4 papers
Data-driven materials science: status, challenges and perspectives
Lauri Himanen, Amber Geurts, Adam S. Foster +1
Data-driven science is heralded as a new paradigm in materials science. In this field, data is the new resource, and knowledge is extracted from materials data sets that are too bi…
Database-driven high-throughput study for hybrid perovskite coating materials
Azimatu Seidu, Lauri Himanen, Jingrui Li +1
We developed a high-throughput screening scheme to acquire candidate coating materials for hybrid perovskites. From more than 1.8 million entries of an inorganic compound database,…
Chemical diversity in molecular orbital energy predictions with kernel ridge regression
Annika Stuke, Milica Todorović, Matthias Rupp +4
Instant machine learning predictions of molecular properties are desirable for materials design, but the predictive power of the methodology is mainly tested on well-known benchmar…
Understanding doped perovskite ferroelectrics with defective dipole model
J. Liu, L. Jin, Z. Jiang +6
While doping is widely used for tuning physical properties of perovskites in experiments, it remains a challenge to exactly know how doping achieves the desired effects. Here, we p…