MétaCan
Menu
Back to cohort
Record W4413478537 · doi:10.55981/jtl.2025.11385

Potassium Permanganate Confined in Porous Carbon Pretreated Using Wet Ozone Oxidation for Hydrogen Sulfide Removal (H2S)

2025· article· id· W4413478537 on OpenAlexaff
Suhirman Suhirman, Teguh Ariyanto, Imam Prasetyo, Meiga Putri Wahyu Hardhianti

Bibliographic record

VenueJurnal Teknologi Lingkungan · 2025
Typearticle
Languageid
FieldEngineering
TopicIndustrial Gas Emission Control
Canadian institutionsPetro-Canada
FundersKementerian Pendidikan, Kebudayaan, Riset, dan TeknologiBadan Pengelola Dana Perkebunan Kelapa Sawit
KeywordsPotassium permanganateHydrogen sulfideOzoneSulfideChemistryCarbon fibersInorganic chemistryEnvironmental chemistryMaterials scienceSulfurOrganic chemistry

Abstract

fetched live from OpenAlex

Abstrak Kontaminan gas merupakan masalah besar pada proses industri dan lingkungan, terutama hidrogen sulfida (H2S). Gas ini tidak berwarna, tidak berbau, korosif terhadap jaringan pipa gas alam, merusak katalis logam, dan menyebabkan hujan asam. Selain itu, gas ini sangat mudah terbakar dan sangat beracun, sehingga perlu dihilangkan meskipun dalam konsentrasi kecil. Salah satu metode untuk menghilangkan H2S, yang belum dipelajari secara luas, adalah oksidasi dengan kalium permanganat (KMnO4) yang diimpregnasikan pada karbon berpori atau dinamai nano-confinement KMnO4. Cangkang sawit (PKS) digunakan sebagai bahan baku karbon berpori, yang melimpah, terbarukan, dan murah. Proses produksi nano-confinement KMnO4 terdiri atas eberapa langkah. Langkah pertama adalah pirolisis cangkang sawit dalam tungku pada suhu 800°C, diikuti oleh aktivasi karbon uap. Ini menghasilkan karbon berpori cangkang sawit (CPKS). Tahap kedua adalah pembuatan karbon berpori dari cangkang sawit yang cenderung hidrofilik dengan cara oksidasi praperlakuan menggunakan ozonasi basah, yang selanjutnya dinamakan CKPS-Oz. Kalium permanganat yang teremban dalam karbon berpori dari cangkang sawit (KMnO4/CPKS-Oz) diproduksi dengan cara impregnasi secara basah variasi KMnO4 sebesar 5, 10, dan 20% wt. Hasil uji kinerja menunjukkan bahwa KMnO4/CPKS-Oz mampu menghilangkan H2S hingga 98% dan lebih efektif dibandingkan hanya menggunakan KMnO4 (67%). Penelitian ini menunjukkan bahwa kombinasi antara oksidasi ozon basah dan impregnasi KMnO₄ ke dalam karbon aktif dari tempurung kelapa sawit (CPKS) menghasilkan peningkatan kapasitas oksidasi gas H₂S secara signifikan. Metode ini merupakan pendekatan baru yang belum banyak dilaporkan dalam pemanfaatan CPKS untuk penghilangan gas H₂S Abstrak A gas contaminant is a big problem in the process industry and environment, especially hydrogen sulfide (H2S). It is colorless, odorless, corrosive to natural gas pipelines, damages metal catalysts, and causes acid rain. Moreover, it is extremely flammable and highly toxic, so it needs to be removed even in small concentrations. One method to remove H2S, which has yet to be studied widely, is oxidation by nano-confinement permanganate potassium (KMnO4) in a porous carbon support. Palm kernel shells (PKS) were used as a raw material of porous carbon, which is abundant, renewable, and cheap. The production process of nano-confinement KMnO4 consists of several steps. The first step is the pyrolysis of palm kernel shells in the furnace at 800°C, followed by steam activation of carbon. It produced palm kernel shells porous carbon (CPKS). The second step was to produce porous carbon of palm kernel shell that tends to be hydrophilic by pretreatment oxidation using wet ozone treatment, which was then named CKPS-Oz. Potassium permanganate confined in porous carbon from palm kernel shell (KMnO4/CPKS-Oz) was produced by incipient wet-impregnation with KMnO4 variations of 5, 10, and 20%wt. The performance test showed that KMnO4/CPKS-Oz could remove H2S up to 98% and was more effective than only using KMnO4 (67%). This work presents a novel synergistic strategy by integrating wet ozone oxidation and KMnO₄ confinement within palm kernel shell–derived porous carbon (CPKS), providing a sustainable and highly efficient material tailored explicitly for hydrogen sulfide (H₂S) removal from gas streams.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.391
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.268
Teacher spread0.245 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJurnal Teknologi LingkunganSame topicIndustrial Gas Emission ControlFrench-language works237,207