Inverse Design of Hybrid Organic-Inorganic Perovskites with Suitable Bandgaps via Proactive Searching Progress.

ABSTRACT: Hybrid organic-inorganic perovskites (HOIPs) have shown the encouraging development in solar cells that have achieved excellent device performance. One of the most important issues has been focused on finding Pb-free candidates with suitable bandgaps, which could accelerate the commercialization of environmentally friendly HOIP-based cells. Herein, we propose a new inverse design method, proactive searching progress (PSP), to efficiently discover potential HOIPs from universal chemical space by combining machine learning (ML) techniques. Compared to the pioneering work on this topic, we carried out our ML study based on 1201 collected HOIP samples with experimental bandgaps rather than theoretical properties. On the basis of 25 selected features, a weighted voting regressor ML model was co

SUBMITTER: Lu T 

PROVIDER: S-EPMC9245129 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature