Encyclopedia Chemistry Chemistry Photocatalysis Efficiency2 From Jcost
ARTICLE 2 claims 1 theorem 1 model
Chemistry Photocatalysis Efficiency2 From Jcost
A machine-checked file named for photocatalysis proves only general facts about a cost function, with no definition tying it to solar fuel.
A template, not a result
Photocatalysis uses light to drive chemical reactions, and solar fuel production aims to split water into hydrogen using sunlight. Practical solar-to-hydrogen efficiencies sit in the single digits, typically 1 to 10 percent. The module named PhotocatalysisEfficiency2FromJCost appears to address this topic, but its formal content stays at the level of a template.
The file defines a cost function domainCost m e = Jcost (m / e), where Jcost is a specific mathematical function from the Recognition Science framework. The Lean code proves three general facts: the cost is zero when the two inputs are equal, it is never negative for positive inputs, and a constant called canonicalThreshold, equal to phi minus 1.5, is positive. These statements hold for any positive real numbers m and e; they say nothing about photons, electrons, or chemical bonds.
In Recognition Science, the framework models recognition events through a ledger, a discrete record of such events, and assigns a forced cost to each recognition. The cost function J(x) = (x + 1/x)/2 - 1 is proved unique under five conditions. The photocatalysis module reuses this cost as a template: it sets m and e as inputs but never defines what they mean for a chemical system. The docstring notes the intended direction: efficiency as J(phi)^(1/2) * phi, giving about 0.557, or J(phi) roughly 11.8 percent, consistent with best reported solar-to-hydrogen values. That paragraph is a research note, not a theorem.
The machine-checked library of formal theorems, which verifies each proof, confirms only the template facts. To turn this into a statement about photocatalysis, one would need a definition of m and e in chemical terms, such as photon flux and electron transfer rate. Without that, the module remains a scaffold: the mathematics is sound, but the subject matter is absent.
MODEL domainCost · IndisputableMonolith/Chemistry/PhotocatalysisEfficiency2FromJCost.lean
def domainCost (m e : ℝ) : ℝ := Jcost (m / e)
THEOREM domainCost_at_eq · domainCost_nonneg · canonicalThreshold_pos · IndisputableMonolith/Chemistry/PhotocatalysisEfficiency2FromJCost.lean
theorem domainCost_at_eq (r : ℝ) (h : r ≠ 0) : domainCost r r = 0 := by
unfold domainCost; rw [div_self h]; exact Jcost_unit0
theorem domainCost_nonneg (m e : ℝ) (hm : 0 < m) (he : 0 < e) : 0 ≤ domainCost m e := by
unfold domainCost; exact Jcost_nonneg (div_pos hm he)
theorem canonicalThreshold_pos : 0 < canonicalThreshold := by
unfold canonicalThreshold; linarith [phi_gt_onePointFive]
What this page does not claim
This module does not prove any efficiency value for a real photocatalyst. The framework does not derive the 1-10 percent solar-to-hydrogen range from first principles.
Verify this page
Every tagged claim above names its theorem. To check one yourself rather than trust this page, elaborate the source module with Lean 4 and audit its axiom basis:
$ lake env lean IndisputableMonolith/Chemistry/PhotocatalysisEfficiency2FromJCost.lean
expected axiom basis: [propext, Classical.choice, Quot.sound] (the Lean kernel's standard three; no RS-specific axioms)
A page whose claims cannot be reproduced this way does not ship. In production, every anchor links to the exact declaration in the public source release, and this block carries the build receipt for the page itself.
Derived articles
This page is generated by a question-recursion engine: the questions its answers raise become the next pages. The current agenda, with open targets marked red:
- What physical definitions of m and e would make this template a theorem about photocatalysis?
- How does the framework's cost function relate to thermodynamic efficiency limits in solar fuel production?
MACHINE LAYER · GROUNDED CLAIM TABLE · CLICK TO EXPAND
MODEL domainCost · IndisputableMonolith/Chemistry/PhotocatalysisEfficiency2FromJCost.lean
def domainCost (m e : ℝ) : ℝ := Jcost (m / e)The file defines a cost function domainCost m e = Jcost (m / e), where Jcost is a specific mathematical function from the Recognition Science framework. domainCost · IndisputableMonolith/Chemistry/PhotocatalysisEfficiency2FromJCost.leanTHEOREM domainCost_at_eq · domainCost_nonneg · canonicalThreshold_pos · IndisputableMonolith/Chemistry/PhotocatalysisEfficiency2FromJCost.lean
theorem domainCost_at_eq (r : ℝ) (h : r ≠ 0) : domainCost r r = 0 := by unfold domainCost; rw [div_self h]; exact Jcost_unit0theorem domainCost_nonneg (m e : ℝ) (hm : 0 < m) (he : 0 < e) : 0 ≤ domainCost m e := by unfold domainCost; exact Jcost_nonneg (div_pos hm he)theorem canonicalThreshold_pos : 0 < canonicalThreshold := by unfold canonicalThreshold; linarith [phi_gt_onePointFive]The Lean code proves three general facts: the cost is zero when the two inputs are equal, it is never negative for positive inputs, and a constant called canonicalThreshold, equal to phi minus 1.5, is positive. domainCost_at_eq · domainCost_nonneg · canonicalThreshold_pos · IndisputableMonolith/Chemistry/PhotocatalysisEfficiency2FromJCost.lean