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Rh 1,4-Conjugate

Rh 1,4-conjugate addition is the thesis-era Rh analogue of the Pd composed-force-field systems: a base MM3 field plus OPT overlay that does not transfer cleanly under our engine.

Scope

  • Type: Transition state (Rh-catalyzed 1,4-conjugate addition)
  • Molecules: 10 TS structures
  • Parameters: 488 (OPT substructure: 24 bonds, 46 angles, 348 torsions)
  • QM reference: B3LYP-D3/6-31G(d)

Publication

Property Value
Thesis Wahlers, J. Ph.D. Dissertation, University of Notre Dame, 2022, Ch. 6
DOI —
System Rh-catalyzed 1,4-conjugate addition
Training set 10 transition-state structures
Engine MacroModel MM3*

What the thesis reports

What the original Q2MM workflow fitted

The Chapter 6 Rh systems continue the same Q2MM strategy: a MacroModel MM3* transition-state force field fit against multiple data types, not just eigenvalues.1

  • Structural targets
  • Hessian/eigenvalue targets
  • MacroModel MM3* optimization
  • External selectivity validation on literature examples

Reported outcomes

Wahlers reports separate internal-fit ranges for two ligand classes:1

  • Bisphosphine systems: slopes 0.94–1.01, R² 0.91–0.99
  • Diene systems: slopes 1.0–1.07, R² 0.92–0.99
  • Bisphosphine selectivity validation: MUE 4.1 kJ/mol, R² = 0.64, 67 structures
  • Diene selectivity validation: MUE 5.3 kJ/mol, R² = 0.37, 69 structures

Our reproduction

Metric Value
Overall eigenvalue R² -3.90
Per-molecule R² range all negative
Positive R² values 0 / 10
Aggregate frequency RMSD 645.7 cm⁻¹ (per-molecule avg: 228.3)

What this means: A negative R² means our engine's reproduction of the published eigenspectrum is worse than simply predicting the average — a complete failure of cross-engine transfer, not a small miss.

Negative across the full training set

All per-molecule R² values are negative. Under our engine, the reproduced eigenspectrum is not preserving the literature fit at all.

Benchmark results

Ratio check failed — optimization skipped

The JaxLoss/ObjectiveFunction ratio is out of the [0.85, 1.15] tolerance (most recent regeneration: ratio ≈ 4.6 × 10³, ratio_status = "out_of_band"). JaxLoss is not a reliable surrogate for this system at the Seminario starting point.

Metric Value
Ratio check ≈ 4.6 × 10³ (out_of_band)
Initial ObjectiveFunction score 2.21 × 10⁷
Optimization Skipped

Why it fails: The Seminario starting FF has deeply negative R² for all 10 molecules (bond_length R² ≈ −58, bond_angle R² ≈ −1.3, eig_diagonal R² ≈ −4.8). The MM PES that comes out of the inverted-Hessian Seminario projection is so far from the QM geometries that the inner geometry minimization inside JaxLoss lands in unphysical local minima — the resulting JaxLoss value is many orders of magnitude larger than the ObjectiveFunction.

This is not a JaxLoss bug; the ratio gate is correctly identifying that the surrogate is unreliable for this parameter regime. The root cause is the poor starting FF — the published Wahlers force field relies on a base MM3 layer that does not transfer cleanly under JaxEngine, and Seminario alone cannot recover from that.

See Optimizer Comparison for the cross-system comparison. Raw numbers are in the convergence baseline in ericchansen/q2mm-data, with full provenance (q2mm git SHA, JAX/OpenMM device, ratio_tol, timestamp).

Comparison and gap analysis

Comparison

The thesis reports respectable-to-strong internal fits across both ligand classes. Our reproduction does not transfer that quality.

As with the Pd systems, this is a composed-force-field transfer problem. The Rh 1,4-conjugate TSFF combines a base MM3 field with an OPT overlay, and that composition is sensitive to engine-specific semantics.

The optimizer story is mixed but still informative: L-BFGS achieves 331.3 cm⁻¹, and Optax Adam reaches 307.0 cm⁻¹, yet the reproduced eigenspectrum remains negative across the entire training set. Better optimizer robustness helps the benchmark objective; it does not remove the transfer gap.

Gap analysis

To close the gap for Rh 1,4-conjugate addition, we would need:

  1. A verified composition path for the base MM3 field plus OPT overlay.
  2. Closer parity for Rh-specific MM3* behavior at the metal center.
  3. A re-fit against the original multi-target Q2MM objective only after the composed starting field behaves as intended.

The negative R² reflects a real transfer gap in the composed FF workflow.

Reproduce

python -m q2mm.diagnostics.cli --system rh-conjugate --backend jax --optimizer optax-adam

Raw data: q2mm-data/benchmarks/rh-1,4-conjugate-addition/.

  1. Wahlers, J. Ph.D. Dissertation, University of Notre Dame, 2022, Ch. 6. The chapter-level ranges are also summarized in Published FF Validation. ↩↩