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Computer-aided molecular design using the signature molecular descriptor: An application to design novel chemical admixtures for concrete.

机译:使用签名分子描述符的计算机辅助分子设计:一种设计用于混凝土的新型化学外加剂的应用。

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摘要

The development of new chemical admixtures for concrete is normally an experimental endeavor in that the molecular scaffolds of existing admixtures are modified and tested. This approach is time consuming, incremental and typically expensive. Alternatively, a computer-aided molecular design (CAMD) approach is proposed that uses the Signature molecular descriptor. CAMD is the application of computer-implemented algorithms that are utilized to design molecules with optimally predicted properties such that they can be tested and evaluated for efficacy. After creating and refining a quantitative structure-property relationship (QSPR) model for a property of interest, a structure enumeration algorithm is employed to generate structures outside of the original training set that have optimally predicted properties. In this research, the novel CAMD approach is shown in application for designing two types of chemical admixtures are of interest: (1) water-reducing admixtures (WRAs) and (2) shrinkage-reducing admixtures (SRAs).;WRAs have been developed to reduce the required water content of concrete while maintaining a flowable cementitious material, described by its rheological properties. A parallel-plate rheometer was used to measure the effect of eighteen low molecular weight organic chemicals on rheology by directly obtaining yield stress and viscosity data. Workability, measured by a mini-slump cone test, is reported for comparison. Chemical structures were examined and analyzed for their effect on flow properties and set time. Sugar acids proved to be the most effective in reducing yield stress, viscosity, and increasing workability. Sugar alcohols with more hydroxyl groups and longer carbon backbone chains decrease plastic viscosity. Results suggest that mini-slump cone test is unreliable for measuring workability, and that more complex rheology-based protocols have to be employed to better translate cement paste workability to application targets. The CAMD methodology using the Signature molecular descriptor was used in order to identify new chemicals with high workability, low yield stress and viscosity, and short set times that might serve as a new generation of WRAs. Beginning with a training set of the eighteen tested compounds, the technique combines the atomic Signatures in novel ways to identify non-intuitive compounds with optimal predicted properties.;For SRAs, the property of interest is the surface tension of compounds in aqueous solutions as this property is related to shrinkage in concrete. By evaluating the initial surface tension reduction of amines and glycol ethers in solution with water, a number of structure-property conjectures associated with the effect of these compounds were developed. Accordingly, 14 compounds were identified and utilized as a training set for the CAMD algorithm and new compounds were identified. The surface tension reduction for the newly identified compounds was experimentally evaluated. Furthermore, the effect of five newly identified compounds on autogenous and drying shrinkage as well as the compressive strength of the cement paste were tested and compared to two commercial SRAs. Results for both types of shrinkage indicate that the designed compounds perform similar to commercial admixtures, yet have different chemical functionalities and better strength development.
机译:用于混凝土的新型化学外加剂的开发通常是一项实验性尝试,因为对现有外加剂的分子支架进行了改性和测试。这种方法耗时,增量并且通常很昂贵。或者,提出了一种使用签名分子描述符的计算机辅助分子设计(CAMD)方法。 CAMD是计算机实现的算法的应用,可用于设计具有最佳预测特性的分子,以便可以对它们进行测试和评估功效。在为感兴趣的属性创建并完善了定量的结构-属性关系(QSPR)模型之后,使用结构枚举算法在原始训练集之外生成具有最佳预测属性的结构。在这项研究中,新颖的CAMD方法在设计两种感兴趣的化学掺合料的应用中得到了展示:(1)减水掺合料(WRA)和(2)减缩掺合料(SRA)。降低混凝土所需的水含量,同时保持一种可流动的胶结材料,其流变性能可以描述。通过直接获得屈服应力和粘度数据,使用平行板流变仪测量了18种低分子量有机化学物质对流变学的影响。报告了通过微型坍落度试验测量的可加工性,以进行比较。检查并分析了化学结构对流动性能和凝固时间的影响。事实证明,糖酸在降低屈服应力,粘度和增加可加工性方面最有效。具有更多羟基和更长碳主链的糖醇会降低塑料粘度。结果表明,微型坍落度圆锥试验对于测量可加工性是不可靠的,必须采用更复杂的基于流变学的方案才能更好地将水泥浆的可加工性转化为应用目标。为了识别具有高可加工性,低屈服应力和粘度以及较短凝固时间的新型化学药品,使用了使用签名分子描述符的CAMD方法,可以用作新一代WRA。从一组18种测试化合物的培训开始,该技术以新颖的方式结合了原子签名,以鉴定具有最佳预测特性的非直觉化合物。对于SRA,关注的特性是水溶液中化合物的表面张力,因为性与混凝土的收缩有关。通过评估水与溶液中胺和乙二醇醚的初始表面张力降低,开发了许多与这些化合物的作用有关的结构性质推测。因此,鉴定出14种化合物并将其用作CAMD算法的训练集,并鉴定了新化合物。通过实验评估了新发现的化合物的表面张力降低。此外,测试了五种新发现的化合物对自生和干燥收缩率以及水泥浆抗压强度的影响,并与两种市售SRA进行了比较。两种收缩率的结果均表明,所设计的化合物的性能与市售掺合物相似,但具有不同的化学官能度和更好的强度发展。

著录项

  • 作者

    Kayello, Hamed.;

  • 作者单位

    The University of Akron.;

  • 授予单位 The University of Akron.;
  • 学科 Chemical engineering.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 248 p.
  • 总页数 248
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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