Carbon‐Dot‐Based White‐Light‐Emitting Diodes with Adjustable Correlated Color Temperature Guided by Machine Learning

Binary Host-induced Exciplex Enabled High Color-Rendering Index of 94 for Carbon Quantum Dot-Based White Light-Emitting Diodes

White light-emitting diodes (WLEDs) with high color-rendering index (CRI, >90) are important for backlight displays and solid-state lighting applications. Although the well-developed colloidal quantum dots (QDs) based on heavy metals such as cadmium and lead are promising candidates for WLEDs, the low CRI still remains a significant limitation. In addition, the severe toxicity of heavy metals greatly limits their widespread use. Herein, the study demonstrates low-cost and environmentally friendly carbon quantum dots (CQDs)-based WLEDs that exhibit a high CRI of 94.33, surpassing that of conventional cadmium/lead-containing QD-based WLEDs. This achievement is attained through the employment of a binary host-induced exciplex strategy. The high hole/electron mobility and suitable energy levels of the donor and acceptor give rise to a broadband orange-yellow emission stemming from the exciplex. As the host, the binary exciplex is capable of contributing blue and orange-yellow emission components while efficiently mitigating the aggregation-induced quenching of CQDs. Meanwhile, CQDs effectively address the deep-red emission gap, enabling the realization of CQDs-based WLEDs with high CRI. These WLEDs also exhibit a remarkably low turn-on voltage of 2.8 V, a maximum luminance exceeding 2000 cd m- 2, a correlated color temperature of 4976 K, and Commission Internationale de l'Eclairage coordinates of (0.34, 0.32).

Optical Properties Prediction for Red and Near-Infrared Emitting Carbon Dots Using Machine Learning

Functional nanostructures build up a basis for the future materials and devices, providing a wide variety of functionalities, a possibility of designing bio-compatible nanoprobes, etc. However, development of new nanostructured materials via trial-and-error approach is obviously limited by laborious efforts on their syntheses, and the cost of materials and manpower. This is one of the reasons for an increasing interest in design and development of novel materials with required properties assisted by machine learning approaches. Here, the dataset on synthetic parameters and optical properties of one important class of light-emitting nanomaterials - carbon dots are collected, processed, and analyzed with optical transitions in the red and near-infrared spectral ranges. A model for prediction of spectral characteristics of these carbon dots based on multiple linear regression is established and verified by comparison of the predicted and experimentally observed optical properties of carbon dots synthesized in three different laboratories. Based on the analysis, the open-source code is provided to be used by researchers for the prediction of optical properties of carbon dots and their synthetic procedures.

Solid-State Fluorescent Carbon Dots with Unprecedented Efficiency from Visible to Near-Infrared Region

Developing solid-state luminescent materials with bright long-wavelength emissions is of considerable practical importance in light-emitting diodes (LEDs) but remains a formidable challenge. Here, a novel structure engineering strategy is reported to realize solid-state fluorescence (FL)-emitted carbon dots (CDs) from visible to near-infrared region. This is the first report of such an extended wavelength emission of self-quenching-resistant solid-state CDs. Notably, the quantum yields of these CDs are remarkably improved up to 67.7%, which is the highest value for solid-state CDs. The surface polymer chains of CDs can efficiently suppress the conjugated sp² carbon cores from π-π stacking inducing aggregation caused FL quenching, and the redshift of FL emissions is attributed to narrowing bandgap caused by an enlarged sp² carbon core. Using these CDs as conversion phosphors, the fabrication of white LEDs with adjustable correlated color temperatures of 1882-5019 K is achieved. Moreover, a plant growth LED device is assembled with a blue-LED chip and deep-red/near-infrared-emitted CDs. Compared with sunlight and white LEDs, the peanuts irradiated by plant growth LED lamp show higher growth efficiency in terms of branches and leaves. This work provides high-quality solid-state CD-based phosphors for LED lighting sources that are required for diverse optoelectronic applications.

Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?

Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers.

