Low-Temperature Electroluminescence Excitation Mapping of Excitons and Trions in Short-Channel Monochiral Carbon Nanotube Devices

Gaulke, Marco; Janissek, Alexander; Peyyety, Naga Anirudh; Alamgir, Imtiaz; Riaz, Adnan; Dehm, Simone; Li, Han; Lemmer, Uli; Flavel, Benjamin S.; Kappes, Manfred M.; Hennrich, Frank; Li, Wei; Chen, Yuan; Pyatkov, Felix; Krupke, Ralph

doi:10.1021/acsnano.9b07207

Cited by 21 publications

(51 citation statements)

References 56 publications

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“…With the NN, it reproduces results obtained from exact diagonalization on a variety of correlation functions, c.f. Figures 7,8,15,12,13,16. The agreement with exact results provides a posteriori evidence that we have an accurate, ergodic method.…”

Section: Discussionsupporting

confidence: 70%

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Leveraging Machine Learning to Alleviate Hubbard Model Sign Problems

Wynen,

Berkowitz,

Krieg

et al. 2020

Preprint

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Lattice Monte Carlo calculations of interacting systems on non-bipartite lattices exhibit an oscillatory imaginary phase known as the phase or sign problem, even at zero chemical potential. One method to alleviate the sign problem is to analytically continue the integration region of the state variables into the complex plane via holomorphic flow equations. For asymptotically large flow times the state variables approach manifolds of constant imaginary phase known as Lefschetz thimbles. However, flowing such variables and calculating the ensuing Jacobian is a computationally demanding procedure. In this paper we demonstrate that neural networks can be trained to parameterize suitable manifolds for this class of sign problem and drastically reduce the computational cost. We apply our method to the Hubbard model on the triangle and tetrahedron, both of which are non-bipartite. At strong interaction strengths and modest temperatures the tetrahedron suffers from a severe sign problem that cannot be overcome with standard reweighting techniques, while it quickly yields to our method. We benchmark our results with exact calculations and comment on future directions of this work.

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Section: Discussionsupporting

confidence: 70%

“…A wide variety of condensed-matter systems, including the doped fermionic Hubbard model, exhibit a rich multiquasi-particle spectrum (see, for example, Refs. [12][13][14][15]) and comprise tantalizing theoretical systems with commercial relevance. Unfortunately, many of these systems exhibit a sign problem as well.…”

Section: Introductionmentioning

confidence: 99%

Leveraging Machine Learning to Alleviate Hubbard Model Sign Problems

Wynen,

Berkowitz,

Krieg

et al. 2020

Preprint

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show abstract

“…The formation of accumulation layers of holes and electrons within the channel depending on the applied gate and drain voltages is easily accomplished with nanotubes as long as electron traps such as water/oxygen [136] are removed. SWCNTs are thus highly suitable for ambipolar light-emitting transistors, not just as individual nanotubes [124,[137][138][139] but also as networks of sorted semiconducting nanotubes. [140][141][142][143] However, the low photoluminescence and even lower electroluminescence efficiencies of SWCNTs remain serious obstacles for any application.…”

Section: Electroluminescent Devicesmentioning

confidence: 99%

Luminescent Defects in Single‐Walled Carbon Nanotubes for Applications

Zaumseil

2021

Advanced Optical Materials

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most applications, only semiconducting nanotubes and ideally only one (n,m) species (monochiral) are desired. This technological need has pushed the search for more controlled and selective growth of SWCNTs [5,6] and even more importantly fueled the development of post-growth purification and sorting of the different nanotube types and chiralities. Various, quite different techniques, such as gelchromatography, [7][8][9] aqueous two-phase separation (ATPE), [10][11][12] and selective polymer-wrapping, [13][14][15][16][17] now make it possible to produce and work with sufficiently large amounts of not only purely semiconducting nanotubes of a certain diameter range but also monochiral nanotubes and even enantiomerically pure samples. [18,19] This high degree of purification and hence the availability of nanotubes as a material with reproducible properties has been critical for applications in electronics [20,21] and energy conversion, [22,23] as well as imaging [24,25] and sensing [26,27] based on the near-infrared photoluminescence (PL) of SWCNTs and its modulation. However, an important paradigm shift occurred when it became clear that defects in the sp 2 carbon lattice of nanotubes are not always detrimental to the photoluminescence yield, but can indeed lead to new electronic states with highly interesting and useful optical properties. [28][29][30] These specific defects, which are variably named sp 3 defects, luminescent defects, organic color centers or quantum defects [31][32][33][34][35] have been at the heart of many recent studies on carbon nanotubes and promise a wide range of potential applications from single-photon emission to in vivo super-resolution imaging. This review will briefly introduce the underlying photo physics and properties of these defects, peruse recent progress in their controlled creation and discuss the various potential applications in detail.Semiconducting single-walled carbon nanotubes show extraordinary electronic and optical properties, such as high charge carrier mobilities and diameter-dependent near-infrared photoluminescence. The introduction of sp 3 defects in the carbon lattice of these nanotubes creates new electronic states that result in even further red-shifted photoluminescence with longer lifetimes and higher photoluminescence yield. These luminescent defects or organic color centers can be tuned chemically by controlling the precise binding configuration and the electrostatic properties of the attached substituents. This review covers the basic photophysics of luminescent sp 3 defects, synthetic methods for their controlled formation and discusses their application as near-infrared single-photon emitters at room temperature, in electroluminescent devices, as versatile optical sensors, and as fluorophores for bioimaging and potential super-resolution microscopy.

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“…The single-photon purity of the CNT light emitter has been observed in the telecom wavelength with defect sites [236], solitary dopant [237], or covalently functionalization [238] for photon emission. The band of emitted light can be narrowed down with the aryl edge functionalization of zigzag CNTs [239].…”

Section: Photoluminescence For Dna Sensingmentioning

confidence: 99%

Emerging Internet of Things driven carbon nanotubes-based devices

Zhang

Pang

et al. 2022

Nano Res.

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Carbon nanotubes (CNTs) have attracted great attentions in the field of electronics, sensors, healthcare, and energy conversion. Such emerging applications have driven the carbon nanotube research in a rapid fashion. Indeed, the structure control over CNTs has inspired an intensive research vortex due to the high promises in electronic and optical device applications. Here, this in-depth review is anticipated to provide insights into the controllable synthesis and applications of high-quality CNTs. First, the general synthesis and post-purification of CNTs are briefly discussed. Then, the state-of-the-art electronic device applications are discussed, including field-effect transistors, gas sensors, DNA biosensors, and pressure gauges. Besides, the optical sensors are delivered based on the photoluminescence. In addition, energy applications of CNTs are discussed such as thermoelectric energy generators. Eventually, future opportunities are proposed for the Internet of Things (IoT) oriented sensors, data processing, and artificial intelligence.

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Low-Temperature Electroluminescence Excitation Mapping of Excitons and Trions in Short-Channel Monochiral Carbon Nanotube Devices

Cited by 21 publications

References 56 publications

Leveraging Machine Learning to Alleviate Hubbard Model Sign Problems

Leveraging Machine Learning to Alleviate Hubbard Model Sign Problems

Luminescent Defects in Single‐Walled Carbon Nanotubes for Applications

Emerging Internet of Things driven carbon nanotubes-based devices

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