PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 15, 2026ACS Applied Nano Materials3 citations

Review of Photon Upconversion Nanomaterials for High-Throughput Applications

View Full Paper
LKL. KeerthanaYZYan ZhangBYBo Yang

Key Points

  • The review aims to summarize progress in photon upconversion nanomaterials and their applications in energy and biomedical technologies.
  • Analyzed recent advances in core-shell designs, plasmonic coupling, and emerging nanomaterials.
  • Discussed theoretical models including rate equations, density functional theory, and Monte Carlo simulations.
  • Identified improvements in efficiency due to new design strategies and materials.
  • Noted persistent challenges concerning scalable fabrication and reproducibility.

Abstract

Photon upconversion, a nonlinear process converting near-infrared light into visible emission, has attracted growing interest for photovoltaics, bioimaging, sensing, and photonic devices. Conventional lanthanide-doped nanomaterials have enabled this field, yet their low-quantum yields and high excitation thresholds limit their applicability. Recent strategies such as core–shell designs, plasmonic coupling, and hybrid composites have significantly enhanced efficiency by suppressing surface quenching and amplifying local electromagnetic fields. Emerging materials, including perovskite quantum dots, carbon quantum dots, and metal–organic frameworks, offer tunable bandgaps, high photostability, and versatile energy transfer pathways, particularly for triplet–triplet annihilation. Complementary theoretical models using rate equations, density functional theory, and Monte Carlo simulations provide insights into dopant optimization and nonradiative losses, accelerating material design. Despite these advances, scalable fabrication, reproducibility, and mitigation of photothermal losses remain key challenges. This review outlines progress in next-generation PUC nanomaterials, bridging experimental and computational approaches to realize efficient, stable, and multifunctional systems for next-generation energy and biomedical technologies.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Keerthana et al. (2026) studied this question.

synapsesocial.com/papers/69b5ff8083145bc643d1c1d1https://doi.org/10.1021/acsanm.5c05470
Ask AI
Helpful
Bookmark
Share
View Full Paper