Skip to content
#diffusion models Open access

High-throughput Materials-to-Device Discovery of Lead-free Double Perovskites Beyond Radiative-limit Metrics

Oct 2026 · JACS Au · 99 references
Perovskite Materials and Applications

Abstract

Abstract Metal halide perovskite solar cells (PSCs) are leading candidates for next-generation photovoltaics, yet their instability and lead toxicity motivate environmentally benign alternatives. Lead-free double perovskites offer improved structural robustness but often exhibit weak near-band-edge absorption and modest efficiencies, making it crucial to identify compositions and phases that balance stability with photovoltaic performance. Here we assemble an initial enumerated phase-diverse library of 31,276 structure–composition entries spanning six symmetry-distinct cubic, tetragonal, and monoclinic configurations and establish a device-guided multiscale workflow for realistic performance evaluation. This framework combines symmetry-aware optical screening, finite-temperature structural-retention assessment, multiscale parameter transfer, 300 K thermal-displacement-averaged optical response, and self-consistent drift–diffusion device modeling. The workflow selects 23 candidates for comparative device-level evaluation under unified conditions. The device-level analysis shows that candidates favored by bandgap or Spectroscopic Limited Maximum Efficiency (SLME) do not necessarily retain their advantage as recombination losses increase. By varying the effective bimolecular recombination coefficient and the Shockley–Read–Hall carrier lifetime, we quantify PCE degradation and ranking evolution as a model-conditioned measure of device-level loss tolerance. The shortlisted candidates reach baseline predicted PCEs of up to 15.26%, while pronounced rank changes under increasing nonradiative recombination loss highlight the limitations of radiative-limit metrics alone. This work therefore recasts lead-free double-perovskite screening from identifying the highest radiative-limit efficiency to prioritizing materials that combine competitive device performance with robust loss tolerance and experimental relevance.

Read PDF

Similar papers

#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Conference Sep 2010

Exploring the Sources of Waste in Kanban Software Development Projects

The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new an...

Marko Ikonen, Petri Kettunen, Nilay V. Oza et al. · 67 citations · ⚡9

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.