Predicting the Temperature Dependence of the Octanol–Air Partition Ratio: A New Model for Estimating $$\Delta {U^{ \circ}_{\text{OA}}}$$
Bibliographic record
Abstract
Abstract The octanol–air partition ratio ( K OA ) describes the partitioning of a chemical between air and octanol and is often used to approximate other partitioning phenomena in environmental chemistry (e.g., blood–air, atmospheric particulate matter–air, polyurethane foam-air). Such partitioning processes often occur at environmental temperatures other than 25 °C. Enthalpies $$\Delta {H^{ \circ}_{\text{OA}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Δ</mml:mi> <mml:msubsup> <mml:mi>H</mml:mi> <mml:mtext>OA</mml:mtext> <mml:mo>∘</mml:mo> </mml:msubsup> </mml:mrow> </mml:math> or internal energies $$\Delta {U^{ \circ}_{\text{OA}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Δ</mml:mi> <mml:msubsup> <mml:mi>U</mml:mi> <mml:mtext>OA</mml:mtext> <mml:mo>∘</mml:mo> </mml:msubsup> </mml:mrow> </mml:math> of phase transfer are used to express the temperature dependence of the K OA . Existing poly-parameter linear free energy relationships (ppLFERs) for predicting $$\Delta {H^{ \circ}_{\text{OA}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Δ</mml:mi> <mml:msubsup> <mml:mi>H</mml:mi> <mml:mtext>OA</mml:mtext> <mml:mo>∘</mml:mo> </mml:msubsup> </mml:mrow> </mml:math> were developed using a relatively small dataset. In this work we utilize a recently developed comprehensive K OA database to create and curate a $$\Delta {U^{ \circ}_{\text{OA}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Δ</mml:mi> <mml:msubsup> <mml:mi>U</mml:mi> <mml:mtext>OA</mml:mtext> <mml:mo>∘</mml:mo> </mml:msubsup> </mml:mrow> </mml:math> dataset containing 195 chemicals and use this dataset in the development of new predictive equations. Using the QSAR development platform QSARINS we evaluate the use of Abraham descriptors, other molecular descriptors, and the log 10 K OA at 25 °C as variables in different multilinear regression equations for $$\Delta {U^{ \circ}_{\text{OA}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Δ</mml:mi> <mml:msubsup> <mml:mi>U</mml:mi> <mml:mtext>OA</mml:mtext> <mml:mo>∘</mml:mo> </mml:msubsup> </mml:mrow> </mml:math> . The $$\Delta {U^{ \circ}_{\text{OA}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Δ</mml:mi> <mml:msubsup> <mml:mi>U</mml:mi> <mml:mtext>OA</mml:mtext> <mml:mo>∘</mml:mo> </mml:msubsup> </mml:mrow> </mml:math> of neutral organic chemicals can be reliably predicted using only the log 10 K OA (RMSE EXT = 6.86 kJ·mol −1 , $${\text{R}^{2} _{\text{adj}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mtext>R</mml:mtext> <mml:mtext>adj</mml:mtext> <mml:mn>2</mml:mn> </mml:msubsup> </mml:math> = 0.94), only the solute’s hydrogen acidity A and the logarithm of the hexadecane–air partition ratio L (RMSE EXT = 7.23 kJ·mol −1 , $${\text{R}^{2} _{\text{adj}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mtext>R</mml:mtext> <mml:mtext>adj</mml:mtext> <mml:mn>2</mml:mn> </mml:msubsup> </mml:math> = 0.93), or A and log 10 K OA (RMSE EXT = 6.76 kJ·mol −1 , $${\text{R}^{2} _{\text{adj}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mtext>R</mml:mtext> <mml:mtext>adj</mml:mtext> <mml:mn>2</mml:mn> </mml:msubsup> </mml:math> = 0.95).
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 | 0.001 | 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".