Efficiency of Energy Conversion in Thermoelectric Nanojunctions

Using first-principles approaches, this study investigated the efficiency of energy conversion in nanojunctions, described by the thermoelectric figure of merit $ZT$. We obtained the qualitative and quantitative descriptions for the dependence of $ZT$ on temperatures and lengths. A characteristic temperature: $T_{0}= \sqrt{\beta/\gamma(l)}$ was observed. When $T\ll T_{0}$, $ZT\propto T^{2}$. When $T\gg T_{0}$, $ZT$ tends to a saturation value. The dependence of $ZT$ on the wire length for the metallic atomic chains is opposite to that for the insulating molecules: for aluminum atomic (conducting) wires, the saturation value of $ZT$ increases as the length increases; while for alkanethiol (insulating) chains, the saturation value of $ZT$ decreases as the length increases. $ZT$ can also be enhanced by choosing low-elasticity bridging materials or creating poor thermal contacts in nanojunctions. The results of this study may be of interest to research attempting to increase the efficiency of energy conversion in nano thermoelectric devices.Comment: 2 figure

Effect of Thermoelectric Cooling in Nanoscale Junctions

We propose a thermoelectric cooling device based on an atomic-sized junction. Using first-principles approaches, we investigate the working conditions and the coefficient of performance (COP) of an atomic-scale electronic refrigerator where the effects of phonon's thermal current and local heating are included. It is observed that the functioning of the thermoelectric nano-refrigerator is restricted to a narrow range of driving voltages. Compared with the bulk thermoelectric system with the overwhelmingly irreversible Joule heating, the 4-Al atomic refrigerator has a higher efficiency than a bulk thermoelectric refrigerator with the same $ZT$ due to suppressed local heating via the quasi-ballistic electron transport and small driving voltages. Quantum nature due to the size minimization offered by atomic-level control of properties facilitates electron cooling beyond the expectation of the conventional thermoelectric device theory.Comment: 8 figure

First-principles quantum transport modeling of thermoelectricity in single-molecule nanojunctions with graphene nanoribbon electrodes

We overview nonequilibrium Green function combined with density functional theory (NEGF-DFT) modeling of independent electron and phonon transport in nanojunctions with applications focused on a new class of thermoelectric devices where a single molecule is attached to two metallic zigzag graphene nanoribbons (ZGNRs) via highly transparent contacts. Such contacts make possible injection of evanescent wavefunctions from ZGNRs, so that their overlap within the molecular region generates a peak in the electronic transmission. Additionally, the spatial symmetry properties of the transverse propagating states in the ZGNR electrodes suppress hole-like contributions to the thermopower. Thus optimized thermopower, together with diminished phonon conductance through a ZGNR/molecule/ZGNR inhomogeneous structure, yields the thermoelectric figure of merit ZT~0.5 at room temperature and 0.5<ZT<2.5 below liquid nitrogen temperature. The reliance on evanescent mode transport and symmetry of propagating states in the electrodes makes the electronic-transport-determined power factor in this class of devices largely insensitive to the type of sufficiently short conjugated organic molecule, which we demonstrate by showing that both 18-annulene and C10 molecule sandwiched by the two ZGNR electrodes yield similar thermopower. Thus, one can search for molecules that will further reduce the phonon thermal conductance (in the denominator of ZT) while keeping the electronic power factor (in the nominator of ZT) optimized. We also show how often employed Brenner empirical interatomic potential for hydrocarbon systems fails to describe phonon transport in our single-molecule nanojunctions when contrasted with first-principles results obtained via NEGF-DFT methodology.Comment: 20 pages, 6 figures; mini-review article prepared for the special issue of the Journal of Computational Electronics on "Simulation of Thermal, Thermoelectric, and Electrothermal Phenomena in Nanostructures", edited by I. Knezevic and Z. Aksamij

Digitalization of business functions under Industry 4.0

Despite the literature’s support that the main function to be affected by the Industry 4.0 movement will be the operations function, the rapid incorporation of new technologies under firms promises to affect each departments of the business dramatically. This chapter aims to highlight the role of each function within Industry 4.0. Moreover, the chapter will determine the actualized benefit of transitioning towards Industry 4.0, separate from the recognized benefits under the literature. In order to achieve this a content analysis was conducted on the 2017 annual activity reports of manufacturing firms listed on the Istanbul Stock Exchange (BIST). Out of the 178 listed manufacturing firms under BIST, only 20 were identified as transitioning towards Industry 4.0. Out of these 20 firms, 16 firms’ annual activity reports mentioned transitioning towards Industry 4.0 and addressed the outcome (benefits) of the applications. Items were subjected to a content analysis based on business functions (Theme 1), sub-categories of business functions (Theme 2) and the common actual benefit (Theme 3) by three different researchers. The unit of analysis, the identified benefits, were 232 items in total and spread across the operations (41%), strategic management (Cost and Competitive Advantage) (22%), technology and process development (15%), procurement and distribution (12%), human resources (8%) and marketing (2%) business functions

The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights

Standardizing convolutional filters that enhance specific structures and patterns in medical imaging enables reproducible radiomics analyses, improving consistency and reliability for enhanced clinical insights. Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking