treatment process in N 2 (PC-NS), and SO 2 -impregnated coke prepared with the presence of SO 2 in the gas during the cooling process (PC-SC). The SO 2 -activated cokes were characterized with nitrogen adsorption/desorption measurements, X-ray photoelectron spectroscopy, thermogravimetric analysis, and their mercury removal performances were investigated in a fixed-bed reactor at 80–200 °C with an initial mercury concentration of 35–120 μg/m 3 . To explore the influence of nonoxidized sulfur species on Hg 0 removal, particular focus was given to the comparison of the reduced sulfur, sulfide sulfur, and elemental sulfur formed during different sulfurization processes, as well as the consequent differences in Hg 0 adsorption characteristics. It found that the sulfur incorporated into the carbon matrix of PC-S by interaction with SO 2 at 650 °C was dominantly organic sulfide. Thermal treatment in N 2 at 800 °C led to an addition of reduced sulfur in PC-NS. An increment of 0.74 at. % elemental sulfur was observed in PC-SC after exposure to SO 2 during the cooling step. The Hg 0 adsorption capacity of PC-SC at low temperatures was significantly enhanced, yielding a mercury capacity of 622 μg/g at 80 °C. However, elemental sulfur suffered from severe temperature sensitivity for mercury binding. The sample PC-NS which contained more reduced sulfur showed the highest Hg 0 adsorption capacity at elevated temperatures above 160 °C. Furthermore, the increment in inlet mercury concentration would lead to higher adsorption capacities and faster adsorption rates. According to the R L obtained from Langmuir isotherms, the Hg 0 adsorption reactivity can be arranged as follows: PC-NS > PC-S > PC-SC. The mercury temperature-programmed desorption results suggested that sulfur species not only had an effect on Hg 0 adsorption capacity but also played an essential role in the thermal stability of the adsorbed mercury compounds. Mercury was principally associated with elemental sulfur in the form of metacinnabar and combined with thermal-stable organic sulfide in cinnabar or organomercuric compounds Hg–SR.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.240
Teacher spread0.226 · 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 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".

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Citations30
Published2020
Admission routes1
Has abstractyes

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