Coherent Dynamics in Solutions of Colloidal Plexcitonic Nanohybrids at Room Temperature

The increasing ability to prepare systems with nanoscale resolution and address their optical properties with ultrashort time precision is revealing quantum phenomena with tremendous potential in quantum nanotechnologies. Colloidal plexcitonic materials promise to play a pivotal role in this scenario. Plexcitons are hybrid states originating from the mixing of the plasmon resonances of metal nanostructures with molecular excitons. They allow nanoscale confinement of electromagnetic fields and the establishment of strong couplings between light and matter, potentially giving rise to controllable and tunable coherent phenomena. However, the characterization of the ultrafast coherent and incoherent dynamics of colloidal plexciton nanohybrids remains highly unexplored. Here, two dimensional electronic spectroscopy (2DES) is employed to study the quantum coherent interactions active after the photoexcitation of these systems. By comparing the response of the nanohybrids with the one of the uncoupled systems, the nonlinear photophysical processes at the base of the coherent dynamics are identified, allowing a step forward toward the effective understanding and exploitation of these nanomaterials

Reconstructing Bioinvasion Dynamics Through Micropaleontologic Analysis Highlights the Role of Temperature Change as a Driver of Alien Foraminifera Invasion

Invasive alien species threaten biodiversity and ecosystem structure and functioning, but incomplete assessments of their origins and temporal trends impair our ability to understand the relative importance of different factors driving invasion success. Continuous time-series are needed to assess invasion dynamics, but such data are usually difficult to obtain, especially in the case of small-sized taxa that may remain undetected for several decades. In this study, we show how micropaleontologic analysis of sedimentary cores coupled with radiometric dating can be used to date the first arrival and to reconstruct temporal trends of foraminiferal species, focusing on the alien Amphistegina lobifera and its cryptogenic congener A. lessonii in the Maltese Islands. Our results show that the two species had reached the Central Mediterranean Sea several decades earlier than reported in the literature, with considerable implications for all previous hypotheses of their spreading patterns and rates. By relating the population dynamics of the two foraminifera with trends in sea surface temperature, we document a strong relationship between sea warming and population outbreaks of both species. We conclude that the micropaleontologic approach is a reliable procedure for reconstructing the bioinvasion dynamics of taxa having mineralized remains, and can be added to the toolkit for studying invasions

Tailoring the pressure-drop in multi-layered open-cell porous inconel structures

This study investigates the pressure-drop behaviour associated with airflow through bulk and structurally tailored multi-layered, open-cell porous Inconel structures over a wide airflow velocity range (0–50 m s-1). The effect of airflow velocity on the pressure-drop behaviour as a function of the sample thickness is presented and related to the flow behaviour corresponding to the relevant flow regimes (Darcy, Forchheimer, Turbulent and Postturbulent). Entrance effects are highlighted as a source of the pressure-drop increase for porous structures with air gaps, regardless of their sizes, as long as they are larger than those generated by loosely-stacked structures. The pressure-drops for gapped porous structures and the mathematical-summation of the pressure drop for the corresponding individual components, were in very good agreement, at lower airflow velocities. The potential for mass-efficient porous structures, providing a high pressure drop, was demonstrated using multiple thin porous laminates separated by air gaps

A framework for data regression of heat transfer data using machine learning

Data availability: The data that has been used is confidential.Machine Learning (ML) algorithms are emerging in various industries as a powerful complement/alternative to traditional data regression methods. A major reason is that, unlike deterministic models, they can be used even in the absence of detailed phenomenological knowledge. Not surprisingly, the use of ML algorithms is being explored also in heat transfer applications. It is of particular interest in systems dealing with complex geometries and underlying phenomena (e.g. fluid phase change, multi-phase flow, heavy fouling build-up). However, heat transfer systems present specific challenges that need addressing, such as the scarcity of high-quality data, the inconsistencies across published data sources, the complex (and often correlated) influence of inputs, the split of data between training and testing sets, and the limited extrapolation capabilities to unseen conditions. In an attempt to help overcome some of these challenges and, more importantly, to provide a systematic approach, this article reviews and analyses past efforts in the application of ML algorithms to heat transfer applications, and proposes a regression framework for their deployment to estimate key quantities (e.g. heat transfer coefficient), to be used for improved design and operation of heat exchangers. The framework consists of six steps: i) data pre-treatment, ii) feature selection, iii) data splitting philosophy, iv) training and testing, v) tuning of hyperparameters, and vi) performance assessment with specific indicators, to support the choice of accurate and robust models. A relevant case study involving the estimation of the condensation heat transfer coefficient in microfin tubes is used to illustrate the proposed framework. Two data-driven algorithms, Deep Neural Networks and Random Forest, are tested and compared in terms of their estimation and extrapolation capabilities. The results show that ML algorithms are generally more accurate in predicting the heat transfer coefficient than a well-known semi-empirical correlation proposed in past studies, where the mean absolute error of the most suitable ML model is 535 [Wm2K-1], compared to the error using the correlation of 1061 [Wm2K-1]. In terms of extrapolation, the selected ML model has a mean absolute error of 1819 [Wm2K-1], while for the correlation is 1111 [Wm2K-1], indicating a disadvantage of the use of semi-empirical models, although the comparison was not entirely suitable, given that the correlation was used as is and no training was done. In addition, feature selection enables simpler models that depend only on features that are potentially most related to the target variable. Special attention is needed however, as overfitting and limited extrapolation capabilities are common difficulties that are encountered when deploying these models.Hexxcell Ltd

