Zero-dimensional graphene quantum dots (GQDs) exhibit many different properties, such as strong fluorescence, nonzero bandgap and solubility in solvents, compared to two-dimensional graphene. GQDs are biocompatible and have low toxicity; hence, they are widely used in the biomedical field. The edge effect of GQDs is of particular interest because edge modification can regulate the performance of nanomaterials. In this review, various preparation methods for GQDs, which can be divided into three main categories, namely top-down, bottom-up and chemical methods, are discussed. The unique optical, electrical, thermal and magnetic properties of GQDs are reviewed. The functionalization of GQDs by doping with heteroatoms and forming composites with other materials is studied, and the characteristics of these GQDs are also discussed. The applications of these GQDs in the fields of optics, electricity, optoelectronics, biomedicine, energy, agriculture and other emerging interdisciplinary fields are reviewed to highlight the enormous potential of nanomaterials. This review reports on the recent advancement in GQD research and suggests future directions for the development of GQDs.

Three-dimensional (3D) printing allows for the creation of complex, layered structures with precise micro and macro architectures that are not achievable through traditional methods. By designing 3D structures with geometric precision, it is possible to achieve selective regulation of mechanical properties, enabling efficient dissipation of mechanical energy. In this study, a series of modular samples inspired by the Bouligand structure were designed and produced using a direct ink writing system, along with a classical printable polydimethylsiloxane ink. By altering the angles of filaments in adjacent layers (from 30° to 90°) and the filament spacing during printing (from 0.8 mm to 2.4 mm), the mechanical properties of these modular samples can be adjusted. Compression mechanical testing revealed that the 3D printed modular Bouligand structures exhibit stress-strain responses that enable multiple adjustments of the elastic modulus from 0.06 MPa to over 0.8 MPa. The mechanical properties were adjusted more than 10 times in printed samples prepared using uniform materials. The gradient control mechanism of mechanical properties during this process was analyzed using finite element analysis. Finally, 3D printed customized modular Bouligand structures can be assembled to create an array with Bouligand structures displaying various orientations and interlayer details tailored to specific requirements. By decomposing the original Bouligand structure and then assembling the modular samples into a specialized array, this research aims to provide parameters for achieving gradient energy absorption structures through modular 3D printing.

Wearable electronics are advancing towards miniaturization and flexibility. However, traditional energy supply methods have largely hindered their development. An effective solution to this problem is to convert human mechanical energy into electricity to power wearable electronic devices. Therefore, it is greatly attractive to design flexible, foldable and even stretchable energy harvesting devices. Herein, we use the electrospinning and kirigami approach to develop a type of highly stretchable kirigami-patterned nanofiber-based triboelectric nanogenerator (K-TENG). Due to its innovative structural design, the K-TENG can achieve a tensile strain of 220%, independent of the tensile properties of the material itself. When a person swings their arms, the K-TENG fixed to the clothing can convert mechanical energy from human movement into electrical energy. The produced electricity can directly drive 50 LED lights and a digital watch, or be stored in a lithium battery to charge the smartwatch and smartphone, respectively. This study employs a new method to fabricate a stretchable triboelectric nanogenerator and demonstrates its promising applications in wearable power technology.

The performance of red InP and blue ZnTeSe-based quantum dots (QDs) and corresponding QD light emitting diodes (QLEDs) has already been improved significantly, whose external quantum efficiencies (EQEs) and luminances have exceeded 20% and 80 000 cd m⁻², respectively. However, the inferior performance of the green InP-based device hinders the commercialization of full-color Cd-free QLED technology. The ease of oxidation of the highly reactive InP cores leads to high non-radiative recombination and poor photoluminescence quantum yield (PL QY) of the InP-based core/shell QDs, limiting the performance of the relevant QLEDs. Here, we proposed a fluoride-free synthesis strategy to in-situ passivate the InP cores, in which zinc myristate reacted with phosphine dangling bonds to form Zn–P protective layer and protect InP cores from the water and oxygen in the environment. The resultant InP/ZnSe/ZnS core/shell QDs demonstrated a high PL QY of 91%. The corresponding green-emitting electroluminescence devices exhibited a maximum EQE of 12.74%, along with a luminance of over 175 000 cd m⁻² and a long T₅₀@100 cd m⁻² lifetime of over 20 000 h.

Soft magnetic composites (SMCs) play a pivotal role in the development of high-frequency, miniaturization and complex forming of modern electronics. However, they usually suffer from a trade-off between high magnetization and good magnetic softness (high permeability and low core loss). In this work, utilizing the order modulation strategy, a critical state in a FeSiBCCr amorphous soft magnetic composite (ASMC), consisting of massive crystal-like orders (CLOs, ∼1 nm in size) with the feature of α-Fe, is designed. This critical-state structure endows the amorphous powder with the enhanced ferromagnetic exchange interactions and the optimized magnetic domains with uniform orientation and fewer micro-vortex dots. Superior comprehensive soft magnetic properties at high frequency emerge in the ASMC, such as a high saturation magnetization (M_s) of 170 emu g⁻¹ and effective permeability (μ_e) of 65 combined with a core loss (P_cv) as low as 70 mW cm⁻³ (0.01 T, 1 MHz). This study provides a new strategy for the development of high-frequency ASMCs, possessing suitable comprehensive soft magnetic performance to match the requirements of the modern magnetic devices used in the third-generation semiconductors and new energy fields.

DFT + U is a widely used treatment in the density functional theory (DFT) to deal with correlated materials that contain open-shell elements, whereby the quantitative and sometimes even qualitative failures of local and semi-local approximations can be corrected without much computational overhead. However, finding appropriate U parameters for a given system and structure is non-trivial and computationally intensive, because the U value has generally a strong chemical and structural dependence. In this work, we address this issue by building a machine learning (ML) model that enables the prediction of material- and structure-specific U values at nearly no computational cost. Using Mn–O system as an example, the ML model is trained by calibrating DFT + U electronic structures with the hybrid functional results of more than 3000 structures. The model allows us to determine an accurate U value (MAE = 0.128 eV, R² = 0.97) for any given Mn–O structure. Further analysis reveals that M–O bond lengths are key local structural properties in determining the U value. This approach of the ML U model is universally applicable, to significantly expand and solidify the use of the DFT + U method.

A close look at Google’s GNoME inorganic materials dataset (Merchant et al 2023 Nature 624 80–85), and 11 things you would like to know.