Q-BOR–FDTD method for solving Schrödinger equation for rotationally symmetric nanostructures with hydrogenic impurity

Firoozi, Arezoo; Mohammadi, Ahmad; Khordad, R.; Jalali, Tahmineh

doi:10.1088/1402-4896/ac48ac

Cited by 4 publications

(12 citation statements)

References 62 publications

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“…The purpose of this section is a more rigorous discussion of the Q-BOR-FDTD method with the purpose of disclosing some of the limitations overlooked by Firoozi et al [1].…”

Section: The Methodsmentioning

confidence: 99%

“…Therefore, it is only necessary to solve equation (2) for sufficiently large values of τ . To this end Firoozi et al [1] resorted to a straightforward discretization algorithm that produces ψ(r i , τ j ) at the points of a suitably chosen mesh. Since…”

Section: The Methodsmentioning

confidence: 99%

“…In order to obtain the ground-state eigenfunction Firoozi et al [1] resorted to the obvious expression φ0 = lim…”

Section: The Methodsmentioning

confidence: 99%

“…. .. Firoozi et al [1] did not pay attention to this point and applied the approach to problems with degenerate states.…”

Section: The Methodsmentioning

confidence: 99%

“…In a recent paper Firoozi et al [1] proposed a numerical approach, named quantum body of revolution finite-difference time-domain (Q-BOR-FDTD) method, for the calculation of eigenvalues and eigenfunctions of the Schrödinger equation.…”

Section: Introductionmentioning

confidence: 99%

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On the Q-BOR-FDTD method

Fernández¹

2022

Preprint

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“…The purpose of this section is a more rigorous discussion of the Q-BOR-FDTD method with the purpose of disclosing some of the limitations overlooked by Firoozi et al [1].…”

Section: The Methodsmentioning

confidence: 99%

Section: The Methodsmentioning

confidence: 99%

“…In order to obtain the ground-state eigenfunction Firoozi et al [1] resorted to the obvious expression φ0 = lim…”

Section: The Methodsmentioning

confidence: 99%

“…. .. Firoozi et al [1] did not pay attention to this point and applied the approach to problems with degenerate states.…”

Section: The Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On the Q-BOR-FDTD method

Fernández¹

2022

Preprint

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Effect of nanoshell geometries, sizes, and quantum emitter parameters on the sensitivity of plasmon-exciton hybrid nanoshells for sensing application

Firoozi

Amphawan

Khordad

et al. 2023

Sci Rep

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A proposed nanosensor based on hybrid nanoshells consisting of a core of metal nanoparticles and a coating of molecules is simulated by plasmon-exciton coupling in semi classical approach. We study the interaction of electromagnetic radiation with multilevel atoms in a way that takes into account both the spatial and the temporal dependence of the local fields. Our approach has a wide range of applications, from the description of pulse propagation in two-level media to the elaborate simulation of optoelectronic devices, including sensors. We have numerically solved the corresponding system of coupled Maxwell-Liouville equations using finite difference time domain (FDTD) method for different geometries. Plasmon-exciton hybrid nanoshells with different geometries are designed and simulated, which shows more sensitive to environment refractive index (RI) than nanosensor based on localized surface plasmon. The effects of nanoshell geometries, sizes, and quantum emitter parameters on the sensitivity of nanosensors to changes in the RI of the environment were investigated. It was found that the cone-like nanoshell with a silver core and quantum emitter shell had the highest sensitivity. The tapered shape of the cone like nanoshell leads to a higher density of plasmonic excitations at the tapered end of the nanoshell. Under specific conditions, two sharp, deep LSPR peaks were evident in the scattering data. These distinguishing features are valuable as signatures in nanosensors requiring fast, noninvasive response.

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Intelligent electromagnetic mapping via physics driven and neural networks on frequency selective surfaces

Miao

Zhang

Zhou

et al. 2023

J. Phys. D: Appl. Phys.

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The high mapping efficiency between various structures and electromagnetic (EM) properties on frequency selective surfaces (FSSs) is the state-of-the-art in EM community. The most straightforward approaches for beams analysis depend on the measurements and conventional EM calculation methods, which are inefficient and time-consuming. Equivalent circuit model (ECM) with excellent intuitiveness and simplicity is put forward extensively. Despite of several applications, the bottlenecks of ECM still exist, i.e., the application scope is restricted in narrow band and specific structure, which is triggered by the ignorance of EM nonlinear coupling. In this work, a lightweight physic model based on neural network (ECM-NN) is proposed for the first time, which exhibits a great physical interpretability and spatial generalization ability. The nonlinear mapping relationship between structures and beams behaviors is interpreted by corresponding simulations. Specially, two deep parametric factors obtained by multi-layer perceptron (MLP) network are introduced to serve as the core of lightweight strategy and compensate for the absence of nonlinearity. Experimental results of single square loop (SL) and double SL indicate that compared with related works, better agreements of the frequency responses and resonant frequencies are achieved by ECM-NN in broadband (0-30 GHz) as well as oblique incident angles (0-60°). The average accuracy of mapping is higher than 98.6%. The discoveries of this work provide a novel strategy for further studies of complex FSSs.

show abstract

Q-BOR–FDTD method for solving Schrödinger equation for rotationally symmetric nanostructures with hydrogenic impurity

Cited by 4 publications

References 62 publications

On the Q-BOR-FDTD method

On the Q-BOR-FDTD method

Effect of nanoshell geometries, sizes, and quantum emitter parameters on the sensitivity of plasmon-exciton hybrid nanoshells for sensing application

Intelligent electromagnetic mapping via physics driven and neural networks on frequency selective surfaces

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