DMREF: Collaborative Research: Self-assembled peptide-pi-electron supramolecular polymers for bioinspired energy harvesting, transport and management

DMREF：合作研究：用于仿生能量收集、运输和管理的自组装肽-π-电子超分子聚合物

• 批准号: 1841807
• 负责人: Andrew Ferguson
• 金额: $ 52.52万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1841807&HistoricalAwards=false
• 关键词: DMREF; Collaborative; Research; Self; assembled

Non-technical Description: Nature exquisitely controls the spatial arrangement of key pigments and dyes in the process of photosynthesis to harness solar energy. Mimicry of controlled dye arrangements in synthetic materials can be realized through tailored design of molecules and molecular arrangements. However, exerting reliable control over the assembly of engineered molecular materials in the crucial 10-100 nanometer "mesoscale" regime, thousands of times smaller than a millimeter, remains elusive. Such mesoscale molecular structures will combine charge and energy transfer activities with capabilities for assembly in biological solutions, and compatibility with biological environments. Given the multitude of molecular design possibilities, it is essential that experimental programs incorporate computer modeling and data-driven screening to guide experimental design and synthesis. Tight integration and mutually reinforcing feedback between computation and experiment can reveal fundamental design rules for molecular assembly, and accelerate the discovery and development of multi-molecule assemblies with tailored structure and function. This project will develop these functional molecular superstructures in a collaboration encompassing molecular synthesis, self-assembly analogous to biological systems, modeling of the structures and electrical properties of the assemblies, and utilizing the assemblies to manage interactions between light and electricity. The PIs are committed to workforce training and development within this project, guiding the next generation of materials and data scientists of diverse socio-economic background in state-of-the-art tools and exposing them to an integrated interdisciplinary mode of work that will define future research. Technical Description: The photophysical and electrical properties of pi-conjugated supramolecular systems depend critically on the explicit nature of the intermolecular electronic interactions. These interactions are governed by the precise molecular structure and chemistry and emergent supramolecular arrangements. The PIs developed a peptide construct that offer a pathway to exert such control over emergent supramolecular structure through tailoring of steric bulk and variable hydrophobicity of the component sequences to influence intermolecular orientations, higher-order fibrilization, and specific electronic outcomes. They initially used an Edisonian approach to uncover these variations, but the goals of this project are to wield explicit engineered control through tightly integrated atomistic simulations and electronic structure calculations. The research activities build upon the team?s strong foundation to accomplish these goals in two specific objectives: (i) the development of sophisticated peptidic semiconductor materials with advanced optoelectronic functionality and (ii) the development of new assembly paradigms leading to heterogeneous peptidic nanomaterials with chemical and electronic gradients and localized electric fields. The execution of this work will entail interconnected efforts by the research team in the (i) synthesis of new pi-electron units and new self-assembling peptides, (ii) molecular and data-driven modeling of the nanomaterial aggregates and their higher-order assemblies, and (iii) characterization of electrical transport within the nanomaterials. This project will make special provision for research opportunities for undergraduate students, women, and underrepresented minorities. The PIs will train and mentor researchers in state-of-the-art experimental and computational tools and expose them to an integrated interdisciplinary mode of work. K-12 outreach activities will inspire excitement and awareness of materials science and encourage students to pursue higher education in science, technology, engineering, and math (STEM) fields.

