Laser-Enhanced Contact Optimization in Silicon Photovoltaics: Mechanisms, Reliability, and Predictive Process Design

TL;DR

This paper reviews laser-enhanced contact optimization (LECO) in silicon solar cells, focusing on mechanisms, reliability, and a predictive process design framework to improve efficiency and stability.

Contribution

It introduces a coupled multiphysics modeling framework and workflow for reliability-aware, scalable LECO process optimization in silicon photovoltaics.

Findings

LECO reduces contact resistivity and recombination, improving device performance.

The framework separates stable optimization from marginal activation, enhancing process robustness.

Insights into current localization and diffusion barriers improve stability margins.

Abstract

Laser-enhanced contact optimization (LECO) has emerged as an important method for simultaneously reducing contact resistivity and metallization-induced recombination in advanced crystalline silicon solar cells, thereby enabling concurrent gains in fill factor and open-circuit voltage, particularly in TOPCon devices. However, broader industrial transferability remains constrained by the need to preserve these gains within a narrow process window and by unresolved, architecture-dependent questions regarding the kinetic stability of some LECO-modified interfaces. LECO is therefore examined in this review as a coupled multiphysics process that links localized electrothermal activation and microstructural evolution to device-level electrical signatures through an instantaneous regime map and a reliability classification based on time-dependent drift. A predictive workflow is outlined that couples transient electrothermal modeling with reduced state metrics, including effective diffusion depth and local areal energy density, and propagates calibrated thresholds across the recipe space. The framework separates stable optimization from marginal activation and latent damage, while explaining why fine-line scaling and copper-containing contact stacks can tighten stability margins through current localization and diffusion-barrier constraints. These insights provide a basis for reliability-aware process-window design and future digital-twin-assisted optimization of LECO for scalable, high-efficiency silicon photovoltaics.