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Phys. Sci. Forum, 2023, ICPSDREE 2022

The 1st International Conference on Physics of Semiconductor Devices, Renewable Energies and Environment

Bechar, Algeria | 14–16 November 2022

Volume Editor:
Mebarka Daoudi, University of Bechar, Algeria

Number of Papers: 9
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Cover Story (view full-size image): The first international conference on Physics of Semiconductor Devices, Renewable Energies and Environment (ICPSDREE) is a virtual and physical scientific conference organized by the faculty of Exact [...] Read more.
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Editorial

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1 pages, 174 KiB  
Editorial
Statement of Peer Review
by Mebarka Daoudi, Syham Kadri, Youcef Himri, Mohamed Bensafi and Abdelkarim Talhi
Phys. Sci. Forum 2023, 6(1), 8; https://doi.org/10.3390/psf2023006008 - 13 Oct 2023
Viewed by 672
Abstract
In submitting conference proceedings to Physical Sciences Forum, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors [...] Full article
6 pages, 2521 KiB  
Editorial
Preface of the First International Conference on Physics of Semiconductor Devices, Renewable Energies, and Environment
by Mebarka Daoudi, Syham Kadri, Youcef Himri, Mohamed Bensafi and Abdelkarim Talhi
Phys. Sci. Forum 2023, 6(1), 9; https://doi.org/10.3390/psf2023006009 - 13 Oct 2023
Viewed by 1122
Abstract
The University of Bechar, Algeria, held an international conference on physics, renewable energies, and environment (ICPSDREE) from 14 to 16 November 2022 [...] Full article
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Research

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2 pages, 2168 KiB  
Abstract
Geothermal Energy in Algeria and the Contribution of Geophysics
by Leila Aliouane and Sid-Ali Ouadfeul
Phys. Sci. Forum 2023, 6(1), 2; https://doi.org/10.3390/psf2023006002 - 27 Mar 2023
Viewed by 1753
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Geothermal energy is one of the cleanest, most accessible and cheapest alternative energies in the whole world [...] Full article
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2 pages, 191 KiB  
Abstract
Methods and Interests of Bioelectric Impedance in Medical Practice
by Lotfi Rahal
Phys. Sci. Forum 2023, 6(1), 3; https://doi.org/10.3390/psf2023006003 - 18 Apr 2023
Viewed by 1080
Abstract
The development of new tools of functional explorations in medicine revolutionized the means of the diagnosis of different pathologies and allowed a clear improvement of the patients’ management [...] Full article

