DMREF: Collaborative Research: Self-assembled peptide-pi-electron supramolecular polymers for bioinspired energy harvesting, transport and management
DMREF: Collaborative Research: Self-assembled peptide-pi-electron supramolecular polymers for bioinspired energy harvesting, transport and management
批准号:
1729011
负责人:
Andrew Ferguson
金额:
$53.68万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-10-01 至 2018-10-31
中文摘要
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英文摘要
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.
期刊论文(3)
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会议论文
Collaborative Research: DMREF: Closed-Loop Design of Polymers with Adaptive Networks for Extreme Mechanics
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批准号:2323730
-
项目类别:Standard Grant
-
资助金额:$42.18万
-
财政年份:2023
-
负责人:Andrew Ferguson
-
依托单位:
Latent Space Simulators for the Efficient Estimation of Long-time Molecular Thermodynamics and Kinetics
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批准号:2152521
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项目类别:Standard Grant
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资助金额:$38.79万
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财政年份:2022
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负责人:Andrew Ferguson
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依托单位:
REU SITE: Research Experience for Undergraduates in Molecular Engineering
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批准号:2050878
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项目类别:Standard Grant
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资助金额:$43.4万
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财政年份:2021
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负责人:Andrew Ferguson
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依托单位:
EAGER: (ST1) Collaborative Research: Exploring the emergence of peptide-based compartments through iterative machine learning, molecular modeling, and cell-free protein synthesis
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批准号:1939463
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项目类别:Standard Grant
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资助金额:$14.99万
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财政年份:2019
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负责人:Andrew Ferguson
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依托单位:
EAGER: Collaborative Research: Type II: Data-Driven Characterization and Engineering of Protein Hydrophobicity
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批准号:1844505
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项目类别:Standard Grant
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资助金额:$5.3万
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财政年份:2019
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负责人:Andrew Ferguson
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依托单位:
Nonlinear dimensionality reduction and enhanced sampling in molecular simulation using auto-associative neural networks
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批准号:1841805
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项目类别:Standard Grant
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资助金额:$30.45万
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财政年份:2018
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负责人:Andrew Ferguson
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依托单位:
CAREER: Teaching Machines to Design Self-Assembling Materials
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批准号:1841800
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项目类别:Continuing Grant
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资助金额:$9.0万
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财政年份:2018
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负责人:Andrew Ferguson
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依托单位:
Nonlinear Manifold Learning of Protein Folding Funnels from Delay-Embedded Experimental Measurements
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批准号:1841810
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项目类别:Standard Grant
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资助金额:$16.2万
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财政年份:2018
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负责人:Andrew Ferguson
-
依托单位:
DMREF: Collaborative Research: Self-assembled peptide-pi-electron supramolecular polymers for bioinspired energy harvesting, transport and management
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批准号:1841807
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项目类别:Standard Grant
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资助金额:$52.52万
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财政年份:2018
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负责人:Andrew Ferguson
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依托单位:
Nonlinear dimensionality reduction and enhanced sampling in molecular simulation using auto-associative neural networks
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批准号:1664426
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项目类别:Standard Grant
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资助金额:$38.01万
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财政年份:2017
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负责人:Andrew Ferguson
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依托单位:
Nonlinear Manifold Learning of Protein Folding Funnels from Delay-Embedded Experimental Measurements
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批准号:1714212
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项目类别:Standard Grant
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资助金额:$21.0万
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财政年份:2017
-
负责人:Andrew Ferguson
-
依托单位:
CAREER: Teaching Machines to Design Self-Assembling Materials
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批准号:1350008
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项目类别:Continuing Grant
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资助金额:$45.0万
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财政年份:2014
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负责人:Andrew Ferguson
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依托单位:
Dimension theory of dynamically defined sets
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批准号:EP/I024328/1
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项目类别:Fellowship
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资助金额:$29.58万
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财政年份:2011
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负责人:Andrew Ferguson
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依托单位:
Electrical identification of single dopant atoms
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批准号:EP/G062331/1
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项目类别:Research Grant
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资助金额:$41.72万
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财政年份:2009
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负责人:Andrew Ferguson
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依托单位:
海外基金