The most common beginner mistake: four materials in one slot

Someone asked r/DIYfragrance what beginners stumble over, and got 31 replies. They opened by confessing one of their own: they mixed up neat civettone with their 10% dilution. Their pets would not come near them, and the smell would not leave the office for three days.

Most of the replies are about attitude — learn the materials before formulating, write everything down, do not buy essential oils from sketchy sellers. All correct, and none of them easily turns into a thing you can check.

The concrete one is in a different thread. Someone described the shape of a beginner formula like this: four musks. Three dry woody ambers. Two hedione-types. Each one made sense when it went in, because each smelled good alone and looked like it might help. But they cover the same ground, so the formula does not get richer — it gets louder and blurrier.

They gave the state a name: olfactory mud.

That claim is checkable. I have 954 public formulas, so I can count how many materials a professional formula puts in one functional slot.

The short version

• Professional formulas put one material in a slot. Of the 410 formulas using any musk, 273 use exactly one; only 9 (0.9%) use four or more.
• Not one formula in 954 stacks four musks alongside three ambers. The shape the beginner described does not occur in these documents.
• The mud has a formal name. Weiss and colleagues showed in 2012 that once equal-intensity components pile up to about 30, different mixtures start smelling the same — they called it olfactory white.
• Worse, from Luckett and colleagues in 2021: adding a material to a complex base was detectable for only one of three esters tested. Your fourth musk is probably not ruining the formula — it is probably not being smelled at all.
• And the argument over whether buying 1 g is a waste: both sides are right. Of 79 common materials, 27 are used at 5% or above (1 g will not finish two 5 g trials) and 13 below 1% (1 g runs 40 trials or more).

About a 10 minute read.

How many go in one slot

I sorted the material names across 954 formulas into three functional slots by keyword — musks, ambers and woody ambers, and jasmonates (the hedione family) — then counted how many each formula puts in each slot.

Slot	Formulas using it	Median when used	Three or more	Four or more
Musk	410 (43.0%)	1	28 (2.9%)	9 (0.9%)
Amber / woody amber	184 (19.3%)	1	8 (0.8%)	1 (0.1%)
Jasmonate	286 (30.0%)	1	1 (0.1%)	0

The full distribution is clearer. For musks:

Musks in the formula	Formulas
0	544
1	273
2	109
3	19
4	6
5	2
8	1

Two thirds of the formulas that use a musk use exactly one. The one with eight musks is the only such formula in the entire corpus.

Jasmonates are more extreme still: 286 formulas use one, 260 of those use exactly one, 25 use two, and exactly one formula in the corpus uses three. With something like hedione, the industry practice is one.

And then the direct check. Formulas with four or more musks and three or more ambers:

Zero.

This is not "never use two"

Do not read the conclusion too far. A hundred and nine formulas use two musks, which is 27% of the ones using any — hardly rare, and we measured that musks co-occur with each other at a high rate to begin with.

The difference is the reason. The line from that thread is worth copying: decide the job before the material. Not "this smells nice, maybe it works here", but "I need lift in the first twenty minutes" or "the base has no contrast", and then pick the one material that does that.

They added a test: if you cannot say in a sentence what a material is doing in there, it usually is not doing anything except taking up room.

One reply matched it exactly: "I definitely am guilty of the too many musks mistake when I first started. I didn't understand how much they can suppress other notes." Suppress is not a metaphor there. It is a named phenomenon in olfactory research.

The mud is called white

Weiss and colleagues, in PNAS in 2012, did this: they selected 86 molecules that span olfactory stimulus space, diluted each to roughly equal intensity, then prepared mixtures containing various numbers of components and asked people to rate how similar pairs of mixtures were.

The result: as the number of non-overlapping, equal-intensity components rose, the mixtures became more similar to each other despite having not a single component in common. At around 30 components, most mixtures smelled alike.

They ran a sharper check too. After participants learned an arbitrarily named 30-component mixture, they readily applied that name to other novel 30-component mixtures spanning stimulus space — but not to mixtures with fewer components, and not to mixtures that did not span the space.

That common percept they called olfactory white, after white light and white noise.

Read the conditions carefully. Olfactory white requires two things: the components must span stimulus space and they must be at equal intensity. A perfume is deliberately neither — it has a lead and a supporting cast, concentrations spanning orders of magnitude, and materials clustered in a few families on purpose.

So mud is not the fate of perfumery. It is what happens when you accidentally push a formula toward those two conditions. Four musks cancelling each other out in the same intensity band is the equal-intensity half.

Rochelle and colleagues, reviewing this literature in the Journal of Agricultural and Food Chemistry in 2018, add another angle: there is evidence that the algorithms the nervous system uses to process odour sensations need input from only three to eight odorants, and that around 250 recognisable odours contribute anything to the aroma of all foods. They also note that in large equal-potency mixtures, a subject's ability to detect individual odorants was vanishingly small.

The one you added may not register at all

Those studies are about too many going blurry. Luckett and colleagues, in Chemical Senses in 2021, asked the earlier question: can you tell when one is added?

They built an odour mixture resembling a generic white wine using modern aroma chemistry, then modified it with three esters common in white wines that vary in chain length and branching, running addition and subtraction discrimination tasks at different concentrations.

