COMPUTATIONAL STUDIES OF MAIN GROUP CLUSTERS AS CATALYSTS IN ORGANIC SYNTHESIS

主族簇作为有机合成催化剂的计算研究

基本信息

  • 批准号:
    2905622
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Studentship
  • 财政年份:
    2023
  • 资助国家:
    英国
  • 起止时间:
    2023 至 无数据
  • 项目状态:
    未结题

项目摘要

The industrial production of chemicals accounts for £34 Bn within the UK manufacturing sector, and up to 90% of chemical products require the use of a catalyst at some point in their preparation. These catalysts are often based on expensive precious metals such as palladium, platinum and rhodium, but excessive mining of these non renewable resources has exacerbated environmental and geopolitical issues associated with their use, as well as the costs. Developing alternatives based on earth abundant main group elements, such as phosphorus, is increasingly urgent and has garnered global attention.Industry favours heterogeneous catalysts because of their greater stability and recyclability, and lower separation/purification costs compared with homogeneous catalysts. One attractive and inexpensive heterogeneous material is red phosphorus, but its catalytic applications are in their infancy. Mechanistic investigations are essential to developing better catalysts, but heterogeneous materials can be difficult to study. Molecular clusters occupy an important middle ground between molecules and bulk solids, allowing them to act as stepping stones. For example, [P7] Zintl clusters can be viewed as a fragment of red phosphorus. Thus, improved understanding of the reactivity patterns of [P7] should inform the corresponding reactions with red phosphorus. It is therefore exciting that the Mehta group has recently found the first application of these clusters in the metal-free catalytic reduction of C=O bonds.[P7] clusters represent a new family of metal-free catalysts. Since discovering that they can mediate the reduction of C=O bonds, the Mehta group has also found that they are competent catalysts for the hydroboration of imines, nitriles and pyridines, and are expected to facilitate many other organic transformations. However, better mechanistic understanding is necessary in order to optimize existing transformations and to uncover new ones. Such understanding can be furnished in exquisite detail by computational quantum chemistry at the density functional theory (DFT) level, which can work in conjunction with experiment to optimise protocols and guide experiment to improved catalysts.This computational PhD project involves three work packages (WPs):WP1: Mechanism of imine, nitrile and pyridine reductions. This WP will establish the mechanism of the catalytic hydroboration of C-N multiple bonds and pyridines. As these catalytic transformations have already been established experimentally, the computational student will begin by working on well-characterized systems, thereby mitigating risk.WP2: New hydrofunctionalization catalytic transformations. WP2 will study how the energy profiles of the catalytic transformations change when the organic substrate is altered from C-N multiply bonded species to more ambitious non-polar multiple bonds, such as alkenes and alkynes. The reductant will also be tuned from hydroboranes to hydrosilanes, hydroamines and H2 gas. Computational predictions will be tested experimentally in the Mehta group, exploring these new catalytic reactions and identifying computed intermediates. Computationally-located transition states, and hence activation energies, will link with experimentally determined kinetic parameters.WP3: Improved catalyst design. The first generation transition metal free Zintl catalysts are based on phosphorus clusters with boron functional groups. WP3 will study how the energy profiles of the catalytic transformations change upon replacing the boron group by aluminium or indium moieties. In addition, the cluster component will be tuned from [P7] to [As7]; the latter feature weaker Group15-Group13 bonds which may alter catalytic behaviour. A number of such catalyst variants have already been synthesized in the Mehta group; optimization of these, and new variants, based on DFT predictions will also be explored experimentally.
化学品的工业生产在英国制造业中占340亿英镑,高达90%的化学产品在制备过程中需要使用催化剂。这些催化剂通常基于昂贵的贵金属,如钯、铂和铑,但这些不可再生资源的过度开采加剧了与其使用相关的环境和地缘政治问题以及成本。开发基于地球上丰富的主族元素(如磷)的替代品越来越紧迫,并已引起全球的关注。工业界青睐多相催化剂,因为与均相催化剂相比,多相催化剂具有更高的稳定性和可回收性,并且分离/纯化成本更低。一种有吸引力且廉价的非均相材料是赤磷,但其催化应用仍处于起步阶段。机理研究对于开发更好的催化剂至关重要,但非均相材料可能很难研究。分子团簇占据了分子和大块固体之间的重要中间地带,使它们能够充当垫脚石。例如,[P7] Zintl团簇可以被视为赤磷的碎片。因此,对[P7]的反应模式的更好理解应该为与赤磷的相应反应提供信息。因此,令人兴奋的是,Mehta集团最近发现了这些簇在C=O键的无金属催化还原中的首次应用。[P7]簇代表了一类新的无金属催化剂。由于发现它们可以介导C=O键的还原,Mehta小组还发现它们是亚胺,腈和吡啶的硼氢化的胜任催化剂,并有望促进许多其他有机转化。然而,为了优化现有的转换并发现新的转换,需要更好的机械理解。这种理解可以通过密度泛函理论(DFT)水平上的计算量子化学提供精致的细节,它可以与实验结合,以优化协议并指导实验改进催化剂。这个计算博士项目涉及三个工作包(WP):WP 1:亚胺,腈和吡啶还原的机理。本工作将建立C-N重键和吡啶的催化硼氢化反应机理。由于这些催化转化已经在实验中建立,计算型学生将开始研究表征良好的系统,从而降低风险。WP 2:新的氢官能化催化转化。WP 2将研究当有机基质从C-N多重键合物种改变为更雄心勃勃的非极性多重键(如烯烃和炔烃)时,催化转化的能量分布如何变化。还原剂也将从氢硼烷调整为氢硅烷、氢胺和H2气体。计算预测将在Mehta小组中进行实验测试,探索这些新的催化反应并识别计算中间体。计算定位的过渡态,因此活化能,将与实验确定的动力学参数。WP 3:改进的催化剂设计。第一代不含过渡金属的Zintl催化剂基于具有硼官能团的磷簇。WP 3将研究在用铝或铟部分取代硼基团后,催化转化的能量分布如何变化。此外,簇组分将从[P7]调整到[As 7];后者具有较弱的15 - 13族键,这可能会改变催化行为。在Mehta组中已经合成了一些这样的催化剂变体;基于DFT预测的这些和新变体的优化也将通过实验进行探索。

