On the temperature dependence of point-defect-mediated luminescence in silicon

Recht, Daniel; Capasso, Federico; Aziz, Michael J.

doi:10.1063/1.3157277

Cited by 13 publications

(9 citation statements)

References 6 publications

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“…A similar model was presented in Ref. 88, but in that work steady state emission was investigated to seek a continuous-wave laser. He we require the full dynamical equations to investigate transient behavior.…”

Section: E2 Silicon Emissive Centersmentioning

confidence: 99%

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Superconducting optoelectronic loop neurons

Shainline

Buckley

McCaughan

et al. 2019

Journal of Applied Physics

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Circuits using superconducting single-photon detectors and Josephson junctions to perform signal reception, synaptic weighting, and integration are investigated. The circuits convert photondetection events into flux quanta, the number of which is determined by the synaptic weight. The current from many synaptic connections is inductively coupled to a superconducting loop that implements the neuronal threshold operation. Designs are presented for synapses and neurons that perform integration as well as detect coincidence events for temporal coding. Both excitatory and inhibitory connections are demonstrated. It is shown that a neuron with a single integration loop can receive input from 1000 such synaptic connections, and neurons of similar design could employ many loops for dendritic processing.

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Section: E2 Silicon Emissive Centersmentioning

confidence: 99%

“…Following Ref. 88 we focus on W centers [12] and assume a hole is always trapped before an electron.…”

Section: E2 Silicon Emissive Centersmentioning

confidence: 99%

Superconducting optoelectronic loop neurons

Shainline

Buckley

McCaughan

et al. 2019

Journal of Applied Physics

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“…The trends are also very similar to the model developed by Recht et al to describe the thermal quenching of PL and EL and our value of E t À E v is comparable to the electron binding energy determined in their work for the W line. 48 As the dopant density increases, it can be seen that the temperature quenching in Fig. 9(b) becomes less apparent.…”

Section: B Dopant Dependencementioning

confidence: 90%

Dopant effects on the photoluminescence of interstitial-related centers in ion implanted silicon

Johnson¹,

Villis²,

Burgess³

et al. 2012

Journal of Applied Physics

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The dopant dependence of photoluminescence (PL) from interstitial-related centers formed by ion implantation and a subsequent anneal in the range 175-525 C is presented. The evolution of these centers is strongly effected by interstitial-dopant clustering even in the low temperature regime. There is a significant decrease in the W line (1018.2 meV) PL intensity with increasing B concentration. However, an enhancement is also observed in a narrow fabrication window in samples implanted with either P or Ga. The anneal temperature at which the W line intensity is optimized is sensitive to the dopant concentration and type. Furthermore, dopants which are implanted but not activated prior to low temperature thermal processing are found to have a more detrimental effect on the resulting PL. Splitting of the X line (1039.8 meV) arising from implantation damage induced strain is also observed. V

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“…These have proved unattractive for optical interconnects due to very low efficiencies at room temperature. Much work in this area was motivated by the prospect of room-temperature light sources [68] for CMOS and telecommunications [69], and in particular room temperature lasers. This includes various point defects in Si including Er [70][71][72][73] and other emissive centers giving rise to electric-dipole-mediated transitions [67,[74][75][76][77][78][79][80][81][82], as well as band-edge or Si nanocrystal-based emission processes [83][84][85].…”

Section: G Electrically-injected Light Sourcementioning

confidence: 99%

Superconducting Optoelectronic Circuits for Neuromorphic Computing

et al. 2017

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Neural networks have proven effective for solving many difficult computational problems. Implementing complex neural networks in software is very computationally expensive. To explore the limits of information processing, it will be necessary to implement new hardware platforms with large numbers of neurons, each with a large number of connections to other neurons. Here we propose a hybrid semiconductor-superconductor hardware platform for the implementation of neural networks and large-scale neuromorphic computing. The platform combines semiconducting few-photon light-emitting diodes with superconducting-nanowire single-photon detectors to behave as spiking neurons. These processing units are connected via a network of optical waveguides, and variable weights of connection can be implemented using several approaches. The use of light as a signaling mechanism overcomes fanout and parasitic constraints on electrical signals while simultaneously introducing physical degrees of freedom which can be employed for computation. The use of supercurrents achieves the low power density necessary to scale to systems with enormous entropy. The proposed processing units can operate at speeds of at least 20 MHz with fully asynchronous activity, light-speed-limited latency, and power densities on the order of 1 mW/cm 2 for neurons with 700 connections operating at full speed at 2 K. The processing units achieve an energy efficiency of ≈ 20 aJ per synapse event. By leveraging multilayer photonics with deposited waveguides and superconductors with feature sizes > 100 nm, this approach could scale to systems with massive interconnectivity and complexity for advanced computing as well as explorations of information processing capacity in systems with an enormous number of information-bearing microstates.

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On the temperature dependence of point-defect-mediated luminescence in silicon

Cited by 13 publications

References 6 publications

Superconducting optoelectronic loop neurons

Superconducting optoelectronic loop neurons

Dopant effects on the photoluminescence of interstitial-related centers in ion implanted silicon

Superconducting Optoelectronic Circuits for Neuromorphic Computing

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