Uniform Monolithic Perovskite Films for Scalable Modules: Anti‐Solvent‐Free Crystallization via Seed Priming and Vacuum Processing

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Authors: Sun‐Ju Kim, Seungyeon Hong, Dong‐Geon Kwun, Yu Jin Kang, Thanh‐Danh Nguyen, In Hwa Cho, Sung Hun Lee, Gye Woon Choi, Geun‐young Yoon, Siyeon Seo, Weifan Luo, Ghewa AlSabeh
+15 more Hwang Dy, Min Jun Choi, JONG‐MIN KIM, Olzhas Kurman, Dong‐Ok Kim, Dong‐Ok Kim, Sohyun Park, Jong H. Kim, O‐Pil Kwon, Jovana V. Milić, Michaël Grätzel, Do‐Hyung Kim, Do‐Hyung Kim, Hyo Jung Kim, Ji‐Youn Seo
Cited by: 1
References: 114

Abstract

ABSTRACT Scaling high‐efficiency perovskite solar cells into commercially viable modules remains challenging. Here, we demonstrate a seed‐primed, vacuum‐assisted crystallization (S‐VAC) strategy that links oleylamine‐induced α‐phase nanocrystal seeding to vacuum‐driven vertical crystal growth. Complementary in situ characterization, including time‐resolved GIWAXS, solution‐state NMR, and dynamic light scattering (DLS), reveals that oleylamine forms uniform ≈1.7 nm α‐phase seeds in the precursor solution via hydrogen bonding with FA + cations and steric stabilization. These seeds prime the substrate for controlled, single‐crystal‐like vertical growth under low‐pressure vacuum processing, thereby eliminating the need for toxic antisolvents. The resulting monolithic perovskite films exhibit strong (100) texture and high uniformity across 15 × 15 cm 2 substrates. Using S‐VAC, we achieve a power conversion efficiency (PCE) of 23.2% for 2.5 × 2.5 cm 2 devices and a certified efficiency of 19.1% for 15 × 15 cm 2 mini‐modules. Encapsulated modules retain >94% of their initial efficiency after one year of continuous outdoor operation. By establishing a molecular‐level basis for oleylamine‐assisted seed formation and demonstrating scalable, antisolvent‐free processing, this work advances seed‐assisted crystallization and supports the practical commercialization of robust and sustainable perovskite photovoltaics.

Fields of Study & Subjects

Perovskite Materials and Applications Machine Learning in Materials Science TiO2 Photocatalysis and Solar Cells

Publication details

Journal / source
Advanced Energy Materials
Publisher
Wiley
Volume
16
Issue
12
Publication date
21 January 2026
Language
EN