Two-dimensional organic-inorganic hybrid perovskites (OIHPs) hold great promise for energy conversion applications, yet their potential is limited by the scarcity of antiferroelectric materials. Our machine learning accelerated molecular dynamics simulations predict intricate phase transitions in ${\left(\mathrm{PMA}\right)}_2\mathrm{Pb}{\mathrm{Br}}_4$, progressing from a wavelike ferroelectric (FE) to a normal FE, and ultimately to an antiferroelectric (AFE) phase as the temperature increases. Correlation analyses indicate that the FE-AFE transition is primarily driven by the structural transformation of the inorganic framework, from distorted to undistorted octahedra, which influences the molecular orientation through steric effects, while maintaining the stacking pattern of benzylammonium (PMA) molecules. The hydrogen bonds connecting the organic and inorganic components are essential for stabilizing both FE and AFE phases. Furthermore, an increased number of hydrogen bonds induces the unique wavelike pattern observed at low temperatures. This work offers insights into optimizing and designing FE and AFE phases in OIHPs by tuning steric effects and hydrogen bonds.

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• Antiferroelectricity
• Ferroelectricity
• Density functional theory
• Machine learning