Genesis

Chiu, Alton; Garvey, Joseph D.; Abdelrahman, Tarek S.

doi:10.1145/2742854.2742883

Cited by 5 publications

(2 citation statements)

References 18 publications

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“…Colloidal redox phenomena are commonly observed when SWCNT are exposed to standard illumination sources. 38,40,41,60 Detection of solution reactivity (ΔpH, Figures 5 and S7) following the coating's pK a supports a photosensitization scheme in which the SWCNT excited state is sensitive to modification of the reduction/oxidation environment, including the addition of ionizable groups to the coating (Figure S9). We further discuss one implication for routine characterization in the Supporting Information.…”

Section: Discussionmentioning

confidence: 89%

“…Many coatings that stably suspend nanotubes, e.g., DNA and cellulose polymers, have pH-dependent redox properties (show electrochemical response in the presence of reducing or oxidizing agents). [49][50][51][52][53][54][55][56][57] Notably, O 2 /H 2 O redox activity is frequently observed in aqueous suspensions of coated nanotubes 35,37,40,41,[58][59][60] as well as in suspensions of biomolecules such as DNA oligomers in contact with dye photosensitizers. 61 Herein, we investigate the excited-state electrochemical behavior of carbon nanotubes and their interaction with nonconducting polymer coatings.…”

Section: Introductionmentioning

confidence: 99%

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Optical Voltammetry of Polymer-Encapsulated Single-Walled Carbon Nanotubes

et al. 2019

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The semiconducting single-walled carbon nanotube (SWCNT), noncovalently wrapped by a polymeric monolayer, is a nanoscale semiconductor-electrolyte interface under investigation for sensing, photonics, and photovoltaic applications. SWCNT complexes are routinely observed to sensitize various electrochemical/redox phenomena, even in the absence of an external field. While the photoluminescence response to gate voltage depends on the redox potential of the nanotube, analogous optical voltammetry of functionalized carbon nanotubes could be conducted in suspension without applying voltage but by varying the solution conditions as well as the chemistry of the encapsulating polymer. Steady-state photoluminescence, absorbance, and in situ measurements of O 2 /H 2 O reactivity show correlation with the pH/pK a -dependent reactivity of πrich coatings. The nanotube emission responses suggest that the presence of photogenerated potential may explain the observed coating electrochemical reactivity. This work finds that electronic and chemical interactions of the nanotube with the encapsulating polymer may play a critical role in applications that depend on radiative recombination, such as optical sensing.

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Section: Discussionmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Optical Voltammetry of Polymer-Encapsulated Single-Walled Carbon Nanotubes

et al. 2019

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Synthesizing benchmarks for predictive modeling

Cummins

Petoumenos

Wang

et al. 2017

2017 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)

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Predictive modeling using machine learning is an effective method for building compiler heuristics, but there is a shortage of benchmarks. Typical machine learning experiments outside of the compilation field train over thousands or millions of examples. In machine learning for compilers, however, there are typically only a few dozen common benchmarks available. This limits the quality of learned models, as they have very sparse training data for what are often high-dimensional feature spaces. What is needed is a way to generate an unbounded number of training programs that finely cover the feature space. At the same time the generated programs must be similar to the types of programs that human developers actually write, otherwise the learning will target the wrong parts of the feature space. We mine open source repositories for program fragments and apply deep learning techniques to automatically construct models for how humans write programs. We sample these models to generate an unbounded number of runnable training programs. The quality of the programs is such that even human developers struggle to distinguish our generated programs from handwritten code. We use our generator for OpenCL programs, CLgen, to automatically synthesize thousands of programs and show that learning over these improves the performance of a state of the art predictive model by 1.27×. In addition, the fine covering of the feature space automatically exposes weaknesses in the feature design which are invisible with the sparse training examples from existing benchmark suites. Correcting these weaknesses further increases performance by 4.30×.

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Automatic Performance Tuning of Stencil Computations on GPUs

Garvey

Abdelrahman

2015

2015 44th International Conference on Parallel Processing

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Genesis

Cited by 5 publications

References 18 publications

Optical Voltammetry of Polymer-Encapsulated Single-Walled Carbon Nanotubes

Optical Voltammetry of Polymer-Encapsulated Single-Walled Carbon Nanotubes

Synthesizing benchmarks for predictive modeling

Automatic Performance Tuning of Stencil Computations on GPUs

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