Journal of Nanoparticle Research最新文献

The two-dimensional material that emerged with the discovery of graphene has attracted great attention due to its interesting optical, electrical and mechanical properties. In recent years, especially two-dimensional (2D) perovskite oxides have attracted attention due to their ability to exhibit insulating, semiconducting or conducting properties. Dion-Jacobson perovskite oxides from the 2D perovskite oxide family have been intensively investigated due to their remarkable chemical and physical properties such as giant magnetoresistance, high-temperature superconductivity, ferroelectricity and photocatalytic activity. In this review, the properties, synthesis methods and device applications of calcium niobate nanosheets (KCa₂Nb₃O₁₀ commonly referred to as CNO), one of the Dion-Jacobson perovskite oxides, are discussed. Promising results have been obtained in Ultraviolet (UV) detection and photocatalytic applications with CNO structures. However, when the literature was examined, no review article was found that examined CNO nanosheets in detail. It is thought that; this study will fill this gap in the literature.

Monodispersed silica nanoparticles (NPs) of 30–204 nm diameter encapsulating {2,2′,2″,2‴-{4′-{[(4,6-dichloro-1,3,5-triazin-2-yl)amino]biphenyl-4-yl}-2,2′:6′,2″-terpyridine-6,6″-diyl}bis(methylenenitrilo)}tetrakis(acetate)–Eu³⁺ (DTBTA–Eu (III)) were prepared in aqueous solutions at various amounts of DTBTA–Eu (III) dissolved in H₂O for various durations of mixing DTBTA–Eu (III) and 3-aminopropyltriethoxysilane. Transmission electron microscopy images indicated that the NPs were uniformly distributed in the solutions, and luminescence emission spectra were assigned to DTBTA–Eu (III), which typically has three peaks at 586, 595, and 614 nm. The apparent amount of DTBTA–Eu (III) encapsulated in silica NPs, which was determined from luminescence emission intensity, increased with NP diameter. The silica NPs encapsulating DTBTA–Eu (III) prepared by adjusting the amounts of concentrated NH₄OH solution and tetraethyl orthosilicate in the presence of hexadecyltrimethylammonium bromide in the first step of preparation had a minimum diameter of 30 nm and an enhanced luminescence lifetime of 1.79 ms.

Treating and diagnosing drug-resistant tumors is an important challenge for rapidly developing nanomedicine. The new polymer-inorganic 10–15 nm nanoparticles based on branched PEGylated polylactide macromolecules with a number-average molecular weight of 14,200 modified with gadolinium (III) oxide offer a promising solution. The advantage of using PEGylated branched polylactides compared to traditional linear block copolymers is the suppression of micelle formation, which allows significantly reducing the theranostic’s particle size. The structure of the nanosized carrier is characterized by ¹H NMR, ¹³C NMR, IR spectroscopy, and XRD, and the expected size of nanoparticles is estimated theoretically and determined experimentally by TEM and SAXS. The DLS method reveals that electrostatic immobilization of doxorubicin hydrochloride is accompanied by the assembly of 80–90 nm aggregates, wherein the full drug release from nanoparticles occurs in accordance with the first-order kinetic equation. The synthesized nanoparticles were shown to possess paramagnetism and promote significant longitudinal relaxivity (6.77 mM⁻¹ × s⁻¹) of proton spins, making them promising agents for positive MRI imaging. They are also nontoxic to HDF fibroblasts at concentrations up to 0.01 mg × ml⁻¹. Immobilization of doxorubicin hydrochloride slightly reduced its cytotoxicity toward HDF cells and promoted an increase in cytotoxicity for doxorubicin-resistant SiHa cancer cells at drug concentrations up to 0.77 μM. Thus, the developed nanoparticles are promising for the creation of new theranostic agents combining the capabilities of doxorubicin immobilization with MRI diagnostics.

Graphical abstract

As potential candidates to be employed as air anodes in metal-air batteries, transition metal phosphides (TMPs) have received considerable attention due to their excellent electrocatalytic activity. This work presents a straightforward method for efficiently fabricating a three-dimensional (3D) reticulated carbon N, P-doped carbon structure generated from polyaniline-phytic acid polymer, with Co₂P and Co₃(PO₄)₂ nanoparticles implanted on the carbon matrix (CoPO-Co₂P@NPC). As-fabricated CoPO-Co₂P@NPC demonstrates impressive bifunctional oxygen reduction reactions (ORR)/oxygen evolution reactions (OER) performances. A diffusion-limiting current density of 6.56 mA cm⁻², a half-wave potential of 0.80 V, and an overpotential of 1.73 V are detected at 10 mA cm⁻². The CoPO-Co₂P@NPC assembled rechargeable Zn-Air battery (RZAB) demonstrates a high-power density of 265 mW cm⁻², with excellent cycling stability over 450 h. The composite based on Co₂P-Co₃(PO₄)₂ demonstrates outstanding bifunctional electrocatalytic performance, which makes it a desirable anode material for RZABs.

Graphical abstract

Selective oxidation of naphthol derivatives under visible light presents an environmentally friendlier alternative to conventional oxidation methods. Here, we report the preparation of a heterogeneous photocatalyst, Pc-3/MCM-41, by immobilizing a cationic zinc phthalocyanine (Pc-3) onto mesoporous MCM-41 silica via electrostatic interactions. Spectroscopic, thermal, and microscopic analyses indicated that Pc-3 was successfully incorporated into the silica support, with reasonably uniform dispersion and minimal aggregation. Under red LED irradiation, the catalyst promoted the oxidation of 1,5-dihydroxynaphthalene (1,5-DHN) to juglone, achieving ca. 80–85% conversion under certain conditions. The catalyst can be recovered by filtration and reused, although its activity declines over several cycles. Kinetic investigations under these conditions revealed a maximum pseudo-first-order rate constant of 0.5484 min⁻¹. Langmuir–Hinshelwood modeling yielded adsorption (K_ad) and reaction rate (k_r) constants of 140.48 mmol⁻¹ and 0.0104 mmol min⁻¹, respectively. Because substrate adsorption caused deactivation, regeneration via washing with N,N-dimethylformamide partially restored catalytic activity. These results highlighted Pc-3/MCM-41 as a promising visible-light photocatalyst for oxidation reactions, though improvements in stability and cycle performance remain necessary.

Understanding hydrogen adsorption on metal nanoparticles is key to improving catalysts for hydrogen energy applications. Using density functional theory, we examine hydrogen adsorption on Pt₁₄₇, Pt₁₄₆Ni₁, Pt₁₃₄Ni₁₃, and Pt₉₂Ni₅₅ to assess how Ni content and distribution affect reactivity. We calculate adsorption energies and H-Pt bond lengths at ten surface sites per cluster. Results show that Ni composition strongly influences preferred adsorption sites and strengths. Multiple hydrogen adsorption reveals that Pt₁₄₇ and Pt₁₄₆Ni₁ clusters exhibit nearly identical adsorption energetics and maintain structural stability. In contrast, higher Ni content in Pt₁₃₄Ni₁₃ and especially Pt₉₂Ni₅₅ weakens hydrogen binding and induces greater lattice distortion, reflecting a trade-off between adsorption strength and structural stability. Analysis of local atomic pressure distributions highlights a strong correlation between surface tensile pressure and hydrogen adsorption behaviour. Clusters with pronounced surface tensile pressure exhibit more favourable adsorption energetics. These insights support the strategic design of bimetallic nanoalloys for efficient hydrogen catalysis.

The melting behavior of high-entropy alloy nanoparticles (HEA-NPs) is a critical determinant of the microstructure and properties of alloys fabricated via melting-sintering processes. A fundamental understanding of this behavior is therefore essential for advancing the development of novel HEA materials. In this study, molecular dynamics simulations were employed to investigate the different trends in surface atomic preferences during the heating and melting processes of Fe–Ni-Cr-Co–Cu HEAs-NPs under various sizes and melting rates. The results indicate that the surface structure of the NPs remains stable before reaching the melting point; once the melting point is attained, the surface melts rapidly first, followed by the overall melting of the NP. During the heating process, Cu and Cr exhibit surface segregation phenomena before melting, and this trend remains stable, unaffected by NP size and heating rate. After reaching the melting point, Cu segregation at the surface intensifies, while Cr no longer segregates to the surface, and the trend of Fe segregation at the surface decreases as the heating rate increases. Furthermore, we conducted an in-depth analysis of the causes of these different trends in surface atomic preferences during the heating and melting process from the perspectives of average atomic potential energy. Atomic potential energy can intuitively display the enthalpy evolution and atomic scale thermodynamic evolution trends in non-equilibrium processes in our work. Our research reveals the melting characteristics and surface atomic preference trends of Fe Ni Cr Co Cu HEA-NPs, providing valuable insights for the application of HEA-NPs in sintered materials.

The capacity of machine learning (ML) to make accurate predictions based on data is transforming the process of discovering, designing, and implementing advanced materials, as it allows breaking the constraints of existing experimental and computational methods. It revolutionizes the understanding, design, and deployment of advanced materials. The present review is a critical overview of the state of ML in nanoscience, including property prediction, optimization of synthesis, high-throughput screening, inverse design, and real-time characterization. It focuses on the application of supervised, unsupervised, semi-supervised, and reinforcement learning approaches within various classes and functions of nanomaterials. Moreover, we discuss the use of generative models and hybrid frameworks to support autonomous discovery of materials as well as the discovery of sustainable nanotechnologies. By integrating current approaches with future trends, this paper summarizes the strong strategic promotion of ML, which enables faster innovation, eliminates resource-intensive tasks, and increases reproducibility. The first originality of the review lies in its cross-domain approach, which integrates the technological, economic, and environmental aspects of ML-driven nanomaterials research. This synthesis serves as both a roadmap and an action agenda for the design of intelligent materials, with applications in the development of electronics, energy industries, catalysis, and biomedical fields, in the context of information-intensive science.

Graphical Abstract

In this work, we synthesized superpara-magnetic cobalt ferrite (CoFe(_{2})O(_{4})) magnetic nanoparticles using the co-precipitation method and performed a comprehensive structural and magnetic characterization. Structural characterization techniques, including X-ray diffraction, Raman spectroscopy, and HRTEM, confirmed the formation of an inverse spinel structure with a lattice parameter of (a = 8.41) Å and an average crystallite size of (D= 17.7pm 6.5) nm. Raman peak fitting revealed broadened modes, consistent with phonon confinement effects. SQUID magnetometry confirmed superparamagnetic-like behavior of the nanoparticles at room temperature, characterized by low coercivity and remanence, with a blocking temperature of 210 K and saturation magnetization of (M_{s}=51) emu/g. Complementing the experimental work, we implemented a two-dimensional Ising model through Monte Carlo simulations to analyze the magnetic response within the nanoparticle system.