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<p>Carbon quantum dots (CQDs) have emerged as versatile nanomaterials with unique optical, electronic, and thermal properties driven by their quantum confinement and surface characteristics. This review critically examines the role of computational quantum chemistry, particularly density functional theory (DFT) and time-dependent DFT (TD-DFT), in advancing the understanding of CQDs. We discuss various computational approaches used to model the structural, electronic, and photophysical properties of CQDs and their interaction with different chemical environments, including solvents and dopants. Emphasis is placed on how computational methods complement experimental studies by elucidating fluorescence mechanisms, predicting molecular structures, and guiding the rational design of CQDs for applications in sensing, bioimaging, catalysis, and optoelectronics. Challenges such as computational cost, the complexity of CQD structural models, and limitations of current theoretical approaches are highlighted. This review also identifies emerging trends and future directions for improving the accuracy and scalability of computational techniques in CQD research.</p>

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Understanding carbon quantum dots through computational methods in quantum chemistry

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月5日

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  • Nidhi Nirmalkar,
  • Deepak Patel,
  • Kamlesh Shrivas,
  • Neeraj Kumari,
  • Kiran Thakur,
  • Bhaskar Sharma,
  • Khemchand Dewangan,
  • Santosh Singh Thakur,
  • Goutam Kumar Patra

摘要

Carbon quantum dots (CQDs) have emerged as versatile nanomaterials with unique optical, electronic, and thermal properties driven by their quantum confinement and surface characteristics. This review critically examines the role of computational quantum chemistry, particularly density functional theory (DFT) and time-dependent DFT (TD-DFT), in advancing the understanding of CQDs. We discuss various computational approaches used to model the structural, electronic, and photophysical properties of CQDs and their interaction with different chemical environments, including solvents and dopants. Emphasis is placed on how computational methods complement experimental studies by elucidating fluorescence mechanisms, predicting molecular structures, and guiding the rational design of CQDs for applications in sensing, bioimaging, catalysis, and optoelectronics. Challenges such as computational cost, the complexity of CQD structural models, and limitations of current theoretical approaches are highlighted. This review also identifies emerging trends and future directions for improving the accuracy and scalability of computational techniques in CQD research.