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What to measure? is a key question in nanoscience, and it is not straightforward to address as different physicochemical properties define a nanoparticle sample. Most prominent among these properties are size, shape, surface charge, and porosity. Today researchers have an unprecedented variety of measurement techniques at their disposal to assign precise numerical values to those parameters. However, methods based on different physical principles probe different aspects, not only of the particles themselves, but also of their preparation history and their environment at the time of measurement. Understanding these connections can be of great value for interpreting characterization results and ultimately controlling the nanoparticle structure–function relationship. Here, the current techniques that enable the precise measurement of these fundamental nanoparticle properties are presented and their practical advantages and disadvantages are discussed. Some recommendations of how the physicochemical parameters of nanoparticles should be investigated and how to fully characterize these properties in different environments according to the intended nanoparticle use are proposed. The intention is to improve comparability of nanoparticle properties and performance to ensure the successful transfer of scientific knowledge to industrial real‐world applications.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
Large-scale nanoimprinted metasurfaces based on silicon photonic crystal slabs were produced and coated with a NaYF4:Yb3+/Er3+ upconversion nanoparticle (UCNP) layer. UCNPs on these metasurfaces yield a more than 500-fold enhanced upconversion emission compared to UCNPs on planar surfaces. It is also demonstrated how the optical response of the UCNPs can be used to estimate the local field energy in the coating layer. Optical simulations using the finite element method validate the experimental results and the calculated spatial three-dimensional field Energy distribution helps us to understand the emission enhancement mechanism of the UCNPs closely attached to the metasurface. In addition, we analyzed the spectral shifts of the resonances for uncoated and coated metasurfaces and metasurfaces submerged in water to enable a prediction of the optimum layer thicknesses for different excitation wavelengths, paving the way to applications such as electromagnetic field sensors or bioassays.
Core–shell nanoparticles have attracted much attention in recent years due to their unique properties and their increasing importance in many technological and consumer products. However, the chemistry of nanoparticles is still rarely investigated in comparison to their size and morphology. In this review, the possibilities, limits, and challenges of X-ray photoelectron spectroscopy (XPS) for obtaining more insights into the composition, thickness, and homogeneity of nanoparticle coatings are discussed with four examples: CdSe/CdS quantum dots with a thick coating and a small core; NaYF4-based upconverting nanoparticles with a large Yb-doped core and a thin Er-doped coating; and two types of polymer nanoparticles with a poly(tetrafluoroethylene) core with either a poly(methyl methacrylate) or polystyrene coating. Different approaches for calculating the thickness of the coating are presented, like a simple numerical modelling or a more complex simulation of the photoelectron peaks. Additionally, modelling of the XPS background for the investigation of coating is discussed. Furthermore, the new possibilities to measure with varying excitation energies or with hard-energy X-ray sources (hard-energy X-ray photoelectron spectroscopy) are described. A discussion about the sources of uncertainty for the determination of the thickness of the coating completes this review.
A solvothermal method was used to prepare a series of Yb3+/Tm3+/Ca2+ co-doped NaYF4 nanoparticles with different Ca2+ contents. Strong upconversion blue fluorescence could be observed under 980 nm laser excitation of the samples. The effect of different Ca2+ contents on the luminescence intensity was investigated, and it was found that the UV-vis upconversion luminescence increased and then decreased with an increasing Ca2+ concentration during the increase of the Ca2+ content from 0 mol% to 25 mol%, reaching the strongest fluorescence at 15 mol%, which was up to about 28 times stronger than that without Ca2+ doping. Furthermore, the mechanism was investigated, and it was found that the doping of Ca2+ disrupted the symmetry of the crystal field, resulting in a significant enhancement of the overall fluorescence. Applied to fluorescence intensity ratio thermometry, the absolute and relative sensitivities are as high as 0.0418 K−1 and 2.31% K−1, respectively, with a minimum temperature resolution of 0.0129 K.
The core−shell NaYF4:Yb3+/Tm3+@NaYF4:Yb3+ upconversion nanoparticles were successfully prepared by a solvothermal method, and a layer of mesoporous silica (mSiO2) was successfully coated on the periphery of the core−shell nanoparticles to transform their surface from lipophilic to hydrophilic, further expanding their applications in biological tissues. The physical phase, morphology, structure, and fluorescence properties were characterized by X-ray diffraction (XRD), field emission transmission electron microscopy (TEM), Fourier infrared spectroscopy (FT-IR), ζ potential analysis, and fluorescence spectroscopy. It was found that the material has a hexagonal structure with good hydrophilicity and emits intense fluorescence under 980 nm pump laser excitation. The non-contact temperature sensing performance of nanoparticles was evaluated by analyzing the upconversion fluorescence of Tm3+ (1G4 → 3F4 and 3F3 → 3H6) in the temperature range of 284−344 K. The absolute and relative sensitivities were found to be 0.0067 K−1 and 1.08 % K−1, respectively, with high-temperature measurement reliability and good temperature cycling performance. More importantly, its temperature measurement in phosphate-buffered saline (PBS) solution is accurate. In addition, the temperature of the cells can be increased by adjusting the laser power density and laser irradiation time. Therefore, an optical temperature sensing platform was built to realize the application of real-time monitoring of cancer cell temperature and the dual function of photothermal therapy.