Assessing Plasmonic Nanoprobes in Electromagnetic Field Enhancement for SERS Detection of Biomarkers

The exploration of the plasmonic field enhancement of nanoprobes consisting of gold and magnetic core@gold shell nanoparticles has found increasing application for the development of surface-enhanced Raman spectroscopy (SERS)-based biosensors. The understanding of factors controlling the electromagnetic field enhancement, as a result of the plasmonic field enhancement of the nanoprobes in SERS biosensing applications, is critical for the design and preparation of the optimal nanoprobes. This report describes findings from theoretical calculations of the electromagnetic field intensity of dimer models of gold and magnetic core@gold shell nanoparticles in immunoassay SERS detection of biomarkers. The electromagnetic field intensities for a series of dimeric nanoprobes with antibody–antigen–antibody binding defined interparticle distances were examined in terms of nanoparticle sizes, core–shell sizes, and interparticle spacing. The results reveal that the electromagnetic field enhancement not only depended on the nanoparticle size and the relative core size and shell thicknesses of the magnetic core@shell nanoparticles but also strongly on the interparticle spacing. Some of the dependencies are also compared with experimental data from SERS detection of selected cancer biomarkers, showing good agreement. The findings have implications for the design and optimization of functional nanoprobes for SERS-based biosensors.

Interparticle Spacing Effect among Quantum Dots with High-Pressure Regulation

In this paper, we explore whether interparticle spacing affects steady-state and transient-state optical properties by comparing close-packed CdSe/ZnS–quantum dots (QDs) and CdSe/ZnS–QDs dispersed in polymethyl methacrylate (PMMA). High–pressure is an effective physical means to adjust the interparticle spacing of QDs, which may artificially expand the application of QDs further. The results under high–pressure indicate that it is the reduced interparticle spacing rather than the enhanced quantum confinement effect with volume compression that has a stronger effect on exciton relaxation of CdSe/ZnS–QDs. This work is hoped to help us further understand the effect of interparticle spacing among QDs in various integrated environments.

Enhancement of Neel Relaxation at Magnetic Heating Performance of Iron Oxide Nanoparticles

The study is based on understand the titanium (Ti) doping effect to enhance the Neel relaxation at magnetic heating performance of magnetite (Fe3O4). Ti doped magnetite ((Fe1-x,Tix)3O4; x= 0.02, 0.03 and 0.05) superparamagnetic nanoparticles were synthesized via sol-gel technique. The analyses were performed for (Fe1-x,Tix)3O4 and core-shell (SiO2 coated (Fe1-x,Tix)3O4) nanoparticles in order to understand the influence of silica coating on the magnetic properties of nanoparticles. The target of study to enhance the Neel relaxation mechanism on magnetic heating. The interparticle spacing and Ti amount were two parameters that we focused on the study. The results provided that coating with SiO2 has no specific effect on heating performance of (Fe1-x,Tix)3O4 nanoparticles. While the increase in temperature (ΔT) under 150 kHz RF signal reached up to 22oC in 10 minutes for SiO2 coated (Fe0.97,Ti0.03)3O4 nanoparticles, which was very close value of uncoated Fe3O4 nanoparticles.

Evaluation of Stationary Creep Rate in Heat-Affected Zone of Martensitic 9–12% Cr Steels

The purpose of the present study was to evaluate the contribution of distinct regions of the simulated heat-affected zone (HAZ) to the overall creep behavior of welded joints in the X20 and P91 steels. The HAZ was simulated by means of dilatometry at four peak temperatures (900, 1000, 1200, and 1350 °C) with a consequent tempering at 650 °C. Microstructure features of the four simulated HAZ regions including precipitates, prior austenite grains, and subgrains were quantified by means of electron microscopy. The quantified parameters and the measured hardness were used in three physical models for evaluation of the stationary creep rate (ε˙ at 170 MPa and 580 °C. The resulting ε˙ values fall within the range 10−8–10−7 s−1, being in good agreement with the experimental data with a similar thermal history, but an order of magnitude lower than the measured values for the parent metal of the studied steels (10−7–10−6 s−1). Depending on the model utilized, their output can be linearly related to hardness, subgrain size, or interparticle spacing. The model relating ε˙ to hardness was the most consistent one in prediction, being always lower for higher peak temperatures.

Multilayer Diffraction Reveals That Colloidal Superlattices Approach the Structural Perfection of Single Crystals

Colloidal superlattices are fascinating materials made of ordered nanocrystals, yet they are rarely called “atomically precise.” That is unsurprising, given how challenging it is to quantify the degree of structural order in these materials. However, once that order crosses a certain threshold, constructive interference of X-rays diffracted by the nanocrystals dominates the diffraction pattern, offering a wealth of structural information. By treating nanocrystals as scattering sources forming a self-probing interferometer, we developed a multilayer diffraction method that enabled the accurate determination of nanocrystal size, interparticle spacing, and their fluctuations for samples of self-assembled CsPbBr₃ and PbS nanomaterials. The average nanocrystal displacement of 0.32-1.4 Å in the studied superlattices provides a figure of merit for their structural perfection and approaches the atomic displacement parameters found in traditional crystals. The method requires a laboratory-grade diffractometer and an open-source fitting algorithm for data analysis, providing a competitive alternative to resource-intensive synchrotron experiments.

Multilayer Diffraction Reveals That Colloidal Superlattices Approach the Structural Perfection of Single Crystals

Colloidal superlattices are fascinating materials made of ordered nanocrystals, yet they are rarely called “atomically precise.” That is unsurprising, given how challenging it is to quantify the degree of structural order in these materials. However, once that order crosses a certain threshold, constructive interference of X-rays diffracted by the nanocrystals dominates the diffraction pattern, offering a wealth of structural information. By treating nanocrystals as scattering sources forming a self-probing interferometer, we developed a multilayer diffraction method that enabled the accurate determination of nanocrystal size, interparticle spacing, and their fluctuations for samples of self-assembled CsPbBr₃ and PbS nanomaterials. The average nanocrystal displacement of 0.32-1.4 Å in the studied superlattices provides a figure of merit for their structural perfection and approaches the atomic displacement parameters found in traditional crystals. The method requires a laboratory-grade diffractometer and an open-source fitting algorithm for data analysis, providing a competitive alternative to resource-intensive synchrotron experiments.

An agent-based approach for modelling collective dynamics in animal groups distinguishing individual speed and orientation

Collective dynamics in animal groups is a challenging theme for the modelling community, being treated with a wide range of approaches. This topic is here tackled by a discrete model. Entering in more details, each agent, represented by a material point, is assumed to move following a first-order Newtonian law, which distinguishes speed and orientation. In particular, the latter results from the balance of a given set of behavioural stimuli, each of them defined by a direction and a weight, that quantifies its relative importance. A constraint on the sum of the weights then avoids implausible simultaneous maximization/minimization of all movement traits. Our framework is based on a minimal set of rules and parameters and is able to capture and classify a number of collective group dynamics emerging from different individual preferred behaviour, which possibly includes attractive, repulsive and alignment stimuli. In the case of a system of animals subjected only to the first two behavioural inputs, we also show how analytical arguments allow us to a priori relate the equilibrium interparticle spacing to critical model coefficients. Our approach is then extended to account for the presence of predators with different hunting strategies, which impact on the behaviour of a prey population. Hints for model refinement and applications are finally given in the conclusive part of the article. This article is part of the theme issue ‘Multi-scale analysis and modelling of collective migration in biological systems’.