A Physical Data Fusion Approach to Optimize Compositional Stability of Halide Perovskites
2020
Compositional search within multinary
perovskites employing brute force synthesis are prohibitively expensive in
large chemical spaces. To identify the most stable multi-cation lead iodide
perovskites containing Cs, formamidinium (FA) and methylammonium (MA), we fuse
results from density functional theory (DFT) calculations and in situ thin-film degradation test
within an end-to-end machine learning (ML) algorithm to inform the
compositional optimization of CsxMAyFA1-x-yPbI3.
We integrate phase thermodynamics modelling as a probabilistic constraint in a Bayesian optimization (BO) loop,
which effectively guides the experimental search while considering both
structural and environmental stability. After three optimization rounds and
only sampling 1.8% of the compositional space, we identify thin-film
compositions centred at Cs0.17MA0.03FA0.80PbI3
that achieve a 3x delay in macroscopic degradation onset under elevated
temperature, humidity, and light compared with the more complex
state-of-the-art Cs0.05(MA0.17FA0.83)0.95Pb(I0.83Br0.17)3.
We find up to 8% of MA can be incorporated into the perovskite structure before
stability is significantly compromised. Cs is beneficial at low concentrations,
however, beyond 17% is found to contribute to reduced stability. Synchrotron-based grazing-incidence
wide-angle X-ray scattering (GIWAXS) further validates that the interplay of
chemical decomposition and phase separation governs the non-linear instability
landscape of this compositional space. We reveal the detrimental role of the ẟ-CsPbI3
minority phase in accelerating degradation and it can be kinetically suppressed
by co-optimising Cs and MA content, providing insights into simplifying
perovskite compositions for further environmental stability enhancement. Our
approach realizes the effectiveness of ML-enabled data fusion in achieving a
holistic, efficient, and physics-informed experimentation for multinary
systems, potentially generalisable to materials search in the vast structural and
alloyed spaces beyond halide perovskites.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
0
References
1
Citations
NaN
KQI