Rigorous Numerical Simulations Research Articles

Integrative Enhancement of Energy‐Level Alignment and Defect Passivation for High‐Performance Lead‐Free Perovskite Solar Cells

AbstractCsGeI2Br‐based perovskites with a favorable bandgap and high absorption coefficient, show great promise as candidates for efficient lead‐free perovskite solar cells (PSCs). However, the significant defect recombination and energy alignment mismatch at the perovskite‐transport layer interface limit both the device's performance and long‐term stability. To overcome these challenges, the photovoltaic potential of the device is unlocked by optimizing the optical and electronic parameters through a rigorous numerical simulation, including the transport layer materials, doping density, bulk/interface defect density, and carrier mobility. As a result, the optimized device achieved a champion power conversion efficiency of 28.00%. To further elucidate the inherent physical behavior, the activator energy of carrier recombination, along with the conduction and valence band offsets, are also investigated. Additionally, different types of device structures, including p‐i‐n and HTL‐free structures, are briefly examined. Finally, a detailed roadmap for enhancing the efficiency of the device is proposed, offering valuable insights for improving inorganic lead‐free CsGeI2Br perovskite solar cells in optoelectronic applications.

Unlocking the solar potential: elevating open circuit voltage in kesterite CZTS thin film solar cells through cutting-edge SCAPS modeling

Abstract Kesterite-based CZTS thin-film solar cells are gaining recognition as a sustainable alternative to traditional photovoltaic technologies that rely on environmentally hazardous and costly absorber materials like c-Si, CdTe, and CIGS. The United Nations Sustainable Development Goals (UNSDGs) 7 (Affordable and Clean Energy) and 13 (Climate Action) are particularly relevant to CZTS technology. However, the efficiency of CZTS solar cells is currently constrained by the relatively low open circuit voltage (Voc), which remains a primary barrier to their widespread adoption. This study uses cutting-edge SCAPS modeling to identify and address CZTS solar cell Voc constraints. The study optimizes acceptor, donor, and neutral defect states, shunt resistance, and interface states to improve device performance. Optimizing these parameters improves Voc and power conversion efficiency using rigorous numerical simulations. By optimizing defect states, the proposed MoS2/CZTS/CdS/ZnO structure achieved an improved open-circuit voltage (Voc) of up to 1.10 V and an efficiency of up to 18.61%. This work makes solar energy more accessible and inexpensive by enhancing CZTS solar cell efficiency, especially in locations where conventional photovoltaic technologies are less practical due to economic or environmental constraints.

Analysis of Falling Block Characteristics in Salt Caverns Energy Storage Space

In the current global energy sector where energy storage technology is highly regarded, the development of storage technology is crucial. Utilizing specific underground space for the storage of oil and gas and other energy sources is the direction of future development, and the space formed by deep-salt-mine water dissolution extraction has gradually become the preferred choice. However, in actual operation, multi-layer salt cavities are prone to collapse of interlayer and bending of pipes, seriously affecting the progress, quality, and safety of the entire energy storage space construction. Therefore, based on relevant principles, a targeted experimental platform was established, by taking photos and measurements of the falling process of specific falling objects, simulating the situation of falling objects in actual energy storage spaces and their impact on related components. In-depth research was conducted on the probability of falling objects hitting the inner pipe and the horizontal impact force under different conditions, and the experimental results were verified by rigorous numerical simulation analysis. The research results show that falling objects impacts can cause related components to bend, with the maximum impact probability reaching 5.1% and the maximum horizontal impact force reaching 24.6 N. In addition, the hydraulic fluctuations caused by the suction and drainage of the cavity pipe column have a relatively small impact on the falling object trajectory. The research findings can provide practical and effective guidance for the safe construction of specific energy storage facilities, ensuring that construction can be carried out safely and efficiently, and contribute to the steady development of the energy storage industry as a whole.

