How strong should my ethanol be — reading "1:1.5 in 50% alcohol" in the database

Someone on r/DIYfragrance asked a question that looks small and is worth answering:

"So I was looking through the good scents company's website for Benzyl Alcohol and Benzyl Acetate and for 'soluble in' it says ethyl alcohol, 1:1.5 in 50% alcohol. I understand ethyl alcohol is another name for ethanol (which I have). But the '1:1.5 in 50% alcohol', how should I interpret that when trying to dilute these materials for testing? Also, is there any reason they specifically say ethyl alcohol instead of alcohol like they typically do?"

Two replies. One said TGSC is just weird sometimes and they would dilute in ethanol as normal. The other got it right:

"If you make 50% water ethanol solution you can get 1 part to dissolve in 1.5 parts of the water/ethanol solution you just made" (actual_ask164)

The notation deserves a serious look, because it is not a formatting quirk but real data, and it answers a bigger question: how strong should your ethanol be?

The short version

• Reading it: 1:1.5 in 50% alcohol means take a 50% water-ethanol mixture, and one part of material needs 1.5 parts of that mixture. The denominator is the solution, not neat ethanol.
• Of 42,225 records, 23,941 (56.7%) have a solubility field, but only 7 leave two or more measurements at different ethanol strengths.
• The slopes of those seven curves differ enormously: vanillin moves 1.5-fold between 70% and 95%; benzyl benzoate moves 1000-fold between 45% and 95%.
• Plotting the seven materials' logP against log10 of their slope gives r = 0.876 (n = 7). More hydrophobic materials are more sensitive to ethanol strength.
• That agrees with pharmaceutical cosolvency theory: a 2010 study of seven chemically unrelated drugs concluded that the hydrophobicity of the solute has a direct impact on solubilization in water-cosolvent mixtures.
• In practice: perfumer's alcohol at 95% dissolves everything, and the moment you add water things start falling out — with logP setting the order in which they go.

The notation

TGSC's solubility field is not one value but a semicolon-separated string of records, each of which may come from a different source in a different format. Benzyl alcohol's field reads in full:

ethyl alcohol, 1:1.5 in 50% alcohol; ethyl alcohol, 1:8-9 in 30% alcohol; most organic solvents; water, 1:25 in water; water, 4.29E+04 mg/L @ 25 °C (exp); paraffin oil; non-discoloring in most media

Broken apart:

Notation	Meaning
1:1.5 in 50% alcohol	One part material dissolves in 1.5 parts of a 50% ethanol-in-water solution
1:8-9 in 30% alcohol	At 30% ethanol, the same one part needs 8 to 9
1:25 in water	In plain water it needs 25
4.29E+04 mg/L @ 25 °C (exp)	Water solubility in another unit, measured

(exp) is experimental and (est) is estimated — this series has measured that 99.8% of the database's appearance values are estimates, so an (exp) is a rare measurement worth noticing.

As for the poster's second question — why ethyl alcohol rather than alcohol — I have no answer. Across the database alcohol appears 10,293 times and ethyl alcohol only 71. It looks like records from different sources using different wording rather than a deliberate distinction. The first reply's "TGSC is just weird sometimes" is probably right.

Seven curves

What is genuinely interesting is that some records leave several measurements of the same material at different ethanol strengths.

Scanning the whole database for solubility fields containing "x% alcohol 1:y" notation with two or more strength points gives 7 materials.

Material	Suppliers	Curve
Benzyl benzoate	84	45% → 1:1000　　95% → 1:2　　(also 90% → 1:2)
Benzyl acetate	100	30% → 1:200　35% → 1:120　40% → 1:70　50% → 1:20　60% → 1:5
Cinnamaldehyde	105	30% → 1:25　　60% → 1:5
Benzyl alcohol	125	30% → 1:8　　50% → 1:1.5
Benzaldehyde	108	50% → 1:8　　60% → 1:2.5
γ-nonalactone	96	50% → 1:5　　60% → 1:2
Vanillin	193	70% → 1:3　　95% → 1:2

The benzyl acetate row is a complete five-point curve. From 30% to 60%, the solution needed drops from 200 parts to 5. Forty-fold.

Benzyl benzoate is more extreme: 1000 parts at 45%, one to two parts at 95%. A thousandfold.

(To be clear: for ranges like 1:8-9 I always took the lower value, so the ratios below are conservative.)

How much the requirement drops from lowest to highest strength

Material	logP	Fold change
Benzyl benzoate	4.00	1000×
Benzyl acetate	2.00	40×
Benzyl alcohol	1.10	5.3×
Cinnamaldehyde	1.90	5.0×
Benzaldehyde	1.50	3.2×
γ-nonalactone	2.20	2.5×
Vanillin	1.20	1.5×

Correlating logP against log10 of the fold change gives r = 0.876 (n = 7).

More hydrophobic materials are more sensitive to ethanol strength.

The sample size needs stating honestly: seven. This series has a rule against reporting ratios on inadequate samples — leather at 9 and gourmand at 12 were both discarded. What differs here is that these seven points are not a sample drawn to infer about a population; they are seven independent measurements used to test a pre-existing theoretical prediction. The evidential character is different. But seven points are seven points, and r = 0.876 should not be treated as a precise estimate.

The theory said this already

The relationship has a name in pharmaceutics: cosolvency, and the standard model is the log-linear model from Yalkowsky and coworkers.

In 2010, Miyako and colleagues measured it in the International Journal of Pharmaceutics. They used seven chemically unrelated drugs (hydrocortisone, sulfanilamide, acetophenetidine, benzocaine, indomethacin, thymol and ibuprofen) against two sets of water-cosolvent mixtures: a group of polar cosolvents consisting of three aliphatic alcohols, and a group of less polar cosolvents (NMP, tetraglycol, labrasol).

Their conclusion:

"The hydrophobicity of the drug has a direct impact on the solubilization obtained in the water-cosolvent mixtures."

And the two groups behave differently. In polar cosolvents — ethanol's class — the solubilization behaviour is typical of polarity match, and combining all solutes and all solvents produces a linear profile. In the less polar cosolvents the positive deviations from the log-linear model are larger and the collective enhancement shows no readily discernible pattern, but taking solute hydrophobicity into account makes a systematic effect clearly apparent.

In 2022, Egert and Langowski evaluated two cosolvency models directly on water-ethanol mixtures: the log-linear model from Yalkowsky and coworkers, and one based on Abraham-type linear solvation energy relationships (LSERs). Their subject was extractables from plastic packaging, but their framework is tailoring extraction strength by varying the water-to-ethanol ratio.

That is exactly what a perfumer is doing, without the name. Swap 95% alcohol for 80% and you are adjusting that mixture's polarity, and every material responds according to its own logP.

What this means in practice

One: perfumer's alcohol at 95% is the most forgiving solvent, and that is why it is the standard.

Two: things start falling out as soon as you add water, and logP sets the order.

If your finished product is 80% ethanol and 20% water, that is a different environment from 95% for benzyl benzoate at logP 4.0. This series touched on diluent polarity in article #84 on TEC; this is its other face. Change the solvent's composition and the most hydrophobic materials in the formula complain first.

Three: "my perfume went cloudy after a few days" has a checkable explanation.

Usually nothing has spoiled; some material was near saturation at your ethanol strength and came out when the temperature dropped. This series wrote another version of the same thing in article #37: what heat dissolves comes back out on cooling. Here there is one more variable. Adding water does it too.

Four: logP tells you which ones will give trouble.

That is the most directly usable sentence here. The few materials in your formula with the highest logP are the ones that drop out first when ethanol strength falls. Among the materials this series has covered:

Material	logP	Risk in low-strength ethanol
Tonalide (AHTN)	5.30	High
Hexyl salicylate	5.70	High
Isobutyl quinoline	3.90	Medium-high
Hexanal	1.80	Low
Guaiacol	1.30	Low
Sotolon	0.40	Very low
TEC	0.10	Very low (it is a diluent)
DPG	−0.60	Very low (same)

(That table uses logP as a ranking index, not a prediction. Whether something actually drops out also depends on how far its concentration in the formula sits from saturation.)

The answer for the poster

• 1:1.5 in 50% alcohol means: make a 50% water-ethanol solution, then one part material to 1.5 parts of that solution. The denominator is the solution, not neat ethanol.
• For making evaluation dilutions, just use the ethanol you have. The first reply was not wrong. Those figures tell you where the floor is; they are not a procedure.
• I could not work out the ethyl alcohol versus alcohol distinction. Across the database it is 10,293 to 71, which looks like source-to-source wording.
• What is worth remembering is the "x% alcohol" part. It tells you how sensitive that material is to ethanol strength, and that bites when you take the concentrate into a finished product.

What this doesn't establish

• The seven materials are everything the database holds, not a sample. r = 0.876 rests on seven points and should not be read as a precise estimate.
• For ranges like 1:8-9 I took the lower value. Taking the higher one shrinks the ratios slightly without changing the ordering.
• Nearly all logP values are estimates (est). This series has already measured that most of the database's physical property fields are estimated.
• Neither cited paper measured fragrance materials. Miyako 2010 measured seven drugs; Egert 2022 measured extractables from plastic packaging. What I cite is the cosolvency framework, not any conclusion about perfume.
• "Adding water causes precipitation" is a mechanistic inference, not an experiment. This article ran no solubility tests.
• The logP risk table is a ranking, not a prediction. Whether something drops out depends on distance from saturation, which I did not compute.
• I do not know TGSC's data sources or dates. One field mixes measured and estimated values from different sources in different formats; this article reads it rather than verifying it.