A Method for Thermal Performance Characterization of Ultra-Thin Vapor Chambers Cooled by Natural Convection

Vapor chamber technologies offer an attractive approach for passive cooling in portable electronic devices. Due to the market trends in device power consumption and thickness, vapor chamber effectiveness must be compared with alternative heat spreading materials at ultrathin form factors and low heat dissipation rates. A test facility is developed to experimentally characterize performance and analyze the behavior of ultrathin vapor chambers that must reject heat to the ambient via natural convection. The evaporatorside and ambient temperatures are measured directly; the condenser-side surface temperature distribution, which has critical ergonomics implications, is measured using an infrared (IR) camera calibrated pixel-by-pixel over the field of view and operating temperature range. The high thermal resistance imposed by natural convection in the vapor chamber heat dissipation pathway requires accurate prediction of the parasitic heat losses from the test facility using a combined experimental and numerical calibration procedure. Solid metal heat spreaders of known thermal conductivity are first tested, and the temperature distribution is reproduced using a numerical model for conduction in the heat spreader and thermal insulation by iteratively adjusting the external boundary conditions. A regression expression for the heat loss is developed as a function of measured operating conditions using the numerical model. A sample vapor chamber is tested for heat inputs below 2.5 W. Performance metrics are developed to characterize heat spreader performance in terms of the effective thermal resistance and the condenser-side temperature uniformity. The study offers a rigorous approach for testing and analysis of new vapor chamber designs, with accurate characterization of their performance relative to other heat spreaders

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

Mind-muscle connection: effects of verbal instructions on muscle activity during bench press exercise

Different attentional foci may modify muscle activation during exercises. Our aim was to determine if it is possible to selectively activate the pectoralis major or triceps brachii muscles according to specific verbal instructions provided during the bench press exercise. 13 resistance-trained males (25.6\ub15.4 yrs, 182.7\ub19.1 cm, 86.4\ub19.7 kg) underwent an electromyographic signals acquisition of the sternocostal head, clavicular head of the pectoralis major, the anterior deltoid, and the long head of the triceps brachii (LT) during bench press exercise. Participants performed one non-instructed set (NIS) of 4 repetitions at 50% 1-repetition maximum (1-RM) and one NIS of 4 repetitions at 80% 1-RM. Four additional sets of 4 repetitions at 50% and 80% 1-RM were randomly performed with verbal instructions to isolate the chest muscles (chest instructed set, CIS) or to isolate the triceps muscles (triceps instructed set, TIS). Participants showed significantly higher LT activation during TIS compared to non-instructed set both at 50% (p=0.0199) and 80% 1-RM (p=0.0061) respectively. TIS elicited a significant (p=0.0250) higher activation of LT compared to CIS. Our results suggest that verbal instructions seem to be effective for increasing activity of the triceps brachii but not the pectoralis major during the bench press

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

nanoparticle deposition during cu water nanofluid pool boiling

The present research activity aims to rigorously investigate nanofluid pool boiling in order to definitively assess this as a technique for controlled nanoparticle coating of surfaces, which can enhance the nucleate boiling performance. This paper presents preliminary nanoparticle deposition results obtained during Cu-water (0.13 wt%) nanofluid pool boiling on a smooth copper surface. The tests were run in an experimental setup designed expressly to study water and nanofluid pool boiling. The square test sample block (27.2 mm × 27.2 mm) is equipped with a rake of four calibrated T-type thermocouples each located in a 13.6-mm deep holes drilled every 5 mm from 1 mm below the top surface. The imposed heat flux and wall superheat can be estimated from measurement of the temperature gradient along the four thermocouples. The samples are characterized by scanning electron microscopy (SEM) to analyse the morphological characteristics of the obtained thin, Cu nanoparticle coating

Di-μ-chlorido-bis­{[2-({[2-(2-pyrid­yl)eth­yl](2-pyridylmeth­yl)amino}meth­yl)phenol]zinc(II)} bis­(perchlorate) dihydrate

