Experimental methods in chemical engineering: Thermogravimetric analysis—TGA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Thermogravimetric analysis (TGA) is a quantitative analytical technique that monitors the mass of a sample from 1 mg to several g as a furnace ramps temperature to as high as 1600°C under a stable or changing gas flow. The first gravimetric test was in 27 BC when Vitruvius measured limestone's change of mass as it calcined to lime. In modern chemical engineering, researchers apply the technique to derive conversions, kinetics, and mechanisms for any process with a change of mass by isothermal, non‐isothermal, and quasi‐isothermal methods. The mass drops as the sample decomposes, volatile compounds evaporate, or the oxidation state decreases, while in reactive environments (with O 2 , for example), the mass of transition metals may increase. TGA is incapable of detecting phase transitions, polymorphic transformations, or reactions for which mass is invariant. DSC or DTA couple with TGA to help deconvolute a DSC plot by separating physical changes from chemical changes. Evolved gas analysis techniques monitor the gaseous products exiting the TGA furnace on‐line as the temperature ramps. A bibliometric map of keywords from articles citing TGA indexed by Web of Science in 2016 and 2017 identified five research clusters: nanoparticles, performance, and films; crystal structures, acid, and oxidation; composites, nanocomposites, and mechanical properties; kinetics, pyrolysis, and temperature; and adsorption, water and wastewater, and aqueous solutions. This review provides an overview of the basic principles of modern TGA.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it