EKSTRAKSI MAGNETIT (Fe3O4) DARI PASIR BESI PESISIR BARATSEBAGAI NANOPARTIKEL DENGAN METODE KOPRESIPITASI
Bibliographic record
Abstract
Pasir besi di Provinsi Lampung tersebar di beberapa wilayah salah satunya Kabupaten Pesisir Barat. Pasir Pantai Mandiri Kabupaten Pesisir Barat berwarna abu-abu kehitaman yang mengindikasikan mengandung mineral besi, seperti magnetit. Sampel pasir besi dari Pantai Mandiri dikarakterisasi menggunakan XRF, dari hasil karakterisasi XRF pasir besi Pantai Mandiri mengandung unsur diantaranya Fe 52,854%; Si 20,553%; Ti 7,600%; Al 7,449% dan Ca 6,873%. Metode kopresipitasi merupakan metode yang banyak digunakan untuk menghasilkan nanopartikel magnetit, karena metode ini yang paling sederhana dan memberikan hasil yang tinggi. Pada penelitian ini dilakukan ekstraksi magnetit dari pasir besi Pantai Mandiri menggunakan metode kopresipitasi dengan pelarut HCl 37% serta agen pengendap NH4OH 25% dan dikarakterisasi menggunakan X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD) dan Scanning Electron Microscope (SEM). Hasil ekstraksi magnetit dari pasir besi Pantai Mandiri dengan variasi pH pada proses pengendapan yaitu pH 9;10;11 diperoleh endapan berwarna hitam dengan persen rendemen berturut-turut 16,42%; 18,24%; dan 21,6%. Hasil ekstraksi Fe3O4 dikarakterisasi menggunakan instrumen XRF diperoleh kandungan Fe3O4 pada masing-masing pH yaitu 84,074% untuk pH 9; 85,094 untuk pH 10 dan 91,747 untuk pH 11. Hasil ekstraksi pada variasi pH 11 dikarakterisasi menggunakan XRD. Dari hasil analisa XRD diperoleh fasa magnetit dengan ukuran 19,23 nm berstruktur kubik dan memiliki konstanta kisi a = b = c = 8,3200Å dengan α = β = γ = 90°. Hasil karakterisasi mengggunakan Scanning Electron Microscope (SEM) morfologi Fe3O4 bentuknya tidak beraturan dan terjadi aglomerasi. Kata kunci: Pasir Besi, Magnetit, Kopresipitasi, Nanopartikel Iron sand in Lampung Province is spread in several areas, one of which is Pesisir Barat Regency. The sand of Mandiri Beach Pesisir Barat Regency is gray-black which indicates it contains iron minerals, such as magnetite. Iron sand samples from Pantai Mandiri were characterized using XRF, from the XRF characterization results the iron sand of Pantai Mandiri contained elements including Fe 52.854%; Si 20.553%; Ti 7,600%; Al 7.449% and Ca 6.873%. The coprecipitation method is a widely used method for producing magnetite nanoparticles, because it is the simplest and gives high yields. In this study, magnetite extraction was carried out from the iron sand of Pantai Mandiri using the coprecipitation method with 37% HCl solvent and 25% NH4OH precipitating agent and characterized using X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD) and Scanning Electron Microscope (SEM). The results of magnetite extraction from the iron sand of Mandiri Beach with pH variations in the deposition process, namely pH 9; 10; 11 obtained a precipitate of black color with a successive percent yield of 16.42%; 18,24%; and 21.6%. Fe3O4 extraction results were characterized using XRF instruments obtained Fe3O4 content at each pH which is 84.074% for pH 9; 85.094 for pH 10 and 91.747 for pH 11. Extraction results at pH variation 11 were characterized using XRD. From the results of XRD analysis, a magnetite phase with a size of 19.23 nm is obtained with a cubic structure and has a lattice constant a = b = c = 8.3200Å with α = β = γ = 90 °. The results of characterization using Scanning Electron Microscope (SEM) morphology Fe3O4 irregular shape and agglomeration occur. Keywords: Iron Sands, Magnetite, Coprecipitation, Nanoparticles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".