Structural Health Monitoring of Biofilms for Sustainable Reactive Nitrogen Management

生物膜的结构健康监测以实现可持续的活性氮管理

基本信息

  • 批准号:
    1937290
  • 负责人:
  • 金额:
    $ 32.91万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-05-15 至 2025-04-30
  • 项目状态:
    未结题

项目摘要

Nitrogen pollution in water causes numerous environmental and public health problems. Among the most pressing include the contamination of drinking water sources with nitrates and stimulation of harmful algal blooms. Although we have known about the importance of controlling nitrogen nutrient release for decades, new and more efficient technologies are needed to prevent nitrogen pollution. A promising technology to remove nitrogen pollution from wastewater is the use of membrane bioreactors. Membrane bioreactors use biofilms (naturally occurring microbial communities attached to surfaces) to create the appropriate conditions for efficient nitrogen removal. This project will develop new state-of-the-science tools and advanced modeling approaches to address gaps in our understanding of the mechanical and structural properties of biofilms. Doing so will help improve the performance of bioreactors to efficiently clean water and prevent nitrogen pollution. Biofilms are very common in nature, so results of this research will benefit many other scientific areas, including the removal of other pollutants from water and preventing the growth of harmful biofilms. Additional benefits of this project include the training of underrepresented students, thus increasing the diversity of the Nation’s STEM workforce. Educational outreach to grade-school students and community groups will increase understanding of the importance of controlling nitrogen pollution and increase the scientific literacy of the Nation. Biofilms - microbial communities attached to surfaces - play critical roles in both engineered bioreactors and natural environments. Despite the importance of biofilm structure as an essential mediator of biofilm growth and activity, relatively little is known about the relationship between biofilm structure and mechanical properties that control retention of biomass in the biofilm. This knowledge gap must be addressed if we are to understand how these properties can be modulated to increase efficiency in biofilm reactors. To address this knowledge gap, the PIs propose to employ a novel methodology, termed Optical Coherence Elastography (OCE), to probe the relationship between mesoscale biofilm viscoelastic mechanical properties, structure, and bulk nitrogen (N) transformation rates. The project team will employ OCE to develop fundamental understanding of biofilm properties in partial nitritation and combined nitritation-anammox biofilm reactors. These two promising technologies for energy-efficient wastewater treatment depend directly on precise control of the retention and activity of key N-cycling microbial populations in biofilms. Efforts will be organized around two specific objectives. Objective will be to investigate how commonly used engineering controls (hydrodynamic regime, surface loading rate, and feeding strategy) influence coupling between mesoscale mechanical properties, mesoscale physical structure, and microscale composition in partial nitritation biofilms. The second objective is to determine how mesoscale biofilm properties control key functional outcomes (bulk N transformation and biomass detachment rates) in partial nitritation and combined nitritation-anammox biofilms. To integrate fundamental scientific advances with engineering applications, the project team will link microscale-mesoscale-macroscale biofilm phenomena observed in laboratory bioreactors to predictive model development for full-scale biofilm-based wastewater treatment systems. Improved understanding of mesoscale biofilm structure, biomechanics, and emergent system function will provide a basis for effective monitoring, modeling, and control of biofilm properties in engineered bioreactors, analogous to structural health monitoring for civil infrastructure and mechanical devices.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.
水中的氮污染导致许多环境和公共卫生问题。其中最紧迫的问题包括硝酸盐污染饮用水源和刺激有害藻类大量繁殖。虽然我们几十年来已经知道控制氮营养物释放的重要性,但需要新的和更有效的技术来防止氮污染。膜生物反应器是去除废水中氮污染的一种很有前途的技术。膜生物反应器使用生物膜(附着在表面的天然微生物群落)来创造有效脱氮的适当条件。该项目将开发新的科学工具和先进的建模方法,以解决我们对生物膜的机械和结构特性的理解中的差距。这样做将有助于提高生物反应器的性能,以有效地清洁水并防止氮污染。生物膜在自然界中非常普遍,因此这项研究的结果将有利于许多其他科学领域,包括从水中去除其他污染物和防止有害生物膜的生长。该项目的其他好处包括培训代表性不足的学生,从而增加了国家STEM劳动力的多样性。对小学生和社区团体的教育推广将增加对控制氮污染重要性的理解,并提高国家的科学素养。生物膜-附着在表面的微生物群落-在工程生物反应器和自然环境中起着关键作用。尽管生物膜结构作为生物膜生长和活性的基本介质的重要性,但关于生物膜结构和控制生物质在生物膜中保留的机械性质之间的关系知之甚少。如果我们要了解如何调节这些特性以提高生物膜反应器的效率,就必须解决这一知识差距。为了解决这一知识缺口,PI建议采用一种新的方法,称为光学相干弹性成像(OCE),以探讨中尺度生物膜粘弹性机械性能,结构和散装氮(N)转化率之间的关系。该项目团队将采用OCE来发展对部分亚硝化和联合亚硝化-厌氧氨氧化生物膜反应器中生物膜特性的基本理解。这两种有前途的节能废水处理技术直接依赖于对生物膜中关键氮循环微生物种群的保留和活性的精确控制。将围绕两个具体目标开展工作。目的将是调查如何常用的工程控制(流体动力学制度,表面负载率,和喂养策略)的影响耦合之间的介观尺度的机械性能,介观尺度的物理结构,和微尺度组成部分亚硝化生物膜。第二个目标是确定中尺度生物膜特性如何控制部分亚硝化和联合亚硝化-厌氧氨氧化生物膜中的关键功能结果(大量N转化和生物量分离率)。为了将基础科学进展与工程应用相结合,项目团队将把实验室生物反应器中观察到的微尺度-中尺度-宏观尺度生物膜现象与全尺度生物膜废水处理系统的预测模型开发联系起来。对中尺度生物膜结构、生物力学和紧急系统功能的更好理解将为工程生物反应器中生物膜特性的有效监测、建模和控制提供基础,类似于民用基础设施和机械设备的结构健康监测。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的知识价值和更广泛的影响审查进行评估来支持的搜索.

