Guiding role and optimization of malic acid in the crystallization of amoxicillin trihydrate
Bibliographic record
Abstract
Abstract This study investigates the role of malic acid, a natural and environmentally friendly acid, in optimizing the crystallization process of amoxicillin trihydrate (AMCT). For the first time, the effects of malic acid on AMCT purity and yield were systematically analyzed and visualized using an Ishikawa diagram to elucidate complex interactions. Full factorial design and multiple response optimization were employed, with experiments conducted using Minitab V19 software. The results demonstrated that malic acid concentration, crystallization time, pH, and stirring speed significantly influence the purity and yield of AMCT crystals. The optimal conditions—2.5 M malic acid, pH 5.5, stirring speed of 1000 rpm, and crystallization time of 60 min—produced crystals with 99.21% purity and 62.6% yield. A comparative analysis with citric acid, previously studied by our group, highlighted malic acid's advantages, including improved yield and balanced purity. This research emphasizes the potential of organic acids as sustainable alternatives in pharmaceutical crystallization, offering insights into eco‐friendly production methods. The findings contribute to industrial applications by promoting green chemistry principles and advancing environmentally conscious pharmaceutical practices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".