Local hybrid functionals are evaluated in linear-response TDDFT computations for a broad range of excited-state properties including excited-state structures, fluorescence, and phosphorescence energies and the vibronic shape of absorption and phosphorescence spectra. Computation of such properties requires the optimization of excited states, which is facilitated by the recent implementation of excited-state gradients for local hybrid functionals in the TURBOMOLE program (Grotjahn, R.; Furche, F.; Kaupp, M. 2019, 15, 5508). Comparison with coupled-cluster reference values reveals competitive performance of local hybrids for excited-state bond lengths with particular advantages for carbon-halogen, carbon-carbon, and carbon-nitrogen bonds. As with most global and range-separated hybrid functionals, carbonyl and thionyl bonds in → π* excited states are found to be too compact. For the emission energies, results depend on the multiplicity of the excited state. While the local hybrid functionals tested perform moderately well, comparable to global hybrids, for singlet states (fluorescence energies), they provide outstanding accuracy for triplet states (phosphorescence energies), only matched by those from the highly empirical M06-2X hybrid functional. The assessment of the shape of vibronic spectra reveals rather small differences between local hybrid functionals and conventional hybrid functionals with comparable exact-exchange admixture. The advantages for phosphorescence energies and the robust performance for the shape of vibronic spectra are combined to showcase the potential of local hybrid functionals for the prediction of phosphorescence spectra.
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December 2024
Department of Information Security, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India.
In Internet of Things (IoT) networks, identifying the primary Medium Access Control (MAC) layer protocol which is suited for a service characteristic is necessary based on the requirements of the application. In this paper, we propose Energy Efficient and Group Priority MAC (EEGP-MAC) protocol using Hybrid Q-Learning Honey Badger Algorithm (QL-HBA) for IoT Networks. This algorithm employs reinforcement agents to select an environment based on predefined actions and tasks.
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December 2024
Industrial and Systems Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.
The framework of the methodology presented in this study is an effort to integrate and optimize the agro-industry sector, especially energy in biogas. In this study, the technique of the system in functional analysis is shown systematically to translate various energy requirements in the factory as criteria for performance and functional design to be integrated, optimized, and energy efficient. The case study results indicated that biogas power plants, with a capacity of 1.
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December 2024
School of Materials Science and Engineering, Liaocheng University, Liaocheng, 252059, Shandong, China.
The welding of titanium alloys is an important topic in today's industrial field, and the interaction between the solder and the base material is crucial for the quality of the welded parts. The structural, elastic, electronic, and thermal properties of Ti-Al-Me (Me = Cu, Fe and Ni) alloys (TAMs) with the face-centered cubic structures were investigated using plane-wave pseudo potential method in the framework of density functional theory. Based on the calculated elastic constants combined with empirical and semi-empirical formulas, physical properties including ductility/brittleness, hardness and anisotropy were calculated.
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December 2024
Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran.
Surface electromyography (sEMG) data has been extensively utilized in deep learning algorithms for hand movement classification. This paper aims to introduce a novel method for hand gesture classification using sEMG data, addressing accuracy challenges seen in previous studies. We propose a U-Net architecture incorporating a MobileNetV2 encoder, enhanced by a novel Bidirectional Long Short-Term Memory (BiLSTM) and metaheuristic optimization for spatial feature extraction in hand gesture and motion recognition.
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December 2024
Innovative Global Program, Shibaura Institute of Technology, Tokyo, 135-8548, Japan.
This paper presents a novel and comprehensive control framework for the Rotary Inverted Pendulum (RIP), focusing on a hybrid control strategy that addresses the limitations of conventional methods in nonlinear and complex systems. The proposed controller synergistically combines an Optimized Fuzzy Logic Controller (OFLC) with Sliding Mode Control (SMC), leveraging the strengths of both techniques to achieve superior performance. The integration of Particle Swarm Optimization (PSO) into the OFLC significantly enhances its adaptability and precision, while the SMC law provides robust disturbance rejection and system stability.
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