The result: only one of the three esters (ethyl propanoate) produced a discriminable mixture.

Two further findings are worth keeping. As the modifier's concentration rose, the difference participants first reported was a change in familiarity, and only later intensity. And sensitivity to addition and subtraction was similar — the authors read this as perceptual stability depending equally on filling in missing information (pattern completion) and disregarding extraneous information.

The bench implication is blunt. Add a twenty-first material to a formula that already has twenty, and the most likely outcome is neither better nor worse but no difference at all. That material consumes stock every batch and adds a chance of error every batch, while contributing below the discrimination threshold.

The thread ended by asking the reverse question: what material did you take out where the formula got better? One answer was safranal. "Low presence in formula but convinced it really helped create a rounder base until I made a trial without it."

That is Luckett's experimental design, run on a kitchen table.

While we're here: is buying 1 g a waste?

The same thread had a small argument. One reply:

"Buying 1g of any material. It's not enough to make anything. 5g and (even 15g) isn't even that much of a price difference so you might as well spend the extra two dollars for 3xs the amount."

The counter:

"With the exception of materials that need to be diluted to 1%, 0.1%, 0.01% or even less (like Geosmin) where 1g is a lifetime supply."

The corpus settles it. Taking the 79 materials appearing in 40 or more formulas, by median dose:

Median dose	Materials	5 g trials from 1 g
≥5%	27	under 4
2–5%	19	4–10
1–2%	20	10–20
<1%	13	over 20

The two ends look like this:

Material	Median dose	1 g → 5 g trials	1 g → 100 g batches
Phenethyl alcohol	10.00%	2	0.1
Bergamot, bergaptene-reduced	10.00%	2	0.1
Galaxolide 50 IPM	9.80%	2	0.1
Beta-damascenone	0.42%	48	2.4
Cis-3-hexenol	0.50%	40	2.0
Rose oxide	0.50%	40	2.0

Both are right about different halves of the palette. One gram of phenethyl alcohol is absurd; one gram of damascenone will outlast your interest in the hobby.

So rewrite the rule as an action: look up the median dose before you order. Buy the large pack above 5%, and the smallest pack below 1%. The frequency and dose article has the full table of 79.

What else the thread got right

Write it down. "This should be Rule #1 of perfumery. If you don't write it down somewhere and have a reference system in place, you won't know what you did later. Everything you do can be instructive but only if you know what it was." A reply added: the only difference between science and screwing around is writing it down.

Label things. The civettone incident is that rule's best advertisement: neat and 10% side by side, one wrong grab, three days of consequences.

Know which denaturant. One reply named a common error as using ethanol denatured with methanol, not knowing that denatured alcohol comes in several kinds. Worth checking what is actually in your bottle.

Think in materials, not notes. One reply put it fully: notes are not really a thing to perfumers; we do not experience a perfume as a series of notes but as a single scent evolving over time. We measured that: the median formula runs 17 materials, and marketing pyramids routinely list more notes than there are materials.

Do not mistake the abstract for the concrete. The longest reply in the mud thread argued that beginners treat longevity, projection, fixatives and the pyramid as if they were physical things, then buy materials and find that the materials do not smell the way they expected. Their advice was to think about stripping down rather than adding.

What this doesn't establish

Slots were assigned by keyword on material names. Twenty keywords for musks, eighteen for ambers, six for jasmonates. Materials in the same family whose names lack those strings are missed, so the counts above are an undercount. That bias only makes "one per slot" more conservative — if the true numbers were higher, my conclusion would weaken, not strengthen.

Olfactory white has strict conditions. Weiss required components at equal intensity spanning stimulus space, and a perfume deliberately satisfies neither. So that figure of 30 cannot be read as "a formula over 30 materials goes muddy". It describes a mechanism, not a ceiling.

Luckett's base was wine, not perfume. Concentration scales, carrier and participant training all differ, so treat the direction rather than the number.

The corpus carries its usual selection bias. Of 954 formulas, 74% carry a patent or source field, and they reflect the habits of those documents. More specifically, these are demonstration formulas whose purpose is to showcase one material — so "one per slot" may come partly from that purpose rather than purely from good taste. I cannot separate the two from the data.

The author of the olfactory-mud post promotes their own app in the same thread, acknowledges the post was AI-assisted, and was challenged on it by another user. I cited it anyway, because the observation is independently checkable and the corpus count above is that independent check. The post itself is not evidence; it is a hypothesis.

References

T. Weiss et al., Perceptual convergence of multi-component mixtures in olfaction implies an olfactory white, PNAS, 109(49), 19959–19964 (2012). PMID 23169632. doi:10.1073/pnas.1208110109

C. R. Luckett et al., Discrimination of Complex Odor Mixtures: A Study Using Wine Aroma Models, Chemical Senses, 46, bjaa079 (2021). PMID 33347541. doi:10.1093/chemse/bjaa079

M. M. Rochelle, G. J. Prévost, T. E. Acree, Computing Odor Images, Journal of Agricultural and Food Chemistry, 66(10), 2219–2225 (2018). PMID 28285523. doi:10.1021/acs.jafc.6b05573

Related: Notes are not materials, What pairs with what, Look up how many formulas it appears in, How do you afford this hobby.