Other

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8 pages, 1548 KiB  
Proceeding Paper
Heating Kinetics of Gold Nanoparticles in Biological Tissues with a Femtosecond Laser
by Selma Mediene and Assia Rachida Senoudi
Phys. Sci. Forum 2023, 6(1), 1; https://doi.org/10.3390/psf2023006001 - 24 Mar 2023
Viewed by 1495
Abstract
This work deals with a numerical study of the different thermal processes in a gold nanoparticle heated with a femtosecond pulse laser and cooled in different biological tissues, such as healthy human prostate, blood, fat, tumor prostate, skin and protein myoglobin. A 40 [...] Read more.
This work deals with a numerical study of the different thermal processes in a gold nanoparticle heated with a femtosecond pulse laser and cooled in different biological tissues, such as healthy human prostate, blood, fat, tumor prostate, skin and protein myoglobin. A 40 nm diameter gold nanoparticle is heated using a femtosecond pulse laser with a duration of 85 fs and a fluence of 1.4 J/m2. A two-temperature model is used to describe the dynamics of the exchange of energy between the electron gas and the phononic lattice in addition to Fourier’s law and the relationship between the thermal conductivity of the external medium and the temperature. The temperature of the external medium near the nanoparticle surface was computed, and the effect of the laser energy was reported. Full article
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8 pages, 2266 KiB  
Proceeding Paper
Development of a Mathematical Model Based on an Artificial Neural Network (ANN) to Predict Nickel Uptake Data by a Natural Zeolite
by Boukhari Mehdi, Daouia Brahmi-Ingrachen, Hayet Belkacemi and Laurence Muhr
Phys. Sci. Forum 2023, 6(1), 4; https://doi.org/10.3390/psf2023006004 - 25 Apr 2023
Cited by 1 | Viewed by 1957
Abstract
In this investigation, an artificial-neural-network-based mathematical model was developed for the prediction of nickel adsorption data. As input variables, the initial concentration, adsorbent dosage, and pH of the nickel solution were chosen, while the removal efficiency was chosen as an output variable. The [...] Read more.
In this investigation, an artificial-neural-network-based mathematical model was developed for the prediction of nickel adsorption data. As input variables, the initial concentration, adsorbent dosage, and pH of the nickel solution were chosen, while the removal efficiency was chosen as an output variable. The hyperparameters were optimized to determine the perfect topology for the model. The study demonstrated that the 3-2-1 ANN architecture was the most suitable topology. The determination coefficient of 0.98 and the mean squared error of 0.02 indicated the high performance of the developed model, which was successfully applied for isotherm data prediction. Full article
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8 pages, 5097 KiB  
Proceeding Paper
Impact of Artificial Intelligence in Renewable Energy Management of Hybrid Systems
by Benhammou Aissa, Tedjini Hamza, Guettaf Yacine and Hartani Mohamed Amine
Phys. Sci. Forum 2023, 6(1), 5; https://doi.org/10.3390/psf2023006005 - 24 May 2023
Cited by 2 | Viewed by 1280
Abstract
The field of energy is of great interest for development, especially in the transportation industry. This paper investigates a hybrid electric vehicle (HEV) with two-wheel drives powered by a fuel cell, battery, DC generators, and supercapacitors. Each energy source is connected to a [...] Read more.
The field of energy is of great interest for development, especially in the transportation industry. This paper investigates a hybrid electric vehicle (HEV) with two-wheel drives powered by a fuel cell, battery, DC generators, and supercapacitors. Each energy source is connected to a specific controllable converter. The authors compared the energy management strategies of the Adaptive Neuro-Fuzzy Inference System (ANFIS) with classical energy management strategies. The proposed ANFIS method reduced hydrogen consumption by 8% compared to the classical approach, and improved efficiency to over 98%. The primary objective of this work is to demonstrate the impact of artificial intelligence in renewable energy management strategies (EMSs), with the aim of improving system performance as much as possible by comparing it with classical methods such as state machine (SM) and PI strategies. Full article
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12 pages, 9135 KiB  
Proceeding Paper
Robust Frequency-Decoupling-Based Power Split of Battery/Supercapacitor Hybrid Energy Storage Systems in DC Microgrids
by Mohamed Amine Hartani, Messaoud Hamouda, Othmane Abdelkhalek, Aissa Benhamou, Bouchaib Ali and Saad Mekhilef
Phys. Sci. Forum 2023, 6(1), 6; https://doi.org/10.3390/psf2023006006 - 21 Jun 2023
Cited by 3 | Viewed by 1001
Abstract
A frequency-decoupling-based power split was used in this study to manage a direct-current microgrid (DC-MG)-based PV and hybridized energy storage system (HESS), which consisted of a battery and a supercapacitor. The HESS control integrated a dual-loop structure for bus voltage regulation and recovery [...] Read more.
A frequency-decoupling-based power split was used in this study to manage a direct-current microgrid (DC-MG)-based PV and hybridized energy storage system (HESS), which consisted of a battery and a supercapacitor. The HESS control integrated a dual-loop structure for bus voltage regulation and recovery and HESS charge/discharge control. Hysteresis current control (HCC) tracked the supercapacitor setpoint current using low-pass filtering (LPF) control. The system reliability was assessed using pulsing, smooth, and disturbed PV and load waveforms with standard and advanced LPF methods. The Matlab simulation results confirmed a superior HESS control performance under varying resource waveforms. Key performance indexes (KPIs) were used to evaluate the bus voltage, HESS current management, loading efficiency, and loading mismatch. Full article
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7 pages, 2798 KiB  
Proceeding Paper
Effect of Sn Doping on the Photocatalytic Properties of ZnO
by Fayssal Boufelgha, Rahima Zellagui, Mohamed-Cherif Benachour, Heider Dehdouh, Fayçal Labrèche and Nourddine Brihi
Phys. Sci. Forum 2023, 6(1), 7; https://doi.org/10.3390/psf2023006007 - 17 Aug 2023
Viewed by 1111
Abstract
In this work, we synthesized solutions of un-doped ZnO and ZnO doped with tin (Sn) by the sol-gel method. From these solutions, we deposited thin layers on glass substrates by the spin-coating technique. The main purpose of this work is to study the [...] Read more.
In this work, we synthesized solutions of un-doped ZnO and ZnO doped with tin (Sn) by the sol-gel method. From these solutions, we deposited thin layers on glass substrates by the spin-coating technique. The main purpose of this work is to study the influence of the incorporation of Sn into the ZnO matrix on the photocatalytic properties of the latter. The crystal structure is hexagonal with a preferential orientation of the crystallites (002), and the reduction in the size of the grains is observed from 21 nm for the un-doped ZnO to 15 nm for the doped ZnO. For both samples, the transparency in the visible region is high and exceeds 75%, and a slight change in the band gap is from 3.22 to 3.23 eV, i.e., it is attributed to a combination of the Burstein–Moss effect and electron-impurity scattering. The methylene blue UV photocatalysis test gives a degradation rate of 40% for un-doped ZnO and 60% for Sn-doped ZnO (2%). This study confirms the remarkable influence of Sn doping on the photocatalytic properties of ZnO and also on its morphological and optical properties. Full article
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