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Super-Resolution Imaging of Surface Adsorption on Single Nanoparticles for Electrochemical Dechlorination

Super-Resolution Imaging of Surface Adsorption on Single Nanoparticles for Electrochemical Dechlorination
用于电化学脱氯的单个纳米颗粒表面吸附的超分辨率成像
批准号:
2303933
负责人:
Peng Chen
金额:
$43.54万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-01 至 2026-06-30

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中文摘要
翻译
在化学系大分子,超分子和纳米化学(MSN)计划的支持下,康奈尔大学陈鹏教授正在应用和开发高分辨率成像方法来量化单个钯(Pd)上的吸附行为参与电化学加氢脱氯反应的分子的纳米颗粒,以及确定它们与电化学电势和原始Pd纳米颗粒表面的关系结构和规模。氯化碳氢化合物广泛用于工业和农业应用,但它们也是环境危害。脱氯是一个关键的解毒过程,其中电化学加氢脱氯是更有效和环境友好的,通过使用电力驱动反应,钯纳米粒子是有前途的电催化剂。Chen小组的研究可以产生基础知识,有助于改善氯酚的电化学脱氯,氯酚是水生环境中的一大类污染物,从而对社会福祉产生积极影响。成像方法也是普遍适用的,因此可以广泛地影响纳米材料科学中的测量科学。对于表面反应,包括纳米颗粒上的电催化,分子-表面相互作用至关重要。对于Pd纳米颗粒催化的电化学加氢脱氯知之甚少,然而,有关的定量吸附行为的氯酚和产物苯酚在Pd表面上,这是在电催化循环的关键步骤。在电化学反应条件下量化吸附通常具有挑战性,特别是在纳米颗粒上,其个体在大小和形状上可以明显不同。拟议的研究可以提供定量的能量学的反应物/中间体/产物吸附在Pd纳米粒子在各种应用的电化学电位,以及它们是如何与初始表面刻面结构和颗粒尺寸。这些知识可以指导使用动态电化学电位调制来操纵分子在Pd基电催化剂上的吸附以提高电化学加氢脱氯效率的努力。该项目的研究生在单分子催化的前沿领域以及通过光学显微镜对非荧光过程进行超分辨率成像的新技术开发方面积累了经验。该奖项反映了NSF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。
英文摘要
With support from the Macromolecular, Supramolecular and Nanochemistry (MSN) Program in the Division of Chemistry, Professor Peng Chen of Cornell University is applying and developing high-resolution imaging approaches to quantify the adsorption behaviors on single palladium (Pd) nanoparticles of molecules involved in electrochemical hydrodechlorination reactions as well as to determine their relations to the electrochemical potential and the original Pd nanoparticle surface structure and size. Chlorinated hydrocarbons are extensively used in industrial and agricultural applications, but they are also environmental hazards. Dechlorination is a key detoxification process, for which electrochemical hydrodechlorination is more efficient and environmentally friendly by using electric power to drive reactions for which Pd nanoparticles are promising electrocatalysts. The research in the Chen group can generate fundamental knowledge that can help improve electrochemical dechlorination of chlorophenols, a large class of pollutants in aquatic environments, thus positively impact societal well-being. The imaging approaches are also generally applicable and thus can broadly impact measurement science in nanoscale materials science. For surface reactions, including electrocatalysis on nanoparticles, molecule-surface interactions are crucial. For Pd nanoparticle-catalyzed electrochemical hydrodechlorination little is known, however, about the quantitative adsorption behaviors of the chlorophenols and the product phenol on Pd surfaces, which are key steps in the electrocatalytic cycle. It is generally challenging to quantify adsorption under electrochemical reaction conditions, especially on nanoparticles, whose individuals can differ markedly in size and shape. The proposed research can provide quantitative insights into the energetics of reactant/intermediate/product adsorption on Pd nanoparticles at various applied electrochemical potentials and how they are related to the initial surface facet structure and particle size. This knowledge can guide the efforts of using dynamic electrochemical potential modulation to manipulate molecular adsorption on Pd-based electrocatalysts to improve the efficiency of electrochemical hydrodechlorination. The graduate student working on this project is gaining experience at the forefront area of single-molecule catalysis as well as in the development of novel techniques for super-resolution imaging of nonfluorescent processes by optical microscopy.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.
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FRG: Collaborative Research: Variationally Stable Neural Networks for Simulation, Learning, and Experimental Design of Complex Physical Systems
  • 批准号:
    2245111
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2023
  • 负责人:
    Peng Chen
  • 依托单位:
Scalable Computational Methods for Large-Scale Stochastic Optimization under High-Dimensional Uncertainty
  • 批准号:
    2245674
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $31.0万
  • 财政年份:
    2022
  • 负责人:
    Peng Chen
  • 依托单位:
Scalable Computational Methods for Large-Scale Stochastic Optimization under High-Dimensional Uncertainty
  • 批准号:
    2012453
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $31.0万
  • 财政年份:
    2020
  • 负责人:
    Peng Chen
  • 依托单位:
Nanoscale Mapping and Manipulation of Activity on Single Catalytic Nanocrystals/Nanostructures
  • 批准号:
    1263736
  • 项目类别:
    Standard Grant
  • 资助金额:
    $31.88万
  • 财政年份:
    2013
  • 负责人:
    Peng Chen
  • 依托单位:
国内基金
海外基金
基于Resolution算法的交互时态逻辑自动验证机
  • 批准号:
    61303018
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    22.0万元
  • 批准年份:
    2013
  • 负责人:
    章岚
  • 依托单位: