That "400 hours" for Ambroxan is where its test stopped, not how long it lasted

Someone on r/DIYfragrance asked a very concrete question. He buys pre-formulated oils for Santal 33 and Tobacco Vanille dupes, gets about 80% scent accuracy, and finds that projection and longevity fall short. He listed what his local supplier stocks — Iso E Super, Hedione, Cedramber, Cashmeran, Ambroxan, Galaxolide, and more — and asked which ones, at what percentage, would boost performance without changing the profile too much.

The top reply didn't give him a formula. It said: you can't make a perfume last longer than it already does, and anything you add to increase longevity will also change the smell.

My first thought was that this is answerable with data. I have a database of forty thousand-odd materials with recorded substantivity. So: how strong is Ambroxan, really?

I ran the query three times. All three were wrong, and why they were wrong turned out to be more interesting than the original question.

First pass: the myth appears to collapse

Start with the basis. 1,871 materials have both a substantivity figure and at least one supplier. You can't use all 1,871 — two groups have to come out first. 266 are censored values, recorded as thresholds like "> 400" or "< 1" rather than measurements. Another 246 were evaluated below full strength, or with no concentration recorded at all. Thirteen rows are in both groups, so 1,372 remain, with a median of 76 hours. This is the same basis as the previous article.

Within those 1,372, Iso E Super sits at 172 hours. 462 materials match or beat it — it ranks in the top 33.7%. Top third. Respectable, and nothing more than that.

Ambroxan? The column says 400 hours. That looks formidable.

Had I stopped there, this article would have said: these two aren't special, hundreds of materials outlast them, stop treating them as magic.

And it would have been wrong.

Second pass: availability

Before going further I checked something else — how easy these two are to buy.

21,494 materials in the database have at least one supplier, and the median supplier count is 3. The 90th percentile is 13. The 99th is 57. The overwhelming majority of materials are sold by two or three houses.

Iso E Super: 79 suppliers, top 0.42%. Ambroxan: 61 suppliers, top 0.86%.

These aren't merely easy to get. They're in the top one percent of the entire database for availability.

Which explains why it's always these two names. The list the poster gave wasn't a list he chose — it was whatever his local supplier happened to stock, and that list looks the way it does because these materials are sold everywhere.

So I ran one more check: do easy-to-buy materials actually last longer? Across those 1,372 rows, the rank correlation is Spearman ρ = −0.046. Zero, with a faint negative lean. In this data there is no visible monotonic relationship between supplier count and longevity. (That rules out an obvious monotonic trend; it does not establish that the two are unrelated in every sense.)

At that point I was satisfied. Clean story: these two aren't the strongest, just the most available, and people mistake familiarity for potency.

Except that half of what I'd just calculated was invalid.

Third pass: open the raw string

The last thing I did was check where that tidy 400.0 came from. The raw field reads:

> 400 hour(s) at 10.00 % in dipropylene glycol

Three qualifiers. None of them survive into the numeric column.

">" — this is not a measurement, it's a floor. The test stopped at 400 hours and the material was still there. Nobody knows the real figure; we know only that it exceeds 400.

"at 10.00 %" — measured at one tenth strength. The 1,372 materials I ranked it against are all at 100%.

"in dipropylene glycol" — dissolved in DPG. That is a different substance from propylene glycol (PG), and as you'll see below, both appear in this same data.

That third one is the ironic part. The same top reply on that thread took a swipe at commercial dupe oils: they are "probably already heavily cut with DPG or God knows what." The solvent the community cites as evidence that a product has been watered down is the exact medium this authoritative number was measured in.

And the fatal detail: Ambroxan was never in those 1,372 rows at all. It trips both exclusion rules at once — censored and below full strength. Both times I ranked it against neat materials, I was comparing two different kinds of thing.

My second mistake was assuming the error had a direction

Having found the ranking was invalid, my first instinct was to flip it: if it exhausted a 400-hour test at one tenth concentration, surely it's stronger than I calculated.

That instinct was also wrong, and less obviously so.

DPG doesn't merely dilute the active material to a tenth. It is a different measurement matrix — it affects evaporation, how the strip absorbs, the concentration reaching the vapour phase. And this field records no application quantity, no substrate, no temperature or humidity, no replicate count, and no panel. Without those, I have no standing to say a 400-hour result at one tenth strength "would be longer neat" — exactly as I have no standing to say it would be shorter.

There is only one defensible statement: this number cannot be placed on that ranking at all, in either direction.

"Ambroxan is long-lasting" is probably true. That confidence just doesn't come from this field.

As for the expectation behind "add Ambroxan and it'll perform" — this data can't rule on it, because it mistakes the longevity of one material for the longevity of a finished perfume, and this field never measured the latter. Add 3% Ambroxan and you don't get 400 hours; you get a perfume with 3% more Ambroxan in it.

That top reply put it more firmly: anything that makes it stronger also makes it different. That is an experienced practitioner's judgement, not something this data confirms or refutes — whether an addition produces a perceptible and unacceptable change depends on the formula, the dose, and actually smelling it. It's here because it points the right way, not because I verified it.

How many materials share the number 400

Back to the 1,372 clean rows. 182 of them have a substantivity of exactly 400 hours — 13.3%.

One in seven materials, sharing a single value.

I was going to write that 400 is simply where this test stops. Fact-checking caught it, because nine rows in the clean sample exceed 400 — up to 901 hours, all recorded at 100.00 % with no >. Seventeen rows across the whole database go above it. So 400 is not a hard ceiling; the scale plainly reaches further.

Which makes those 182 rows more awkward, not less: you cannot tell which of them is a real 400-hour measurement and which is a test someone stopped and recorded as 400. In the column they look identical.

Worse, among the 266 censored rows I excluded, a great many look like this:

> 400 hour(s) at 10.00 % in dipropylene glycol
> 400 hour(s) at  3.00 % in propylene glycol

A material that passes 400 hours at 3% dilution and a material recorded at 400 hours neat land in the same cell: 400.0. Which is stronger, I don't know — for the same reason as the previous section: different concentrations, different solvents, no conversion available. What I do know is that the column makes them look identical.

Across the whole basis, 499 of 1,871 rows — 26.7% — carry a qualifier the numeric column throws away. One material in four gives you a number that answers a different question than the one you asked.

So what's the better question

The poster asked what to add to make it stronger. This data can't answer it, because the question assumes longevity is something you can stack, while the field measures one material under test conditions.

The more useful question is: where did this number come from?

At what concentration was it measured? Is it a value or a ceiling? Dissolved in what? Material names mislead — Iso E Super is filed here as patchouli ethanone — a common material name rather than a strict systematic one, while Iso E Super is itself a trade name for a mixture of isomers — and searching the trade name finds nothing — and material numbers mislead in a different way. They don't lie. They discard part of what was known and hand you a clean-looking float.

This is the third time this one field has caught me. First when I tried using boiling point as a stand-in. Second when I failed to exclude censored values — and wrote that I had excluded them when I hadn't. This time, ranking a 10% dilution against neat materials.

All three share a cause: the numeric column looks ready to use, so I used it.