CDS&E: Collaborative Research: Towards computational discovery of synthetically feasible porous organic frameworks

共价有机骨架（COFs）是一类新兴的有机材料，具有低密度、高热稳定性和稳定的孔隙率，应用于分子分离、催化、储能、半导体、药物传递和单分子传感器等领域。它们是通过有机构建块（BB）分子的动态共价组装构建的，在这个过程中，BB本质上聚合形成延伸的晶体材料。COF“宇宙”，即所有可能的COF结构的集合，是巨大的，可能包含数十亿种具有不同孔径、几何形状、化学成分和功能的潜在候选物。到目前为止，这个“宇宙”中只有一小部分被合成，尽管新的cof不断被报道。然而，目前报道的具有两种以上孔隙类型的COFs仍然很少，这是一个关键的缺点，因为具有不同孔径组合的COFs有望增强约束下的催化作用、分子分离过程和气体储存应用。设计合成碳纳米管的一个重要思想，被称为网状化学，是识别刚性BB分子，这些分子可以通过共价键独特地组装成所需的碳纳米管图案。虽然非常有用，但相关的化学设计通常是手动实现的，因此不能扩展到更复杂的拓扑结构，也不能枚举cof的巨大空间。在此背景下，本研究的目标是开发一种计算方法来自动生成具有多种孔径的合成可行的二维共价有机框架，从而指导合成复杂结构的实验工作。合成可行性考虑的是构建块是否可以使用已知的化学物质和起始材料轻松创建，并轻松组装成所需的晶体COF结构。本研究汇集了化学信息学、反应网络生成、高级分子模拟和人工智能等工具，创建了一种自动化方法来识别COFs，这些COFs可以使用容易获得的起始材料和经过验证的有机化学物质合成。该方法将用于创建具有复杂（特别是杂孔）拓扑结构的COFs数据库。给定目标结构，该方法将通过粗粒度的分子样斑块粒子模拟来识别必要的构建块结构及其化学功能。结果信息将用于使用基于强化学习的有偏差自动网络生成过程来生成潜在的分子构建块。然后将使用化学信息学工具和算法评估这些分子构建块的合成复杂性。对于最具合成可行性的分子，它们的合成路线将通过自动网络生成，使用反合成的概念来生成。这个过程的最终结果将是一个理论上确定的合成可行的COFs，它们的构建块和它们的合成路线的列表。这样的列表将为每个贴片编制，并根据综合分数进行排名。通过该策略确定的一些最有希望的COFs将在自下而上的组装中进行实验验证，该组装涉及构建块的合成及其使用正交反应化学的组装。为了整合研究和教育，pi将采用学生主导原创科学研究内容创造的概念，作为课程培训的一部分，或“班级采购”，通过设计课程项目，利用整个学生群体的累积专业知识来确定合成新构建模块的策略，从而改进网络生成的规则。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Covalent organic frameworks (COFs) belong to an emerging class of organic materials with low density, high thermal stability, and stable porosity, with applications including molecular separations, catalysis, energy storage, semiconductors, drug delivery, and single-molecule sensors. They are constructed via dynamic covalent assembly of organic building-block (BB) molecules, a process wherein the BBs essentially polymerize to form an extended crystalline material. The COF “universe,” i.e. the set of all possible COF structures, is vast and potentially comprises billions of potential candidates with varying pore size and geometry, chemical composition, and functionality. Only a small fraction of this “universe” has been synthesized so far, although new COFs are continuously being reported. Nevertheless, there are still very few reported COFs with more than two types of pores, a critical shortcoming because COFs with combinations of pore sizes hold promise for enhancing catalysis under confinement, molecular separation processes, and gas storage applications. A prominent idea for designed synthesis of COFs, known as reticular chemistry, is to identify rigid BB molecules that can be uniquely assembled into the desired COF pattern via covalent bonds. While extremely useful, the related chemical design is often implemented manually, and is therefore not scalable to more complex topologies nor is it able to enumerate the vast space of COFs. In this context, the goal of this research is to develop a computational method to automatically generate synthetically feasible 2D covalent organic frameworks with multiple pore sizes and thereby guide experimental efforts to synthesize complex structures. Synthetic feasibility considers whether the building block(s) can be easily created using known chemistries and starting materials and easily assembled into the requisite crystalline COF structure.This research brings together tools from cheminformatics, reaction network generation, advanced molecular simulations, and artificial intelligence to create an automated method to identify COFs that can be synthesized using easily available starting materials and proven organic chemistries. This method will be used to create a database of COFs with complex (in particular heteroporous) topology. Given a target structure, the method will identify the necessary building block structure and its chemical functionality via coarse-grained molecule-like patchy particle simulations. The resulting information will be used to generate potential molecular building blocks using a reinforcement learning-based biased automated network generation process. The synthetic complexity of these molecular building blocks will then be evaluated using cheminformatics tools and algorithms. For the most synthetically feasible molecules, their synthesis routes will be generated using the concept of retrosynthesis via automated network generation. The end result of this process will be a list of theoretically determined synthetically feasible COFs, their building blocks, and their synthesis routes. Such lists will be compiled for each tiling and ranked based on the synthesis scores. A few of the most promising COFs identified through this strategy will be verified experimentally in a bottom-up assembly involving synthesis of the building blocks and their assembly using orthogonal reaction chemistries. To integrate research and education, the PIs will employ the concept of student-led creation of original scientific research content as part of curricular training, or “class sourcing,” by designing course projects wherein the cumulative expertise of the entire cohort of students is leveraged to identify strategies to synthesize new building blocks and thereby improve rules for network generation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.