ReviewRSC advances2025
Density functional theory-accelerated design of perovskite quantum dots: unlocking atomic-level control for next-generation optoelectronics and sensors.
Review in RSC advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Excitonic and Optical Transduction Mechanisms in Quantum Dot Sensors for Environmental Pollutant Detection.Sensors (Basel, Switzerland) · 2026Review
- Multiscale Modeling of Quantum Dot Solar Cells: Integration of Density Functional Theory, SCAPS, Lambert W Analysis, and Machine Learning.ACS omega · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Density functional theory (DFT) accelerates the rational design of lead-halide and lead-free perovskite quantum dots (PQDs) by delivering atomic-level control over electronic structure, surface chemistry, and charge dynamics, with direct relevance to next-generation optoelectronics and sensing. Using hybrid functionals (HSE06 + SOC), spin-orbit coupling, and machine-learning integration, this study systematically maps bandgap tunability (1.8-3.0 eV
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.