Dynamic deadband intermittent event-triggered strategy for formation control of multiple unmanned surface vehicles

This paper focuses on the leaderless formation control of multiple unmanned surface vehicles (MUSVs) with external disturbances, communication interruptions, and model parametric uncertainties. Firstly, the auxiliary variables are introduced to transform MUSVs’ formation control into consensus achievement of these auxiliary variables. Then, to realize consensus of these auxiliary variables, the reference variables which can achieve the average consensus are defined based on the proposed dynamic deadband intermittent event-triggered mechanism (ETM). Superior to general dynamic ETMs, the proposed dynamic deadband ETM applies nonlinear coupled communication protocols and ensures the existence of positive minimum inter-event times (PMIET). Further, by guaranteeing the auxiliary variables superior tracking capability for the reference variables, the consensus of the auxiliary variables can be achieved. Thus, the desired formation is realized. Besides, the adaptive strategy and the radial basis function neural network (RBFNN) are utilized against external disturbances and dynamic uncertainties. Finally, through rigorous theoretical analysis and numerical simulations, the effectiveness and superiority of the proposed method are effectively demonstrated.

Trace‐level fuel contaminant detection using an ultrasensitive HC‐photonic crystal fibre sensor

AbstractFuel adulteration involving the illicit mixing of substances such as kerosene and diesel with petrol poses significant risks to engine performance, environmental safety and consumer health. This paper presents a novel HC‐PCF sensor designed to accurately detect and identify adulterants in petroleum‐based fuels with unprecedented sensitivity and selectivity. The proposed HC‐PCF sensor features a unique circular core structure surrounded by a carefully engineered square cladding region, enabling highly sensitive detection of refractive index changes caused by the presence of adulterants. Through rigorous numerical simulations and optimisation, our design achieves remarkable maximum relative sensitivities of 98.56%, 98.95%, and 99.32% for petrol, kerosene, and diesel, respectively, outperforming many previously reported techniques. A comprehensive analysis of the sensor's performance reveals an ultra‐low confinement loss of 4.08 × 10−10 dB/m, 1.08 × 10−13 dB/m, and 2.95 × 10−12 dB/m and effective material loss of 0.0040 cm−1, 0.0036 cm−1, and 0.0034 cm−1, highlighting its exceptional light‐guiding capabilities and sensitivity. The sensor's high responsiveness facilitates the detection of even trace levels of adulterants by capturing minute refractive index variations as low as possible, enabling real‐time monitoring and timely intervention in adulteration incidents. The proposed HC‐PCF sensor exhibits high selectivity, precisely targeting the refractive index signatures of fuels, ensuring accurate detection even in complex chemical environments. Its compact size and robust design make it suitable for deployment in various fuel quality control applications, from transportation to industrial settings. Overall, this work introduces cutting‐edge HC‐PCF sensor technology that addresses the critical need for reliable fuel adulteration detection with unparalleled sensitivity and selectivity, contributing to enhanced product quality, consumer protection, and environmental sustainability in the energy sector.

Determination of diffusion coefficients through gels with non-negligible finite-volume effects in the compartments of the diffusion cell

Diffusion cells are used to measure diffusion coefficients (DM) in gels. These measurements are of interest to understand and predict the availability of nutritive or toxic chemical species in waters, soils and sediments. When the diffusive flux from the donor to the acceptor compartment is constant (steady-state regime), DM is determined from the slope of the linear plot of the acceptor concentration vs time. However, at long enough times, there is a non-negligible concentration depletion in the donor compartment concomitant to a concentration increase in the acceptor compartment. Accordingly, the accumulation plot bends downwards preventing a linear fitting. This is the case of metals whose solubility (especially depending on pH values) limits the concentration in the donor compartment and the time required to reach concentrations above the limit of quantification in the acceptor compartment implies a non-negligible decrease of the concentration in the donor compartment. In this work, a simple linear regression is shown to provide the diffusion coefficient values from experiments exhibiting finite-volume effects. This expression is validated against rigorous numerical simulation as well as reported values in the literature. Diffusion coefficients of Zn, Ni and Pb in agarose cross-linked polyacrylamide (APA) gels (used in Diffusive Gradients in Thin-Film devices, DGT) are determined under finite-volume effects. The resulting values agree with those obtained under the standard linear regime.