Diversity and Tailorability of Photoelectrochemical Properties of Carbon Dots

As a new kind of carbon based functional material, carbon dots (CDs) have sparked much interest in recent years. The tunable structure, composition, and morphology of CDs unlocks opportunities to enable diversity in their photoelectrochemical properties, and thus they show great potential in various applications such as biology, catalysis, sensors, and energy storage. Nevertheless, the related understanding of CDs is insufficient at present due to their inherent complexity of microstructure, which involves the intersection of high polymer, bulk carbon, and quantum dot (QD). A good understanding of the underlying mechanism behind the properties of CDs is still a formidable challenge, requiring the integration of robust knowledge from organic chemistry, materials science, and solid state physics. Within this context, discovering more appealing properties, elucidating fundamental factors that affect the properties and proposing effective engineering strategies that can realize specific functions for CDs are now highly pursued by researchers.At the beginning of this Account, the main features of CDs are introduced, where not only the basic structural, compositional and morphological characteristics but also the rich photoelectrochemical properties are elucidated, among which the band gap, chirality, photoinduced potential, and electron sink effect are particularly emphasized. Furthermore, new analysis techniques including transient photoinduced current (TPC), transient photoinduced voltage (TPV), and machine learning (ML) to reveal the unique properties of CDs are described. Then, several appealing strategies that aim to rationally tailor CDs for oriented applications are highlighted. These regulation strategies are morphology modulation (e.g., developing CDs with new geometrical configuration, controlling the particle size), phase engineering (e.g., altering the phase crystallinity, introducing the foreign atoms), surface functionalization (e.g., grafting various types of functional groups), and interfacial tuning (e.g., building CD-based nanohybrids with well-defined interfaces). Although the fundamental investigation of CDs is relatively undeveloped because of their complexity, this does not hinder their wide application. At the same time, exploring the extensive applications of CDs will promote their in-depth understanding. Finally, the chances for building a CD-centered blueprint for sustainable society are explored and challenges for future research in the field of CDs are proposed as follows: (i) the controllable synthesis of CDs with uniform size; (ii) search for novel CDs with unique structure, morphology, or composition; (iii) quantitative understanding of the property of CDs; (iv) performance enhancement by external forces such as magnetism or heat injection; (v) construction of the dual carbon concept; (vi) further research on different photocatalytic applications. On the whole, this Account may provide meaningful references for the understanding of the microstructure-property correlation as well as the regulation of CDs, thereby promoting their transition from fundamental research to practical application.

Machine learning guided microwave-assisted quantum dot synthesis and an indication of residual H2O2 in human teeth

The current preparation methods of carbon quantum dots (CDs) involve many reaction parameters, which leads to many possibilities in the synthesis processes and high uncertainty of the resultant production performance. Recently, machine learning (ML) methods have shown great potential in correlating the selected features in many applications, which can help understand the relevant structure-function relationships of CDs and discover better synthesis recipes as well. In this work, we employ the ML approach to guide the blue CD synthesis in microwave systems. After optimizing the synthesis parameters and conditions, the quantum yield (QY) increases to about 200% higher than the average value of the prepared samples without ML guidance. The obtained CDs are applied as fluorescent probes to monitor hydrogen peroxide (H₂O₂) in human teeth. The CD probe exhibits a linear relationship with the concentration of H₂O₂ ranging from 0 to 1.1 M with a lower detection limit of 0.12 M, which can effectively detect the residual H₂O₂ after bleaching teeth. This work shows that the adopted ML methods have considerable advantages in guiding the synthesis of high-quality CDs, which could accelerate the development of other novel functional materials in energy, biomedical, and environmental remediation applications.

Localized Excitonic Electroluminescence from Carbon Nanodots

Localized excitons are expected to achieve high-performance electroluminescence and have been widely investigated in GaN-based light-emitting diodes (LEDs). Although carbon nanodot (CD) based LEDs have been achieved with the radiative recombination of electrons and holes, localized excitonic electroluminescence has been not reported before. In this Letter, localized excitonic electroluminescent devices have been fabricated using fluorescent CDs as an active layer. The CDs show strong localized excitonic yellow emission with a fluorescence quantum yield of 76% and Stokes shift of 2.1 eV. The CD-based LEDs present a sub-bandgap turn-on voltage of 2.4 V and a maximum luminance of 60.2 cd m^-2, which is the lowest driving voltage among the CD-based electroluminescent devices. Localized centers trap carriers effectively, resulting in sub-bandgap light emission. The current results manifest that localized excitons may furnish a promising approach to boost the development of CD-based LEDs.

Facile Synthesis of Water-Stable Multicolor Carbonized Polymer Dots from a Single Unconjugated Glucose for Engineering White Light-Emitting Diodes with a High Color Rendering Index

Tunable emission carbonized polymer dots (CPDs) are highly desirable for the preparation of optoelectronic devices, especially white light-emitting diodes (WLEDs). In most available studies, polychromatic CPDs are synthesized using aromatic molecules as precursors. However, few studies report the successful synthesis of polychromatic CPDs using two or more unconjugated precursors. In this work, we prepare multicolor fluorescent CPDs from a single unconjugated precursor, glucose, via a hydrothermal reaction. By controlling the particle size and degree of graphitization of the synthesized CPDs, their emission wavelength can be tuned in the range 440-625 nm (i.e., almost the entire visible region). Furthermore, the CPDs can be used to construct LEDs of varying colors, including WLEDs (CIE coordinates: 0.34, 0.36) with the correlated color temperature and color rendering index of 4997 K and 92.69, respectively. In brief, the strategy proposed in this study successfully converts unconjugated glucose into high-performance LEDs with great application potential.