“Fast” and “Slow” Metastable Defects in a-Si:H

A two-step light soaking experiment at high and low intensities provided convincing evidence that defect generation and annealing in a-Si:H are controlled by defect states of different characteristics. We point out that the total defect density by itself cannot uniquely determine the state of material or be described by a single rate equation, even though it might be the only quantity that is experimentally measurable. A system of rate equations for all defect components, therefore, must be established in order to accurately describe the defect kinetics. A simple two-component model in which defects are categorized as “fast” or “slow” is shown to be adequate to explain a variety of experimental results in a consistent fashion.

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Thermal and Optical Stretched Exponentials in Defect Kinetics in a-Si:H

MRS Proceedings ◽

10.1557/proc-297-607 ◽

1993 ◽

Vol 297 ◽

Cited By ~ 1

Author(s):

David Redfield ◽

Richard Bube

Keyword(s):

Solar Cell ◽

Rate Equation ◽

Defect Density ◽

Dispersion Parameter ◽

Thermally Induced ◽

Defect Generation ◽

Weak Light ◽

New Equation ◽

Stretched Exponentials ◽

Dispersive Character

Dispersive description of defect generation in a-Si:H that leads to stretched-exponential transients is extended by relaxing the assumption that light-induced processes and thermally induced processes have the same dispersive character. This is done by separating the rate equation for the defect density into two parts, one thermal and one optical, each with its own dispersion parameter. The solutions of this new equation — which must be obtained numerically — generally have two distinct parts: there may be a two-part rise or a peak, depending on the relative values of the two stretch parameters. Using this formulation we have readily simulated the recently observed peak in relaxation of a previously heavily degraded solar cell while exposed to a weak light. We find no way to explain other reports in similar two-part experiments that relaxation is faster under weak excitation than without.

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Radiometric Chronology of Neh–nar Glacier, Kashmir

Journal of Glaciology ◽

10.3189/s0022143000011813 ◽

1982 ◽

Vol 28 (98) ◽

pp. 91-105 ◽

Cited By ~ 1

Author(s):

V. N. Nijampurkar ◽

N. Bhandari ◽

C. P. Vohra ◽

V. Krishnan

Keyword(s):

Average Rate ◽

Component Model ◽

Vertical Profiles ◽

Kashmir Valley ◽

Movement Rate ◽

Accumulation Zone ◽

Core Samples ◽

Surface Samples ◽

Two Component

AbstractSurface and core samples of Neh–nar Glacier in the Kashmir Valley have been analysed for the radionuclides 32Si. 210Pb, 40K, and 137Cs. The lateral and vertical profiles (at an altitude of about 4 140 m) reveal:(1)32Si activity decreasing slowly from the accumulation zone to 4 050 m altitude and then abruptly towards the snout.(2)Five zones of alternating high and low 210Pb activity in the surface samples.(3)An horizon at between 2 and 3 m depth containing 210Pb activity above natural levels. This horizon is also associated with 137Cs and a maximum in total ß activity.The ice samples have been dated on the basis of a simplified two–component model, the “fresh“contribution determined by 2l0Pb and the old component by 32Si. The following conclusions can be drawn from these observations:(1)The model age of the snout ice is c. 850 years.(2)The average rate of ice movement in the lower glacier is about 2 m/year, which compares well with the annual movement rate of 2.65 m/year observed since 1974.

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Estimation of Galactic Model Parameters by Interval Method

Symposium - International Astronomical Union ◽

10.1017/s0074180900230635 ◽

1996 ◽

Vol 169 ◽

pp. 713-714

Author(s):

S. A. Kutuzov

Keyword(s):

Mutual Interaction ◽

Component Model ◽

Model Parameters ◽

Interval Method ◽

Two Component ◽

The Galaxy ◽

Galactic Model

The interval method of estimating model parameters (MPs) for the Galaxy was suggested earlier (Kutuzov 1988). Intervals are proposed to be used both for observational estimates of galactic parameters (GPs) and for the values of MPs. In this work we consider a model as a tool for studying mutual interaction of GPs. Two-component model is considered (Kutuzov, Ossipkov 1989). We have to estimate the array P of eight MPs.