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

George Wells其他文献

PC100. Prolonged Versus Brief Balloon Inflation for Arterial Angioplasty
  • DOI:
    10.1016/j.jvs.2019.04.343
  • 发表时间:
    2019-06-01
  • 期刊:
  • 影响因子:
  • 作者:
    Mark Rockley;Prasad Jetty;George Wells;Katie Rockley;Dean Fergusson
  • 通讯作者:
    Dean Fergusson
EFFECT OF HIGH DOSE FOLIC ACID SUPPLEMENTATION THROUGHOUT PREGNANCY ON PREECLAMPSIA (FACT): A DOUBLE-BIND, RANDOMIZED CONTROLLED MULTICENTRE TRIAL
  • DOI:
    10.1016/j.jogc.2019.02.244
  • 发表时间:
    2019-05-01
  • 期刊:
  • 影响因子:
  • 作者:
    Mark Walker;Shi Wu Wen;Ruth Rennicks White;Natalie Rybak;Laura M. Gaudet;Stephen Robson;William Hague;Donnette Simms-Stewart;Guillermo Carroli;Graeme Smith;William D. Fraser;George Wells;Sandra T. Davidge;John Kingdom;Doug Coyle;Dean Fergusson;Daniel Corsi;Josee Champagne;Elham Sabri;Tim Ramsay
  • 通讯作者:
    Tim Ramsay
EFFICACY AND SAFETY OF BIVALIRUDIN IN PATIENTS UNDERGOING PHARMACOINVASIVE STRATEGY FOLLOWING FIBRINOLYSIS FOR ST-SEGMENT ELEVATION MYOCARDIAL INFARCTION
  • DOI:
    10.1016/s0735-1097(17)34581-3
  • 发表时间:
    2017-03-21
  • 期刊:
  • 影响因子:
  • 作者:
    Mohammed Rashid;Jordan Bernick;George Wells;Melissa Blondeau;Aun-Yeong Chong;Alexander Dick;Michael Froeschl;Chris Glover;Benjamin Hibbert;Marino Labinaz;Christina Osborne;Juan Russo;Derek So;Michel Le May
  • 通讯作者:
    Michel Le May
TCT-487 Door-to-Balloon Time as a Function of Mode of Referral: Results from the Ontario Provincial Cardiac Care Network Database
  • DOI:
    10.1016/j.jacc.2012.08.519
  • 发表时间:
    2012-10-23
  • 期刊:
  • 影响因子:
  • 作者:
    Michel Le May;Warren Cantor;Madhu Natarajan;Daniel Purdham;Marina Brezinov;Kori Kingsbury;George Wells
  • 通讯作者:
    George Wells
Physiologic Response Predicts Freedom From Reintervention More Accurately Than Angiogram Following Endovascular Revascularization for Peripheral Vascular Disease
  • DOI:
    10.1016/j.jvs.2019.07.025
  • 发表时间:
    2019-10-01
  • 期刊:
  • 影响因子:
  • 作者:
    Mark Rockley;Prasad Jetty;George Wells
  • 通讯作者:
    George Wells

George Wells的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('George Wells', 18)}}的其他基金

ECO-CBET: Collaborative Research: Towards a Circular Nitrogen Bioeconomy: Tandem Bio- and Chemocatalysis for Sustainable Nitrogen Recovery and Nitrous Oxide Mitigation
ECO-CBET:合作研究:迈向循环氮生物经济:串联生物催化和化学催化实现可持续氮回收和一氧化二氮减排
  • 批准号:
    2033793
  • 财政年份:
    2020
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Continuing Grant
EAGER: Optical Coherence Elastography (OCE): A novel tool for rapid, nondestructive, spatially resolved quantification of mesoscale biofilm mechanical properties
EAGER:光学相干弹性成像 (OCE):一种快速、无损、空间分辨量化中尺度生物膜机械性能的新型工具
  • 批准号:
    1701105
  • 财政年份:
    2017
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Standard Grant
IRFP: Towards Sustainable Wastewater Treatment: Mass Transport Limitations, Microbial Diversity, and Nitrous Oxide Production in Anammox Nutrient Removal Processes
IRFP:迈向可持续废水处理:厌氧氨氧化营养物去除过程中的质量传输限制、微生物多样性和一氧化二氮生产
  • 批准号:
    1064615
  • 财政年份:
    2011
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Fellowship Award

