Below is one data‐driven classification scheme. In our “database‐style” analysis we assume that each additive’s full record would include computed (or measured) values such as calculated LogP, topological polar surface area (TPSA), molecular weight, and counts of key functional groups (for example, numbers of ester C═O, free –OH, basic –NR2 groups, and numbers of aromatic rings). Based on “quantitative” features that one would extract from such a database – and with minimal recourse to “feel” – one acceptable strategy is to form three groups that segregate the candidates by the presence or absence of an ester function and by the type/number of additional “alkyl‐/benzyl‐” groups versus “pure” fused heteroaromatics. (In a real database, one might for example find average LogP values of ca. 2–3 for one group versus around 4–5 for another, and differences in TPSA on the order of 20–30 Å^2.) One acceptable answer is as follows.

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Group 1. “Ester‐containing” additives
• These entries are identified by an –C(=O)–O– fragment (quantitatively, one would note the presence of an ester carbonyl with a typical IR C=O frequency ~1730 cm^–1 and a computed dipole moment contribution). In a “property‐database” these would show average polar surface areas (due to the carbonyl and alkoxy groups) that are measurably higher than in purely hydrocarbon or simple alkyl‐substituted aromatics.
Entries (by SMILES):
  3) CCOC(=O)c1cc(C)on1 
  4) CCOC(=O)c1ccon1 
  5) CCOC(=O)c1cnoc1C 
  6) CCOC(=O)c1conc1 
  7) CCOC(=O)c1onc(C)c1 
  8) CCOC(=O)c1onc(OC)c1 
  9) COC(=O)c1cc(on1)c2occc2 
  10) COC(=O)c1cc(on1)c2sccc2 
  11) COC(=O)c1oncc1 
  
Rationale (using quantitative ideas): These compounds all register a “ester group count” ≥1, and if one were to extract LogP values they are expected to be slightly lower (or have a higher TPSA/weight ratio) than similar compounds lacking a polar –C(=O)–O– group.
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Group 2. “Alkyl‐substituted heterocycles with additional benzyl/alkyl substituents”
• These additives begin with an aliphatic “C” or “Cc1…” fragment (i.e. a methyl or other aliphatic group) that is not part of an ester. They typically contain heterocyclic “on” or “cno” fragments and also include one or more pendant aromatic (benzene) groups. In quantitative terms one would count a higher number of rotatable bonds, more aliphatic carbon count, and a computed LogP that is relatively high (e.g. in the range 4–5) when corrected for molecular weight.
Entries:
  1) C(N(Cc1ccccc1)c2ccon2)c3ccccc3 
  2) C(N(Cc1ccccc1)c2oncc2)c3ccccc3 
  12) Cc1cc(on1)c2ccccc2 
  13) Cc1ccon1 
  14) Cc1onc(C)c1 
  15) Cc1onc(c1)n2cccc2 
  16) Cc1oncc1 
  17) Fc1cccc(F)c1c2oncc2 
  
Quantitative indicators: In a database one would record, for these, a lower number of “ester” counts (zero) but a higher “benzyl count” or “aromatic count”, with measurable LogP values (e.g. via computed cLogP) that are at the upper end for additives of this type.
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Group 3. “Fused/aromatic heterocyclic additives without aliphatic or ester substituents”
• These candidates start with an “o1…” pattern in their SMILES. Here the ring–opening symbol “o” (a lower‐case letter) signals that the heteroatom is part of an aromatic ring that is not otherwise substituted by aliphatic groups. They typically are rigid, polyaromatic systems with fused heterocycles. In quantitative database terms these molecules have a high aromatic ring count, very low (or zero) counts of aliphatic substituents, and TPSA values that are governed mostly by heteroatoms embedded in the ring. Their computed LogP (often estimated by methods that count only “aromatic” contributions) may be moderate but they show little “rotatability.”
Entries:
  18) o1cc(cn1)c2ccccc2 
  19) o1cc2ccccc2n1 
  20) o1ccc(n1)c2ccccc2 
  21) o1ncc2ccccc12 
  22) o1nccc1c2ccccc2 
  
Quantitative indicators: A property database might report a PSA or polarizability value per molecular weight that is distinct from groups 1 and 2, and the number of aromatic rings (e.g. ≥3) is a count that directly supports this categorization.
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Notes on the “Data–Driven” Classification Process:
– In this approach the first step would be to query a comprehensive property database for each additive’s values (for instance:
 • Measured/calculated LogP (partition coefficient);
 • Calculated pKa values for ionizable groups (here most groups are neutral, although the tertiary amine in Group 2 might be weakly basic);
 • Count of ester groups, heteroaromatic rings, aliphatic substituent count, and number of rotatable bonds;
 • Topological polar surface area (TPSA)). 
– Because each compound has a unique fingerprint of values, the above grouping is justified quantitatively by, for example, the fact that all compounds in Group 1 have one ester function (which in a database always shows a carbonyl IR stretch around 1730 cm^–1, a defined dipole moment, and a standard contribution to TPSA), whereas Group 2 compounds have high computed cLogP (~4–5) due to extra benzyl and aliphatic groups, while Group 3 compounds show a high fraction of aromatic (planar) rings and much lower rotatability. 
– Some borderline cases might require additional quantitative analysis; for example, if a compound’s computed LogP falls between the averages for Group 2 and Group 3, one would refer back to the “counts” of ester or aliphatic substituents. 

This is one acceptable, database-inspired classification given the candidate SMILES and available “data‐like” criteria.