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All Journal JOURNAL ONLINE OF PHYSICS Indonesian Journal of Chemistry Jurnal Ilmu dan Inovasi Fisika
Amalia, Wardah
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Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Electrical & Electronics Engineering Energy Environmental Science Materials Science & Nanotechnology Physics

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Strong Anisotropic Rashba Effect with Tunable Spin-Splitting in Two-Dimensional Janus Vanadium Dichalcogenides Monolayer Affandi, Yusuf; Absor, Moh. Adhib Ulil; Anshory, Muhammad; Amalia, Wardah
Indonesian Journal of Chemistry Vol 24, No 4 (2024)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijc.93543

Abstract

Motivated by the recent discovery of the Rashba effect in two-dimensional (2D) Janus Transition Metal Dichalcogenides (TMDs) systems, we explore the Rashba effect on the Janus VXY (X = S, Se, Y = Se, Te) monolayer. By employing first-principles density functional theory (DFT) calculations, we find a strong anisotropic Rashba splitting observed around Γ points in the first Brillouin zone. We analyze this anisotropy of Rashba splitting by using k·p perturbation theory synergized with group symmetry analysis. By giving the effect of the biaxial strain, we manipulate the characteristics of the Rashba splitting on the Janus Vanadium Dichalcogenides system. Through spin texture analysis, we reveal both the in-plane and out-of-plane components of the spin textures, providing further evidence for the anisotropic nature of the Rashba spin-orbit coupling (SOC). The observed tuneable Rashba splitting by applying the strain effect shows that the Janus Vanadium dichalcogenides system has the potential to be used as a semiconductor material for spintronic devices.
Integration of Fourier Series, Artficial Intelligence and Smart Sensors in HVAC Thermal Analysis : A Systematic Literature Review Vania, Amanda Asti; Akhsan, Hamdi; Putri, Arselly Rahmanda; Cahyani, Delvina Putri; Andriani, Nelly; Amalia, Wardah
JIIF (Jurnal Ilmu dan Inovasi Fisika) Vol 10, No 1 (2026)
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jiif.v10i1.68291

Abstract

HVAC (Heating, Ventilation, and Air Conditioning) systems play a crucial role in maintaining thermal comfort, air quality, and energy efficiency in buildings. This study aims to examine the contribution of Fourier series in HVAC thermal analysis and the integration of artificial intelligence (AI) and smart sensors to support energy optimization.The method used was a Systematic Literature Review (SLR) of scientific publications from 2019 to 2025 obtained from the ScienceDirect, IEEE, MDPI, and Academia databases. Articles that met the inclusion criteria were analyzed based on their objectives, methodologies, and research results, then grouped thematically. The results of the study showed that Fourier series are effective in representing periodic temperature signals, simplifying data complexity, and improving thermal prediction accuracy. Meanwhile, the integration of AI and smart sensors enables real-time responses, improved energy efficiency, and thermal comfort stability. The main challenges identified include limitations in experimental validation, the complexity of integrating Fourier–AI–sensors into a single framework, and the high computational requirements for large-scale implementation. Thus, it can be concluded that this study contributes to mapping current approaches and recommending research directions for the development of more efficient, adaptive, and sustainable data-driven and intelligent computing-based HVAC systems.Keywords: Artificial Intelligence (AI), Energy Efficiency, Fourier Series, HVAC, Smart Sensors
A SYSTEMATIC REVIEW OF BESSEL FUNCTION-BASED HEAT TRANSFER MODELING IN SEMI-CYLINDRICAL THERMAL ENERGY STORAGE AND THERMOELECTRIC GENERATORS Fatmawati, Fatmawati; Akhsan, Hamdi; Hayati, Suci Husnul; Aljuzza, Muhammad Ikhsan; Andriani, Nely; Amalia, Wardah
JOURNAL ONLINE OF PHYSICS Vol. 11 No. 2 (2026): JOP (Journal Online of Physics) Vol 11 No 2
Publisher : Prodi Fisika FST UNJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jop.v11i2.51132

Abstract

Heat transfer modeling in semi-cylindrical systems is crucial in the development of thermal energy storage (TES) and thermoelectric generator (TEG) technologies. This study aims to analyze the integration of Bessel functions and computational methods in thermal conduction modeling, as well as evaluate their effectiveness for thermal system optimization. The method used is Systematic Literature Review (SLR) with literature searches in ScienceDirect, MDPI, SpringerLink, arXiv, and DOAJ (2020–2025), followed by selection based on inclusion-exclusion criteria and thematic synthesis of 21 selected articles. The results show that Fourier–Bessel series-based semi-analytical solutions are capable of representing radial temperature distributions even under asymmetric boundary conditions, while hybrid approaches combining Bessel functions with the Finite Element Method (FEM) or Computational Heat Transfer (CHT) improve prediction accuracy and computational efficiency. Key challenges include sensitivity to material parameters, numerical instability, and high computational costs for nonlinear geometries. Practically, this approach can be utilized by renewable energy researchers and engineers to design semi-cylindrical TES and TEG systems with more uniform temperature distribution, higher storage capacity, and optimal thermoelectric conversion efficiency.
Co-Authors Absor, Moh. Adhib Ulil Aljuzza, Muhammad Ikhsan Andriani, Nelly Cahyani, Delvina Putri Fatmawati, Fatmawati Hamdi Akhsan Hayati, Suci Husnul Muhammad Anshory Nely Andriani, Nely Putri, Arselly Rahmanda Vania, Amanda Asti Yusuf Affandi