Modeling of the leader-follower satellite formation for long baseline

Abstract Interferometric Synthetic Aperture Radar (InSAR) represents a crucial component of synthetic aperture radar technologies, with the accuracy of measurements significantly improving as the baseline length increases. In comparison with the traditional Hill-Clohessy-Wiltshire (HCW) equations, the application of curvilinear coordinate systems for modeling satellite formations in circular orbits has demonstrated enhanced precision, especially when the formations span larger distances. However, these improvements were initially limited to circular orbits. Addressing this limitation, this study introduces a novel approach by incorporating elliptical orbits into the model, thereby refining the state transition matrix through the incorporation of eccentricity factors and maintaining the direct correlation with the temporal dynamics of satellite motion in three dimensions. Through rigorous numerical simulations, it has been established that this refined model substantially improves accuracy in leader-follower satellite formations.

Advanced Numerical Techniques for Supersonic Flow Analysis: From Euler Equations to Practical Applications in Aerospace and Turbomachinery Engineering

This paper explores advanced numerical techniques for analyzing supersonic flow, with a particular focus on the application of Euler equations in aerospace and turbomachinery engineering. Theoretical foundations such as boundary conditions, error evaluation, grid partitioning, and the Successive Over-Relaxation (SOR) method are thoroughly examined. Rigorous numerical simulations are conducted to investigate the final velocity field distribution and convergence characteristics under various conditions. The research underscores the precision and efficiency of these numerical methods, highlighting their practical applications in the aerodynamic design of aircraft and potential use in turbomachinery design. The findings contribute significantly to the advancement of computational fluid dynamics in supersonic flow regimes, providing valuable insights for engineers and researchers engaged in this specialized area. The study not only enhances understanding of complex flow dynamics but also supports the development of more effective engineering solutions in high-speed applications.

Design and Simulation for Minimizing Non-Radiative Recombination Losses in CsGeI2Br Perovskite Solar Cells.

CsGeI2Br-based perovskites, with their favorable band gap and high absorption coefficient, are promising candidates for the development of efficient lead-free perovskite solar cells (PSCs). However, bulk and interfacial carrier non-radiative recombination losses hinder the further improvement of power conversion efficiency and stability in PSCs. To overcome this challenge, the photovoltaic potential of the device is unlocked by optimizing the optical and electronic parameters through rigorous numerical simulation, which include tuning perovskite thickness, bulk defect density, and series and shunt resistance. Additionally, to make the simulation data as realistic as possible, recombination processes, such as Auger recombination, must be considered. In this simulation, when the Auger capture coefficient is increased to 10-29 cm6 s-1, the efficiency drops from 31.62% (without taking Auger recombination into account) to 29.10%. Since Auger recombination is unavoidable in experiments, carrier losses due to Auger recombination should be included in the analysis of the efficiency limit to avoid significantly overestimating the simulated device performance. Therefore, this paper provides valuable insights for designing realistic and efficient lead-free PSCs.

Stochastic Optimal Control Analysis for HBV Epidemic Model with Vaccination

In this study, we explore the concept of symmetry as it applies to the dynamics of the Hepatitis B Virus (HBV) epidemic model. By incorporating symmetric principles in the stochastic model, we ensure that the control strategies derived are not only effective but also consistent across varying conditions, and ensure the reliability of our predictions. This paper presents a stochastic optimal control analysis of an HBV epidemic model, incorporating vaccination as a pivotal control measure. We formulate a stochastic model to capture the complex dynamics of HBV transmission and its progression to acute and chronic stages. By leveraging stochastic differential equations, we examine the model’s stationary distribution and asymptotic behavior, elucidating the impact of random perturbations on disease dynamics. Optimal control theory is employed to derive control strategies aimed at minimizing the disease burden and vaccination costs. Through rigorous numerical simulations using the fourth-order Runge–Kutta method, we demonstrate the efficacy of the proposed control measures. Our findings highlight the critical role of vaccination in controlling HBV spread and provide insights into the optimization of vaccination strategies under stochastic conditions. The symmetry within the proposed model equations allows for a balanced approach to analyzing both acute and chronic stages of HBV.

Periodicity alters topological states in thermal diffusion system

Periodicity alters topological states in thermal diffusion system

Simultaneous estimation of multiple order phase derivatives using deep learning method in digital holographic interferometry

Simultaneous estimation of multiple order phase derivatives using deep learning method in digital holographic interferometry

On simulating light diffraction by layered structures with multiple wedges.