项目成果

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其他文献

Internet-administered, low-intensity cognitive behavioral therapy for parents of children treated for cancer: A feasibility trial (ENGAGE).
针对癌症儿童父母的互联网管理、低强度认知行为疗法:可行性试验 (ENGAGE)。
  • DOI:
    10.1002/cam4.5377
  • 发表时间:
    2023-03
  • 期刊:
  • 影响因子:
    4
  • 作者:
  • 通讯作者:
Differences in child and adolescent exposure to unhealthy food and beverage advertising on television in a self-regulatory environment.
在自我监管的环境中,儿童和青少年在电视上接触不健康食品和饮料广告的情况存在差异。
  • DOI:
    10.1186/s12889-023-15027-w
  • 发表时间:
    2023-03-23
  • 期刊:
  • 影响因子:
    4.5
  • 作者:
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The association between rheumatoid arthritis and reduced estimated cardiorespiratory fitness is mediated by physical symptoms and negative emotions: a cross-sectional study.
类风湿性关节炎与估计心肺健康降低之间的关联是由身体症状和负面情绪介导的:一项横断面研究。
  • DOI:
    10.1007/s10067-023-06584-x
  • 发表时间:
    2023-07
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
  • 通讯作者:
ElasticBLAST: accelerating sequence search via cloud computing.
ElasticBLAST:通过云计算加速序列搜索。
  • DOI:
    10.1186/s12859-023-05245-9
  • 发表时间:
    2023-03-26
  • 期刊:
  • 影响因子:
    3
  • 作者:
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Amplified EQCM-D detection of extracellular vesicles using 2D gold nanostructured arrays fabricated by block copolymer self-assembly.
使用通过嵌段共聚物自组装制造的 2D 金纳米结构阵列放大 EQCM-D 检测细胞外囊泡。
  • DOI:
    10.1039/d2nh00424k
  • 发表时间:
    2023-03-27
  • 期刊:
  • 影响因子:
    9.7
  • 作者:
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的其他文献

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Field Assisted Sintering of Nuclear Fuel Simulants
核燃料模拟物的现场辅助烧结
  • 批准号:
    2908917
  • 财政年份:
    2027
  • 资助金额:
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Assessment of new fatigue capable titanium alloys for aerospace applications
评估用于航空航天应用的新型抗疲劳钛合金
  • 批准号:
    2879438
  • 财政年份:
    2027
  • 资助金额:
    --
  • 项目类别:
    Studentship
Developing a 3D printed skin model using a Dextran - Collagen hydrogel to analyse the cellular and epigenetic effects of interleukin-17 inhibitors in
使用右旋糖酐-胶原蛋白水凝胶开发 3D 打印皮肤模型,以分析白细胞介素 17 抑制剂的细胞和表观遗传效应
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