Performance Reconstruction of Eco-Friendly Gas Mixtures for Improved Resistive Plate Chambers at GIF++ Using Geant4

TL;DR

This work develops a macroscopic reconstruction to predict iRPC performance under GIF++ irradiation by translating Geant4-observed energy deposition into a field-dependent induced charge via an effective gain $G(E)$, anchored to the standard CMS mixture to fix the absolute scale. By extracting macroscopic Townsend parameters $(A,B)$ from the STD reference, the framework propagates to four alternative gas mixtures (two CO$_2$-based and two eco-friendly HFO/CO$_2$ blends) to generate efficiency curves and working points without invoking microscopic transport. The approach yields consistent ordering of mixtures, with eco-friendly variants requiring higher fields to reach the same efficiency, and demonstrates internal consistency between $(A,B)$ and the derived working points. Overall, the method provides a predictive tool for ranking and selecting gas mixtures for iRPCs, reducing experimental overhead while enabling rapid assessment of eco-friendly candidates.

Abstract

A macroscopic reconstruction is developed to infer iRPC performance using Geant4 observables and one experimental anchor. The Geant4 energy deposition is used to estimate the primary ionization yield, while the efficiency turn-on is modeled through an induced-charge description encoded in an effective gain G(E). The absolute scale is fixed by calibrating the standard CMS mixture to its GIF++ efficiency curve and extracting macroscopic Townsend parameters (A,B). The same procedure is propagated to four alternative mixtures, including two HFO and CO2 eco-friendly blends, to reconstruct efficiency curves and working points, enabling detector mixture screening without microscopic transport inputs.

Figures (7)

• Figure 1: Schematic geometry of the double gap iRPC simulated in this work.
• Figure 2: Macroscopic reconstruction pipeline. The experimental efficiency of the STD mixture at GIF++ is converted into a field-dependent sensitivity $S_{\mathrm{STD}}(E)$ and then into the absolute gain and macroscopic parameters $G_{\mathrm{STD}}(E)$ and $(A_{\mathrm{STD}},B_{\mathrm{STD}})$. Combined with the Geant4 primary ionization yields $\langle N_0^{\mathrm{mix}}(E)\rangle$, the framework reconstructs $G_{\mathrm{mix}}(E)$, $S_{\mathrm{mix}}(E)$ and the efficiency curves $\varepsilon_{\mathrm{mix}}(HV)$.
• Figure 3: Reconstructed effective gain $G_{\mathrm{STD}}(E)$ for the standard CMS gas mixture, obtained from the experimental efficiency curve measured at GIF++ (left). Townsend Fit representation for the STD mixture (right).
• Figure 4: Reconstructed effective gain $G_{\mathrm{eff}}(E)$ for all gas mixtures.
• Figure 5: Reconstructed muon response for all gas mixtures. (left) Sensitivity $S_\mu(E)$ as a function of the effective electric field. (right) Efficiency $\varepsilon_\mu(HV)$ as a function of the applied high voltage. In both panels, the dashed horizontal line marks the 95% level used to define the working point.