When ring makes the difference: coordination properties of Cu2+/Cu+ complexes with sulfur-pendant polyazamacrocycles for radiopharmaceutical applications

Three polyazamacrocyclic ligands, i.e. 1,5,9-tris[2-(methylsulfanyl)ethyl]-1,5,9-triazacyclododecane (TACD3S), 1,4,7,10-tetrakis[2-(methylsulfanyl)ethyl]-1,4,7,10-tetrazacyclotridecane (TRI4S) and 1,4,8,11-tetrakis[2-(methylsulfanyl)ethyl]-1,4,8,11-tetrazacyclotetradecane (TE4S), were considered as potential chelators for the medically relevant copper radioisotopes. The ligands have been synthesized through facile, single-step reactions, and their acidity constants have been measured in aqueous solution at 25 degrees C. The kinetic, thermodynamic, electrochemical and structural properties of their Cu2+ and Cu+ complexes were investigated in aqueous solution at 25 degrees C using spectroscopic (UV-Visible, EPR, NMR) and electrochemical techniques (pH-potentiometric titrations, cyclic voltammetry and electrolysis). TACD3S was demonstrated to be unable to stabilize Cu2+, whereas for TRI4S and TE4S the formation of stable monocupric (CuL2+) and monocuprous (CuL+) complexes was detected. TRI4S coordinates Cu(2+)via a [4N] and a [4N]S array of donor atoms while with TE4S only the latter geometry exists. The thermodynamic stability and the kinetic inertness of the copper complexes formed by TACD3S, TRI4S and TE4S were compared with those previously reported for 1,4,7,10-tetrakis-[2-(methylsulfanyl)ethyl]-1,4,7,10-tetrazacyclododecane (DO4S) to unravel the influence of the ring size and the nitrogen donor array on the copper chelation properties of these sulfur-rich macrocycles. The copresence of four nitrogen atoms is an essential feature to allow effective copper coordination when a 12-member ring is employed, as the Cu2+-DO4S complexes were far more stable than those of Cu2+-TACD3S. Furthermore, the larger ring size of TRI4S and TE4S, when compared to DO4S, progressively increases the rate of the Cu2+ complexation reactions but decreases the thermodynamic stability of the Cu2+ complexes. Despite this, the ability of TRI4S and TE4S to stably accommodate both copper oxidation states makes them very attractive for application in nuclear medicine as they could avoid the demetallation after the biologically triggered Cu2+/Cu+ reduction

Experimental investigation of pressure-drop characteristics across multi-layer porous metal structures

This study investigates the effect of airflow (in the range of 0–70 m s-1) on the pressure-drop characteristics for a novel multi-layered, nickel-based porous metal, as a function of thickness (affected by sectioning) and density (affected by compression). In addition to generating unique data for these materials, the study highlights the need for precise pinpointing of the different flow regimes (Darcy, Forchheimer and Turbulent) in order to enable accurate determination of the permeability (K) and form drag coefficient (C) defined by the Forchheimer equation and to understand the complex dependence of length-normalised pressure drop on sample thickness

Lung fibrosis quantified by HRCT in scleroderma patients with different disease forms and ANA specificities

Objective: to define the prevalence of interstitial lung fibrosis in systemic sclerosis (SSc) and its relationship with the different clinical forms of disease and ANA specificities. Methods: fifty patients with SSc were submitted to pulmonary high resolution computed tomography (HRCT). Lung abnormalities were evaluated according to Warrick's score that considers both the severity and the extent of fibrotic lesions. Results: pulmonary HRCT abnormalities were observed in 84% of SSc patients. Ground glass aspects (60%), irregular pleural margins (56%) and septal/subpleural lines (68%) were the most common lesions. The distribution of these abnormalities favoured the posterior basilar segments of both lungs. HRCT findings were significantly more frequent in males and in patients with the cutaneous diffuse form of SSc and with the specific antibody anti-Scl70. Conclusions: HRCT is a very useful method for the diagnosis of interstitial lung fibrosis in SSc. Warrick's score permits to quantify the HRCT findings and to evaluate their relationship with the disease clinical forms and ANA specificities

The contact angle of nanofluids as thermophysical property

Droplet volume and temperature affect contact angle significantly. Phase change heat transfer processes of nanofluids – suspensions containing nanometre-sized particles – can only be modelled properly by understanding these effects. The approach proposed here considers the limiting contact angle of a droplet asymptotically approaching zero-volume as a thermophysical property to characterise nanofluids positioned on a certain substrate under a certain atmosphere. Graphene oxide, alumina, and gold nanoparticles are suspended in deionised water. Within the framework of a round robin test carried out by nine independent European institutes the contact angle of these suspensions on a stainless steel solid substrate is measured with high accuracy. No dependence of nanofluids contact angle of sessile droplets on the measurement device is found. However, the measurements reveal clear differences of the contact angle of nanofluids compared to the pure base fluid. Physically founded correlations of the contact angle in dependency of droplet temperature and volume are obtained from the data. Extrapolating these functions to zero droplet volume delivers the searched limiting contact angle depending only on the temperature. It is for the first time, that this specific parameter, is understood as a characteristic material property of nanofluid droplets placed on a certain substrate under a certain atmosphere. Together with the surface tension it provides the foundation of proper modelling phase change heat transfer processes of nanofluids