Chemical Reaction Stoichiometry: A Key Link between Thermodynamics and Kinetics, and an Excel Implementation
Bibliographic record
Abstract
<div>The Law of Conservation of Mass (LCM) is one of the most important principles in chemistry. It applies to both closed and steady-state open flow systems undergoing chemical change. Various special methods are generally taught for its implementation, including inspection, oxidation-reduction, and ion-electron approaches, which typically fall under the topic of "balancing a chemical equation". However, apart from the simplest case described by a single such equation, only matrix methods are applicable.</div><div><br></div><div>This paper describes Chemical Reaction Stoichiometry (CRS), and its implementation of the LCM for chemically reacting systems by its expression in terms of a nonunique set of independent chemical equations of the appropriate number. Such equations have the superficial appearance of, but are distinct from, an actual chemical reaction mechanism. The underlying matrix method is based on ideas from basic linear algebra; in addition to being generally applicable to systems of any complexity, it obviates the need for the aforementioned special methods in single-reaction systems.</div><div><br></div><div>We provide an easy-to-use spreadsheet implementation of CRS that includes many worked examples.</div>
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 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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".