Layered structures containing small-angle wedges are widely used as linear variable filters (LVFs) in microspectrometers, sensors, and hyperspectral imaging systems. Here, we propose a method based on the scattering matrix formalism allowing one to describe the optical properties of layered structures with multiple wedges. As examples, we consider a single-wedge LVF with Bragg claddings and an LVF with three wedges, the latter exhibiting a flat-top resonant transmission peak. We show that the proposed method provides a two orders of magnitude increase in speed compared to the rigorous numerical simulations based on the Fourier modal method. At the same time, as we demonstrate, the results obtained with these two methods are very close to each other. The proposed approach is promising for the design and investigation of LVFs containing several wedge-shaped layers.

Insights of infected Schwann cells extinction and inherited randomness in a stochastic model of leprosy

Investigating disease progression, transmission of infection and impacts of Multidrug Therapy (MDT) to inhibit demyelination in leprosy involves a certain amount of difficulty in terms of the in-built uncertain complicated and complex intracellular cell dynamical interactions. To tackle this scenario and to elucidate a more realistic, rationalistic approach of examining the infection mechanism and associated drug therapeutic interventions, we propose a four-dimensional ordinary differential equation-based model. Stochastic processes has been employed on this deterministic system by formulating the Kolmogorov forward equation introducing a transition state and the quasi-stationary distribution, exact distribution analysis have been investigated which allow us to estimate an expected time to extinction of the infected Schwann cells into the human body more prominently. Additionally, to explore the impact of uncertainty in the key intracellular factors, the stochastic system is investigated incorporating random perturbations and environmental noises in the disease dissemination, proliferation and reinfection rates. Rigorous numerical simulations validating the analytical outcomes provide us significant novel insights on the progression of leprosy and unravelling the existing major treatment complexities. Analytical experiments along with the simulations utilizing Monte-Carlo method and Euler-Maruyama scheme involving stochasticity predicts that the bacterial density is underestimated due to the recurrence of infection and suggests that maintaining a drug-efficacy rate in the range 0.6-0.8 would be substantially efficacious in eradicating leprosy.

Investigation of self-focusing of Gaussian laser beams within magnetized plasma via source-dependent expansion method

Self-focusing emerges as a nonlinear optical phenomenon resulting from an intense laser field and plasma interaction. This study investigates the self-focusing behavior of Gaussian laser beams within magnetized plasma environments utilizing a novel approach, source-dependent expansion. By employing source-dependent expansion, we explore the intricate dynamics of laser beam propagation, considering the influence of plasma density and external magnetic fields. The interplay between the beam's Gaussian profile and the self-focusing mechanism through rigorous mathematical analysis and numerical simulations, particularly in the presence of plasma-induced nonlinearities, is elucidated here. Our findings reveal crucial insight into the evolution of laser beams under diverse parameters, including the ponderomotive force, relativistic factors, plasma frequency, polarization states, external magnetic field, wavelength, and laser intensity. This research not only contributes to advancing our fundamental understanding of laser–plasma interactions but also holds promise for optimizing laser-driven applications.

Quantum logarithmic multifractality

Through a combination of rigorous analytical derivations and extensive numerical simulations, this work reports an exotic multifractal behavior, dubbed “logarithmic multifractality,” in effectively infinite-dimensional systems undergoing the Anderson transition. In contrast to conventional multifractality observed in finite dimensions, logarithmic multifractality at infinite dimension introduces an algebraic behavior with respect to the logarithm of system size or time. We demonstrate this phenomenon across eigenstate statistics, spatial correlations, and wave packet dynamics. Our findings offer crucial insights into strong finite-size effects and slow dynamics in complex systems undergoing the Anderson transition, such as the many-body localization transition. Published by the American Physical Society 2024

Stability Analysis of Gravity Dam using Matlab Programming

Gravity dams are critical structures in civil engineering, designed to withstand the immense forces exerted by water pressure and gravity. Ensuring their stability is paramount to prevent catastrophic failures that could result in significant economic and environmental consequences. This study presents a comprehensive stability analysis of a gravity dam using MATLAB programming. The analysis focuses on evaluating the structural integrity and safety factors of the dam under various loading conditions, including hydrostatic pressure and seismic forces. MATLAB's computational capabilities are utilized to perform rigorous numerical simulations, incorporating finite element analysis (FEA) and stability criteria assessments. Key aspects of the stability analysis include the determination of critical failure modes such as sliding, overturning, and base pressure distribution. Through MATLAB programming, the study explores different dam geometries and material properties to assess their influence on overall stability. Furthermore, sensitivity analyses are conducted to investigate the impact of uncertainties in input parameters on the dam's stability margins. This provides insights into potential weak points and allows for optimization of design parameters to enhance dam safety.