The title compound, [Zn2Cl2(C20H21N3O)2](ClO4)2·2H2O, consists of a dinuclear ZnII cationic complex, two disordered perchlorate anions and two water mol­ecules as solvate. The [Zn2(μ-Cl)2(HL)2]2+ cation [HL is 2-({[2-(2-pyrid­yl)eth­yl](2-pyridylmeth­yl)amino}meth­yl)phenol] has a centrosymmetric structure with the ZnII ions in a distorted octa­hedral environment surrounded by an N3OCl2 donor set. HL acts as a tetra­dentate ligand through three N atoms from one amine group and two pyridyl arms and one O atom from the phenolic arm. The three N-donor sites of the HL ligand are arranged in meridional fashion, with the pyridine rings coordinated in trans positions with respect to each other. Consequently, the amine and phenol groups are trans to the asymmetric di-μ-chlorido exogenous bridges. A polymeric chain is formed along [010] by C(12)R 4 2(8) inter­molecular hydrogen bonding. The perchlorate anion is disordered and was modelled by two sites in a 0.345 (18):0.655 (18) ratio. Water–perchlorate O—H⋯O inter­actions form cyclic structures, while phenol–water O—H⋯O inter­actions generate an infinite chain. In addition, weak inter­molecular C—H⋯π(Ph) inter­actions between pyridine donor and phenol acceptor groups of neighboring cations build a two-dimensional polymeric structure parallel to (110)

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

Agglutination of benthic foraminifera in relation to mesoscale bathymetric features in the abyssal NE Atlantic (Porcupine Abyssal Plain)

Abyssal hills, small topographic features rising above the abyssal seafloor (< 1000 m altitude), have distinct environmental characteristics compared to abyssal plains, notably the presence of coarser-grained sediments. As a result, they are a major source of habitat heterogeneity in the deep sea. The aim of this study was to investigate whether there is a link between abyssal hills and the test characteristics of selected agglutinated benthic foraminiferal species. We analysed 1) the overall morphometry, and 2) the granulometric and chemical (elemental) characteristics of the agglutinated tests of ten common foraminiferal species (Adercotryma glomerata, Ammobaculites agglutinans, Cribrostomoides subglobosus, Lagenammina sp.1, Nodulina dentaliniformis, Portatrochammina murrayi, three Reophax sp. and Recurvoides sp. 9) at four sites (two on top of abyssal hills and two on the adjacent plain) in the area of the Porcupine Abyssal Plain Sustained Observatory, northeast Atlantic. The foraminiferal test data were compared with the particle size distribution and elemental composition of sediments from the study sites in order to explore possible grain size and mineral selectivity. We found differences in the visual appearance of the tests (i.e. the degree of irregularity in their shape), which was confirmed by morphometric analyses, related to seafloor topography. The agglutinated foraminifera selected different sized particles on hills and plains, reflecting the distinct granulometric characteristics of these settings. These characteristics (incorporation of coarse particles, test morphometry) could provide evidence for the recognition of ancient abyssal hill environments, as well as other palaeoceanographic settings that were characterised by enhanced current flow. Furthermore, analyses of sediment samples from the hill and plain sites using wavelength dispersive X-ray fluorescence (WD-XRF) yielded different elemental profiles from the plains, probably a result of winnowing on the hills, although all samples were carbonate-rich. In contrast, the majority of the agglutinated tests were rich in silica, suggesting a preferential selection for quartz

Mind-muscle connection: effects of verbal instructions on muscle activity during bench press exercise

Different attentional foci may modify muscle activation during exercises. Our aim was to determine if it is possible to selectively activate the pectoralis major or triceps brachii muscles according to specific verbal instructions provided during the bench press exercise. 13 resistance-trained males (25.6±5.4 yrs, 182.7±9.1 cm, 86.4±9.7 kg) underwent an electromyographic signals acquisition of the sternocostal head, clavicular head of the pectoralis major, the anterior deltoid, and the long head of the triceps brachii (LT) during bench press exercise. Participants performed one non-instructed set (NIS) of 4 repetitions at 50% 1-repetition maximum (1-RM) and one NIS of 4 repetitions at 80% 1-RM. Four additional sets of 4 repetitions at 50% and 80% 1-RM were randomly performed with verbal instructions to isolate the chest muscles (chest instructed set, CIS) or to isolate the triceps muscles (triceps instructed set, TIS). Participants showed significantly higher LT activation during TIS compared to non-instructed set both at 50% (p=0.0199) and 80% 1-RM (p=0.0061) respectively. TIS elicited a significant (p=0.0250) higher activation of LT compared to CIS. Our results suggest that verbal instructions seem to be effective for increasing activity of the triceps brachii but not the pectoralis major during the bench press