非技术描述：大自然在光合作用利用太阳能的过程中巧妙地控制着关键颜料和染料的空间排列。 合成材料中受控染料排列的模拟可以通过分子和分子排列的定制设计来实现。然而，在关键的 10-100 纳米“介观尺度”（比一毫米小数千倍）范围内对工程分子材料的组装进行可靠的控制仍然难以实现。这种介观分子结构将电荷和能量转移活性与在生物溶液中组装的能力以及与生物环境的兼容性结合起来。鉴于分子设计的可能性众多，实验程序必须结合计算机建模和数据驱动的筛选来指导实验设计和合成。计算和实验之间的紧密集成和相互增强的反馈可以揭示分子组装的基本设计规则，并加速具有定制结构和功能的多分子组装体的发现和开发。该项目将通过合作开发这些功能性分子超结构，包括分子合成、类似于生物系统的自组装、组件的结构和电特性建模，以及利用组件来管理光和电之间的相互作用。 PI 致力于该项目中的劳动力培训和发展，指导具有不同社会经济背景的下一代材料和数据科学家使用最先进的工具，并使他们接触到综合的跨学科工作模式，该模式将定义未来的研究。技术描述：π共轭超分子系统的光物理和电学性质主要取决于分子间电子相互作用的明确性质。这些相互作用受到精确的分子结构和化学以及新兴的超分子排列的控制。 PI 开发了一种肽构建体，该构建体提供了一种途径，通过调整组件序列的空间体积和可变疏水性来影响分子间取向、高阶纤维化和特定的电子结果，从而对新兴超分子结构进行控制。他们最初使用爱迪生方法来揭示这些变化，但该项目的目标是通过紧密集成的原子模拟和电子结构计算来进行显式工程控制。研究活动建立在团队的坚实基础上，以实现两个具体目标：（i）开发具有先进光电功能的复杂肽半导体材料，以及（ii）开发新的组装范例，从而产生异质肽纳米材料化学和电子梯度以及局部电场。 这项工作的执行需要研究团队在（i）合成新的π电子单元和新的自组装肽，（ii）纳米材料聚集体及其高阶的分子和数据驱动建模方面进行相互关联的努力组件，以及（iii）纳米材料内电传输的表征。该项目将为本科生、女性和代表性不足的少数族裔提供特别的研究机会。 PI 将培训和指导研究人员使用最先进的实验和计算工具，并使他们接触综合的跨学科工作模式。 K-12 推广活动将激发人们对材料科学的兴趣和认识，并鼓励学生在科学、技术、工程和数学 (STEM) 领域接受高等教育。

项目成果

Evolution of π-Peptide Self-Assembly: From Understanding to Prediction and Control

α-肽自组装的演变：从理解到预测和控制

• DOI: 10.1021/acs.langmuir.2c02399
• 发表时间: 2022-12
• 期刊: Langmuir
• 影响因子: 3.9
• 作者: Ferguson, Andrew L.;Tovar, John D.
• 通讯作者: Tovar, John D.

Patchy Particle Model of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides

α-共轭光电肽分级自组装的斑块粒子模型

• DOI: 10.1021/acs.jpcb.8b05781
• 发表时间: 2018-10
• 期刊: The Journal of Physical Chemistry B
• 作者: Mansbach, Rachael A.;Ferguson, Andrew L.
• 通讯作者: Ferguson, Andrew L.

Revealing the Sequence-Structure–Electronic Property Relation of Self-Assembling π-Conjugated Oligopeptides by Molecular and Quantum Mechanical Modeling

通过分子和量子力学建模揭示自组装α-共轭寡肽的序列结构与电子性质关系

• DOI: 10.1021/acs.langmuir.9b02593
• 发表时间: 2019-11
• 期刊: Langmuir
• 影响因子: 3.9
• 作者: Thurston, Bryce A.;Shapera, Ethan P.;Tovar, John D.;Schleife, André;Ferguson, Andrew L.
• 通讯作者: Ferguson, Andrew L.

Hybrid computational–experimental data-driven design of self-assembling π-conjugated peptides

自组装α-共轭肽的混合计算-实验数据驱动设计

• DOI: 10.1039/d1dd00047k
• 发表时间: 2022-01
• 期刊: Digital Discovery
• 作者: Shmilovich, Kirill;Panda, Sayak Subhra;Stouffer, Anna;Tovar, John D.;Ferguson, Andrew L.
• 通讯作者: Ferguson, Andrew L.

Controlling Supramolecular Chirality in Peptide−π-Peptide Networks by Variation of the Alkyl Spacer Length

通过改变烷基间隔基长度控制肽-肽网络中的超分子手性

• DOI: 10.1021/acs.langmuir.9b02683
• 发表时间: 2019-10
• 期刊: Langmuir
• 影响因子: 3.9
• 作者: Panda, Sayak Subhra;Shmilovich, Kirill;Ferguson, Andrew L.;Tovar, John D.
• 通讯作者: Tovar, John D.