相似国自然基金

重大传染病防治关键技术研究-重大传染病防治关键技术研究-基于One Health的SFTS防治技术体系构建与应用
  • 批准号:
    2025C02186
  • 批准年份:
    2025
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
人兽共患病One Health防控决策路径研究
  • 批准号:
  • 批准年份:
    2024
  • 资助金额:
    5.0 万元
  • 项目类别:
    省市级项目
基于 One Health 策略的 mcr 阳性多重耐药 ST34 型沙门菌的流行传播机制及溯源研究
  • 批准号:
    Y24H190002
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
基于One Health理念的人兽共患病防控决策机制及实施路径研究
  • 批准号:
  • 批准年份:
    2022
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
One Health 导向下人畜共患病公共危机四维防控体系研究
  • 批准号:
    2019JJ50277
  • 批准年份:
    2019
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
基于时间序列Shapelets的u-Health心电图可解释早期分类研究
  • 批准号:
    61702468
  • 批准年份:
    2017
  • 资助金额:
    24.0 万元
  • 项目类别:
    青年科学基金项目
基于One Health理念建立动物职业暴露人群流感监测体系的研究
  • 批准号:
    81473034
  • 批准年份:
    2014
  • 资助金额:
    60.0 万元
  • 项目类别:
    面上项目
基于广义Health-Jarrow-Morton模型的固定收益证券定价方法研究
  • 批准号:
    70771075
  • 批准年份:
    2007
  • 资助金额:
    20.0 万元
  • 项目类别:
    面上项目

相似海外基金

STTR Phase I: Machine Learning-Based Smart Data Compression Solutions for Structural Health Monitoring Sensors
STTR 第一阶段:用于结构健康监测传感器的基于机器学习的智能数据压缩解决方案
  • 批准号:
    2321884
  • 财政年份:
    2023
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Standard Grant
Flexible polymer-based sensors for structural health monitoring in renewable energy-generating devices
用于可再生能源发电设备结构健康监测的柔性聚合物传感器
  • 批准号:
    2893927
  • 财政年份:
    2023
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Studentship
Artificial Intelligence for structural health monitoring using graphene sensor systems (InteGraph)
使用石墨烯传感器系统进行结构健康监测的人工智能 (InteGraph)
  • 批准号:
    10066187
  • 财政年份:
    2023
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Collaborative R&D
Structural Health Monitoring for Maintaining Aging Civil Infrastructure
维护老化民用基础设施的结构健康监测
  • 批准号:
    2886618
  • 财政年份:
    2023
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Studentship
I-Corps: Artificial intelligence-based software package for end-to-end structural health monitoring of infrastructure systems
I-Corps:基于人工智能的软件包,用于基础设施系统的端到端结构健康监测
  • 批准号:
    2306180
  • 财政年份:
    2023
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Standard Grant
Development and validation of an automated structural health monitoring system for post-earthquake building safety evaluations
用于震后建筑安全评估的自动结构健康监测系统的开发和验证
  • 批准号:
    22KF0087
  • 财政年份:
    2023
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Grant-in-Aid for JSPS Fellows
USES of novel Ultrasonic and Seismic Embedded Sensors for the non-destructive evaluation and structural health monitoring of critical infrastructure
使用新型超声波和地震嵌入式传感器对关键基础设施进行无损评估和结构健康监测
  • 批准号:
    EP/X027392/1
  • 财政年份:
    2023
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Research Grant
Automated analysis approaches for Structural Health Monitoring on aerospace primary structure with ultrasonic and electromagnetic sensor arrays
利用超声波和电磁传感器阵列对航空航天主结构进行结构健康监测的自动分析方法
  • 批准号:
    2737813
  • 财政年份:
    2022
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Studentship
Structural Health Monitoring of Reinforced Concrete Structures with Advanced Concrete Mixtures
采用先进混凝土混合物的钢筋混凝土结构的结构健康监测
  • 批准号:
    RGPIN-2018-03790
  • 财政年份:
    2022
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Discovery Grants Program - Individual
Real-time Artificial Intelligence (AI) Prediction of Seepage Failure and Evacuation Assistance by Structural Health Monitoring of River Levees
通过河堤结构健康监测实时人工智能(AI)预测渗漏故障并协助疏散
  • 批准号:
    22K04313
  • 财政年份:
    2022
  • 资助金额:
    $ 32.91万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了