Meta-Analysis3 min read

Products Survive, Compounds Die: What 120 Invention Candidates Taught Us

After evaluating 120+ invention candidates across 5 rounds of a structured generate-critique-disprove-audit cycle, we found that service/API ideas survived at ~27% while compound-level ideas survived at 0%. Every compound promotion was killed as prior art. The anti-portfolio reveals systematic patterns in what kills ideas.

LG
Lattice Graph Research

Products Survive, Compounds Die: What 120 Invention Candidates Taught Us

The Numbers

We ran five rounds of a structured invention discovery loop — generate, critique, disprove, audit, learn, regenerate — evaluating 120+ candidates for commercially viable materials-science products. The cumulative kill rate was approximately 89%.

RoundCandidatesSurvivorsKill Rate
R1251156%
R227389%
R4202 confirmed + 1 second-look85%
R5480 clean (2 wounded)100%
Total120+~16~87%

The Master Pattern: Products vs. Compounds

The single most important finding: service and API ideas survived at roughly 27%, while compound-level ideas survived at exactly 0%. All four compound promotions were killed because we chose well-published optima — the best-studied formulas in the literature are, by definition, already claimed.

Patentable compositions live in the gaps between published data points, not at the optima. Selecting the best-studied formula guarantees a prior art kill.

The Anti-Portfolio: 14 Named Kills

Killed IdeaKill Reason
Mixed-Electrolyte Space-Charge SSEUnproven mechanism, single unreplicated study, multi-billion manufacturing gap
PGM-Free HER Catalysts by DurabilityPt cathode cost already low ($200-500/kW); 200h vs 80,000h durability gap; real bottleneck is OER not HER
Battery Degradation from FormationVoltaiq (Siemens), Liminal, Monolith already dominate
Patent-Gated IP PortfolioDFT-only patents unenforceable under 35 U.S.C. 112 (requires experimental data)
Electrolyte Formulation OptimizerAionics $10.6M, 4-year head start, CMU IP
Perovskite Degradation OracleNo 25-year ground truth; 1000h→25yr extrapolation unreasonable
Thermoelectric ZT ScreeningAlphabet Energy $52.7M deadpooled; prediction-to-experiment gap
Materials Dark MatterGNoME already did this at Google scale; 380K structures = prior art
Coolant Compatibility OracleDecision-grade data is proprietary wet-lab; NIST TDE already reconciles what's public
Na-cathode compositionNo FTO (Tiamat exclusive NVPF license); a composition is a paper, not a company
Patent-Clear LMFP Multi-Dopant FinderDoped/fractional targets return 0 rows in warehouse; real fight is coating/process IP
SIB Patent-Thicket Heat MapPatentsView feed deprecated (HTTP 410); incumbents sell it
PFAS-Exposure Liability MapCrowded funded PFAS-compliance suites (IntegrityNext, 3E, Source Intelligence)
Spectroscopy-to-Structure InversionDiffractGPT free web app; Bruker/JEOL ship products; 10-100x overpriced

Systemic Kill Patterns

  • Named funded competitors are the sharpest kill. If someone with $10M+ and a 3-year head start already occupies the space, late entry is structurally dead.
  • Wrong figure of merit kills instantly. PGM-free HER catalysts failed because the real bottleneck is OER, not HER — and Pt cathode cost is already below $500/kW.
  • "Important" problems are crowded problems. PFAS and REE clusters scored 96-97 priority and produced 0/11 survivors.
  • Prior deadpools in the space are strong negative signal. Alphabet Energy's $52.7M deadpool tells you more than any market analysis.
  • A predictor whose validation data accrues at service-life speed is a lab business, not a data business. Perovskite degradation needs 25 years of ground truth. You don't have 25 years.

What We Changed

After these findings, we stopped generating compound-level candidates entirely and focused on service/API ideas where the defensible unit is the join — the cross-source data fusion — not the composition. We also added a mandatory prior-art pre-check before any compound promotion, and a forcing-function budget check before pursuing any high-priority domain.

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