In the paper a computational study of the electrocaloric effect is presented for a cubic nanocluster consisting of 8 sites. The system of interest is described by means of an extended Hubbard model in external electric field at half filling of the energy levels. The thermodynamic description is obtained within canonical ensemble formalism on the basis of exact numerical diagonalization of the system Hamiltonian. In particular, the entropy and the specific heat are determined as a function of temperature and external electric field. The electrocaloric effect is described quantitatively by isothermal entropy change. The behaviour of this quantity is thoroughly analysed as a function of extended Hubbard model parameters, temperature and electric field variation magnitude. The existence of direct and inverse electrocaloric effect is predicted for some range of model parameters. A high sensitivity to Hubbard model parameters is shown, what paves the way towards controlling and tuning the effect. A non-linear, quadratic dependence of isothermal entropy change on electric field variation magnitude is demonstrated. The potential for applications of electrocaloric effect in strongly correlated nanoclusters is shown.
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http://dx.doi.org/10.1038/s41598-018-23443-x | DOI Listing |
ChemSusChem
January 2025
CSIR Central Glass & Ceramic Research Institute, EMDD, 196 Raja S C Mullick Road, 700032, Kolkata, INDIA.
The advancement of photocatalytic technology for solar-driven hydrogen (H2) production remains hindered by several challenges in developing efficient photocatalysts. A key issue is the rapid recombination of charge carriers, which significantly limits the light-harvesting ability of materials like BiOCl and Cu2SnS3 quantum dots (CTS QDs), despite the faster charge mobility and quantum confinement effect, respectively. Herein, a BiOCl/CTS (BCTS) heterostructure was synthesized by loading CTS QDs onto BiOCl 2D nanosheets (NSs), that demonstrated excellent photocatalytic activity under visible light irradiation.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Chemistry, College of Science, King Saud University, PO Box 2455, Riyadh, 11541, Saudi Arabia.
The ongoing challenge of water pollution necessitates innovative approaches to remove organic contaminants from wastewater. In this work, new two-dimensional S-scheme heterojunction photocatalysts BiO/CdS and MoS/BiO/CdS that are intended for the effective photocatalytic destruction of 4-nitrophenol, a dangerous organic pollutant, are synthesized and characterized. Utilizing a solvothermal method, successfully generated these ternary nanocomposites, which were characterized through various techniques including X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), high resolution transmission electronmicroscopy (HRTEM), Brunauer-Emmett-Telle (BET) and diffuse reflectance spectroscopy (DRS).
View Article and Find Full Text PDFEnviron Res
January 2025
State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, P.R. China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, P.R. China.
Antibiotic resistant bacteria (ARB) and antibiotic resistant genes (ARGs) have become increasing concerning issues, threatening human health. Persulfate-based advanced oxidation processes (PS-AOPs), due to their remarkable potential in combating antibiotic resistance, have garnered significant attention in the field of disinfection in recent years. In this review, we systematically evaluated the efficacy and underlying mechanism of PS integration with various activation methods for the elimination of ARB/ARGs.
View Article and Find Full Text PDFMethods
January 2025
School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, Viet Nam. Electronic address:
In the field of medical science, skin segmentation has gained significant importance, particularly in dermatology and skin cancer research. This domain demands high precision in distinguishing critical regions (such as lesions or moles) from healthy skin in medical images. With growing technological advancements, deep learning models have emerged as indispensable tools in addressing these challenges.
View Article and Find Full Text PDFBrain Stimul
January 2025
State Key Laboratory of Advanced Medical Materials and Devices, Tianjin Key Laboratory of Neuromodulation and Neurorepair, Institute of Biomedical Engineering, Tianjin Institutes of Health Science, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300192, China; Neuroscience Center, Chinese Academy of Medical Sciences, Beijing, 102206, China. Electronic address:
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