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Record W2986508374 · doi:10.14203/metalurgi.v26i1.7

MASIH TERBUKANYA PELUANG PENELITIAN PROSES CARON UNTUK MENGOLAH LATERIT KADAR RENDAH DI INDONESIA

2015· article· id· W2986508374 on OpenAlexaboutno aff
Puguh Prasetiyo

Bibliographic record

VenueMetalurgi · 2015
Typearticle
Languageid
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMaterials science

Abstract

fetched live from OpenAlex

Indonesia memiliki cadangan nikel pada peringkat dua dunia. Cadangan tersebut berupa bijih nikel oksida yang  lazim disebut  laterit, berada di Kawasan Timur Indonesia (KTI) terutama di Sulawesi Tenggara dan Halmahera. Adapun laterit terdiri dari limonit berkadar Ni 1,5 %. Laterit kadar tinggi saprolit berkadar   Ni>1,8 % sudah diolah di Sulawesi Tenggara dengan jalur pyrometalurgi oleh PT Antam (Aneka Tambang) untuk memproduksi FeNi (ferro nikel) di Pomalaa, dan PT INCO Canada untuk memproduksi nikel mattte (Ni-matte) di Soroako. Laterit kadar rendah yang terdiri dari limonit dan saprolit dengan kandungan Ni 6 % atau MgO > 10 %) diolah dengan proses Caron. Dalam perkembangannya setelah tahun 1990-an, proses Caron mulai ditinggalkan karena mengkonsumsi energi tinggi dengan perolehan yang rendah untuk nikel (Ni : 70 – 80 %) maupun kobal (Co maks 50 %). Selanjutnya beralih ke proses HPAL karena proses ini mengkonsumsi energi rendah dengan perolehan tinggi untuk nikel (Ni > 90%) maupun kobal (Co > 90 %). Dengan melihat kenyataan kegagalan tiga HPAL plant generasi kedua di Australia (Bulong tutup 2003, Cawse tutup 2008, dan Murrin Murrin berpindah kepemilikan ke Minara pada 2003/2004 dan beralih ke heap leach tahun 2007). Serta masih berlangsungnya Caron plant di Cuba (Nicaro dan Punta Gorda), Queensland Nickel di Yabulu Australia, dan Tocantin Brasilia. Maka proses Caron masih punya peluang untuk mengolah laterit kadar rendah di Indonesia. Peluang tersebut semakin terbuka apabila perolehan metal (recovery Ni dan Co) pada proses Caron bisa ditingkatkan setara dengan perolehan metal (recovery Ni dan Co) pada proses HPAL, dan ekonomis konsumsi energinya. Abstract Indonesia had the resources of nickel at the second in the world. The resources are nickel oxide which said laterite. The abundant of laterite locate at Sulawesi Tenggara (South-East Sulawesi) and Halmahera. There are two main mineral in laterite, limonit contains Ni 1,5%. The high grade nickel saprolit contains Ni>1,8% has been processed in Sulawesi Tenggara to produce FeNi (ferro nickel) in Pomalaa by PT Antam, and to produce Ni-matte (nickel matte) in Sorowako by PT INCO Canada. The low grade laterite (limonit and saprolit contains Ni 90 % and Co > 90 %). The fact three HPAL plant in Australia unsuccessful (Bulong closed on 2003, Cawse closed on 2008, and Murrin Murrin taked over by Minara and change to heap leach on 2007) and the Caron plant still exist in Cuba (Nicaro and Punta Gorda), Queensland Nickel di Australia, and Tocantin Brasilia. Then Caron’s process still have opportunity to process the low grade laterite in Indonesia if the recovery of metal can be increase as same as HPAL and the consume of energy can be decreased.

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 score0.012
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.036
GPT teacher head0.267
Teacher spread0.230 · 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".

Quick stats

Citations4
Published2015
Admission routes1
Has abstractyes

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