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相关概念视频

Combustion Energy: A Measure of Stability in Alkanes and Cycloalkanes02:14

Combustion Energy: A Measure of Stability in Alkanes and Cycloalkanes

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The low reactivity in alkanes can be attributed to the non-polar nature of C–C and C–H σ bonds. Alkanes, therefore, were  initially termed as “paraffins,” derived from the Latin words: parum, meaning “too little,” and affinis, meaning “affinity.”
Alkanes undergo combustion in the presence of excess oxygen and high-temperature conditions to give carbon dioxide and water. A combustion reaction is the energy source in natural gas, liquified...
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Flame Photometry: Overview01:02

Flame Photometry: Overview

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Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
589
Atomic Spectroscopy: Effects of Temperature01:27

Atomic Spectroscopy: Effects of Temperature

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Atomization, converting samples into gas-phase atoms and ions, is essential for atomic spectroscopy. The flame temperature required for atomization affects the efficiency of the atomic spectroscopic methods by increasing the atomization efficiency and the relative population of the excited and ground states.
At thermal equilibrium, the relative populations of excited and ground state atoms can be estimated using the Maxwell–Boltzmann distribution. For example, an increase in temperature...
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Heating and Cooling Curves02:44

Heating and Cooling Curves

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When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
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Measurement: Derived Units03:02

Measurement: Derived Units

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The International System of Units or SI system, by international agreement, has fixed measurement units for seven fundamental properties: length, mass, time, temperature, electric current, amount of substance, and luminosity. These are called the SI base units.
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Flame Photometry: Lab01:16

Flame Photometry: Lab

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In a flame photometer, when a solution like potassium chloride is aspirated into the flame, the solvent evaporates, leaving behind dehydrated salt. This salt dissociates into free gaseous atoms in their ground state. Some of these atoms absorb energy from the flame, leading to their excitation. The excited atoms return to the ground state, emitting photons at characteristic wavelengths. Because only electronic transitions are involved, the resulting emission lines are very narrow. The intensity...
246

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相关实验视频

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Combustion Chemistry of Fuels: Quantitative Speciation Data Obtained from an Atmospheric High-temperature Flow Reactor with Coupled Molecular-beam Mass Spectrometer
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Combustion Chemistry of Fuels: Quantitative Speciation Data Obtained from an Atmospheric High-temperature Flow Reactor with Coupled Molecular-beam Mass Spectrometer

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定量结构-属性关系建模自燃温度:评估和比较分析.

J Chen1, L Zhu1, J Wang1

  • 1College of Chemical Engineering, Zhejiang University of Technology, Hangzhou, China.

SAR and QSAR in environmental research
|February 19, 2024
PubMed
概括

这项研究将量化结构与属性关系 (QSPR) 模型用于预测自燃温度 (AIT),引入基于图形的新型深度学习,以加强化学危险评估.

科学领域:

  • 化学安全和危险评估.
  • 计算化学和化学信息学
  • 量化结构与财产关系 (QSPR) 建模.

背景情况:

  • 自燃温度 (AIT) 是评估化学物质危险性的关键参数.
  • 准确的AIT预测对于建立强大的安全协议和方法至关重要.
  • 现有的QSPR模型需要进一步研究以提高性能和可靠性.

研究的目的:

  • 为AIT预测进行传统QSPR模型和新型深度学习方法的基准测试.
  • 在AIT建模中首次引入和评估基于图形的深度学习技术.
  • 通过专注于数据质量和高级功能工程来增强AIT预测.

主要方法:

  • 评估传统的QSPR模型:多线性回归,支持向量回归和人工神经网络.
  • 基于图形的深度学习的应用,特别是传递信息的神经网络.
  • 实施最先进的功能工程工作流程和图形数据增强技术.
  • 在建模过程中明确考虑数据质量.

主要成果:

  • 传统QSPR模型的预测性能与基于图形的新型深度学习模型的比较.
  • 在QSPR中展示先进特征工程和数据增强的有效性.
  • 建立未来AIT预测研究的基准.
关键词:
多重线性回归的多重线性回归.这就是QSPR.人工神经网络的人工神经网络传递信息的神经网络的神经网络模拟建模模型的使用方法支持向量的回归.

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Reaction Kinetics and Combustion Dynamics of I4O9 and Aluminum Mixtures
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Combustion Chemistry of Fuels: Quantitative Speciation Data Obtained from an Atmospheric High-temperature Flow Reactor with Coupled Molecular-beam Mass Spectrometer
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Combustion Chemistry of Fuels: Quantitative Speciation Data Obtained from an Atmospheric High-temperature Flow Reactor with Coupled Molecular-beam Mass Spectrometer

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Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames
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Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames

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结论:

  • 基于图形的深度学习为准确的AIT预测提供了有希望的进步.
  • 数据质量评估和复杂的功能工程的整合对于QSPR模型开发至关重要.
  • 这项工作为通过先进的计算方法改进化学危险评估提供了基础.