Optimization of inter-subband absorption of InGaAsSb/GaAs quantum wells structure

Chenini, L.; Aissat, A.; Vilcot, J.P.

doi:10.1016/j.spmi.2019.03.015

Cited by 12 publications

(7 citation statements)

References 25 publications

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“…The kink in the relaxation of the SPV as well as the Rashba modification is correlated with τ cross , indicating that the reversal of the Lifshitz transition plays a key role in the relaxation. Furthermore, the new states near the Fermi level imply an increase in conductivity at the surface affecting spin-dependent transport properties, and occupation of the QW2 band bottom would influence intersubband optical absorption 67 . As such, this ultrafast-field effect device provides many opportunities for applications that are sensitive to the DOS at the chemical potential and requires further attention exploring the DOS-dependent scattering dynamics.…”

Section: Discussionmentioning

confidence: 99%

Driving ultrafast spin and energy modulation in quantum well states via photo-induced electric fields

et al. 2022

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The future of modern optoelectronics and spintronic devices relies on our ability to control the spin and charge degrees of freedom at ultrafast timescales. Rashba spin-split quantum well states, 2D states that develop at the surface of strong spin-orbit coupling materials, are ideal given the tunability of their energy and spin states. So far, however, most studies have only demonstrated such control in a static way. In this study, we demonstrate control of the spin and energy degrees of freedom of surface quantum well states on Bi2Se3 at picosecond timescales. By means of a focused laser pulse, we modulate the band-bending, producing picosecond time-varying electric fields at the material’s surface, thereby reversibly modulating the quantum well spectrum and Rashba effect. Moreover, we uncover a dynamic quasi-Fermi level, dependent on the Lifshitz transition of the second quantum well band bottom. These results open a pathway for light-driven spintronic devices with ultrafast switching of electronic phases, and offer the interesting prospect to extend this ultrafast photo-gating technique to a broader host of 2D materials.

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Section: Discussionmentioning

confidence: 99%

Driving ultrafast spin and energy modulation in quantum well states via photo-induced electric fields

et al. 2022

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“…We use the eight-band k · p Schrödinger equation to derive the wave functions, energy levels, and interband transition energies of the QW structures unless otherwise stated. The probability of the ISB transitions between an initial state i and a final state f can be obtained by evaluating the ISB transition dipole moments z fi : , | z f i | ∝ | ∫ ψ f * false( z false) z ψ i false( z false) d z | where ψ f * and ψ i are the wave functions of the initial and final states, respectively, and z is the direction perpendicular to the QW layers.…”

Section: Methodsmentioning

confidence: 99%

“…For absorption coefficients in doped structures, the Poisson equation was also included to reflect charge self-consistency: normal∇ · [ ε 0 ε r false( boldx false) ∇ ϕ false( boldx false) ] = prefix− ρ ( x ) where ε 0 is the vacuum permittivity, ε r ( x ) is the static dielectric constant tensor at position x , and ϕ is the electrostatic potential. On the basis of ISB transition dipole matrix element z fi , we further calculate the absorption coefficient using , α ( ω ) = e 2 ω ( N i − N f ) ℏ italicε 0 n c z i j 2 normalΓ / 2 ( E j − E i − ℏ ω ) 2 + normalΓ 2 / 4 where c is the speed of light in vacuum, n is the refractive index, and Γ is the energy line width in terms of the full width at half-maximum (fwhm), which is derived as Γ = ℏ /τ, with τ being the relaxation time. N i is the volume carrier density, which can be derived from the two-dimensional density of states and the Fermi–Dirac function: , …”

Section: Methodsmentioning

confidence: 99%

“…On the basis of ISB transition dipole matrix element z fi , we further calculate the absorption coefficient using , α ( ω ) = e 2 ω ( N i − N f ) ℏ italicε 0 n c z i j 2 normalΓ / 2 ( E j − E i − ℏ ω ) 2 + normalΓ 2 / 4 where c is the speed of light in vacuum, n is the refractive index, and Γ is the energy line width in terms of the full width at half-maximum (fwhm), which is derived as Γ = ℏ /τ, with τ being the relaxation time. N i is the volume carrier density, which can be derived from the two-dimensional density of states and the Fermi–Dirac function: , N normali = m * k normalB T π ℏ 2 .25em ln ( 1 1 − f i ) = m * k normalB T π…”

Section: Methodsmentioning

confidence: 99%

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Intersubband Transitions in Lead Halide Perovskite-Based Quantum Wells for Mid-Infrared Detectors

Nie

2023

J. Phys. Chem. Lett.

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Due to their excellent optical and electrical properties as well as versatile growth and fabrication processes, lead halide perovskites have been widely considered as promising candidates for green energy and applications related to optoelectronics. Here, we investigate their potential applications at infrared wavelengths by modeling the intersubband transitions in perovskite-based quantum well systems. Both single-well and double-well structures are studied, and their energy levels as well as the corresponding wave functions and intersubband transition energies are calculated by solving the onedimensional Schrodinger equations. Via adjustment of the quantum well and barrier thicknesses, the intersubband transition energies can be tuned to cover a broad infrared wavelength range. We also find that the lead halide perovskite-based quantum wells possess high absorption coefficients. The widely tunable transition energies and high absorption coefficients of the perovskite-based quantum well systems, combined with their unique material and electrical properties, may enable an alternative material system for infrared photodetector applications.

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“…Solution to a problem solved by genetic algorithms is evolved. The genetic algorithm is a method for solving optimization problems that is based on natural selection (Chenini, Aissat, & Vilcot, 2019;Cheong & Koh, 2019;Wang, Duan, & Yang, 2018;Zhao & Liu, 2018), the process that drives biological evolution. The genetic algorithm repeatedly modifies a population of individual solutions (Pérez-Galarce, Candia-Véjar, Astudillo, & Bardeen, 2018).…”

Section: Genetic Algorithmmentioning

confidence: 99%

Introducing a Novel Method to Solve Shortest Path Problems Based on Structure of Network Using Genetic Algorithm

Behzadi

Kolbadinejad²

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The shortest path problem is widely applied in transportation, communication and computer networks. It addresses the challenges of determining a path with minimum distance, time or cost from a source to the destination. Network analysis provides strong decision support for users in searching shortest path. A lot of algorithms are designed for solving shortest path but most of them did not considered the conditions of the networks. Genetic Algorithm is a kind of Algorithm that has a lot of efficiency and it can be used for solving many kinds of problems. It also can be used based on the condition of the problems.In this paper, Genetic Algorithm is used for solving shortest path in multistage process planning (MPP) problem. New mutations as well as crossover parameters are defined for each network based on the conditions of them. The results of our experimental demonstrate the effectiveness of the models.

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Optimization of inter-subband absorption of InGaAsSb/GaAs quantum wells structure

Cited by 12 publications

References 25 publications

Driving ultrafast spin and energy modulation in quantum well states via photo-induced electric fields

Driving ultrafast spin and energy modulation in quantum well states via photo-induced electric fields

Intersubband Transitions in Lead Halide Perovskite-Based Quantum Wells for Mid-Infrared Detectors

Introducing a Novel Method to Solve Shortest Path Problems Based on Structure of Network Using Genetic Algorithm

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