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Method for controllably preparing semiconductor single-walled carbon nanotubes by combining high-throughput screening and machine learning

A single-walled carbon nanotube, semiconducting technology, applied in the field of high-throughput screening and machine learning combined with controllable preparation of semiconducting single-walled carbon nanotubes, can solve the problem of low efficiency, time-consuming semiconducting single-walled carbon nanotubes, Inaccurate and other issues, to speed up design, reduce research time and energy consumption, and standardize the effect of preparation

Active Publication Date: 2022-03-29
INST OF METAL RESEARCH - CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, it is time-consuming, inefficient and imprecise to manually process the high-throughput Raman spectral surface scan data to extract the position and number of breathing modes related to the growth parameters and then calculate the content of semiconducting SWNTs. of

Method used

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  • Method for controllably preparing semiconductor single-walled carbon nanotubes by combining high-throughput screening and machine learning
  • Method for controllably preparing semiconductor single-walled carbon nanotubes by combining high-throughput screening and machine learning
  • Method for controllably preparing semiconductor single-walled carbon nanotubes by combining high-throughput screening and machine learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] In this example, the method for the controllable preparation of semiconducting single-walled carbon nanotubes by combining high-throughput screening and machine learning is as follows:

[0046] First, 64 kinds of discrete cobalt / platinum / molybdenum catalyst thin film arrays were prepared on digitally marked silicon wafers by using a combined mask to assist ion beam deposition, and the thickness range of cobalt / platinum / molybdenum catalyst thin film arrays was 0~0.9nm (excluding 0, the thickness interval is 0.1nm), the coating process see figure 1 , coating thickness and mask rotation sequence are shown in Table 1, and the cobalt / platinum / molybdenum catalyst film array prepared is shown in figure 2 (a). The growth process is as follows: first, oxidize the cobalt / platinum / molybdenum catalyst array sample at 500°C for 10 minutes in an air atmosphere, and push the sample out of the high-temperature zone; secondly, raise the temperature of the tube furnace to 850°C, After...

Embodiment 2

[0049] In this example, the method for the controllable preparation of semiconducting single-walled carbon nanotubes by combining high-throughput screening and machine learning is as follows:

[0050] First, 64 kinds of discrete cobalt / platinum / molybdenum catalyst thin film arrays were prepared on digitally marked silicon wafers by using a combined mask to assist ion beam deposition, and the thickness range of cobalt / platinum / molybdenum catalyst thin film arrays was 0~0.9nm (excluding 0, the thickness interval is 0.1nm), the coating process see figure 1 , coating thickness and mask rotation sequence are shown in Table 1, and the cobalt / platinum / molybdenum catalyst film array prepared is shown in figure 2(a). The growth process is as follows: first, oxidize the cobalt / platinum / molybdenum catalyst array sample at 500°C for 10 minutes in an air atmosphere, and push the sample out of the high-temperature zone; secondly, raise the temperature of the tube furnace to 875°C, After ...

Embodiment 3

[0053] In this example, the method for the controllable preparation of semiconducting single-walled carbon nanotubes by combining high-throughput screening and machine learning is as follows:

[0054] First, 64 kinds of discrete cobalt / platinum / molybdenum catalyst thin film arrays were prepared on digitally marked silicon wafers by using a combined mask to assist ion beam deposition, and the thickness range of cobalt / platinum / molybdenum catalyst thin film arrays was 0~0.9nm (excluding 0, the thickness interval is 0.1nm), the coating process see figure 1 , coating thickness and mask rotation sequence are shown in Table 1, and the cobalt / platinum / molybdenum catalyst film array prepared is shown in figure 2 (a). The growth process is as follows: first, oxidize the cobalt / platinum / molybdenum catalyst array sample at 500°C for 10 minutes in an air atmosphere, and push the sample out of the high-temperature zone; secondly, raise the temperature of the tube furnace to 900°C, After...

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Abstract

The invention relates to the field of efficient and controllable preparation of semiconducting dominant single-walled carbon nanotubes, in particular to a method for controllable preparation of semiconducting single-walled carbon nanotubes through combination of high-throughput screening and machine learning. A combined mask plate is adopted to assist ion beam coating, and a discrete catalyst array is deposited on the digitally-marked silicon wafer in a high-flux mode; automatically representing the single-walled carbon nanotubes discretely distributed on the surface by adopting a Raman spectrometer and obtaining respiratory model information; the method comprises the following steps: automatically extracting the position and number of breathing modes from high-flux Raman spectrum data through an independently designed data mining tool, calculating and judging the conductive property of the single-walled carbon nanotubes on each catalyst array, and calculating the content of the metallic or semiconducting single-walled carbon nanotubes in combination with multi-wavelength Raman breathing mode data; and collecting high-throughput data to train a machine learning model, carrying out importance sorting on growth parameters influencing the conductive properties of the carbon nanotubes, and providing guidance for controllable preparation of high-purity semiconductor single-walled carbon nanotubes.

Description

technical field [0001] The invention relates to the field of efficient and controllable preparation of single-walled carbon nanotubes with superior semiconducting properties, specifically a method for the controllable preparation of semiconducting single-walled carbon nanotubes by combining high-throughput screening and machine learning, which is suitable for efficient screening of catalyst groups High-purity semiconducting single-walled carbon nanotubes were prepared by using process parameters such as temperature, growth temperature, reduction time, and carbon source concentration. Background technique [0002] Semiconducting single-walled carbon nanotubes have a large current on / off ratio and high carrier mobility, and are one of the ideal channel materials for future high-performance field-effect transistors. In order to obtain high-purity semiconducting single-walled carbon nanotubes, researchers have conducted in-depth explorations on the controllable growth of semicon...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C01B32/162G06N20/00C01B32/159
CPCC01B32/162G06N20/00C01B32/159C01B2202/22
Inventor 张莉莉吉忠海高张丹刘畅成会明
Owner INST OF METAL RESEARCH - CHINESE ACAD OF SCI
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