Data-Driven Design of Electroactive Spacer Molecules to Tune Charge Carrier Dynamics in Layered Halide Perovskite Heterostructures
Source abstract
Abstract
Crafting rational heterojunctions with nanostructured materials is instrumental in fostering effective interfacial charge separation and transport for optoelectronics. Layered halide perovskites (LHPs) that form heterojunctions between organic spacer molecules and inorganic metal halide layers exhibit tunable photophysics owing to their customizable band alignment. However, controlling photogenerated carrier dynamics by strategically designing layered perovskite heterojunctions remains largely unexplored. We combine a data-driven approach with time-domain density functional theory (TD-DFT) and non-adiabatic molecular dynamics (NAMD) to screen and select electronically active spacer dications (A′) that introduce a type-II heterojunction in the lead iodide-based Dion–Jacobson phase LHPs. The composition–structure–electronic property correlations reveal that the number of nitrogens in aromatic heterocycles is the key factor in designing electron-accepting spacers in these perovskites. The detailed atomistic simulations validate the design strategy further by modeling (A′)PbI 4 perovskites, which incorporate three different screened electroactive A′ spacers. The computed excited charge carrier dynamics illustrate the phonon-mediated ultrafast interfacial electron transfer from the inorganic conduction band edge to the lower-lying unoccupied orbitals of spacers, exhibiting photoluminescence quenching in these (A′)PbI 4 perovskites. The spatially separated electrons and holes at the type-II heterojunction interface prolong the excited charge carrier lifetime, boosting the carrier transport and exciton dynamics. Our work illustrates a robust in silico approach for designing LHPs with exciting optoelectronic properties originating from their fine-tuned heterojunctions.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Perovskite Materials and Applications · Machine Learning in Materials Science · Electronic and Structural Properties of Oxides
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Chemistry, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi 110016, India
Department of Materials Science and Engineering, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi 110016, India
Funding
Science and Engineering Research Board · Indian Institute of Technology Delhi · Ministry of Education, India · Human Resource Development Group
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