Multi-user, High-Throughput Facility for Compositional Analysis of Molecules and Materials

用于分子和材料成分分析的多用户、高通量设备

• 批准号: RTI-2021-00146
• 负责人: Chitnis, Saurabh
• 金额: $ 7.93万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Research Tools and Instruments
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=717883
• 关键词: Multi; user; Throughput; Facility; Compositional

Establishing the elemental composition of samples is essential across all disciplines of experimental chemistry. While spectroscopic methods such as nuclear magnetic resonance (NMR) and mass spectrometry (MS) provide complementary information about connectivity, the high-sensitivity and phase-independence of elemental analysis (EA) makes it the gold standard for i) characterizing insoluble solids, ii) for samples that are unresponsive to other techniques (e.g. NMR-silent nuclei, 3-D materials), and iii) for assessing bulk purity. Since starting up in 2018, the principal applicant has established an internationally recognized program of strategic molecular design to elicit new properties from main group elements (see profile in Chem. Commun. Emerging Investigators Issue, 9 independent publications, invited book chapter, 2 conferences organized in 2 years). A key aspect of this program involves using geometric design to access fundamentally new types of materials that contain 3-D molecular cages in the back bone. Due to their all-heteroatom backbone and cage microstructure, these polymers have mobile electrons for conductivity and physical properties of rigid-rod systems, making them potentially valuable electronic and structural materials. Networks derived from such polymers behave as precursors to shape-defined metal phosphide ceramics. Characterizing these fascinating but insoluble solid-state materials requires high-frequency access to C, H, N, S, O analysis (to map 5/6 elements comprising them). Lacking this data, the principal applicant is unable to proceed, thereby forfeiting impactful science and his position as a recognized leader at a sensitive career stage. EA data is critical to this project and will provide immediately actionable insights to guide research in the moment it happens. For example, frequent assays of monomer batches are required to access high molecular weight inorganic polymers, interpret polymerization kinetics, and detect end groups. The organic residue in ceramics must also be quantified as their functional properties (e.g. conductivity) are influenced by such impurities. Besides the principal applicant, 6 additional groups (Freund, Thompson, Turculet, Stradiotto, Speed, Doucette) are critically impeded by timely access to this data as samples are either not amenable to solution methods or too sensitive to be analyzed at external facilities with unpredictable delays. This data is vital in catalysis, where impurities can mediate side-reactions, and in synthetic chemistry more broadly when salt metathesis reactions (involving NMR-silent metal halides or radicals) are involved. EA data also provides key insights in proteomics research as an unbiased evaluation of analyte recovery for proteins from biological systems. In light of the above, this joint application from 7 researchers spanning multiple career stages across 4 disciplines seeks funding for a system capable of high-throughput C, H, N, S, O analysis.

确定样品的元素组成在实验化学的所有学科中都是必不可少的。虽然核磁共振（NMR）和质谱（MS）等光谱方法提供了有关连通性的补充信息，但元素分析（EA）的高灵敏度和相位独立性使其成为i）表征不溶性固体，ii）对其他技术无响应的样品（例如NMR沉默核，3-D材料）和iii）评估散装纯度的黄金标准。 自2018年启动以来，主申请人已经建立了一个国际公认的战略分子设计计划，以从主族元素中获得新的特性（参见Chem. Commun.新兴调查员问题，9个独立出版物，邀请书章，2年内组织的2次会议）。该计划的一个关键方面涉及使用几何设计来获得在脊柱中包含3D分子笼的新型材料。由于它们的全杂原子主链和笼状微结构，这些聚合物具有移动的电子，从而具有刚性棒体系的导电性和物理性质，使它们成为潜在的有价值的电子和结构材料。由这种聚合物衍生的网络表现为形状限定的金属磷化物陶瓷的前体。表征这些迷人但不溶性的固态材料需要高频访问C，H，N，S，O分析（以映射组成它们的5/6元素）。如果没有这些数据，主申请人就无法继续进行，从而失去了有影响力的科学和他作为敏感职业阶段公认领导者的地位。EA数据对该项目至关重要，并将提供立即可操作的见解，以在发生时指导研究。例如，需要对单体批次进行频繁的分析，以获得高分子量无机聚合物，解释聚合动力学，并检测端基。陶瓷中的有机残留物也必须量化，因为它们的功能特性（例如导电性）受到这些杂质的影响。 除主要申请人外，另外6个组（Freund、Thompson、Turculet、Stradiotto、Speed、Doucette）因无法及时获取该数据而受到严重阻碍，因为样品要么不适合溶液方法，要么过于敏感，无法在外部机构进行分析，延迟不可预测。这些数据在催化中至关重要，杂质可以介导副反应，并且在更广泛的合成化学中，当涉及盐复分解反应（涉及NMR沉默金属卤化物或自由基）时。EA数据还为蛋白质组学研究提供了关键见解，作为对生物系统中蛋白质的分析物回收的无偏见评估。 鉴于上述情况，来自4个学科多个职业阶段的7名研究人员的联合申请旨在为能够进行高通量C，H，N，S，O分析的系统寻求资金。