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Review Summary Generation in Online Systems: Frameworks for Supervised and Unsupervised Scenarios

ACM Transactions on the Web ◽

10.1145/3448015 ◽

2021 ◽

Vol 15 (3) ◽

pp. 1-33

Author(s):

Wenjun Jiang ◽

Jing Chen ◽

Xiaofei Ding ◽

Jie Wu ◽

Jiawei He ◽

...

Keyword(s):

Decision Making ◽

Real World ◽

Text Summarization ◽

Experimental Results ◽

Product Review ◽

Comprehensive Review ◽

Online Systems ◽

Real World Datasets ◽

Different Characteristics

In online systems, including e-commerce platforms, many users resort to the reviews or comments generated by previous consumers for decision making, while their time is limited to deal with many reviews. Therefore, a review summary, which contains all important features in user-generated reviews, is expected. In this article, we study “how to generate a comprehensive review summary from a large number of user-generated reviews.” This can be implemented by text summarization, which mainly has two types of extractive and abstractive approaches. Both of these approaches can deal with both supervised and unsupervised scenarios, but the former may generate redundant and incoherent summaries, while the latter can avoid redundancy but usually can only deal with short sequences. Moreover, both approaches may neglect the sentiment information. To address the above issues, we propose comprehensive Review Summary Generation frameworks to deal with the supervised and unsupervised scenarios. We design two different preprocess models of re-ranking and selecting to identify the important sentences while keeping users’ sentiment in the original reviews. These sentences can be further used to generate review summaries with text summarization methods. Experimental results in seven real-world datasets (Idebate, Rotten Tomatoes Amazon, Yelp, and three unlabelled product review datasets in Amazon) demonstrate that our work performs well in review summary generation. Moreover, the re-ranking and selecting models show different characteristics.

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A Two‐Component Model for the Light Curves of Hypernovae

The Astrophysical Journal ◽

10.1086/376591 ◽

2003 ◽

Vol 593 (2) ◽

pp. 931-940 ◽

Cited By ~ 112

Author(s):

Keiichi Maeda ◽

Paolo A. Mazzali ◽

Jingsong Deng ◽

Ken’ichi Nomoto ◽

Yuzuru Yoshii ◽

...

Keyword(s):

Light Curves ◽

Component Model ◽

Two Component

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A modified two-component model for particle production and multiplicity distribution at high-energy

Lettere al Nuovo Cimento ◽

10.1007/bf02745901 ◽

1975 ◽

Vol 13 (16) ◽

pp. 615-619

Author(s):

S. Minami

Keyword(s):

Particle Production ◽

Multiplicity Distribution ◽

High Energy ◽

Component Model ◽

Two Component

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Investigations of Tail and Defect States in a-Si0.6Ge0.4:H Alloys by PDS and ESR - Implications for the Interaction of Weak and Dangling Bonds

MRS Proceedings ◽

10.1557/proc-377-571 ◽

1995 ◽

Vol 377 ◽

Author(s):

Tilo P. Drüsedau ◽

Andreas N. Panckow ◽

Bernd Schröder

Keyword(s):

Silicon Germanium ◽

Defect Density ◽

State Density ◽

Model Parameters ◽

Defect States ◽

Conversion Model ◽

Order Of Magnitude ◽

Underlying Mechanisms ◽

Amorphous Silicon Germanium ◽

Excess Absorption

ABSTRACTInvestigations on the gap state density were performed on a variety of samples of hydrogenated amorphous silicon germanium alloys (Ge fraction around 40 at%) containing different amounts of hydrogen. From subgap absorption measurements the values of the “integrated excess absorption” and the “defect absorption” were determined. Using a calibration constant, which is well established for the determination of the defect density from the integrated excess absorption of a-Si:H and a-Ge:H, it was found that the defect density is underestimated by nearly one order of magnitude. The underlying mechanisms for this discrepancy are discussed. The calibration constants for the present alloys are determined to 8.3×1016 eV−1 cnr2 and 1.7×1016 cm−2 for the excess and defect absorption, respectively. The defect density of the films was found to depend on the Urbach energy according to the law derived from Stutzmann's dangling bond - weak bond conversion model for a-Si:H. However, the model parameters - the density of states at the onset of the exponential tails N*=27×1020 eV−1 cm−3 and the position of the demarcation energy Edb-E*=0.1 eV are considerably smaller than in a-Si:H.

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