Achieving Low Voltage Plasma Discharge in Aqueous Solution Using Lithographically Defined Electrodes and Metal/Dielectric Nanoparticles.

Because of the high dielectric strength of water, it is extremely difficult to discharge plasma in a controllable way in the aqueous phase. By using lithographically defined electrodes and metal/dielectric nanoparticles, we create electric field enhancement that enables plasma discharge in liquid electrolytes at significantly reduced applied voltages. Here, we use high voltage (10-30 kV) nanosecond pulse (20 ns) discharges to generate a transient plasma in the aqueous phase. An electrode geometry with a radius of curvature of approximately 10 μm, a gap distance of 300 μm, and an estimated field strength of 5 × 106 V/cm resulted in a reduction in the plasma discharge threshold from 28 to 23 kV. A second structure had a radius of curvature of around 5 μm and a gap distance of 100 μm had an estimated field strength of 9 × 106 V/cm but did not perform as well as the larger gap electrodes. Adding gold nanoparticles (20 nm diameter) in solution further reduced the threshold for plasma discharge to 17 kV due to the electric field enhancement at the water/gold interface, with an estimated E-field enhancement of 4×. Adding alumina nanoparticles decorated with Pt reduced the plasma discharge threshold to 14 kV. In this scenario, the emergence of a triple point at the juncture of alumina, Pt, and water results in the coexistence of three distinct dielectric constants at a singular location. This leads to a notable concentration of electric field, effectively aiding in the initiation of plasma discharge at a reduced voltage. To gain a more comprehensive and detailed understanding of the electric field enhancement mechanism, we performed rigorous numerical simulations. These simulations provide valuable insights into the intricate interplay between the lithographically defined electrodes, the nanoparticles, and the resulting electric field distribution, enabling us to extract crucial information and optimize the design parameters for enhanced performance.

Nano-structured metamaterial absorber based on a plus-shaped resonator for optical wavelength applications

Metamaterial absorbers have sparked widespread interest due to their remarkable electromagnetic properties, which enable a wide range of applications in light absorption and manipulation. This study introduces a new three-layer nanomaterial absorber (NMA) unit cell composed of nickel (Ni), silicon dioxide (SiO2), and nickel (Ni) designed to operate across the entire visible spectrum (390–780 nm). We demonstrate the NMA’s exceptional absorption characteristics through rigorous numerical simulations using industry-standard software, achieving a mean absorption rate of 97.17% and a maximum absorption peak of 99.99% at 694.89 nm under standard angles. Furthermore, the NMA unit cell has good impedance matching, efficient coupling between capacitors and inductors, and significant plasmonic resonance properties. Fabrication feasibility and potential applications in solar energy harvesting, optical sensing, and light detection.

Advanced Design and Manufacturing Approaches for Structures with Enhanced Thermal Management Performance: A Review

AbstractAdvanced design methods and manufacturing techniques are crucial for developing thermal management structures, essential for the efficient operation of complex equipment. This study provides a thorough review of design methodologies and advanced manufacturing technologies for thermal management materials and structures. It identifies key challenges and critically evaluates the integration of innovative design principles, such as biomimicry and topology optimization, into thermal management solutions. The analysis delves into the evolution of design theories and preparation techniques, with a specific focus on modern needs and research directions, particularly highlighting components fabricated using additive manufacturing and their effectiveness in meeting advanced thermal management requirements. Current research focuses on designing structures tailored to various cooling methods, including air‐cooling, liquid‐cooling, heat exchanger cooling, and heat pipe cooling. These designs utilize phase change materials, electrocaloric cooling, and thermoelectric cooling materials to achieve optimal thermal management performance. Additionally, emerging innovations like solid‐liquid mixed heat transfer and the elastocaloric effect are garnering increased interest. Enhancing the design of thermal management structures through rigorous numerical simulations is critical for improving engineering applicability. However, overcoming challenges related to the commercialization and practical utilization of these advanced structures remains a pressing need.