Inputs
Enter baseline and templated values. Use weights to match your experimental priorities.
Example data table
These values illustrate a moderate-to-strong template effect. Replace them with your experimental measurements.
| Scenario | k (1/s) | Yield (%) | Ea (kJ/mol) | Selectivity (%) |
|---|---|---|---|---|
| Baseline | 0.010 | 60 | 70 | 55 |
| Templated | 0.040 | 78 | 62 | 72 |
Formula used
- Rate enhancement: ER = kT / k0
- Yield gain (%): GY = ((YT − Y0) / Y0) × 100
- Energy reduction: ΔEa = Ea0 − EaT
- Arrhenius ratio: kT/k0 ≈ exp(ΔEa×1000 / (R·T))
- Consistency: C = min(pred, obs) / max(pred, obs) (0–1)
- Component scores (0–100): derived from ln ratio, gains, and ΔEa, then clamped.
- Index: TEI = Σ(wi·scorei) with normalized weights.
The scoring is designed for comparison across experiments rather than absolute kinetics. Adjust weights to reflect what “better” means in your workflow.
How to use this calculator
- Measure or estimate baseline values (k0, yield, activation energy).
- Run the templated condition and record kT, yield, and activation energy.
- Enter temperature for the Arrhenius comparison and consistency score.
- Enable selectivity if you track product distribution or enantiomeric outcomes.
- Set weights to emphasize your priority metrics, then click Estimate.
- Use CSV for lab logs and PDF for reports or sharing.
Why Template Effects Matter
Molecular templates can preorganize reactive partners, increasing effective molarity and lowering entropic penalties. In practice, chemists often see higher apparent rate constants, improved yields, and cleaner product distributions when a template controls geometry. This estimator combines those signals to summarize whether templating provides a net advantage for a specific transformation and temperature.
Choosing Comparable Measurements
For rate, use k values derived from the same kinetic model and units, such as pseudo-first-order fits or initial-rate methods. Keep baseline and templated runs at matched solvent, catalyst loading, ionic strength, and mixing. Record yield using the same quantitation method, preferably calibrated NMR or GC with an internal standard. Activation energies should be extracted from consistent temperature series, not single-point comparisons.
Interpreting the Template Effect Index
The index ranges from 0 to 100 and is built from weighted component scores for rate enhancement, yield gain, activation-energy reduction, and optional selectivity improvement. Weights are normalized so the overall scale remains stable. A strong score typically reflects multi-metric agreement: faster kinetics, higher conversion to desired product, and lower energetic barriers. A moderate score often indicates one dominant benefit with smaller tradeoffs.
Using Arrhenius Consistency Wisely
The Arrhenius ratio estimates the expected kT/k0 from the activation-energy difference at the chosen temperature. The consistency metric compares the predicted and observed ratios on a 0–1 scale. Values near 1 suggest your kinetic acceleration is compatible with the measured ΔEa. Lower values can flag data issues, mechanism changes, or template effects dominated by preorganization rather than barrier lowering.
Reporting and Sharing Results
Use the component table to document which metric drives the improvement and why the chosen weights match project goals. For screening, keep weights fixed across a series to rank templates fairly. Export CSV for notebooks and audit trails, and generate a PDF summary for team reviews. Always report temperature and methods alongside TEI to support reproducible decisions. If selectivity is enabled, enter regioselectivity, ee, or desired/total product. The calculator treats improvements symmetrically with yield, helping compare templates that trade speed for control. When baseline values are near zero, interpret percent gains cautiously in practice.
FAQs
What does the Template Effect Index represent?
It is a 0–100 composite score that summarizes improvements in rate, yield, activation-energy reduction, and optional selectivity, using your chosen weights. Higher values indicate stronger overall benefits under templated conditions.
Why are weights normalized automatically?
Normalization keeps the index on a stable 0–100 scale even if you change individual weights. This helps you compare different experiments without inflating the score by entering larger numbers.
When should I enable selectivity?
Enable it when product control matters, such as regioselectivity, enantiomeric excess, or desired/total product. If you only care about speed and yield, leave it off to avoid diluting the index.
How should I interpret the Arrhenius consistency value?
Consistency compares the observed rate ratio with the ratio predicted from the activation-energy difference at your temperature. Values near 1 mean strong agreement; lower values can suggest mechanism changes, noisy fits, or non-energetic templating effects.
Can I use this for different kinetic orders?
Yes, as long as k0 and kT are comparable outputs from the same model and units. For example, compare two pseudo-first-order constants, not a second-order constant against a first-order constant.
What if my baseline yield is very small?
Percent gain can look extreme when the baseline is near zero. Consider also the absolute yield difference and rely more on rate and energy components, or adjust weights to reflect your decision criteria.