Quantifying transfer coefficients in battery recycling routes for material flow analysis: current state and future...

The growing volume of end-of-life batteries in the European Union necessitates robust quantification of secondary raw material recovery potential to support material flow analysis and policy evaluation. However, empirical data on recycling process performance remain limited. Transfer coefficients (TCs) quantify the fraction of a material transferred from input into a specific output stream at each process step. The product of step-wise TCs along a route determines recovery for each element and links process-level performance to system-level recovery outcomes. This study compiles route-specific TCs for five lithium-ion battery recycling routes encompassing pyrometallurgical, hydrometallurgical, mechanical, and direct recycling, alongside established processes for zinc-based, nickel-based, and lead-acid batteries. TCs compiled from patents, peer-reviewed literature, and industry data were integrated into a Python-based recovery model, generating 36,358 scenario-ready values from 2010 to 2050. Two scenarios are analysed: business-as-usual, with technological stagnation and continued black mass export, and recovery scenario aligned with EU Battery Regulation targets. A gap analysis reveals highly element-specific challenges. While TCs for cobalt, nickel, and copper already approach regulatory thresholds, lithium recovery from pyrometallurgy-based routes are far below the regulatory target. Non-regulated materials such as graphite, manganese, and phosphorus show zero or marginal recovery, a structural blind spot in the regulatory framework. A structural decomposition shows that process-level efficiency is the dominant driver of system-wide recovery for most elements, whereas route composition acts as a secondary and often counteractive effect. The publicly available TC dataset provides a transparent basis for secondary supply estimation while highlighting uncertainties requiring industrial-scale validation and chemistry-differentiated parameterisation.