From Materials to Devices: Multiscale Modeling of Colloidal Quantum Dot Optoelectronics

Colloidal quantum dots (CQDs) have emerged as a versatile platform for optoelectronics due to their solution processability, size-dependent tunable bandgaps and strong light-matter interaction. In this review, we systematically examine how theoretical models for CQD optoelectronic devices have been developed and applied. This review emphasizes the importance of integrating theoretical models across CQD materials and optoelectronic devices to enable accurate prediction of key optoelectronic performance. Recent advances in theoretical frameworks for CQD optoelectronics have enabled the prediction of material properties (electronic structure, defect formation, absorption and emission spectra) through atomic-scale simulations and device behaviors (charge separation, transport, recombination and multiplication) through device-scale simulations. These integrated approaches propose the design principles for developing the CQD architectures with optimized optoelectronic performances, enabling practical implementation in device fabrication. We conclude that the future incorporation of machine learning with theoretical CQD models ensures the exploration of previously inaccessible CQD materials and device architectures, accelerating the commercialization of CQD-based optoelectronic applications.