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Pirolisis Kilat Spirulina platensis dengan Katalis Ni/Al-SBA-15

2025· article· id· W4414768444 on OpenAlexaff
Ade Putri Wahyuni, RR Dirgarini Julia Nurlianti Subagyono, Rahmat Gunawan, Veliyana Londong Allo, Maykel Manawan

Bibliographic record

VenueALCHEMY Jurnal Penelitian Kimia · 2025
Typearticle
Languageid
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsCatalysisPyrolysisFourier transform infrared spectroscopyInfrared spectroscopy

Abstract

fetched live from OpenAlex

<p>Studi ini mempelajari aktivitas katalis Ni/Al-SBA-15 dalam pirolisis kilat mikroalga <em>Spirulina platensis </em>dan perannya pada komposisi kimia produk yang dihasilkan. Katalis Ni/Al-SBA-15 yang disintesis dengan metode <em>ultrasonic-assisted sol-gel</em> memiliki luas permukaan 522,54 m²/g, diameter pori 6,6 nm, dan volume pori 0,86 cm³/g. Analisis <em>Fourier transform infrared </em>(FTIR) katalis mengidentifikasi gugus siloksan, silanol, dan hidroksil, sementara analisis <em>low-angle </em>dan <em>wide-angle</em> <em>X-ray diffraction</em> (XRD) menunjukkan puncak difraksi khas Al-SBA-15 dan NiO. Pirolisis tanpa katalis Ni/Al-SBA-15 menghasilkan produk turunan karbohidrat (10,7%), lipid (53,8%), protein (6,3%), dan klorofil (6,2%). Setelah inkorporasi katalis Ni/Al-SBA-15, produk turunan karbohidrat meningkat menjadi 35,2%, protein menjadi 10,9%, klorofil menjadi 10,7%, namun produk turunan lipid menurun menjadi 15,5%. Hasil ini menunjukan aktivitas katalis dalam meningkatkan konversi senyawa penyusun utama mikroalga, khususnya memecah lipid menjadi senyawa dengan berat molekul lebih kecil. Hal ini mengindikasikan bahwa metode sintesis katalis yang digunakan dapat menghasilkan material yang memiliki distribusi situs aktif yang relatif homogen dan aktivitas katalitik pada pirolisis mikroalga <em>Spirulina platensis</em>.</p><p><strong><strong>Flash Pyrolysis of <em>Spirulina platensis</em> with Ni/Al-SBA-15 Catalyst</strong>. </strong>This study investigates the activity of Ni/Al-SBA-15 catalyst in flash pyrolysis of microalgae <em>Spirulina platensis</em> and its role in the chemical composition of the resulting products. The Ni/Al-SBA-15 catalyst synthesized by the ultrasonic-assisted sol-gel method had a surface area of 522.54 m²/g, pore diameter of 6.6 nm, and pore volume of 0.86 cm³/g. Fourier transform infrared (FTIR) analysis of the catalyst identified siloxane, silanol, and hydroxyl groups; meanwhile, low and wide-angle X-ray diffraction (XRD) analysis showed typical diffraction peaks of Al-SBA-15 and NiO. Pyrolysis without Ni/Al-SBA-15 catalyst produced carbohydrate-derived products (10.7%), lipids (53.8%), proteins (6.3%), and chlorophyll (6.2%). After incorporating Ni/Al-SBA-15 catalyst, carbohydrate-derived products increased to 35.2%, protein to 10.9%, and chlorophyll to 10.7%, but lipid-derived products decreased to 15.5%. These results showed the activity of the catalyst in increasing the conversion of the main constituent compounds of microalgae, especially breaking down lipids into smaller molecular weight compounds. This finding indicated that the catalyst synthesis method produced materials with a relatively homogeneous distribution of active sites and catalytic activity in the pyrolysis of microalgae <em>Spirulina platensis</em>.</p>

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.246
Teacher spread0.235 · 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 designNot applicable
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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Citations0
Published2025
Admission routes1
Has abstractyes

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